[ { "path": ".gitignore", "content": "# Byte-compiled / optimized / DLL files\n__pycache__/\n*.py[cod]\n*$py.class\n\n# C extensions\n*.so\n\n# Distribution / packaging\n.Python\nbuild/\ndevelop-eggs/\ndist/\ndownloads/\neggs/\n.eggs/\nlib/\nlib64/\nparts/\nsdist/\nvar/\nwheels/\nshare/python-wheels/\n*.egg-info/\n.installed.cfg\n*.egg\nMANIFEST\n\n# PyInstaller\n# Usually these files are written by a python script from a template\n# before PyInstaller builds the exe, so as to inject date/other infos into it.\n*.manifest\n*.spec\n\n# Installer logs\npip-log.txt\npip-delete-this-directory.txt\n\n# Unit test / coverage reports\nhtmlcov/\n.tox/\n.nox/\n.coverage\n.coverage.*\n.cache\nnosetests.xml\ncoverage.xml\n*.cover\n*.py,cover\n.hypothesis/\n.pytest_cache/\ncover/\n\n# Translations\n*.mo\n*.pot\n\n# Django stuff:\n*.log\nlocal_settings.py\ndb.sqlite3\ndb.sqlite3-journal\n\n# Flask stuff:\ninstance/\n.webassets-cache\n\n# Scrapy stuff:\n.scrapy\n\n# Sphinx documentation\ndocs/_build/\n\n# PyBuilder\n.pybuilder/\ntarget/\n\n# Jupyter Notebook\n.ipynb_checkpoints\n\n# IPython\nprofile_default/\nipython_config.py\n\n# pyenv\n# For a library or package, you might want to ignore these files since the code is\n# intended to run in multiple environments; otherwise, check them in:\n# .python-version\n\n# pipenv\n# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.\n# However, in case of collaboration, if having platform-specific dependencies or dependencies\n# having no cross-platform support, pipenv may install dependencies that don't work, or not\n# install all needed dependencies.\n#Pipfile.lock\n\n# poetry\n# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.\n# This is especially recommended for binary packages to ensure reproducibility, and is more\n# commonly ignored for libraries.\n# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control\n#poetry.lock\n\n# pdm\n# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.\n#pdm.lock\n# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it\n# in version control.\n# https://pdm.fming.dev/#use-with-ide\n.pdm.toml\n\n# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm\n__pypackages__/\n\n# Celery stuff\ncelerybeat-schedule\ncelerybeat.pid\n\n# SageMath parsed files\n*.sage.py\n\n# Environments\n.env\n.venv\nenv/\nvenv/\nENV/\nenv.bak/\nvenv.bak/\n\n# Spyder project settings\n.spyderproject\n.spyproject\n\n# Rope project settings\n.ropeproject\n\n# mkdocs documentation\n/site\n\n# mypy\n.mypy_cache/\n.dmypy.json\ndmypy.json\n\n# Pyre type checker\n.pyre/\n\n# pytype static type analyzer\n.pytype/\n\n# Cython debug symbols\ncython_debug/\n\n# PyCharm\n# JetBrains specific template is maintained in a separate JetBrains.gitignore that can\n# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore\n# and can be added to the global gitignore or merged into this file. For a more nuclear\n# option (not recommended) you can uncomment the following to ignore the entire idea folder.\n#.idea/\n**/.DS_STORE" }, { "path": "LangChain Cookbook Part 1 - Fundamentals.ipynb", "content": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"id\": \"359697d5\",\n \"metadata\": {},\n \"source\": [\n \"# LangChain Cookbook 👨‍🍳👩‍🍳\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"11d788b0\",\n \"metadata\": {},\n \"source\": [\n \"*This cookbook is based off the [LangChain Conceptual Documentation](https://docs.langchain.com/docs/)*\\n\",\n \"\\n\",\n \"**Goal:** Provide an introductory understanding of the components and use cases of LangChain via [ELI5](https://www.dictionary.com/e/slang/eli5/#:~:text=ELI5%20is%20short%20for%20%E2%80%9CExplain,a%20complicated%20question%20or%20problem.) examples and code snippets. For use cases check out [part 2](https://github.com/gkamradt/langchain-tutorials/blob/main/LangChain%20Cookbook%20Part%202%20-%20Use%20Cases.ipynb). See [video tutorial](https://www.youtube.com/watch?v=2xxziIWmaSA) of this notebook.\\n\",\n \"\\n\",\n \"\\n\",\n \"**Links:**\\n\",\n \"* [LC Conceptual Documentation](https://docs.langchain.com/docs/)\\n\",\n \"* [LC Python Documentation](https://python.langchain.com/en/latest/)\\n\",\n \"* [LC Javascript/Typescript Documentation](https://js.langchain.com/docs/)\\n\",\n \"* [LC Discord](https://discord.gg/6adMQxSpJS)\\n\",\n \"* [www.langchain.com](https://langchain.com/)\\n\",\n \"* [LC Twitter](https://twitter.com/LangChainAI)\\n\",\n \"\\n\",\n \"\\n\",\n \"### **What is LangChain?**\\n\",\n \"> LangChain is a framework for developing applications powered by language models.\\n\",\n \"\\n\",\n \"**~~TL~~DR**: LangChain makes the complicated parts of working & building with AI models easier. It helps do this in two ways:\\n\",\n \"\\n\",\n \"1. **Integration** - Bring external data, such as your files, other applications, and api data, to your LLMs\\n\",\n \"2. **Agency** - Allow your LLMs to interact with it's environment via decision making. Use LLMs to help decide which action to take next\\n\",\n \"\\n\",\n \"### **Why LangChain?**\\n\",\n \"1. **Components** - LangChain makes it easy to swap out abstractions and components necessary to work with language models.\\n\",\n \"\\n\",\n \"2. **Customized Chains** - LangChain provides out of the box support for using and customizing 'chains' - a series of actions strung together.\\n\",\n \"\\n\",\n \"3. **Speed 🚢** - This team ships insanely fast. You'll be up to date with the latest LLM features.\\n\",\n \"\\n\",\n \"4. **Community 👥** - Wonderful discord and community support, meet ups, hackathons, etc.\\n\",\n \"\\n\",\n \"Though LLMs can be straightforward (text-in, text-out) you'll quickly run into friction points that LangChain helps with once you develop more complicated applications.\\n\",\n \"\\n\",\n \"*Note: This cookbook will not cover all aspects of LangChain. It's contents have been curated to get you to building & impact as quick as possible. For more, please check out [LangChain Conceptual Documentation](https://docs.langchain.com/docs/)*\\n\",\n \"\\n\",\n \"*Update Oct '23: This notebook has been expanded from it's original form*\\n\",\n \"\\n\",\n \"You'll need an OpenAI api key to follow this tutorial. You can have it as an environement variable, in an .env file where this jupyter notebook lives, or insert it below where 'YourAPIKey' is. Have if you have questions on this, put these instructions into [ChatGPT](https://chat.openai.com/).\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 1,\n \"id\": \"e9815081\",\n \"metadata\": {\n \"hide_input\": false\n },\n \"outputs\": [],\n \"source\": [\n \"from dotenv import load_dotenv\\n\",\n \"import os\\n\",\n \"\\n\",\n \"load_dotenv()\\n\",\n \"\\n\",\n \"openai_api_key=os.getenv('OPENAI_API_KEY', 'YourAPIKey')\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"05bb564d\",\n \"metadata\": {},\n \"source\": [\n \"# LangChain Components\\n\",\n \"\\n\",\n \"## Schema - Nuts and Bolts of working with Large Language Models (LLMs)\\n\",\n \"\\n\",\n \"### **Text**\\n\",\n \"The natural language way to interact with LLMs\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 2,\n \"id\": \"8e0dc06c\",\n \"metadata\": {\n \"hide_input\": false\n },\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"'What day comes after Friday?'\"\n ]\n },\n \"execution_count\": 2,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"# You'll be working with simple strings (that'll soon grow in complexity!)\\n\",\n \"my_text = \\\"What day comes after Friday?\\\"\\n\",\n \"my_text\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"2f39eb39\",\n \"metadata\": {},\n \"source\": [\n \"### **Chat Messages**\\n\",\n \"Like text, but specified with a message type (System, Human, AI)\\n\",\n \"\\n\",\n \"* **System** - Helpful background context that tell the AI what to do\\n\",\n \"* **Human** - Messages that are intented to represent the user\\n\",\n \"* **AI** - Messages that show what the AI responded with\\n\",\n \"\\n\",\n \"For more, see OpenAI's [documentation](https://platform.openai.com/docs/guides/chat/introduction)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 3,\n \"id\": \"99b0935b\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain.chat_models import ChatOpenAI\\n\",\n \"from langchain.schema import HumanMessage, SystemMessage, AIMessage\\n\",\n \"\\n\",\n \"# This it the language model we'll use. We'll talk about what we're doing below in the next section\\n\",\n \"chat = ChatOpenAI(temperature=.7, openai_api_key=openai_api_key)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"a2d2f7af\",\n \"metadata\": {},\n \"source\": [\n \"Now let's create a few messages that simulate a chat experience with a bot\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 4,\n \"id\": \"878d6a36\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"AIMessage(content='You could try a caprese salad with fresh tomatoes, mozzarella, and basil.')\"\n ]\n },\n \"execution_count\": 4,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"chat(\\n\",\n \" [\\n\",\n \" SystemMessage(content=\\\"You are a nice AI bot that helps a user figure out what to eat in one short sentence\\\"),\\n\",\n \" HumanMessage(content=\\\"I like tomatoes, what should I eat?\\\")\\n\",\n \" ]\\n\",\n \")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"0a425aaa\",\n \"metadata\": {},\n \"source\": [\n \"You can also pass more chat history w/ responses from the AI\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 5,\n \"id\": \"8fd3fe88\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"AIMessage(content='You should also explore the charming streets of the Old Town and indulge in delicious French cuisine.')\"\n ]\n },\n \"execution_count\": 5,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"chat(\\n\",\n \" [\\n\",\n \" SystemMessage(content=\\\"You are a nice AI bot that helps a user figure out where to travel in one short sentence\\\"),\\n\",\n \" HumanMessage(content=\\\"I like the beaches where should I go?\\\"),\\n\",\n \" AIMessage(content=\\\"You should go to Nice, France\\\"),\\n\",\n \" HumanMessage(content=\\\"What else should I do when I'm there?\\\")\\n\",\n \" ]\\n\",\n \")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"ff5ee37a\",\n \"metadata\": {},\n \"source\": [\n \"You can also exclude the system message if you want\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 6,\n \"id\": \"238a49f6\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"AIMessage(content='Friday')\"\n ]\n },\n \"execution_count\": 6,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"chat(\\n\",\n \" [\\n\",\n \" HumanMessage(content=\\\"What day comes after Thursday?\\\")\\n\",\n \" ]\\n\",\n \")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"66bf9634\",\n \"metadata\": {},\n \"source\": [\n \"### **Documents**\\n\",\n \"An object that holds a piece of text and metadata (more information about that text)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 7,\n \"id\": \"3bbf58b2\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain.schema import Document\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 8,\n \"id\": \"6ad9bef6\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"Document(page_content=\\\"This is my document. It is full of text that I've gathered from other places\\\", metadata={'my_document_id': 234234, 'my_document_source': 'The LangChain Papers', 'my_document_create_time': 1680013019})\"\n ]\n },\n \"execution_count\": 8,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"Document(page_content=\\\"This is my document. It is full of text that I've gathered from other places\\\",\\n\",\n \" metadata={\\n\",\n \" 'my_document_id' : 234234,\\n\",\n \" 'my_document_source' : \\\"The LangChain Papers\\\",\\n\",\n \" 'my_document_create_time' : 1680013019\\n\",\n \" })\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"3bd19754\",\n \"metadata\": {},\n \"source\": [\n \"But you don't have to include metadata if you don't want to\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 9,\n \"id\": \"0798d3ca\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"Document(page_content=\\\"This is my document. It is full of text that I've gathered from other places\\\")\"\n ]\n },\n \"execution_count\": 9,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"Document(page_content=\\\"This is my document. It is full of text that I've gathered from other places\\\")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"2e462b5d\",\n \"metadata\": {},\n \"source\": [\n \"## Models - The interface to the AI brains\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"b27fe982\",\n \"metadata\": {},\n \"source\": [\n \"### **Language Model**\\n\",\n \"A model that does text in ➡️ text out!\\n\",\n \"\\n\",\n \"*Check out how I changed the model I was using from the default one to ada-001 (a very cheap, low performing model). See more models [here](https://platform.openai.com/docs/models)*\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 10,\n \"id\": \"74b1a72a\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain.llms import OpenAI\\n\",\n \"\\n\",\n \"llm = OpenAI(model_name=\\\"text-ada-001\\\", openai_api_key=openai_api_key)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 11,\n \"id\": \"6399c295\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"'\\\\n\\\\nSaturday'\"\n ]\n },\n \"execution_count\": 11,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"llm(\\\"What day comes after Friday?\\\")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"3ef89bfa\",\n \"metadata\": {},\n \"source\": [\n \"### **Chat Model**\\n\",\n \"A model that takes a series of messages and returns a message output\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 12,\n \"id\": \"bf091777\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain.chat_models import ChatOpenAI\\n\",\n \"from langchain.schema import HumanMessage, SystemMessage, AIMessage\\n\",\n \"\\n\",\n \"chat = ChatOpenAI(temperature=1, openai_api_key=openai_api_key)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 13,\n \"id\": \"f4260711\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"AIMessage(content='Why did the math book go to New York? Because it had too many problems and needed a change of scenery!')\"\n ]\n },\n \"execution_count\": 13,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"chat(\\n\",\n \" [\\n\",\n \" SystemMessage(content=\\\"You are an unhelpful AI bot that makes a joke at whatever the user says\\\"),\\n\",\n \" HumanMessage(content=\\\"I would like to go to New York, how should I do this?\\\")\\n\",\n \" ]\\n\",\n \")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"05c028f9\",\n \"metadata\": {},\n \"source\": [\n \"### Function Calling Models\\n\",\n \"\\n\",\n \"[Function calling models](https://openai.com/blog/function-calling-and-other-api-updates) are similar to Chat Models but with a little extra flavor. They are fine tuned to give structured data outputs.\\n\",\n \"\\n\",\n \"This comes in handy when you're making an API call to an external service or doing extraction.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 14,\n \"id\": \"1020ff45\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"AIMessage(content='', additional_kwargs={'function_call': {'name': 'get_current_weather', 'arguments': '{\\\\n \\\"location\\\": \\\"Boston, MA\\\"\\\\n}'}})\"\n ]\n },\n \"execution_count\": 14,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"chat = ChatOpenAI(model='gpt-3.5-turbo-0613', temperature=1, openai_api_key=openai_api_key)\\n\",\n \"\\n\",\n \"output = chat(messages=\\n\",\n \" [\\n\",\n \" SystemMessage(content=\\\"You are an helpful AI bot\\\"),\\n\",\n \" HumanMessage(content=\\\"What’s the weather like in Boston right now?\\\")\\n\",\n \" ],\\n\",\n \" functions=[{\\n\",\n \" \\\"name\\\": \\\"get_current_weather\\\",\\n\",\n \" \\\"description\\\": \\\"Get the current weather in a given location\\\",\\n\",\n \" \\\"parameters\\\": {\\n\",\n \" \\\"type\\\": \\\"object\\\",\\n\",\n \" \\\"properties\\\": {\\n\",\n \" \\\"location\\\": {\\n\",\n \" \\\"type\\\": \\\"string\\\",\\n\",\n \" \\\"description\\\": \\\"The city and state, e.g. San Francisco, CA\\\"\\n\",\n \" },\\n\",\n \" \\\"unit\\\": {\\n\",\n \" \\\"type\\\": \\\"string\\\",\\n\",\n \" \\\"enum\\\": [\\\"celsius\\\", \\\"fahrenheit\\\"]\\n\",\n \" }\\n\",\n \" },\\n\",\n \" \\\"required\\\": [\\\"location\\\"]\\n\",\n \" }\\n\",\n \" }\\n\",\n \" ]\\n\",\n \")\\n\",\n \"output\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"0f399a1d\",\n \"metadata\": {},\n \"source\": [\n \"See the extra `additional_kwargs` that is passed back to us? We can take that and pass it to an external API to get data. It saves the hassle of doing output parsing.\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"c2b70f23\",\n \"metadata\": {},\n \"source\": [\n \"### **Text Embedding Model**\\n\",\n \"Change your text into a vector (a series of numbers that hold the semantic 'meaning' of your text). Mainly used when comparing two pieces of text together.\\n\",\n \"\\n\",\n \"*BTW: Semantic means 'relating to meaning in language or logic.'*\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 15,\n \"id\": \"1655de82\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain.embeddings import OpenAIEmbeddings\\n\",\n \"\\n\",\n \"embeddings = OpenAIEmbeddings(openai_api_key=openai_api_key)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 16,\n \"id\": \"a2c85e7e\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"text = \\\"Hi! It's time for the beach\\\"\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 17,\n \"id\": \"ddc5a368\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"Here's a sample: [-0.00019600906371495047, -0.0031846734422911363, -0.0007734206914647714, -0.019472001962491232, -0.015092319017854244]...\\n\",\n \"Your embedding is length 1536\\n\"\n ]\n }\n ],\n \"source\": [\n \"text_embedding = embeddings.embed_query(text)\\n\",\n \"print (f\\\"Here's a sample: {text_embedding[:5]}...\\\")\\n\",\n \"print (f\\\"Your embedding is length {len(text_embedding)}\\\")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"c38fe99f\",\n \"metadata\": {},\n \"source\": [\n \"## Prompts - Text generally used as instructions to your model\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"8b9318ed\",\n \"metadata\": {},\n \"source\": [\n \"### **Prompt**\\n\",\n \"What you'll pass to the underlying model\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 18,\n \"id\": \"2d270239\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"\\n\",\n \"The statement is incorrect. Tomorrow is Tuesday, not Wednesday.\\n\"\n ]\n }\n ],\n \"source\": [\n \"from langchain.llms import OpenAI\\n\",\n \"\\n\",\n \"llm = OpenAI(model_name=\\\"text-davinci-003\\\", openai_api_key=openai_api_key)\\n\",\n \"\\n\",\n \"# I like to use three double quotation marks for my prompts because it's easier to read\\n\",\n \"prompt = \\\"\\\"\\\"\\n\",\n \"Today is Monday, tomorrow is Wednesday.\\n\",\n \"\\n\",\n \"What is wrong with that statement?\\n\",\n \"\\\"\\\"\\\"\\n\",\n \"\\n\",\n \"print(llm(prompt))\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"74988254\",\n \"metadata\": {},\n \"source\": [\n \"### **Prompt Template**\\n\",\n \"An object that helps create prompts based on a combination of user input, other non-static information and a fixed template string.\\n\",\n \"\\n\",\n \"Think of it as an [f-string](https://realpython.com/python-f-strings/) in python but for prompts\\n\",\n \"\\n\",\n \"*Advanced: Check out LangSmithHub(https://smith.langchain.com/hub) for many more communit prompt templates*\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 19,\n \"id\": \"abcc212d\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"Final Prompt: \\n\",\n \"I really want to travel to Rome. What should I do there?\\n\",\n \"\\n\",\n \"Respond in one short sentence\\n\",\n \"\\n\",\n \"-----------\\n\",\n \"LLM Output: Visit the Colosseum, the Vatican, and the Trevi Fountain.\\n\"\n ]\n }\n ],\n \"source\": [\n \"from langchain.llms import OpenAI\\n\",\n \"from langchain import PromptTemplate\\n\",\n \"\\n\",\n \"llm = OpenAI(model_name=\\\"text-davinci-003\\\", openai_api_key=openai_api_key)\\n\",\n \"\\n\",\n \"# Notice \\\"location\\\" below, that is a placeholder for another value later\\n\",\n \"template = \\\"\\\"\\\"\\n\",\n \"I really want to travel to {location}. What should I do there?\\n\",\n \"\\n\",\n \"Respond in one short sentence\\n\",\n \"\\\"\\\"\\\"\\n\",\n \"\\n\",\n \"prompt = PromptTemplate(\\n\",\n \" input_variables=[\\\"location\\\"],\\n\",\n \" template=template,\\n\",\n \")\\n\",\n \"\\n\",\n \"final_prompt = prompt.format(location='Rome')\\n\",\n \"\\n\",\n \"print (f\\\"Final Prompt: {final_prompt}\\\")\\n\",\n \"print (\\\"-----------\\\")\\n\",\n \"print (f\\\"LLM Output: {llm(final_prompt)}\\\")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"ed40bac2\",\n \"metadata\": {},\n \"source\": [\n \"### **Example Selectors**\\n\",\n \"An easy way to select from a series of examples that allow you to dynamic place in-context information into your prompt. Often used when your task is nuanced or you have a large list of examples.\\n\",\n \"\\n\",\n \"Check out different types of example selectors [here](https://python.langchain.com/docs/modules/model_io/prompts/example_selectors/)\\n\",\n \"\\n\",\n \"If you want an overview on why examples are important (prompt engineering), check out [this video](https://www.youtube.com/watch?v=dOxUroR57xs)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 20,\n \"id\": \"aaf36cd9\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stderr\",\n \"output_type\": \"stream\",\n \"text\": [\n \"/Users/gregorykamradt/opt/anaconda3/lib/python3.9/site-packages/deeplake/util/check_latest_version.py:32: UserWarning: A newer version of deeplake (3.7.2) is available. It's recommended that you update to the latest version using `pip install -U deeplake`.\\n\",\n \" warnings.warn(\\n\"\n ]\n }\n ],\n \"source\": [\n \"from langchain.prompts.example_selector import SemanticSimilarityExampleSelector\\n\",\n \"from langchain.vectorstores import Chroma\\n\",\n \"from langchain.embeddings import OpenAIEmbeddings\\n\",\n \"from langchain.prompts import FewShotPromptTemplate, PromptTemplate\\n\",\n \"from langchain.llms import OpenAI\\n\",\n \"\\n\",\n \"llm = OpenAI(model_name=\\\"text-davinci-003\\\", openai_api_key=openai_api_key)\\n\",\n \"\\n\",\n \"example_prompt = PromptTemplate(\\n\",\n \" input_variables=[\\\"input\\\", \\\"output\\\"],\\n\",\n \" template=\\\"Example Input: {input}\\\\nExample Output: {output}\\\",\\n\",\n \")\\n\",\n \"\\n\",\n \"# Examples of locations that nouns are found\\n\",\n \"examples = [\\n\",\n \" {\\\"input\\\": \\\"pirate\\\", \\\"output\\\": \\\"ship\\\"},\\n\",\n \" {\\\"input\\\": \\\"pilot\\\", \\\"output\\\": \\\"plane\\\"},\\n\",\n \" {\\\"input\\\": \\\"driver\\\", \\\"output\\\": \\\"car\\\"},\\n\",\n \" {\\\"input\\\": \\\"tree\\\", \\\"output\\\": \\\"ground\\\"},\\n\",\n \" {\\\"input\\\": \\\"bird\\\", \\\"output\\\": \\\"nest\\\"},\\n\",\n \"]\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 21,\n \"id\": \"12b4798b\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# SemanticSimilarityExampleSelector will select examples that are similar to your input by semantic meaning\\n\",\n \"\\n\",\n \"example_selector = SemanticSimilarityExampleSelector.from_examples(\\n\",\n \" # This is the list of examples available to select from.\\n\",\n \" examples, \\n\",\n \" \\n\",\n \" # This is the embedding class used to produce embeddings which are used to measure semantic similarity.\\n\",\n \" OpenAIEmbeddings(openai_api_key=openai_api_key), \\n\",\n \" \\n\",\n \" # This is the VectorStore class that is used to store the embeddings and do a similarity search over.\\n\",\n \" Chroma, \\n\",\n \" \\n\",\n \" # This is the number of examples to produce.\\n\",\n \" k=2\\n\",\n \")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 22,\n \"id\": \"2cf30107\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"similar_prompt = FewShotPromptTemplate(\\n\",\n \" # The object that will help select examples\\n\",\n \" example_selector=example_selector,\\n\",\n \" \\n\",\n \" # Your prompt\\n\",\n \" example_prompt=example_prompt,\\n\",\n \" \\n\",\n \" # Customizations that will be added to the top and bottom of your prompt\\n\",\n \" prefix=\\\"Give the location an item is usually found in\\\",\\n\",\n \" suffix=\\\"Input: {noun}\\\\nOutput:\\\",\\n\",\n \" \\n\",\n \" # What inputs your prompt will receive\\n\",\n \" input_variables=[\\\"noun\\\"],\\n\",\n \")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 23,\n \"id\": \"369442bb\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"Give the location an item is usually found in\\n\",\n \"\\n\",\n \"Example Input: tree\\n\",\n \"Example Output: ground\\n\",\n \"\\n\",\n \"Example Input: bird\\n\",\n \"Example Output: nest\\n\",\n \"\\n\",\n \"Input: plant\\n\",\n \"Output:\\n\"\n ]\n }\n ],\n \"source\": [\n \"# Select a noun!\\n\",\n \"my_noun = \\\"plant\\\"\\n\",\n \"# my_noun = \\\"student\\\"\\n\",\n \"\\n\",\n \"print(similar_prompt.format(noun=my_noun))\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 24,\n \"id\": \"9bb910f2\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"' pot'\"\n ]\n },\n \"execution_count\": 24,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"llm(similar_prompt.format(noun=my_noun))\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"8474c91d\",\n \"metadata\": {},\n \"source\": [\n \"### **Output Parsers Method 1: Prompt Instructions & String Parsing**\\n\",\n \"A helpful way to format the output of a model. Usually used for structured output. LangChain has a bunch more output parsers listed on their [documentation](https://python.langchain.com/docs/modules/model_io/output_parsers).\\n\",\n \"\\n\",\n \"Two big concepts:\\n\",\n \"\\n\",\n \"**1. Format Instructions** - A autogenerated prompt that tells the LLM how to format it's response based off your desired result\\n\",\n \"\\n\",\n \"**2. Parser** - A method which will extract your model's text output into a desired structure (usually json)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 25,\n \"id\": \"58353756\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain.output_parsers import StructuredOutputParser, ResponseSchema\\n\",\n \"from langchain.prompts import ChatPromptTemplate, HumanMessagePromptTemplate\\n\",\n \"from langchain.llms import OpenAI\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 26,\n \"id\": \"ee36f881\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"llm = OpenAI(model_name=\\\"text-davinci-003\\\", openai_api_key=openai_api_key)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 27,\n \"id\": \"fa59be3f\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# How you would like your response structured. This is basically a fancy prompt template\\n\",\n \"response_schemas = [\\n\",\n \" ResponseSchema(name=\\\"bad_string\\\", description=\\\"This a poorly formatted user input string\\\"),\\n\",\n \" ResponseSchema(name=\\\"good_string\\\", description=\\\"This is your response, a reformatted response\\\")\\n\",\n \"]\\n\",\n \"\\n\",\n \"# How you would like to parse your output\\n\",\n \"output_parser = StructuredOutputParser.from_response_schemas(response_schemas)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 28,\n \"id\": \"d1079f0a\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"The output should be a markdown code snippet formatted in the following schema, including the leading and trailing \\\"```json\\\" and \\\"```\\\":\\n\",\n \"\\n\",\n \"```json\\n\",\n \"{\\n\",\n \"\\t\\\"bad_string\\\": string // This a poorly formatted user input string\\n\",\n \"\\t\\\"good_string\\\": string // This is your response, a reformatted response\\n\",\n \"}\\n\",\n \"```\\n\"\n ]\n }\n ],\n \"source\": [\n \"# See the prompt template you created for formatting\\n\",\n \"format_instructions = output_parser.get_format_instructions()\\n\",\n \"print (format_instructions)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 29,\n \"id\": \"9aaae5be\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"\\n\",\n \"You will be given a poorly formatted string from a user.\\n\",\n \"Reformat it and make sure all the words are spelled correctly\\n\",\n \"\\n\",\n \"The output should be a markdown code snippet formatted in the following schema, including the leading and trailing \\\"```json\\\" and \\\"```\\\":\\n\",\n \"\\n\",\n \"```json\\n\",\n \"{\\n\",\n \"\\t\\\"bad_string\\\": string // This a poorly formatted user input string\\n\",\n \"\\t\\\"good_string\\\": string // This is your response, a reformatted response\\n\",\n \"}\\n\",\n \"```\\n\",\n \"\\n\",\n \"% USER INPUT:\\n\",\n \"welcom to califonya!\\n\",\n \"\\n\",\n \"YOUR RESPONSE:\\n\",\n \"\\n\"\n ]\n }\n ],\n \"source\": [\n \"template = \\\"\\\"\\\"\\n\",\n \"You will be given a poorly formatted string from a user.\\n\",\n \"Reformat it and make sure all the words are spelled correctly\\n\",\n \"\\n\",\n \"{format_instructions}\\n\",\n \"\\n\",\n \"% USER INPUT:\\n\",\n \"{user_input}\\n\",\n \"\\n\",\n \"YOUR RESPONSE:\\n\",\n \"\\\"\\\"\\\"\\n\",\n \"\\n\",\n \"prompt = PromptTemplate(\\n\",\n \" input_variables=[\\\"user_input\\\"],\\n\",\n \" partial_variables={\\\"format_instructions\\\": format_instructions},\\n\",\n \" template=template\\n\",\n \")\\n\",\n \"\\n\",\n \"promptValue = prompt.format(user_input=\\\"welcom to califonya!\\\")\\n\",\n \"\\n\",\n \"print(promptValue)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 30,\n \"id\": \"b116bb23\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"'```json\\\\n{\\\\n\\\\t\\\"bad_string\\\": \\\"welcom to califonya!\\\", \\\\n\\\\t\\\"good_string\\\": \\\"Welcome to California!\\\"\\\\n}\\\\n```'\"\n ]\n },\n \"execution_count\": 30,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"llm_output = llm(promptValue)\\n\",\n \"llm_output\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 31,\n \"id\": \"985aa814\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"{'bad_string': 'welcom to califonya!', 'good_string': 'Welcome to California!'}\"\n ]\n },\n \"execution_count\": 31,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"output_parser.parse(llm_output)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"07045ae3\",\n \"metadata\": {},\n \"source\": [\n \"### **Output Parsers Method 2: OpenAI Fuctions**\\n\",\n \"When OpenAI released function calling, the game changed. This is recommended method when starting out.\\n\",\n \"\\n\",\n \"They trained models specifically for outputing structured data. It became super easy to specify a Pydantic schema and get a structured output.\\n\",\n \"\\n\",\n \"There are many ways to define your schema, I prefer using Pydantic Models because of how organized they are. Feel free to reference OpenAI's [documention](https://platform.openai.com/docs/guides/gpt/function-calling) for other methods.\\n\",\n \"\\n\",\n \"In order to use this method you'll need to use a model that supports [function calling](https://openai.com/blog/function-calling-and-other-api-updates#:~:text=Developers%20can%20now%20describe%20functions%20to%20gpt%2D4%2D0613%20and%20gpt%2D3.5%2Dturbo%2D0613%2C). I'll use `gpt4-0613`\\n\",\n \"\\n\",\n \"**Example 1: Simple**\\n\",\n \"\\n\",\n \"Let's get started by defining a simple model for us to extract from.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 32,\n \"id\": \"3593699b\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain.pydantic_v1 import BaseModel, Field\\n\",\n \"from typing import Optional\\n\",\n \"\\n\",\n \"class Person(BaseModel):\\n\",\n \" \\\"\\\"\\\"Identifying information about a person.\\\"\\\"\\\"\\n\",\n \"\\n\",\n \" name: str = Field(..., description=\\\"The person's name\\\")\\n\",\n \" age: int = Field(..., description=\\\"The person's age\\\")\\n\",\n \" fav_food: Optional[str] = Field(None, description=\\\"The person's favorite food\\\")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"17033d15\",\n \"metadata\": {},\n \"source\": [\n \"Then let's create a chain (more on this later) that will do the extracting for us\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 33,\n \"id\": \"60b7be09\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"Person(name='Sally, Joey, Caroline', age=13, fav_food='spinach')\"\n ]\n },\n \"execution_count\": 33,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"from langchain.chains.openai_functions import create_structured_output_chain\\n\",\n \"\\n\",\n \"llm = ChatOpenAI(model='gpt-4-0613', openai_api_key=openai_api_key)\\n\",\n \"\\n\",\n \"chain = create_structured_output_chain(Person, llm, prompt)\\n\",\n \"chain.run(\\n\",\n \" \\\"Sally is 13, Joey just turned 12 and loves spinach. Caroline is 10 years older than Sally.\\\"\\n\",\n \")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"37370210\",\n \"metadata\": {},\n \"source\": [\n \"Notice how we only have data on one person from that list? That is because we didn't specify we wanted multiple. Let's change our schema to specify that we want a list of people if possible.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 34,\n \"id\": \"df4ad5e6\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from typing import Sequence\\n\",\n \"\\n\",\n \"class People(BaseModel):\\n\",\n \" \\\"\\\"\\\"Identifying information about all people in a text.\\\"\\\"\\\"\\n\",\n \"\\n\",\n \" people: Sequence[Person] = Field(..., description=\\\"The people in the text\\\")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"aa2bc127\",\n \"metadata\": {},\n \"source\": [\n \"Now we'll call for People rather than Person\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 35,\n \"id\": \"5ba430d5\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"People(people=[Person(name='Sally', age=13, fav_food=None), Person(name='Joey', age=12, fav_food='spinach'), Person(name='Caroline', age=23, fav_food=None)])\"\n ]\n },\n \"execution_count\": 35,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"chain = create_structured_output_chain(People, llm, prompt)\\n\",\n \"chain.run(\\n\",\n \" \\\"Sally is 13, Joey just turned 12 and loves spinach. Caroline is 10 years older than Sally.\\\"\\n\",\n \")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"12db9b8b\",\n \"metadata\": {},\n \"source\": [\n \"Let's do some more parsing with it\\n\",\n \"\\n\",\n \"**Example 2: Enum**\\n\",\n \"\\n\",\n \"Now let's parse when a product from a list is mentioned\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 36,\n \"id\": \"6616a735\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"import enum\\n\",\n \"\\n\",\n \"llm = ChatOpenAI(model='gpt-4-0613', openai_api_key=openai_api_key)\\n\",\n \"\\n\",\n \"class Product(str, enum.Enum):\\n\",\n \" CRM = \\\"CRM\\\"\\n\",\n \" VIDEO_EDITING = \\\"VIDEO_EDITING\\\"\\n\",\n \" HARDWARE = \\\"HARDWARE\\\"\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 37,\n \"id\": \"a5250ff5\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"class Products(BaseModel):\\n\",\n \" \\\"\\\"\\\"Identifying products that were mentioned in a text\\\"\\\"\\\"\\n\",\n \"\\n\",\n \" products: Sequence[Product] = Field(..., description=\\\"The products mentioned in a text\\\")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 38,\n \"id\": \"dd7e0bbf\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"Products(products=[, , ])\"\n ]\n },\n \"execution_count\": 38,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"chain = create_structured_output_chain(Products, llm, prompt)\\n\",\n \"chain.run(\\n\",\n \" \\\"The CRM in this demo is great. Love the hardware. The microphone is also cool. Love the video editing\\\"\\n\",\n \")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"7b43cec2\",\n \"metadata\": {},\n \"source\": [\n \"## Indexes - Structuring documents to LLMs can work with them\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"d3f904e9\",\n \"metadata\": {},\n \"source\": [\n \"### **Document Loaders**\\n\",\n \"Easy ways to import data from other sources. Shared functionality with [OpenAI Plugins](https://openai.com/blog/chatgpt-plugins) [specifically retrieval plugins](https://github.com/openai/chatgpt-retrieval-plugin)\\n\",\n \"\\n\",\n \"See a [big list](https://python.langchain.com/en/latest/modules/indexes/document_loaders.html) of document loaders here. A bunch more on [Llama Index](https://llamahub.ai/) as well.\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"7d4719d4\",\n \"metadata\": {},\n \"source\": [\n \"**HackerNews**\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 39,\n \"id\": \"ba88e05b\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain.document_loaders import HNLoader\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 40,\n \"id\": \"ee693520\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"loader = HNLoader(\\\"https://news.ycombinator.com/item?id=34422627\\\")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 41,\n \"id\": \"88d89ad7\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"data = loader.load()\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 42,\n \"id\": \"e814f930\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"Found 76 comments\\n\",\n \"Here's a sample:\\n\",\n \"\\n\",\n \"Ozzie_osman 8 months ago \\n\",\n \" | next [–] \\n\",\n \"\\n\",\n \"LangChain is awesome. For people not sure what it's doing, large language models (LLMs) are very Ozzie_osman 8 months ago \\n\",\n \" | parent | next [–] \\n\",\n \"\\n\",\n \"Also, another library to check out is GPT Index (https://github.com/jerryjliu/gpt_index)\\n\"\n ]\n }\n ],\n \"source\": [\n \"print (f\\\"Found {len(data)} comments\\\")\\n\",\n \"print (f\\\"Here's a sample:\\\\n\\\\n{''.join([x.page_content[:150] for x in data[:2]])}\\\")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"c564583f\",\n \"metadata\": {},\n \"source\": [\n \"**Books from Gutenberg Project**\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 43,\n \"id\": \"72964fb8\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain.document_loaders import GutenbergLoader\\n\",\n \"\\n\",\n \"loader = GutenbergLoader(\\\"https://www.gutenberg.org/cache/epub/2148/pg2148.txt\\\")\\n\",\n \"\\n\",\n \"data = loader.load()\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 44,\n \"id\": \"47140a26\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \" At Paris, just after dark one gusty evening in the autumn of 18-,\\r\\n\",\n \"\\n\",\n \"\\n\",\n \" I was enjoying the twofold luxury of meditation \\n\"\n ]\n }\n ],\n \"source\": [\n \"print(data[0].page_content[1855:1984])\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"7f1386b0\",\n \"metadata\": {},\n \"source\": [\n \"**URLs and webpages**\\n\",\n \"\\n\",\n \"Let's try it out with [Paul Graham's website](http://www.paulgraham.com/)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 45,\n \"id\": \"46a54e7d\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"'New: \\\\n\\\\nHow to Do Great Work |\\\\nRead |\\\\nWill |\\\\nTruth\\\\n\\\\n\\\\n\\\\n\\\\n\\\\nWant to start a startup? Get funded by Y Combinator.\\\\n\\\\n\\\\n\\\\n\\\\n\\\\n\\\\n\\\\n\\\\n\\\\n© mmxxiii pg'\"\n ]\n },\n \"execution_count\": 45,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"from langchain.document_loaders import UnstructuredURLLoader\\n\",\n \"\\n\",\n \"urls = [\\n\",\n \" \\\"http://www.paulgraham.com/\\\",\\n\",\n \"]\\n\",\n \"\\n\",\n \"loader = UnstructuredURLLoader(urls=urls)\\n\",\n \"\\n\",\n \"data = loader.load()\\n\",\n \"\\n\",\n \"data[0].page_content\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"0e9601db\",\n \"metadata\": {},\n \"source\": [\n \"### **Text Splitters**\\n\",\n \"Often times your document is too long (like a book) for your LLM. You need to split it up into chunks. Text splitters help with this.\\n\",\n \"\\n\",\n \"There are many ways you could split your text into chunks, experiment with [different ones](https://python.langchain.com/en/latest/modules/indexes/text_splitters.html) to see which is best for you.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 46,\n \"id\": \"95713e57\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain.text_splitter import RecursiveCharacterTextSplitter\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 47,\n \"id\": \"a54455f5\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"You have 1 document\\n\"\n ]\n }\n ],\n \"source\": [\n \"# This is a long document we can split up.\\n\",\n \"with open('data/PaulGrahamEssays/worked.txt') as f:\\n\",\n \" pg_work = f.read()\\n\",\n \" \\n\",\n \"print (f\\\"You have {len([pg_work])} document\\\")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 48,\n \"id\": \"d19acb18\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"text_splitter = RecursiveCharacterTextSplitter(\\n\",\n \" # Set a really small chunk size, just to show.\\n\",\n \" chunk_size = 150,\\n\",\n \" chunk_overlap = 20,\\n\",\n \")\\n\",\n \"\\n\",\n \"texts = text_splitter.create_documents([pg_work])\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 49,\n \"id\": \"e3090f05\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"You have 610 documents\\n\"\n ]\n }\n ],\n \"source\": [\n \"print (f\\\"You have {len(texts)} documents\\\")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 50,\n \"id\": \"87a0f45a\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"Preview:\\n\",\n \"February 2021Before college the two main things I worked on, outside of school,\\n\",\n \"were writing and programming. I didn't write essays. I wrote what \\n\",\n \"\\n\",\n \"beginning writers were supposed to write then, and probably still\\n\",\n \"are: short stories. My stories were awful. They had hardly any plot,\\n\"\n ]\n }\n ],\n \"source\": [\n \"print (\\\"Preview:\\\")\\n\",\n \"print (texts[0].page_content, \\\"\\\\n\\\")\\n\",\n \"print (texts[1].page_content)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"ad9e670d\",\n \"metadata\": {},\n \"source\": [\n \"There are a ton of different ways to do text splitting and it really depends on your retrieval strategy and application design. Check out more splitters [here](https://python.langchain.com/docs/modules/data_connection/document_transformers/)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"1f85defb\",\n \"metadata\": {},\n \"source\": [\n \"### **Retrievers**\\n\",\n \"Easy way to combine documents with language models.\\n\",\n \"\\n\",\n \"There are many different types of retrievers, the most widely supported is the VectoreStoreRetriever\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 51,\n \"id\": \"8cccbd82\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain.document_loaders import TextLoader\\n\",\n \"from langchain.text_splitter import RecursiveCharacterTextSplitter\\n\",\n \"from langchain.vectorstores import FAISS\\n\",\n \"from langchain.embeddings import OpenAIEmbeddings\\n\",\n \"\\n\",\n \"loader = TextLoader('data/PaulGrahamEssays/worked.txt')\\n\",\n \"documents = loader.load()\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 52,\n \"id\": \"1dab1c20\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# Get your splitter ready\\n\",\n \"text_splitter = RecursiveCharacterTextSplitter(chunk_size=1000, chunk_overlap=50)\\n\",\n \"\\n\",\n \"# Split your docs into texts\\n\",\n \"texts = text_splitter.split_documents(documents)\\n\",\n \"\\n\",\n \"# Get embedding engine ready\\n\",\n \"embeddings = OpenAIEmbeddings(openai_api_key=openai_api_key)\\n\",\n \"\\n\",\n \"# Embedd your texts\\n\",\n \"db = FAISS.from_documents(texts, embeddings)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 53,\n \"id\": \"e62372be\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# Init your retriever. Asking for just 1 document back\\n\",\n \"retriever = db.as_retriever()\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 54,\n \"id\": \"e0534bbd\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"VectorStoreRetriever(tags=['FAISS'], vectorstore=)\"\n ]\n },\n \"execution_count\": 54,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"retriever\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 55,\n \"id\": \"3846a3b5\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"docs = retriever.get_relevant_documents(\\\"what types of things did the author want to build?\\\")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 56,\n \"id\": \"db383cc8\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"standards; what was the point? No one else wanted one either, so\\n\",\n \"off they went. That was what happened to systems work.I wanted not just to build things, but to build things that would\\n\",\n \"last.In this di\\n\",\n \"\\n\",\n \"much of it in grad school.Computer Science is an uneasy alliance between two halves, theory\\n\",\n \"and systems. The theory people prove things, and the systems people\\n\",\n \"build things. I wanted to build things. \\n\"\n ]\n }\n ],\n \"source\": [\n \"print(\\\"\\\\n\\\\n\\\".join([x.page_content[:200] for x in docs[:2]]))\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"24193139\",\n \"metadata\": {},\n \"source\": [\n \"### **VectorStores**\\n\",\n \"Databases to store vectors. Most popular ones are [Pinecone](https://www.pinecone.io/) & [Weaviate](https://weaviate.io/). More examples on OpenAIs [retriever documentation](https://github.com/openai/chatgpt-retrieval-plugin#choosing-a-vector-database). [Chroma](https://www.trychroma.com/) & [FAISS](https://engineering.fb.com/2017/03/29/data-infrastructure/faiss-a-library-for-efficient-similarity-search/) are easy to work with locally.\\n\",\n \"\\n\",\n \"Conceptually, think of them as tables w/ a column for embeddings (vectors) and a column for metadata.\\n\",\n \"\\n\",\n \"Example\\n\",\n \"\\n\",\n \"| Embedding | Metadata |\\n\",\n \"| ----------- | ----------- |\\n\",\n \"| [-0.00015641732898075134, -0.003165106289088726, ...] | {'date' : '1/2/23} |\\n\",\n \"| [-0.00035465431654651654, 1.4654131651654516546, ...] | {'date' : '1/3/23} |\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 57,\n \"id\": \"3c5533ad\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain.document_loaders import TextLoader\\n\",\n \"from langchain.text_splitter import RecursiveCharacterTextSplitter\\n\",\n \"from langchain.vectorstores import FAISS\\n\",\n \"from langchain.embeddings import OpenAIEmbeddings\\n\",\n \"\\n\",\n \"loader = TextLoader('data/PaulGrahamEssays/worked.txt')\\n\",\n \"documents = loader.load()\\n\",\n \"\\n\",\n \"# Get your splitter ready\\n\",\n \"text_splitter = RecursiveCharacterTextSplitter(chunk_size=1000, chunk_overlap=50)\\n\",\n \"\\n\",\n \"# Split your docs into texts\\n\",\n \"texts = text_splitter.split_documents(documents)\\n\",\n \"\\n\",\n \"# Get embedding engine ready\\n\",\n \"embeddings = OpenAIEmbeddings(openai_api_key=openai_api_key)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 58,\n \"id\": \"661fdf19\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"You have 78 documents\\n\"\n ]\n }\n ],\n \"source\": [\n \"print (f\\\"You have {len(texts)} documents\\\")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 59,\n \"id\": \"e99ac0ea\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"embedding_list = embeddings.embed_documents([text.page_content for text in texts])\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 60,\n \"id\": \"89e7758c\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"You have 78 embeddings\\n\",\n \"Here's a sample of one: [-0.001058628615053026, -0.01118234211553424, -0.012874804746266883]...\\n\"\n ]\n }\n ],\n \"source\": [\n \"print (f\\\"You have {len(embedding_list)} embeddings\\\")\\n\",\n \"print (f\\\"Here's a sample of one: {embedding_list[0][:3]}...\\\")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"8ac358c5\",\n \"metadata\": {},\n \"source\": [\n \"Your vectorstore store your embeddings (☝️) and make them easily searchable\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"f9b9b79b\",\n \"metadata\": {},\n \"source\": [\n \"## Memory\\n\",\n \"Helping LLMs remember information.\\n\",\n \"\\n\",\n \"Memory is a bit of a loose term. It could be as simple as remembering information you've chatted about in the past or more complicated information retrieval.\\n\",\n \"\\n\",\n \"We'll keep it towards the Chat Message use case. This would be used for chat bots.\\n\",\n \"\\n\",\n \"There are many types of memory, explore [the documentation](https://python.langchain.com/en/latest/modules/memory/how_to_guides.html) to see which one fits your use case.\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"f43b49da\",\n \"metadata\": {},\n \"source\": [\n \"### Chat Message History\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 61,\n \"id\": \"893a18c1\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain.memory import ChatMessageHistory\\n\",\n \"from langchain.chat_models import ChatOpenAI\\n\",\n \"\\n\",\n \"chat = ChatOpenAI(temperature=0, openai_api_key=openai_api_key)\\n\",\n \"\\n\",\n \"history = ChatMessageHistory()\\n\",\n \"\\n\",\n \"history.add_ai_message(\\\"hi!\\\")\\n\",\n \"\\n\",\n \"history.add_user_message(\\\"what is the capital of france?\\\")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 62,\n \"id\": \"a2949fda\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"[AIMessage(content='hi!'),\\n\",\n \" HumanMessage(content='what is the capital of france?')]\"\n ]\n },\n \"execution_count\": 62,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"history.messages\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 63,\n \"id\": \"9b74d5cf\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"AIMessage(content='The capital of France is Paris.')\"\n ]\n },\n \"execution_count\": 63,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"ai_response = chat(history.messages)\\n\",\n \"ai_response\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 64,\n \"id\": \"529e168f\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"[AIMessage(content='hi!'),\\n\",\n \" HumanMessage(content='what is the capital of france?'),\\n\",\n \" AIMessage(content='The capital of France is Paris.')]\"\n ]\n },\n \"execution_count\": 64,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"history.add_ai_message(ai_response.content)\\n\",\n \"history.messages\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"f29fc79c\",\n \"metadata\": {},\n \"source\": [\n \"## Chains ⛓️⛓️⛓️\\n\",\n \"Combining different LLM calls and action automatically\\n\",\n \"\\n\",\n \"Ex: Summary #1, Summary #2, Summary #3 > Final Summary\\n\",\n \"\\n\",\n \"Check out [this video](https://www.youtube.com/watch?v=f9_BWhCI4Zo&t=2s) explaining different summarization chain types\\n\",\n \"\\n\",\n \"There are [many applications of chains](https://python.langchain.com/en/latest/modules/chains/how_to_guides.html) search to see which are best for your use case.\\n\",\n \"\\n\",\n \"We'll cover two of them:\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"c34ba415\",\n \"metadata\": {},\n \"source\": [\n \"### 1. Simple Sequential Chains\\n\",\n \"\\n\",\n \"Easy chains where you can use the output of an LLM as an input into another. Good for breaking up tasks (and keeping your LLM focused)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 65,\n \"id\": \"79fc0950\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain.llms import OpenAI\\n\",\n \"from langchain.chains import LLMChain\\n\",\n \"from langchain.prompts import PromptTemplate\\n\",\n \"from langchain.chains import SimpleSequentialChain\\n\",\n \"\\n\",\n \"llm = OpenAI(temperature=1, openai_api_key=openai_api_key)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 66,\n \"id\": \"43d4494a\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"template = \\\"\\\"\\\"Your job is to come up with a classic dish from the area that the users suggests.\\n\",\n \"% USER LOCATION\\n\",\n \"{user_location}\\n\",\n \"\\n\",\n \"YOUR RESPONSE:\\n\",\n \"\\\"\\\"\\\"\\n\",\n \"prompt_template = PromptTemplate(input_variables=[\\\"user_location\\\"], template=template)\\n\",\n \"\\n\",\n \"# Holds my 'location' chain\\n\",\n \"location_chain = LLMChain(llm=llm, prompt=prompt_template)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 67,\n \"id\": \"b6c8e00f\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"template = \\\"\\\"\\\"Given a meal, give a short and simple recipe on how to make that dish at home.\\n\",\n \"% MEAL\\n\",\n \"{user_meal}\\n\",\n \"\\n\",\n \"YOUR RESPONSE:\\n\",\n \"\\\"\\\"\\\"\\n\",\n \"prompt_template = PromptTemplate(input_variables=[\\\"user_meal\\\"], template=template)\\n\",\n \"\\n\",\n \"# Holds my 'meal' chain\\n\",\n \"meal_chain = LLMChain(llm=llm, prompt=prompt_template)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 68,\n \"id\": \"7e0b83f2\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"overall_chain = SimpleSequentialChain(chains=[location_chain, meal_chain], verbose=True)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 69,\n \"id\": \"7d19c64d\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"\\n\",\n \"\\n\",\n \"\\u001b[1m> Entering new SimpleSequentialChain chain...\\u001b[0m\\n\",\n \"\\u001b[36;1m\\u001b[1;3m\\n\",\n \"A classic dish from Rome is Spaghetti alla Carbonara, featuring egg, Parmesan cheese, black pepper, and pancetta or guanciale.\\u001b[0m\\n\",\n \"\\u001b[33;1m\\u001b[1;3m\\n\",\n \"Ingredients:\\n\",\n \"- 8oz spaghetti \\n\",\n \"- 4 tablespoons olive oil\\n\",\n \"- 4oz diced pancetta or guanciale\\n\",\n \"- 2 cloves garlic, minced\\n\",\n \"- 2 eggs, lightly beaten\\n\",\n \"- 2 tablespoons parsley, chopped \\n\",\n \"- ½ cup grated Parmesan \\n\",\n \"- Salt and black pepper to taste\\n\",\n \"\\n\",\n \"Instructions:\\n\",\n \"1. Bring a pot of salted water to a boil and add the spaghetti. Cook according to package directions. \\n\",\n \"2. Meanwhile, add the olive oil to a large skillet over medium-high heat. Add the diced pancetta and garlic, and cook until pancetta is browned and garlic is fragrant.\\n\",\n \"3. In a medium bowl, whisk together the eggs, parsley, Parmesan, and salt and pepper.\\n\",\n \"4. Drain the cooked spaghetti and add it to the skillet with the pancetta and garlic. Remove from heat and pour the egg mixture over the spaghetti, stirring to combine. \\n\",\n \"5. Serve the spaghetti alla carbonara with additional Parmesan cheese and black pepper.\\u001b[0m\\n\",\n \"\\n\",\n \"\\u001b[1m> Finished chain.\\u001b[0m\\n\"\n ]\n }\n ],\n \"source\": [\n \"review = overall_chain.run(\\\"Rome\\\")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"f6191bf5\",\n \"metadata\": {},\n \"source\": [\n \"### 2. Summarization Chain\\n\",\n \"\\n\",\n \"Easily run through long numerous documents and get a summary. Check out [this video](https://www.youtube.com/watch?v=f9_BWhCI4Zo) for other chain types besides map-reduce\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 70,\n \"id\": \"6f218c3e\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"\\n\",\n \"\\n\",\n \"\\u001b[1m> Entering new MapReduceDocumentsChain chain...\\u001b[0m\\n\",\n \"\\n\",\n \"\\n\",\n \"\\u001b[1m> Entering new LLMChain chain...\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3mWrite a concise summary of the following:\\n\",\n \"\\n\",\n \"\\n\",\n \"\\\"January 2017Because biographies of famous scientists tend to \\n\",\n \"edit out their mistakes, we underestimate the \\n\",\n \"degree of risk they were willing to take.\\n\",\n \"And because anything a famous scientist did that\\n\",\n \"wasn't a mistake has probably now become the\\n\",\n \"conventional wisdom, those choices don't\\n\",\n \"seem risky either.Biographies of Newton, for example, understandably focus\\n\",\n \"more on physics than alchemy or theology.\\n\",\n \"The impression we get is that his unerring judgment\\n\",\n \"led him straight to truths no one else had noticed.\\n\",\n \"How to explain all the time he spent on alchemy\\n\",\n \"and theology? Well, smart people are often kind of\\n\",\n \"crazy.But maybe there is a simpler explanation. Maybe\\\"\\n\",\n \"\\n\",\n \"\\n\",\n \"CONCISE SUMMARY:\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3mWrite a concise summary of the following:\\n\",\n \"\\n\",\n \"\\n\",\n \"\\\"the smartness and the craziness were not as separate\\n\",\n \"as we think. Physics seems to us a promising thing\\n\",\n \"to work on, and alchemy and theology obvious wastes\\n\",\n \"of time. But that's because we know how things\\n\",\n \"turned out. In Newton's day the three problems \\n\",\n \"seemed roughly equally promising. No one knew yet\\n\",\n \"what the payoff would be for inventing what we\\n\",\n \"now call physics; if they had, more people would \\n\",\n \"have been working on it. And alchemy and theology\\n\",\n \"were still then in the category Marc Andreessen would \\n\",\n \"describe as \\\"huge, if true.\\\"Newton made three bets. One of them worked. But \\n\",\n \"they were all risky.\\\"\\n\",\n \"\\n\",\n \"\\n\",\n \"CONCISE SUMMARY:\\u001b[0m\\n\",\n \"\\n\",\n \"\\u001b[1m> Finished chain.\\u001b[0m\\n\",\n \"\\n\",\n \"\\n\",\n \"\\u001b[1m> Entering new LLMChain chain...\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3mWrite a concise summary of the following:\\n\",\n \"\\n\",\n \"\\n\",\n \"\\\" Biographies of famous scientists often edit out their mistakes, giving readers the wrong impression that they never faced any risks to achieve successful results. An example of this is Newton, whose smartness is assumed to have led straight him to truths without any detours into alchemy or theology - despite the fact that he spent a lot of time on both fields. Maybe the simpler explanation is that he was willing to take risks, even if it means potentially making mistakes.\\n\",\n \"\\n\",\n \" In the 17th century, Newton took a risk and made three bets, one of which turned out to be a successful invention of what we now call physics. The other two bets were on less popular subjects of the time such as alchemy and theology. People did not know then what the payoff would be, but the bets still seemed relatively promising.\\\"\\n\",\n \"\\n\",\n \"\\n\",\n \"CONCISE SUMMARY:\\u001b[0m\\n\",\n \"\\n\",\n \"\\u001b[1m> Finished chain.\\u001b[0m\\n\",\n \"\\n\",\n \"\\u001b[1m> Finished chain.\\u001b[0m\\n\"\n ]\n },\n {\n \"data\": {\n \"text/plain\": [\n \"\\\" Biographies tend to omit famous scientists' mistakes from their stories, but Newton was willing to take risks and explore multiple fields to make his discoveries. He placed three risky bets, one of which resulted in the creation of physics as we know it today.\\\"\"\n ]\n },\n \"execution_count\": 70,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"from langchain.chains.summarize import load_summarize_chain\\n\",\n \"from langchain.document_loaders import TextLoader\\n\",\n \"from langchain.text_splitter import RecursiveCharacterTextSplitter\\n\",\n \"\\n\",\n \"loader = TextLoader('data/PaulGrahamEssays/disc.txt')\\n\",\n \"documents = loader.load()\\n\",\n \"\\n\",\n \"# Get your splitter ready\\n\",\n \"text_splitter = RecursiveCharacterTextSplitter(chunk_size=700, chunk_overlap=50)\\n\",\n \"\\n\",\n \"# Split your docs into texts\\n\",\n \"texts = text_splitter.split_documents(documents)\\n\",\n \"\\n\",\n \"# There is a lot of complexity hidden in this one line. I encourage you to check out the video above for more detail\\n\",\n \"chain = load_summarize_chain(llm, chain_type=\\\"map_reduce\\\", verbose=True)\\n\",\n \"chain.run(texts)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"84f6193c\",\n \"metadata\": {},\n \"source\": [\n \"## Agents 🤖🤖\\n\",\n \"\\n\",\n \"Official LangChain Documentation describes agents perfectly (emphasis mine):\\n\",\n \"> Some applications will require not just a predetermined chain of calls to LLMs/other tools, but potentially an **unknown chain** that depends on the user's input. In these types of chains, there is a “agent” which has access to a suite of tools. Depending on the user input, the agent can then **decide which, if any, of these tools to call**.\\n\",\n \"\\n\",\n \"\\n\",\n \"Basically you use the LLM not just for text output, but also for decision making. The coolness and power of this functionality can't be overstated enough.\\n\",\n \"\\n\",\n \"Sam Altman emphasizes that the LLMs are good '[reasoning engine](https://www.youtube.com/watch?v=L_Guz73e6fw&t=867s)'. Agent take advantage of this.\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"3ce05d51\",\n \"metadata\": {},\n \"source\": [\n \"### Agents\\n\",\n \"\\n\",\n \"The language model that drives decision making.\\n\",\n \"\\n\",\n \"More specifically, an agent takes in an input and returns a response corresponding to an action to take along with an action input. You can see different types of agents (which are better for different use cases) [here](https://python.langchain.com/en/latest/modules/agents/agents/agent_types.html).\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"f696b65c\",\n \"metadata\": {},\n \"source\": [\n \"### Tools\\n\",\n \"\\n\",\n \"A 'capability' of an agent. This is an abstraction on top of a function that makes it easy for LLMs (and agents) to interact with it. Ex: Google search.\\n\",\n \"\\n\",\n \"This area shares commonalities with [OpenAI plugins](https://platform.openai.com/docs/plugins/introduction).\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"a11f8231\",\n \"metadata\": {},\n \"source\": [\n \"### Toolkit\\n\",\n \"\\n\",\n \"Groups of tools that your agent can select from\\n\",\n \"\\n\",\n \"Let's bring them all together:\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 71,\n \"id\": \"67d5d82d\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain.agents import load_tools\\n\",\n \"from langchain.agents import initialize_agent\\n\",\n \"from langchain.llms import OpenAI\\n\",\n \"import json\\n\",\n \"\\n\",\n \"llm = OpenAI(temperature=0, openai_api_key=openai_api_key)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 72,\n \"id\": \"0ddcdbb9\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"serpapi_api_key=os.getenv(\\\"SERP_API_KEY\\\", \\\"YourAPIKey\\\")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 73,\n \"id\": \"44fad67f\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"toolkit = load_tools([\\\"serpapi\\\"], llm=llm, serpapi_api_key=serpapi_api_key)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 74,\n \"id\": \"f544a74b\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"agent = initialize_agent(toolkit, llm, agent=\\\"zero-shot-react-description\\\", verbose=True, return_intermediate_steps=True)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 75,\n \"id\": \"c4882754\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"\\n\",\n \"\\n\",\n \"\\u001b[1m> Entering new AgentExecutor chain...\\u001b[0m\\n\",\n \"\\u001b[32;1m\\u001b[1;3m I should try to find out what band Natalie Bergman is a part of.\\n\",\n \"Action: Search\\n\",\n \"Action Input: \\\"Natalie Bergman band\\\"\\u001b[0m\\n\",\n \"Observation: \\u001b[36;1m\\u001b[1;3m['Natalie Bergman is an American singer-songwriter. She is one half of the duo Wild Belle, along with her brother Elliot Bergman. Her debut solo album, Mercy, was released on Third Man Records on May 7, 2021. She is based in Los Angeles.', 'Natalie Bergman type: American singer-songwriter.', 'Natalie Bergman main_tab_text: Overview.', 'Natalie Bergman kgmid: /m/0qgx4kh.', 'Natalie Bergman genre: Folk.', 'Natalie Bergman parents: Susan Bergman, Judson Bergman.', 'Natalie Bergman born: 1988 or 1989 (age 34–35).', 'Natalie Bergman is an American singer-songwriter. She is one half of the duo Wild Belle, along with her brother Elliot Bergman. Her debut solo album, Mercy, ...']\\u001b[0m\\n\",\n \"Thought:\\u001b[32;1m\\u001b[1;3m I should search for the first album of Wild Belle\\n\",\n \"Action: Search\\n\",\n \"Action Input: \\\"Wild Belle first album\\\"\\u001b[0m\\n\",\n \"Observation: \\u001b[36;1m\\u001b[1;3mIsles\\u001b[0m\\n\",\n \"Thought:\\u001b[32;1m\\u001b[1;3m I now know the final answer\\n\",\n \"Final Answer: Isles is the first album of the band that Natalie Bergman is a part of.\\u001b[0m\\n\",\n \"\\n\",\n \"\\u001b[1m> Finished chain.\\u001b[0m\\n\"\n ]\n }\n ],\n \"source\": [\n \"response = agent({\\\"input\\\":\\\"what was the first album of the\\\" \\n\",\n \" \\\"band that Natalie Bergman is a part of?\\\"})\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"3f9c30d2\",\n \"metadata\": {},\n \"source\": [\n \"![Wild Belle](data/WildBelle1.png)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"14f4b368\",\n \"metadata\": {},\n \"source\": [\n \"🎵Enjoy🎵\\n\",\n \"https://open.spotify.com/track/1eREJIBdqeCcqNCB1pbz7w?si=c014293b63c7478c\"\n ]\n }\n ],\n \"metadata\": {\n \"kernelspec\": {\n \"display_name\": \"Python 3 (ipykernel)\",\n \"language\": \"python\",\n \"name\": \"python3\"\n },\n \"language_info\": {\n \"codemirror_mode\": {\n \"name\": \"ipython\",\n \"version\": 3\n },\n \"file_extension\": \".py\",\n \"mimetype\": \"text/x-python\",\n \"name\": \"python\",\n \"nbconvert_exporter\": \"python\",\n \"pygments_lexer\": \"ipython3\",\n \"version\": \"3.9.13\"\n }\n },\n \"nbformat\": 4,\n \"nbformat_minor\": 5\n}\n" }, { "path": "LangChain Cookbook Part 2 - Use Cases.ipynb", "content": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"id\": \"359697d5\",\n \"metadata\": {},\n \"source\": [\n \"# LangChain Cookbook Part 2: Use Cases👨‍🍳👩‍🍳\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"11d788b0\",\n \"metadata\": {},\n \"source\": [\n \"*This cookbook is based on the [LangChain Conceptual Documentation](https://docs.langchain.com/docs/)*\\n\",\n \"\\n\",\n \"**Goals:**\\n\",\n \"\\n\",\n \"1. Inspire you to build\\n\",\n \"2. Provide an introductory understanding of the main use cases of LangChain via [ELI5](https://www.dictionary.com/e/slang/eli5/#:~:text=ELI5%20is%20short%20for%20%E2%80%9CExplain,a%20complicated%20question%20or%20problem.) examples and code snippets. For an introduction to the *fundamentals* of LangChain check out [Cookbook Part 1: Fundamentals](https://github.com/gkamradt/langchain-tutorials/blob/main/LangChain%20Cookbook%20Part%201%20-%20Fundamentals.ipynb).\\n\",\n \"\\n\",\n \"**LangChain Links:**\\n\",\n \"* [LC Conceptual Documentation](https://docs.langchain.com/docs/)\\n\",\n \"* [LC Python Documentation](https://python.langchain.com/en/latest/)\\n\",\n \"* [LC Javascript/Typescript Documentation](https://js.langchain.com/docs/)\\n\",\n \"* [LC Discord](https://discord.gg/6adMQxSpJS)\\n\",\n \"* [www.langchain.com](https://langchain.com/)\\n\",\n \"* [LC Twitter](https://twitter.com/LangChainAI)\\n\",\n \"\\n\",\n \"\\n\",\n \"### **What is LangChain?**\\n\",\n \"> LangChain is a framework for developing applications powered by language models.\\n\",\n \"*[Source](https://blog.langchain.dev/announcing-our-10m-seed-round-led-by-benchmark/#:~:text=LangChain%20is%20a%20framework%20for%20developing%20applications%20powered%20by%20language%20models)*\\n\",\n \"\\n\",\n \"**TLDR**: LangChain makes the complicated parts of working & building with AI models easier. It helps do this in two ways:\\n\",\n \"\\n\",\n \"1. **Integration** - Bring external data, such as your files, other applications, and api data, to your LLMs\\n\",\n \"2. **Agency** - Allow your LLMs to interact with its environment via decision making. Use LLMs to help decide which action to take next\\n\",\n \"\\n\",\n \"### **Why LangChain?**\\n\",\n \"1. **Components** - LangChain makes it easy to swap out abstractions and components necessary to work with language models.\\n\",\n \"\\n\",\n \"2. **Customized Chains** - LangChain provides out of the box support for using and customizing 'chains' - a series of actions strung together.\\n\",\n \"\\n\",\n \"3. **Speed 🚢** - This team ships insanely fast. You'll be up to date with the latest LLM features.\\n\",\n \"\\n\",\n \"4. **Community 👥** - Wonderful [discord](https://discord.gg/6adMQxSpJS) and community support, meet ups, hackathons, etc.\\n\",\n \"\\n\",\n \"Though LLMs can be straightforward (text-in, text-out) you'll quickly run into friction points that LangChain helps with once you develop more complicated applications.\\n\",\n \"\\n\",\n \"### **Main Use Cases**\\n\",\n \"\\n\",\n \"* **Summarization** - Express the most important facts about a body of text or chat interaction\\n\",\n \"* **Question and Answering Over Documents** - Use information held within documents to answer questions or query\\n\",\n \"* **Extraction** - Pull structured data from a body of text or an user query\\n\",\n \"* **Evaluation** - Understand the quality of output from your application\\n\",\n \"* **Querying Tabular Data** - Pull data from databases or other tabular source\\n\",\n \"* **Code Understanding** - Reason about and digest code\\n\",\n \"* **Interacting with APIs** - Query APIs and interact with the outside world\\n\",\n \"* **Chatbots** - A framework to have a back and forth interaction with a user combined with memory in a chat interface\\n\",\n \"* **Agents** - Use LLMs to make decisions about what to do next. Enable these decisions with tools.\\n\",\n \"\\n\",\n \"Want to see live examples of these use cases? Head over to the [LangChain Project Gallery](https://github.com/gkamradt/langchain-tutorials)\\n\",\n \"\\n\",\n \"#### **Authors Note:**\\n\",\n \"\\n\",\n \"* This cookbook will not cover all aspects of LangChain. It's contents have been curated to get you to building & impact as quick as possible. For more, please check out [LangChain Technical Documentation](https://python.langchain.com/en/latest/index.html)\\n\",\n \"* This notebook assumes is that you've seen part 1 of this series [Fundamentals](https://github.com/gkamradt/langchain-tutorials/blob/main/LangChain%20Cookbook%20Part%201%20-%20Fundamentals.ipynb). This notebook is focused on what to do and how to apply those fundamentals.\\n\",\n \"* You'll notice I repeat import statements throughout the notebook. My intention is to lean on the side of clarity and help you see the full code block in one spot. No need to go back and forth to see when we imported a package.\\n\",\n \"* We use the default models throughout the notebook, at the time of writing they were davinci-003 and gpt-3.5-turbo. You would no doubt get better results with GPT4\\n\",\n \"\\n\",\n \"Let's get started\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"8e323fb6\",\n \"metadata\": {},\n \"source\": [\n \"Throughout this tutorial we will use OpenAI's various [models](https://platform.openai.com/docs/models/overview). LangChain makes it easy to [subsistute LLMs](https://langchain.com/integrations.html#:~:text=integrations%20LangChain%20provides.-,LLMs,-LLM%20Provider) so you can BYO-LLM if you want\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 1,\n \"id\": \"e9815081\",\n \"metadata\": {\n \"hide_input\": false\n },\n \"outputs\": [],\n \"source\": [\n \"from dotenv import load_dotenv\\n\",\n \"import os\\n\",\n \"\\n\",\n \"load_dotenv()\\n\",\n \"\\n\",\n \"openai_api_key = os.getenv('OPENAI_API_KEY', 'YourAPIKeyIfNotSet')\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 2,\n \"id\": \"dcd3587c\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/html\": [\n \"\"\n ],\n \"text/plain\": [\n \"\"\n ]\n },\n \"metadata\": {},\n \"output_type\": \"display_data\"\n }\n ],\n \"source\": [\n \"# Run this cell if you want to make your display wider\\n\",\n \"from IPython.display import display, HTML\\n\",\n \"display(HTML(\\\"\\\"))\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"05bb564d\",\n \"metadata\": {},\n \"source\": [\n \"# LangChain Use Cases\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"1bbdb1dc\",\n \"metadata\": {},\n \"source\": [\n \"## Summarization\\n\",\n \"\\n\",\n \"One of the most common use cases for LangChain and LLMs is summarization. You can summarize any piece of text, but use cases span from summarizing calls, articles, books, academic papers, legal documents, user history, a table, or financial documents. It's super helpful to have a tool which can summarize information quickly.\\n\",\n \"\\n\",\n \"* **Deep Dive** - (Coming Soon)\\n\",\n \"* **Examples** - [Summarizing B2B Sales Calls](https://www.youtube.com/watch?v=DIw4rbpI9ic)\\n\",\n \"* **Use Cases** - Summarize Articles, Transcripts, Chat History, Slack/Discord, Customer Interactions, Medical Papers, Legal Documents, Podcasts, Tweet Threads, Code Bases, Product Reviews, Financial Documents\\n\",\n \"\\n\",\n \"### Summaries Of Short Text\\n\",\n \"\\n\",\n \"For summaries of short texts, the method is straightforward, in fact you don't need to do anything fancy other than simple prompting with instructions\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 3,\n \"id\": \"0c292592\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain.llms import OpenAI\\n\",\n \"from langchain import PromptTemplate\\n\",\n \"\\n\",\n \"# Note, the default model is already 'text-davinci-003' but I call it out here explicitly so you know where to change it later if you want\\n\",\n \"llm = OpenAI(temperature=0, model_name='text-davinci-003', openai_api_key=openai_api_key)\\n\",\n \"\\n\",\n \"# Create our template\\n\",\n \"template = \\\"\\\"\\\"\\n\",\n \"%INSTRUCTIONS:\\n\",\n \"Please summarize the following piece of text.\\n\",\n \"Respond in a manner that a 5 year old would understand.\\n\",\n \"\\n\",\n \"%TEXT:\\n\",\n \"{text}\\n\",\n \"\\\"\\\"\\\"\\n\",\n \"\\n\",\n \"# Create a LangChain prompt template that we can insert values to later\\n\",\n \"prompt = PromptTemplate(\\n\",\n \" input_variables=[\\\"text\\\"],\\n\",\n \" template=template,\\n\",\n \")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"f539cb53\",\n \"metadata\": {},\n \"source\": [\n \"Let's let's find a confusing text online. *[Source](https://www.smithsonianmag.com/smart-news/long-before-trees-overtook-the-land-earth-was-covered-by-giant-mushrooms-13709647/)*\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 4,\n \"id\": \"0df2cde6\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"confusing_text = \\\"\\\"\\\"\\n\",\n \"For the next 130 years, debate raged.\\n\",\n \"Some scientists called Prototaxites a lichen, others a fungus, and still others clung to the notion that it was some kind of tree.\\n\",\n \"“The problem is that when you look up close at the anatomy, it’s evocative of a lot of different things, but it’s diagnostic of nothing,” says Boyce, an associate professor in geophysical sciences and the Committee on Evolutionary Biology.\\n\",\n \"“And it’s so damn big that when whenever someone says it’s something, everyone else’s hackles get up: ‘How could you have a lichen 20 feet tall?’”\\n\",\n \"\\\"\\\"\\\"\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"03d31842\",\n \"metadata\": {},\n \"source\": [\n \"Let's take a look at what prompt will be sent to the LLM\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 5,\n \"id\": \"406eb8a3\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"------- Prompt Begin -------\\n\",\n \"\\n\",\n \"%INSTRUCTIONS:\\n\",\n \"Please summarize the following piece of text.\\n\",\n \"Respond in a manner that a 5 year old would understand.\\n\",\n \"\\n\",\n \"%TEXT:\\n\",\n \"\\n\",\n \"For the next 130 years, debate raged.\\n\",\n \"Some scientists called Prototaxites a lichen, others a fungus, and still others clung to the notion that it was some kind of tree.\\n\",\n \"“The problem is that when you look up close at the anatomy, it’s evocative of a lot of different things, but it’s diagnostic of nothing,” says Boyce, an associate professor in geophysical sciences and the Committee on Evolutionary Biology.\\n\",\n \"“And it’s so damn big that when whenever someone says it’s something, everyone else’s hackles get up: ‘How could you have a lichen 20 feet tall?’”\\n\",\n \"\\n\",\n \"\\n\",\n \"------- Prompt End -------\\n\"\n ]\n }\n ],\n \"source\": [\n \"print (\\\"------- Prompt Begin -------\\\")\\n\",\n \"\\n\",\n \"final_prompt = prompt.format(text=confusing_text)\\n\",\n \"print(final_prompt)\\n\",\n \"\\n\",\n \"print (\\\"------- Prompt End -------\\\")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"a95e53d9\",\n \"metadata\": {},\n \"source\": [\n \"Finally let's pass it through the LLM\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 6,\n \"id\": \"bc7e4b42\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"\\n\",\n \"For 130 years, people argued about what Prototaxites was. Some thought it was a lichen, some thought it was a fungus, and some thought it was a tree. But no one could agree. It was so big that it was hard to figure out what it was.\\n\"\n ]\n }\n ],\n \"source\": [\n \"output = llm(final_prompt)\\n\",\n \"print (output)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"751c6359\",\n \"metadata\": {},\n \"source\": [\n \"This method works fine, but for longer text, it can become a pain to manage and you'll run into token limits. Luckily LangChain has out of the box support for different methods to summarize via their [load_summarize_chain](https://python.langchain.com/en/latest/use_cases/summarization.html).\\n\",\n \"\\n\",\n \"### Summaries Of Longer Text\\n\",\n \"\\n\",\n \"*Note: This method will also work for short text too*\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 7,\n \"id\": \"3441484b\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain.llms import OpenAI\\n\",\n \"from langchain.chains.summarize import load_summarize_chain\\n\",\n \"from langchain.text_splitter import RecursiveCharacterTextSplitter\\n\",\n \"\\n\",\n \"llm = OpenAI(temperature=0, openai_api_key=openai_api_key)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"e95b575c\",\n \"metadata\": {},\n \"source\": [\n \"Let's load up a longer document\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 8,\n \"id\": \"6c33f9bb\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"April 2008(This essay is derived from a talk at the 2008 Startup School.)About a month after we started Y Combinator we came up with the\\n\",\n \"phrase that became our motto: Make something people want. We've\\n\",\n \"learned a lot since then, but if I were choosing now that's still\\n\",\n \"the one I'd pick.\\n\"\n ]\n }\n ],\n \"source\": [\n \"with open('data/PaulGrahamEssays/good.txt', 'r') as file:\\n\",\n \" text = file.read()\\n\",\n \"\\n\",\n \"# Printing the first 285 characters as a preview\\n\",\n \"print (text[:285])\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"b489d2a2\",\n \"metadata\": {},\n \"source\": [\n \"Then let's check how many tokens are in this document. [get_num_tokens](https://python.langchain.com/en/latest/reference/modules/llms.html#langchain.llms.OpenAI.get_num_tokens) is a nice method for this.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 9,\n \"id\": \"5e0e8181\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"There are 3970 tokens in your file\\n\"\n ]\n }\n ],\n \"source\": [\n \"num_tokens = llm.get_num_tokens(text)\\n\",\n \"\\n\",\n \"print (f\\\"There are {num_tokens} tokens in your file\\\")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"5bf8eda6\",\n \"metadata\": {},\n \"source\": [\n \"While you could likely stuff this text in your prompt, let's act like it's too big and needs another method.\\n\",\n \"\\n\",\n \"First we'll need to split it up. This process is called 'chunking' or 'splitting' your text into smaller pieces. I like the [RecursiveCharacterTextSplitter](https://python.langchain.com/en/latest/modules/indexes/text_splitters/examples/recursive_text_splitter.html) because it's easy to control but there are a [bunch](https://python.langchain.com/en/latest/modules/indexes/text_splitters.html) you can try\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 10,\n \"id\": \"25dd80dc\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"You now have 4 docs intead of 1 piece of text\\n\"\n ]\n }\n ],\n \"source\": [\n \"text_splitter = RecursiveCharacterTextSplitter(separators=[\\\"\\\\n\\\\n\\\", \\\"\\\\n\\\"], chunk_size=5000, chunk_overlap=350)\\n\",\n \"docs = text_splitter.create_documents([text])\\n\",\n \"\\n\",\n \"print (f\\\"You now have {len(docs)} docs intead of 1 piece of text\\\")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"3e7547a3\",\n \"metadata\": {},\n \"source\": [\n \"Next we need to load up a chain which will make successive calls to the LLM for us. Want to see the prompt being used in the chain below? Check out the [LangChain documentation](https://github.com/hwchase17/langchain/blob/master/langchain/chains/summarize/map_reduce_prompt.py)\\n\",\n \"\\n\",\n \"For information on the difference between chain types, check out this video on [token limit workarounds](https://youtu.be/f9_BWhCI4Zo)\\n\",\n \"\\n\",\n \"*Note: You could also get fancy and make the first 4 calls of the map_reduce run in parallel too*\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 11,\n \"id\": \"28ddd9c0\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# Get your chain ready to use\\n\",\n \"chain = load_summarize_chain(llm=llm, chain_type='map_reduce') # verbose=True optional to see what is getting sent to the LLM\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 12,\n \"id\": \"be0b2d04\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \" This essay looks at the idea of benevolence in startups, and how it can help them succeed. It explains how benevolence can improve morale, make people want to help, and help startups be decisive. It also looks at how markets have evolved to value potential dividends and potential earnings, and how users dislike their new operating system. The author argues that starting a company with benevolent aims is currently undervalued, and that Y Combinator's motto of \\\"Make something people want\\\" is a powerful concept.\\n\"\n ]\n }\n ],\n \"source\": [\n \"# Use it. This will run through the 4 documents, summarize the chunks, then get a summary of the summary.\\n\",\n \"output = chain.run(docs)\\n\",\n \"print (output)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"a2d664fc\",\n \"metadata\": {},\n \"source\": [\n \"## Question & Answering Using Documents As Context\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"ad87c72b\",\n \"metadata\": {},\n \"source\": [\n \"*[LangChain Question & Answer Docs](https://python.langchain.com/en/latest/use_cases/question_answering.html)*\\n\",\n \"\\n\",\n \"In order to use LLMs for question and answer we must:\\n\",\n \"\\n\",\n \"1. Pass the LLM relevant context it needs to answer a question\\n\",\n \"2. Pass it our question that we want answered\\n\",\n \"\\n\",\n \"Simplified, this process looks like this \\\"llm(your context + your question) = your answer\\\"\\n\",\n \"\\n\",\n \"* **Deep Dive** - [Question A Book](https://youtu.be/h0DHDp1FbmQ), [Ask Questions To Your Custom Files](https://youtu.be/EnT-ZTrcPrg), [Chat Your Data JS (1000 pages of Financial Reports)](https://www.youtube.com/watch?v=Ix9WIZpArm0&t=1051s), [LangChain Q&A webinar](https://www.crowdcast.io/c/rh66hcwivly0)\\n\",\n \"* **Examples** - [ChatPDF](https://www.chatpdf.com/)\\n\",\n \"* **Use Cases** - Chat your documents, ask questions to academic papers, create study guides, reference medical information\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"685e15f3\",\n \"metadata\": {},\n \"source\": [\n \"### Simple Q&A Example\\n\",\n \"\\n\",\n \"Here let's review the convention of `llm(your context + your question) = your answer`\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 13,\n \"id\": \"9ebd8451\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain.llms import OpenAI\\n\",\n \"\\n\",\n \"llm = OpenAI(temperature=0, openai_api_key=openai_api_key)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 14,\n \"id\": \"b4795187\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"context = \\\"\\\"\\\"\\n\",\n \"Rachel is 30 years old\\n\",\n \"Bob is 45 years old\\n\",\n \"Kevin is 65 years old\\n\",\n \"\\\"\\\"\\\"\\n\",\n \"\\n\",\n \"question = \\\"Who is under 40 years old?\\\"\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"2184b11b\",\n \"metadata\": {},\n \"source\": [\n \"Then combine them.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 15,\n \"id\": \"0c53650d\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"Rachel is under 40 years old.\\n\"\n ]\n }\n ],\n \"source\": [\n \"output = llm(context + question)\\n\",\n \"\\n\",\n \"# I strip the text to remove the leading and trailing whitespace\\n\",\n \"print (output.strip())\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"385180ca\",\n \"metadata\": {},\n \"source\": [\n \"As we ramp up our sophistication, we'll take advantage of this convention more.\\n\",\n \"\\n\",\n \"The hard part comes in when you need to be selective about *which* data you put in your context. This field of study is called \\\"[document retrieval](https://python.langchain.com/en/latest/modules/indexes/retrievers.html)\\\" and tightly coupled with AI Memory.\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"53ed4080\",\n \"metadata\": {},\n \"source\": [\n \"### Using Embeddings\\n\",\n \"\\n\",\n \"I informally call what were about to go through as \\\"The VectorStore Dance\\\". It's the process of splitting your text, embedding the chunks, putting the embeddings in a DB, and then querying them. For a full video on this check out [How To Question A Book](https://www.youtube.com/watch?v=h0DHDp1FbmQ)\\n\",\n \"\\n\",\n \"The goal is to select relevant chunks of our long text, but which chunks do we pull? The most popular method is to pull *similar* texts based off comparing vector embeddings.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 16,\n \"id\": \"a7a02ccc\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain import OpenAI\\n\",\n \"\\n\",\n \"# The vectorstore we'll be using\\n\",\n \"from langchain.vectorstores import FAISS\\n\",\n \"\\n\",\n \"# The LangChain component we'll use to get the documents\\n\",\n \"from langchain.chains import RetrievalQA\\n\",\n \"\\n\",\n \"# The easy document loader for text\\n\",\n \"from langchain.document_loaders import TextLoader\\n\",\n \"\\n\",\n \"# The embedding engine that will convert our text to vectors\\n\",\n \"from langchain.embeddings.openai import OpenAIEmbeddings\\n\",\n \"\\n\",\n \"llm = OpenAI(temperature=0, openai_api_key=openai_api_key)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"40afcfec\",\n \"metadata\": {},\n \"source\": [\n \"Let's load up a longer document\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 17,\n \"id\": \"5772bc26\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"You have 1 document\\n\",\n \"You have 74663 characters in that document\\n\"\n ]\n }\n ],\n \"source\": [\n \"loader = TextLoader('data/PaulGrahamEssays/worked.txt')\\n\",\n \"doc = loader.load()\\n\",\n \"print (f\\\"You have {len(doc)} document\\\")\\n\",\n \"print (f\\\"You have {len(doc[0].page_content)} characters in that document\\\")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"fb87424c\",\n \"metadata\": {},\n \"source\": [\n \"Now let's split our long doc into smaller pieces\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 18,\n \"id\": \"b4a6e452\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"text_splitter = RecursiveCharacterTextSplitter(chunk_size=3000, chunk_overlap=400)\\n\",\n \"docs = text_splitter.split_documents(doc)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 19,\n \"id\": \"723e8aec\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"Now you have 29 documents that have an average of 2,930 characters (smaller pieces)\\n\"\n ]\n }\n ],\n \"source\": [\n \"# Get the total number of characters so we can see the average later\\n\",\n \"num_total_characters = sum([len(x.page_content) for x in docs])\\n\",\n \"\\n\",\n \"print (f\\\"Now you have {len(docs)} documents that have an average of {num_total_characters / len(docs):,.0f} characters (smaller pieces)\\\")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 20,\n \"id\": \"9b591198\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# Get your embeddings engine ready\\n\",\n \"embeddings = OpenAIEmbeddings(openai_api_key=openai_api_key)\\n\",\n \"\\n\",\n \"# Embed your documents and combine with the raw text in a pseudo db. Note: This will make an API call to OpenAI\\n\",\n \"docsearch = FAISS.from_documents(docs, embeddings)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"a1b13348\",\n \"metadata\": {},\n \"source\": [\n \"Create your retrieval engine\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 21,\n \"id\": \"47cd969d\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"qa = RetrievalQA.from_chain_type(llm=llm, chain_type=\\\"stuff\\\", retriever=docsearch.as_retriever())\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"6aa2963c\",\n \"metadata\": {},\n \"source\": [\n \"Now it's time to ask a question. The retriever will go get the similar documents and combine with your question for the LLM to reason through.\\n\",\n \"\\n\",\n \"Note: It may not seem like much, but the magic here is that we didn't have to pass in our full original document.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 22,\n \"id\": \"6a062c85\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"' The author describes painting as good work.'\"\n ]\n },\n \"execution_count\": 22,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"query = \\\"What does the author describe as good work?\\\"\\n\",\n \"qa.run(query)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"be503d53\",\n \"metadata\": {},\n \"source\": [\n \"If you wanted to do more you would hook this up to a cloud vector database, use a tool like metal and start managing your documents, with external data sources\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"d3d04dc9\",\n \"metadata\": {},\n \"source\": [\n \"## Extraction\\n\",\n \"*[LangChain Extraction Docs](https://python.langchain.com/en/latest/use_cases/extraction.html)*\\n\",\n \"\\n\",\n \"Extraction is the process of parsing data from a piece of text. This is commonly used with output parsing in order to *structure* our data.\\n\",\n \"\\n\",\n \"* **Deep Dive** - [Use LLMs to Extract Data From Text (Expert Level Text Extraction](https://youtu.be/xZzvwR9jdPA), [Structured Output From OpenAI (Clean Dirty Data)](https://youtu.be/KwAXfey-xQk)\\n\",\n \"* **Examples** - [OpeningAttributes](https://twitter.com/GregKamradt/status/1646500373837008897)\\n\",\n \"* **Use Cases:** Extract a structured row from a sentence to insert into a database, extract multiple rows from a long document to insert into a database, extracting parameters from a user query to make an API call\\n\",\n \"\\n\",\n \"A popular library for extraction is [Kor](https://eyurtsev.github.io/kor/). We won't cover it today but I highly suggest checking it out for advanced extraction.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 23,\n \"id\": \"904d43c0\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# To help construct our Chat Messages\\n\",\n \"from langchain.schema import HumanMessage\\n\",\n \"from langchain.prompts import PromptTemplate, ChatPromptTemplate, HumanMessagePromptTemplate\\n\",\n \"\\n\",\n \"# We will be using a chat model, defaults to gpt-3.5-turbo\\n\",\n \"from langchain.chat_models import ChatOpenAI\\n\",\n \"\\n\",\n \"# To parse outputs and get structured data back\\n\",\n \"from langchain.output_parsers import StructuredOutputParser, ResponseSchema\\n\",\n \"\\n\",\n \"chat_model = ChatOpenAI(temperature=0, model_name='gpt-3.5-turbo', openai_api_key=openai_api_key)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"6923ca8b\",\n \"metadata\": {},\n \"source\": [\n \"### Vanilla Extraction\\n\",\n \"\\n\",\n \"Let's start off with an easy example. Here I simply supply a prompt with instructions with the type of output I want.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 24,\n \"id\": \"ab1cce97\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"instructions = \\\"\\\"\\\"\\n\",\n \"You will be given a sentence with fruit names, extract those fruit names and assign an emoji to them\\n\",\n \"Return the fruit name and emojis in a python dictionary\\n\",\n \"\\\"\\\"\\\"\\n\",\n \"\\n\",\n \"fruit_names = \\\"\\\"\\\"\\n\",\n \"Apple, Pear, this is an kiwi\\n\",\n \"\\\"\\\"\\\"\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 25,\n \"id\": \"38f16ea4\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"{'Apple': '🍎', 'Pear': '🍐', 'kiwi': '🥝'}\\n\",\n \"\\n\"\n ]\n }\n ],\n \"source\": [\n \"# Make your prompt which combines the instructions w/ the fruit names\\n\",\n \"prompt = (instructions + fruit_names)\\n\",\n \"\\n\",\n \"# Call the LLM\\n\",\n \"output = chat_model([HumanMessage(content=prompt)])\\n\",\n \"\\n\",\n \"print (output.content)\\n\",\n \"print (type(output.content))\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"39d6cff3\",\n \"metadata\": {},\n \"source\": [\n \"Let's turn this into a proper python dictionary\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 26,\n \"id\": \"314286b4\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"{'Apple': '🍎', 'Pear': '🍐', 'kiwi': '🥝'}\\n\",\n \"\\n\"\n ]\n }\n ],\n \"source\": [\n \"output_dict = eval(output.content)\\n\",\n \"\\n\",\n \"print (output_dict)\\n\",\n \"print (type(output_dict))\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"3909eb29\",\n \"metadata\": {},\n \"source\": [\n \"While this worked this time, it's not a long term reliable method for more advanced use cases\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"b6a0a90d\",\n \"metadata\": {},\n \"source\": [\n \"### Using LangChain's Response Schema\\n\",\n \"\\n\",\n \"LangChain's response schema will does two things for us: \\n\",\n \"\\n\",\n \"1. Autogenerate the a prompt with bonafide format instructions. This is great because I don't need to worry about the prompt engineering side, I'll leave that up to LangChain!\\n\",\n \"\\n\",\n \"2. Read the output from the LLM and turn it into a proper python object for me\\n\",\n \"\\n\",\n \"Here I define the schema I want. I'm going to pull out the song and artist that a user wants to play from a pseudo chat message.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 27,\n \"id\": \"dc2ba0be\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# The schema I want out\\n\",\n \"response_schemas = [\\n\",\n \" ResponseSchema(name=\\\"artist\\\", description=\\\"The name of the musical artist\\\"),\\n\",\n \" ResponseSchema(name=\\\"song\\\", description=\\\"The name of the song that the artist plays\\\")\\n\",\n \"]\\n\",\n \"\\n\",\n \"# The parser that will look for the LLM output in my schema and return it back to me\\n\",\n \"output_parser = StructuredOutputParser.from_response_schemas(response_schemas)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 28,\n \"id\": \"f9e3c6cf\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"The output should be a markdown code snippet formatted in the following schema, including the leading and trailing \\\"\\\\`\\\\`\\\\`json\\\" and \\\"\\\\`\\\\`\\\\`\\\":\\n\",\n \"\\n\",\n \"```json\\n\",\n \"{\\n\",\n \"\\t\\\"artist\\\": string // The name of the musical artist\\n\",\n \"\\t\\\"song\\\": string // The name of the song that the artist plays\\n\",\n \"}\\n\",\n \"```\\n\"\n ]\n }\n ],\n \"source\": [\n \"# The format instructions that LangChain makes. Let's look at them\\n\",\n \"format_instructions = output_parser.get_format_instructions()\\n\",\n \"print(format_instructions)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 29,\n \"id\": \"d702900c\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# The prompt template that brings it all together\\n\",\n \"# Note: This is a different prompt template than before because we are using a Chat Model\\n\",\n \"\\n\",\n \"prompt = ChatPromptTemplate(\\n\",\n \" messages=[\\n\",\n \" HumanMessagePromptTemplate.from_template(\\\"Given a command from the user, extract the artist and song names \\\\n \\\\\\n\",\n \" {format_instructions}\\\\n{user_prompt}\\\") \\n\",\n \" ],\\n\",\n \" input_variables=[\\\"user_prompt\\\"],\\n\",\n \" partial_variables={\\\"format_instructions\\\": format_instructions}\\n\",\n \")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 30,\n \"id\": \"bb6adde9\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"Given a command from the user, extract the artist and song names \\n\",\n \" The output should be a markdown code snippet formatted in the following schema, including the leading and trailing \\\"\\\\`\\\\`\\\\`json\\\" and \\\"\\\\`\\\\`\\\\`\\\":\\n\",\n \"\\n\",\n \"```json\\n\",\n \"{\\n\",\n \"\\t\\\"artist\\\": string // The name of the musical artist\\n\",\n \"\\t\\\"song\\\": string // The name of the song that the artist plays\\n\",\n \"}\\n\",\n \"```\\n\",\n \"I really like So Young by Portugal. The Man\\n\"\n ]\n }\n ],\n \"source\": [\n \"fruit_query = prompt.format_prompt(user_prompt=\\\"I really like So Young by Portugal. The Man\\\")\\n\",\n \"print (fruit_query.messages[0].content)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 31,\n \"id\": \"b8664302\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"{'artist': 'Portugal. The Man', 'song': 'So Young'}\\n\",\n \"\\n\"\n ]\n }\n ],\n \"source\": [\n \"fruit_output = chat_model(fruit_query.to_messages())\\n\",\n \"output = output_parser.parse(fruit_output.content)\\n\",\n \"\\n\",\n \"print (output)\\n\",\n \"print (type(output))\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"b68b8eeb\",\n \"metadata\": {},\n \"source\": [\n \"Awesome, now we have a dictionary that we can use later down the line\\n\",\n \"\\n\",\n \"Warning: The parser looks for an output from the LLM in a specific format. Your model may not output the same format every time. Make sure to handle errors with this one. GPT4 and future iterations will be more reliable.\\n\",\n \"\\n\",\n \"For more advanced parsing check out [Kor](https://eyurtsev.github.io/kor/)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"f2fb4ba6\",\n \"metadata\": {},\n \"source\": [\n \"## Evaluation\\n\",\n \"\\n\",\n \"*[LangChain Evaluation Docs](https://python.langchain.com/en/latest/use_cases/evaluation.html)*\\n\",\n \"\\n\",\n \"Evaluation is the process of doing quality checks on the output of your applications. Normal, deterministic, code has tests we can run, but judging the output of LLMs is more difficult because of the unpredictableness and variability of natural language. LangChain provides tools that aid us in this journey.\\n\",\n \"\\n\",\n \"* **Deep Dive** - Coming Soon\\n\",\n \"* **Examples** - [Lance Martin's Advanced](https://twitter.com/RLanceMartin) [Auto-Evaluator](https://github.com/rlancemartin/auto-evaluator)\\n\",\n \"* **Use Cases:** Run quality checks on your summarization or Question & Answer pipelines, check the output of you summarization pipeline\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 32,\n \"id\": \"9fbaa6e1\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# Embeddings, store, and retrieval\\n\",\n \"from langchain.embeddings.openai import OpenAIEmbeddings\\n\",\n \"from langchain.vectorstores import FAISS\\n\",\n \"from langchain.chains import RetrievalQA\\n\",\n \"\\n\",\n \"# Model and doc loader\\n\",\n \"from langchain import OpenAI\\n\",\n \"from langchain.document_loaders import TextLoader\\n\",\n \"\\n\",\n \"# Eval!\\n\",\n \"from langchain.evaluation.qa import QAEvalChain\\n\",\n \"\\n\",\n \"llm = OpenAI(temperature=0, openai_api_key=openai_api_key)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 33,\n \"id\": \"9f35fa12\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"You have 1 document\\n\",\n \"You have 74663 characters in that document\\n\"\n ]\n }\n ],\n \"source\": [\n \"# Our long essay from before\\n\",\n \"loader = TextLoader('data/PaulGrahamEssays/worked.txt')\\n\",\n \"doc = loader.load()\\n\",\n \"\\n\",\n \"print (f\\\"You have {len(doc)} document\\\")\\n\",\n \"print (f\\\"You have {len(doc[0].page_content)} characters in that document\\\")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"7acca7da\",\n \"metadata\": {},\n \"source\": [\n \"First let's do the Vectorestore dance so we can do question and answers\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 34,\n \"id\": \"1955faef\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"Now you have 29 documents that have an average of 2,930 characters (smaller pieces)\\n\"\n ]\n }\n ],\n \"source\": [\n \"text_splitter = RecursiveCharacterTextSplitter(chunk_size=3000, chunk_overlap=400)\\n\",\n \"docs = text_splitter.split_documents(doc)\\n\",\n \"\\n\",\n \"# Get the total number of characters so we can see the average later\\n\",\n \"num_total_characters = sum([len(x.page_content) for x in docs])\\n\",\n \"\\n\",\n \"print (f\\\"Now you have {len(docs)} documents that have an average of {num_total_characters / len(docs):,.0f} characters (smaller pieces)\\\")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 35,\n \"id\": \"890b85ca\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# Embeddings and docstore\\n\",\n \"embeddings = OpenAIEmbeddings(openai_api_key=openai_api_key)\\n\",\n \"docsearch = FAISS.from_documents(docs, embeddings)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"7a0d6e25\",\n \"metadata\": {},\n \"source\": [\n \"Make your retrieval chain. Notice how I have an `input_key` parameter now. This tells the chain which key from a dictionary I supply has my prompt/query in it. I specify `question` to match the question in the dict below\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 36,\n \"id\": \"ddb3f3b5\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"chain = RetrievalQA.from_chain_type(llm=llm, chain_type=\\\"stuff\\\", retriever=docsearch.as_retriever(), input_key=\\\"question\\\")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"b37dd0cd\",\n \"metadata\": {},\n \"source\": [\n \"Now I'll pass a list of questions and ground truth answers to the LLM that I know are correct (I validated them as a human).\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 37,\n \"id\": \"d93d08bf\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"question_answers = [\\n\",\n \" {'question' : \\\"Which company sold the microcomputer kit that his friend built himself?\\\", 'answer' : 'Healthkit'},\\n\",\n \" {'question' : \\\"What was the small city he talked about in the city that is the financial capital of USA?\\\", 'answer' : 'Yorkville, NY'}\\n\",\n \"]\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"98c4b591\",\n \"metadata\": {},\n \"source\": [\n \"I'll use `chain.apply` to run both my questions one by one separately.\\n\",\n \"\\n\",\n \"One of the cool parts is that I'll get my list of question and answers dictionaries back, but there'll be another key in the dictionary `result` which will be the output from the LLM.\\n\",\n \"\\n\",\n \"Note: I specifically made my 2nd question ambigious and tough to answer in one pass so the LLM would get it incorrect\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 38,\n \"id\": \"a4a4e041\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"[{'question': 'Which company sold the microcomputer kit that his friend built himself?',\\n\",\n \" 'answer': 'Healthkit',\\n\",\n \" 'result': ' The microcomputer kit was sold by Heathkit.'},\\n\",\n \" {'question': 'What was the small city he talked about in the city that is the financial capital of USA?',\\n\",\n \" 'answer': 'Yorkville, NY',\\n\",\n \" 'result': ' The small city he talked about is New York City, which is the financial capital of the United States.'}]\"\n ]\n },\n \"execution_count\": 38,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"predictions = chain.apply(question_answers)\\n\",\n \"predictions\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"ed1226c9\",\n \"metadata\": {},\n \"source\": [\n \"We then have the LLM compare my ground truth answer (the `answer` key) with the result from the LLM (`result` key).\\n\",\n \"\\n\",\n \"Or simply, we are asking the LLM to grade itself. What a wild world we live in.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 39,\n \"id\": \"ae119b18\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# Start your eval chain\\n\",\n \"eval_chain = QAEvalChain.from_llm(llm)\\n\",\n \"\\n\",\n \"# Have it grade itself. The code below helps the eval_chain know where the different parts are\\n\",\n \"graded_outputs = eval_chain.evaluate(question_answers,\\n\",\n \" predictions,\\n\",\n \" question_key=\\\"question\\\",\\n\",\n \" prediction_key=\\\"result\\\",\\n\",\n \" answer_key='answer')\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 40,\n \"id\": \"c2882750\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"[{'text': ' CORRECT'}, {'text': ' INCORRECT'}]\"\n ]\n },\n \"execution_count\": 40,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"graded_outputs\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"5b30268b\",\n \"metadata\": {},\n \"source\": [\n \"This is correct! Notice how the answer in question #1 was \\\"Healthkit\\\" and the prediction was \\\"The microcomputer kit was sold by Heathkit.\\\" The LLM knew that the answer and result were the same and gave us a \\\"correct\\\" label. Awesome.\\n\",\n \"\\n\",\n \"For #2 it knew they were not the same and gave us an \\\"incorrect\\\" label\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"d2745752\",\n \"metadata\": {},\n \"source\": [\n \"## Querying Tabular Data\\n\",\n \"\\n\",\n \"*[LangChain Querying Tabular Data Docs](https://python.langchain.com/en/latest/use_cases/tabular.html)*\\n\",\n \"\\n\",\n \"The most common type of data in the world sits in tabular form (ok, ok, besides unstructured data). It is super powerful to be able to query this data with LangChain and pass it through to an LLM \\n\",\n \"\\n\",\n \"* **Deep Dive** - Coming Soon\\n\",\n \"* **Examples** - TBD\\n\",\n \"* **Use Cases:** Use LLMs to query data about users, do data analysis, get real time information from your DBs\\n\",\n \"\\n\",\n \"For futher reading check out \\\"Agents + Tabular Data\\\" ([Pandas](https://python.langchain.com/en/latest/modules/agents/toolkits/examples/pandas.html), [SQL](https://python.langchain.com/en/latest/modules/agents/toolkits/examples/sql_database.html), [CSV](https://python.langchain.com/en/latest/modules/agents/toolkits/examples/csv.html))\\n\",\n \"\\n\",\n \"Let's query an SQLite DB with natural language. We'll look at the [San Francisco Trees](https://data.sfgov.org/City-Infrastructure/Street-Tree-List/tkzw-k3nq) dataset.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 41,\n \"id\": \"9b19c2d0\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain import OpenAI, SQLDatabase, SQLDatabaseChain\\n\",\n \"\\n\",\n \"llm = OpenAI(temperature=0, openai_api_key=openai_api_key)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"294a4e7f\",\n \"metadata\": {},\n \"source\": [\n \"We'll start off by specifying where our data is and get the connection ready\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 42,\n \"id\": \"6044d54e\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"sqlite_db_path = 'data/San_Francisco_Trees.db'\\n\",\n \"db = SQLDatabase.from_uri(f\\\"sqlite:///{sqlite_db_path}\\\")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"203eedd4\",\n \"metadata\": {},\n \"source\": [\n \"Then we'll create a chain that take our LLM, and DB. I'm setting `verbose=True` so you can see what is happening underneath the hood.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 43,\n \"id\": \"dccf0957\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stderr\",\n \"output_type\": \"stream\",\n \"text\": [\n \"/Users/gregorykamradt/opt/anaconda3/lib/python3.9/site-packages/langchain/chains/sql_database/base.py:63: UserWarning: Directly instantiating an SQLDatabaseChain with an llm is deprecated. Please instantiate with llm_chain argument or using the from_llm class method.\\n\",\n \" warnings.warn(\\n\"\n ]\n }\n ],\n \"source\": [\n \"db_chain = SQLDatabaseChain(llm=llm, database=db, verbose=True)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 44,\n \"id\": \"99cdbc44\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"\\n\",\n \"\\n\",\n \"\\u001b[1m> Entering new SQLDatabaseChain chain...\\u001b[0m\\n\",\n \"How many Species of trees are there in San Francisco?\\n\",\n \"SQLQuery:\\u001b[32;1m\\u001b[1;3mSELECT COUNT(DISTINCT \\\"qSpecies\\\") FROM \\\"SFTrees\\\";\\u001b[0m\\n\",\n \"SQLResult: \\u001b[33;1m\\u001b[1;3m[(578,)]\\u001b[0m\\n\",\n \"Answer:\\u001b[32;1m\\u001b[1;3mThere are 578 Species of trees in San Francisco.\\u001b[0m\\n\",\n \"\\u001b[1m> Finished chain.\\u001b[0m\\n\"\n ]\n },\n {\n \"data\": {\n \"text/plain\": [\n \"'There are 578 Species of trees in San Francisco.'\"\n ]\n },\n \"execution_count\": 44,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"db_chain.run(\\\"How many Species of trees are there in San Francisco?\\\")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"6bd61598\",\n \"metadata\": {},\n \"source\": [\n \"This is awesome! There are actually a few steps going on here.\\n\",\n \"\\n\",\n \"**Steps:**\\n\",\n \"1. Find which table to use\\n\",\n \"2. Find which column to use\\n\",\n \"3. Construct the correct sql query\\n\",\n \"4. Execute that query\\n\",\n \"5. Get the result\\n\",\n \"6. Return a natural language reponse back\\n\",\n \"\\n\",\n \"Let's confirm via pandas\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 45,\n \"id\": \"299ff6ca\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"import sqlite3\\n\",\n \"import pandas as pd\\n\",\n \"\\n\",\n \"# Connect to the SQLite database\\n\",\n \"connection = sqlite3.connect(sqlite_db_path)\\n\",\n \"\\n\",\n \"# Define your SQL query\\n\",\n \"query = \\\"SELECT count(distinct qSpecies) FROM SFTrees\\\"\\n\",\n \"\\n\",\n \"# Read the SQL query into a Pandas DataFrame\\n\",\n \"df = pd.read_sql_query(query, connection)\\n\",\n \"\\n\",\n \"# Close the connection\\n\",\n \"connection.close()\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 46,\n \"id\": \"f1b2dd89\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"578\\n\"\n ]\n }\n ],\n \"source\": [\n \"# Display the result in the first column first cell\\n\",\n \"print(df.iloc[0,0])\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"c48b5a42\",\n \"metadata\": {},\n \"source\": [\n \"Nice! The answers match.\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"04293535\",\n \"metadata\": {},\n \"source\": [\n \"## Code Understanding\\n\",\n \"\\n\",\n \"*[LangChain Code Understanding Docs](https://python.langchain.com/en/latest/use_cases/code.html)*\\n\",\n \"\\n\",\n \"One of the most exciting abilities of LLMs is code undestanding. People around the world are leveling up their output in both speed & quality due to AI help. A big part of this is having a LLM that can understand code and help you with a particular task.\\n\",\n \"\\n\",\n \"* **Deep Dive** - Coming Soon\\n\",\n \"* **Examples** - TBD\\n\",\n \"* **Use Cases:** Co-Pilot-esque functionality that can help answer questions from a specific library, help you generate new code\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 47,\n \"id\": \"f3101c11\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# Helper to read local files\\n\",\n \"import os\\n\",\n \"\\n\",\n \"# Vector Support\\n\",\n \"from langchain.vectorstores import FAISS\\n\",\n \"from langchain.embeddings.openai import OpenAIEmbeddings\\n\",\n \"\\n\",\n \"# Model and chain\\n\",\n \"from langchain.chat_models import ChatOpenAI\\n\",\n \"\\n\",\n \"# Text splitters\\n\",\n \"from langchain.text_splitter import CharacterTextSplitter\\n\",\n \"from langchain.document_loaders import TextLoader\\n\",\n \"\\n\",\n \"llm = ChatOpenAI(model_name='gpt-3.5-turbo', openai_api_key=openai_api_key)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"2c4dfd6d\",\n \"metadata\": {},\n \"source\": [\n \"We will do the Vectorstore dance again\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 48,\n \"id\": \"8a9247e8\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"embeddings = OpenAIEmbeddings(disallowed_special=(), openai_api_key=openai_api_key)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"bf12eb2c\",\n \"metadata\": {},\n \"source\": [\n \"I put a small python package [The Fuzz](https://github.com/seatgeek/thefuzz) (personal indie favorite) in the data folder of this repo.\\n\",\n \"\\n\",\n \"The loop below will go through each file in the library and load it up as a doc\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 49,\n \"id\": \"bd3973a2\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"root_dir = 'data/thefuzz'\\n\",\n \"docs = []\\n\",\n \"\\n\",\n \"# Go through each folder\\n\",\n \"for dirpath, dirnames, filenames in os.walk(root_dir):\\n\",\n \" \\n\",\n \" # Go through each file\\n\",\n \" for file in filenames:\\n\",\n \" try: \\n\",\n \" # Load up the file as a doc and split\\n\",\n \" loader = TextLoader(os.path.join(dirpath, file), encoding='utf-8')\\n\",\n \" docs.extend(loader.load_and_split())\\n\",\n \" except Exception as e: \\n\",\n \" pass\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"136cae5e\",\n \"metadata\": {},\n \"source\": [\n \"Let's look at an example of a document. It's just code!\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 50,\n \"id\": \"85a39161\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"You have 175 documents\\n\",\n \"\\n\",\n \"------ Start Document ------\\n\",\n \"import unittest\\n\",\n \"import re\\n\",\n \"import pycodestyle\\n\",\n \"\\n\",\n \"from thefuzz import fuzz\\n\",\n \"from thefuzz import process\\n\",\n \"from thefuzz import utils\\n\",\n \"from thefuzz.string_processing import StringProcessor\\n\",\n \"\\n\",\n \"\\n\",\n \"class StringProcessingTest(unittest.TestCase):\\n\",\n \" def test_replace_non_letters_non_numbers_with_whitespace(self):\\n\",\n \" \\n\"\n ]\n }\n ],\n \"source\": [\n \"print (f\\\"You have {len(docs)} documents\\\\n\\\")\\n\",\n \"print (\\\"------ Start Document ------\\\")\\n\",\n \"print (docs[0].page_content[:300])\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"02634791\",\n \"metadata\": {},\n \"source\": [\n \"Embed and store them in a docstore. This will make an API call to OpenAI\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 51,\n \"id\": \"94427072\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"docsearch = FAISS.from_documents(docs, embeddings)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 52,\n \"id\": \"2071f3c4\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# Get our retriever ready\\n\",\n \"qa = RetrievalQA.from_chain_type(llm=llm, chain_type=\\\"stuff\\\", retriever=docsearch.as_retriever())\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 53,\n \"id\": \"0536b828\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"query = \\\"What function do I use if I want to find the most similar item in a list of items?\\\"\\n\",\n \"output = qa.run(query)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 54,\n \"id\": \"b9074fb6\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"You can use the `process.extractOne()` function from `thefuzz` package to find the most similar item in a list of items. Here's an example:\\n\",\n \"\\n\",\n \"```\\n\",\n \"from thefuzz import process\\n\",\n \"\\n\",\n \"choices = [\\\"apple\\\", \\\"banana\\\", \\\"orange\\\", \\\"pear\\\"]\\n\",\n \"query = \\\"pineapple\\\"\\n\",\n \"\\n\",\n \"best_match = process.extractOne(query, choices)\\n\",\n \"print(best_match)\\n\",\n \"```\\n\",\n \"\\n\",\n \"This would output `(u'apple', 36)`, which means that the most similar item to \\\"pineapple\\\" in the list of choices is \\\"apple\\\", with a similarity score of 36.\\n\"\n ]\n }\n ],\n \"source\": [\n \"print (output)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 55,\n \"id\": \"f53860e6\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"query = \\\"Can you write the code to use the process.extractOne() function? Only respond with code. No other text or explanation\\\"\\n\",\n \"output = qa.run(query)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 56,\n \"id\": \"27e56a5d\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"import fuzzywuzzy.process as process\\n\",\n \"\\n\",\n \"choices = [\\n\",\n \" \\\"new york mets vs chicago cubs\\\",\\n\",\n \" \\\"chicago cubs at new york mets\\\",\\n\",\n \" \\\"atlanta braves vs pittsbugh pirates\\\",\\n\",\n \" \\\"new york yankees vs boston red sox\\\"\\n\",\n \"]\\n\",\n \"\\n\",\n \"query = \\\"new york mets at chicago cubs\\\"\\n\",\n \"\\n\",\n \"best = process.extractOne(query, choices)\\n\",\n \"print(best[0])\\n\"\n ]\n }\n ],\n \"source\": [\n \"print (output)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"c7deae05\",\n \"metadata\": {},\n \"source\": [\n \"[¡Shibby!](https://thumbs.gfycat.com/WateryBeneficialDeermouse-size_restricted.gif)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"f3b2783a\",\n \"metadata\": {},\n \"source\": [\n \"## Interacting with APIs\\n\",\n \"\\n\",\n \"*[LangChain API Interaction Docs](https://python.langchain.com/en/latest/use_cases/apis.html)*\\n\",\n \"\\n\",\n \"If the data or action you need is behind an API, you'll need your LLM to interact with APIs\\n\",\n \"\\n\",\n \"* **Deep Dive** - Coming Soon\\n\",\n \"* **Examples** - TBD\\n\",\n \"* **Use Cases:** Understand a request from a user and carry out an action, be able to automate more real-world workflows\\n\",\n \"\\n\",\n \"This topic is closely related to Agents and Plugins, though we'll look at a simple use case for this section. For more information, check out [LangChain + plugins](https://python.langchain.com/en/latest/use_cases/agents/custom_agent_with_plugin_retrieval_using_plugnplai.html) documentation.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 57,\n \"id\": \"352685c0\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain.chains import APIChain\\n\",\n \"from langchain.llms import OpenAI\\n\",\n \"\\n\",\n \"llm = OpenAI(temperature=0, openai_api_key=openai_api_key)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"e6b834fe\",\n \"metadata\": {},\n \"source\": [\n \"LangChain's APIChain has the ability to read API documentation and understand which endpoint it needs to call.\\n\",\n \"\\n\",\n \"In this case I wrote (purposefully sloppy) API documentation to demonstrate how this works\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 58,\n \"id\": \"3ff4b986\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"api_docs = \\\"\\\"\\\"\\n\",\n \"\\n\",\n \"BASE URL: https://restcountries.com/\\n\",\n \"\\n\",\n \"API Documentation:\\n\",\n \"\\n\",\n \"The API endpoint /v3.1/name/{name} Used to find informatin about a country. All URL parameters are listed below:\\n\",\n \" - name: Name of country - Ex: italy, france\\n\",\n \" \\n\",\n \"The API endpoint /v3.1/currency/{currency} Uesd to find information about a region. All URL parameters are listed below:\\n\",\n \" - currency: 3 letter currency. Example: USD, COP\\n\",\n \" \\n\",\n \"Woo! This is my documentation\\n\",\n \"\\\"\\\"\\\"\\n\",\n \"\\n\",\n \"chain_new = APIChain.from_llm_and_api_docs(llm, api_docs, verbose=True)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"221aa3a6\",\n \"metadata\": {},\n \"source\": [\n \"Let's try to make an API call that is meant for the country endpoint\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 59,\n \"id\": \"e6d9cae4\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"\\n\",\n \"\\n\",\n \"\\u001b[1m> Entering new APIChain chain...\\u001b[0m\\n\",\n \"\\u001b[32;1m\\u001b[1;3m https://restcountries.com/v3.1/name/france\\u001b[0m\\n\",\n \"\\u001b[33;1m\\u001b[1;3m[{\\\"name\\\":{\\\"common\\\":\\\"France\\\",\\\"official\\\":\\\"French Republic\\\",\\\"nativeName\\\":{\\\"fra\\\":{\\\"official\\\":\\\"République française\\\",\\\"common\\\":\\\"France\\\"}}},\\\"tld\\\":[\\\".fr\\\"],\\\"cca2\\\":\\\"FR\\\",\\\"ccn3\\\":\\\"250\\\",\\\"cca3\\\":\\\"FRA\\\",\\\"cioc\\\":\\\"FRA\\\",\\\"independent\\\":true,\\\"status\\\":\\\"officially-assigned\\\",\\\"unMember\\\":true,\\\"currencies\\\":{\\\"EUR\\\":{\\\"name\\\":\\\"Euro\\\",\\\"symbol\\\":\\\"€\\\"}},\\\"idd\\\":{\\\"root\\\":\\\"+3\\\",\\\"suffixes\\\":[\\\"3\\\"]},\\\"capital\\\":[\\\"Paris\\\"],\\\"altSpellings\\\":[\\\"FR\\\",\\\"French Republic\\\",\\\"République française\\\"],\\\"region\\\":\\\"Europe\\\",\\\"subregion\\\":\\\"Western Europe\\\",\\\"languages\\\":{\\\"fra\\\":\\\"French\\\"},\\\"translations\\\":{\\\"ara\\\":{\\\"official\\\":\\\"الجمهورية الفرنسية\\\",\\\"common\\\":\\\"فرنسا\\\"},\\\"bre\\\":{\\\"official\\\":\\\"Republik Frañs\\\",\\\"common\\\":\\\"Frañs\\\"},\\\"ces\\\":{\\\"official\\\":\\\"Francouzská republika\\\",\\\"common\\\":\\\"Francie\\\"},\\\"cym\\\":{\\\"official\\\":\\\"French Republic\\\",\\\"common\\\":\\\"France\\\"},\\\"deu\\\":{\\\"official\\\":\\\"Französische Republik\\\",\\\"common\\\":\\\"Frankreich\\\"},\\\"est\\\":{\\\"official\\\":\\\"Prantsuse Vabariik\\\",\\\"common\\\":\\\"Prantsusmaa\\\"},\\\"fin\\\":{\\\"official\\\":\\\"Ranskan tasavalta\\\",\\\"common\\\":\\\"Ranska\\\"},\\\"fra\\\":{\\\"official\\\":\\\"République française\\\",\\\"common\\\":\\\"France\\\"},\\\"hrv\\\":{\\\"official\\\":\\\"Francuska Republika\\\",\\\"common\\\":\\\"Francuska\\\"},\\\"hun\\\":{\\\"official\\\":\\\"Francia Köztársaság\\\",\\\"common\\\":\\\"Franciaország\\\"},\\\"ita\\\":{\\\"official\\\":\\\"Repubblica francese\\\",\\\"common\\\":\\\"Francia\\\"},\\\"jpn\\\":{\\\"official\\\":\\\"フランス共和国\\\",\\\"common\\\":\\\"フランス\\\"},\\\"kor\\\":{\\\"official\\\":\\\"프랑스 공화국\\\",\\\"common\\\":\\\"프랑스\\\"},\\\"nld\\\":{\\\"official\\\":\\\"Franse Republiek\\\",\\\"common\\\":\\\"Frankrijk\\\"},\\\"per\\\":{\\\"official\\\":\\\"جمهوری فرانسه\\\",\\\"common\\\":\\\"فرانسه\\\"},\\\"pol\\\":{\\\"official\\\":\\\"Republika Francuska\\\",\\\"common\\\":\\\"Francja\\\"},\\\"por\\\":{\\\"official\\\":\\\"República Francesa\\\",\\\"common\\\":\\\"França\\\"},\\\"rus\\\":{\\\"official\\\":\\\"Французская Республика\\\",\\\"common\\\":\\\"Франция\\\"},\\\"slk\\\":{\\\"official\\\":\\\"Francúzska republika\\\",\\\"common\\\":\\\"Francúzsko\\\"},\\\"spa\\\":{\\\"official\\\":\\\"República francés\\\",\\\"common\\\":\\\"Francia\\\"},\\\"srp\\\":{\\\"official\\\":\\\"Француска Република\\\",\\\"common\\\":\\\"Француска\\\"},\\\"swe\\\":{\\\"official\\\":\\\"Republiken Frankrike\\\",\\\"common\\\":\\\"Frankrike\\\"},\\\"tur\\\":{\\\"official\\\":\\\"Fransa Cumhuriyeti\\\",\\\"common\\\":\\\"Fransa\\\"},\\\"urd\\\":{\\\"official\\\":\\\"جمہوریہ فرانس\\\",\\\"common\\\":\\\"فرانس\\\"},\\\"zho\\\":{\\\"official\\\":\\\"法兰西共和国\\\",\\\"common\\\":\\\"法国\\\"}},\\\"latlng\\\":[46.0,2.0],\\\"landlocked\\\":false,\\\"borders\\\":[\\\"AND\\\",\\\"BEL\\\",\\\"DEU\\\",\\\"ITA\\\",\\\"LUX\\\",\\\"MCO\\\",\\\"ESP\\\",\\\"CHE\\\"],\\\"area\\\":551695.0,\\\"demonyms\\\":{\\\"eng\\\":{\\\"f\\\":\\\"French\\\",\\\"m\\\":\\\"French\\\"},\\\"fra\\\":{\\\"f\\\":\\\"Française\\\",\\\"m\\\":\\\"Français\\\"}},\\\"flag\\\":\\\"\\\\uD83C\\\\uDDEB\\\\uD83C\\\\uDDF7\\\",\\\"maps\\\":{\\\"googleMaps\\\":\\\"https://goo.gl/maps/g7QxxSFsWyTPKuzd7\\\",\\\"openStreetMaps\\\":\\\"https://www.openstreetmap.org/relation/1403916\\\"},\\\"population\\\":67391582,\\\"gini\\\":{\\\"2018\\\":32.4},\\\"fifa\\\":\\\"FRA\\\",\\\"car\\\":{\\\"signs\\\":[\\\"F\\\"],\\\"side\\\":\\\"right\\\"},\\\"timezones\\\":[\\\"UTC-10:00\\\",\\\"UTC-09:30\\\",\\\"UTC-09:00\\\",\\\"UTC-08:00\\\",\\\"UTC-04:00\\\",\\\"UTC-03:00\\\",\\\"UTC+01:00\\\",\\\"UTC+02:00\\\",\\\"UTC+03:00\\\",\\\"UTC+04:00\\\",\\\"UTC+05:00\\\",\\\"UTC+10:00\\\",\\\"UTC+11:00\\\",\\\"UTC+12:00\\\"],\\\"continents\\\":[\\\"Europe\\\"],\\\"flags\\\":{\\\"png\\\":\\\"https://flagcdn.com/w320/fr.png\\\",\\\"svg\\\":\\\"https://flagcdn.com/fr.svg\\\",\\\"alt\\\":\\\"The flag of France is composed of three equal vertical bands of blue, white and red.\\\"},\\\"coatOfArms\\\":{\\\"png\\\":\\\"https://mainfacts.com/media/images/coats_of_arms/fr.png\\\",\\\"svg\\\":\\\"https://mainfacts.com/media/images/coats_of_arms/fr.svg\\\"},\\\"startOfWeek\\\":\\\"monday\\\",\\\"capitalInfo\\\":{\\\"latlng\\\":[48.87,2.33]},\\\"postalCode\\\":{\\\"format\\\":\\\"#####\\\",\\\"regex\\\":\\\"^(\\\\\\\\d{5})$\\\"}}]\\u001b[0m\\n\",\n \"\\n\",\n \"\\u001b[1m> Finished chain.\\u001b[0m\\n\"\n ]\n },\n {\n \"data\": {\n \"text/plain\": [\n \"' France is an officially-assigned, independent country located in Western Europe. Its capital is Paris and its official language is French. Its currency is the Euro (€). It has a population of 67,391,582 and its borders are with Andorra, Belgium, Germany, Italy, Luxembourg, Monaco, Spain, and Switzerland.'\"\n ]\n },\n \"execution_count\": 59,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"chain_new.run('Can you tell me information about france?')\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"09235fc3\",\n \"metadata\": {},\n \"source\": [\n \"Let's try to make an API call that is meant for the currency endpoint\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 60,\n \"id\": \"c2735073\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"\\n\",\n \"\\n\",\n \"\\u001b[1m> Entering new APIChain chain...\\u001b[0m\\n\",\n \"\\u001b[32;1m\\u001b[1;3m https://restcountries.com/v3.1/currency/COP\\u001b[0m\\n\",\n \"\\u001b[33;1m\\u001b[1;3m[{\\\"name\\\":{\\\"common\\\":\\\"Colombia\\\",\\\"official\\\":\\\"Republic of Colombia\\\",\\\"nativeName\\\":{\\\"spa\\\":{\\\"official\\\":\\\"República de Colombia\\\",\\\"common\\\":\\\"Colombia\\\"}}},\\\"tld\\\":[\\\".co\\\"],\\\"cca2\\\":\\\"CO\\\",\\\"ccn3\\\":\\\"170\\\",\\\"cca3\\\":\\\"COL\\\",\\\"cioc\\\":\\\"COL\\\",\\\"independent\\\":true,\\\"status\\\":\\\"officially-assigned\\\",\\\"unMember\\\":true,\\\"currencies\\\":{\\\"COP\\\":{\\\"name\\\":\\\"Colombian peso\\\",\\\"symbol\\\":\\\"$\\\"}},\\\"idd\\\":{\\\"root\\\":\\\"+5\\\",\\\"suffixes\\\":[\\\"7\\\"]},\\\"capital\\\":[\\\"Bogotá\\\"],\\\"altSpellings\\\":[\\\"CO\\\",\\\"Republic of Colombia\\\",\\\"República de Colombia\\\"],\\\"region\\\":\\\"Americas\\\",\\\"subregion\\\":\\\"South America\\\",\\\"languages\\\":{\\\"spa\\\":\\\"Spanish\\\"},\\\"translations\\\":{\\\"ara\\\":{\\\"official\\\":\\\"جمهورية كولومبيا\\\",\\\"common\\\":\\\"كولومبيا\\\"},\\\"bre\\\":{\\\"official\\\":\\\"Republik Kolombia\\\",\\\"common\\\":\\\"Kolombia\\\"},\\\"ces\\\":{\\\"official\\\":\\\"Kolumbijská republika\\\",\\\"common\\\":\\\"Kolumbie\\\"},\\\"cym\\\":{\\\"official\\\":\\\"Gweriniaeth Colombia\\\",\\\"common\\\":\\\"Colombia\\\"},\\\"deu\\\":{\\\"official\\\":\\\"Republik Kolumbien\\\",\\\"common\\\":\\\"Kolumbien\\\"},\\\"est\\\":{\\\"official\\\":\\\"Colombia Vabariik\\\",\\\"common\\\":\\\"Colombia\\\"},\\\"fin\\\":{\\\"official\\\":\\\"Kolumbian tasavalta\\\",\\\"common\\\":\\\"Kolumbia\\\"},\\\"fra\\\":{\\\"official\\\":\\\"République de Colombie\\\",\\\"common\\\":\\\"Colombie\\\"},\\\"hrv\\\":{\\\"official\\\":\\\"Republika Kolumbija\\\",\\\"common\\\":\\\"Kolumbija\\\"},\\\"hun\\\":{\\\"official\\\":\\\"Kolumbiai Köztársaság\\\",\\\"common\\\":\\\"Kolumbia\\\"},\\\"ita\\\":{\\\"official\\\":\\\"Repubblica di Colombia\\\",\\\"common\\\":\\\"Colombia\\\"},\\\"jpn\\\":{\\\"official\\\":\\\"コロンビア共和国\\\",\\\"common\\\":\\\"コロンビア\\\"},\\\"kor\\\":{\\\"official\\\":\\\"콜롬비아 공화국\\\",\\\"common\\\":\\\"콜롬비아\\\"},\\\"nld\\\":{\\\"official\\\":\\\"Republiek Colombia\\\",\\\"common\\\":\\\"Colombia\\\"},\\\"per\\\":{\\\"official\\\":\\\"جمهوری کلمبیا\\\",\\\"common\\\":\\\"کلمبیا\\\"},\\\"pol\\\":{\\\"official\\\":\\\"Republika Kolumbii\\\",\\\"common\\\":\\\"Kolumbia\\\"},\\\"por\\\":{\\\"official\\\":\\\"República da Colômbia\\\",\\\"common\\\":\\\"Colômbia\\\"},\\\"rus\\\":{\\\"official\\\":\\\"Республика Колумбия\\\",\\\"common\\\":\\\"Колумбия\\\"},\\\"slk\\\":{\\\"official\\\":\\\"Kolumbijská republika\\\",\\\"common\\\":\\\"Kolumbia\\\"},\\\"spa\\\":{\\\"official\\\":\\\"República de Colombia\\\",\\\"common\\\":\\\"Colombia\\\"},\\\"srp\\\":{\\\"official\\\":\\\"Република Колумбија\\\",\\\"common\\\":\\\"Колумбија\\\"},\\\"swe\\\":{\\\"official\\\":\\\"Republiken Colombia\\\",\\\"common\\\":\\\"Colombia\\\"},\\\"tur\\\":{\\\"official\\\":\\\"Kolombiya Cumhuriyeti\\\",\\\"common\\\":\\\"Kolombiya\\\"},\\\"urd\\\":{\\\"official\\\":\\\"جمہوریہ کولمبیا\\\",\\\"common\\\":\\\"کولمبیا\\\"},\\\"zho\\\":{\\\"official\\\":\\\"哥伦比亚共和国\\\",\\\"common\\\":\\\"哥伦比亚\\\"}},\\\"latlng\\\":[4.0,-72.0],\\\"landlocked\\\":false,\\\"borders\\\":[\\\"BRA\\\",\\\"ECU\\\",\\\"PAN\\\",\\\"PER\\\",\\\"VEN\\\"],\\\"area\\\":1141748.0,\\\"demonyms\\\":{\\\"eng\\\":{\\\"f\\\":\\\"Colombian\\\",\\\"m\\\":\\\"Colombian\\\"},\\\"fra\\\":{\\\"f\\\":\\\"Colombienne\\\",\\\"m\\\":\\\"Colombien\\\"}},\\\"flag\\\":\\\"\\\\uD83C\\\\uDDE8\\\\uD83C\\\\uDDF4\\\",\\\"maps\\\":{\\\"googleMaps\\\":\\\"https://goo.gl/maps/RdwTG8e7gPwS62oR6\\\",\\\"openStreetMaps\\\":\\\"https://www.openstreetmap.org/relation/120027\\\"},\\\"population\\\":50882884,\\\"gini\\\":{\\\"2019\\\":51.3},\\\"fifa\\\":\\\"COL\\\",\\\"car\\\":{\\\"signs\\\":[\\\"CO\\\"],\\\"side\\\":\\\"right\\\"},\\\"timezones\\\":[\\\"UTC-05:00\\\"],\\\"continents\\\":[\\\"South America\\\"],\\\"flags\\\":{\\\"png\\\":\\\"https://flagcdn.com/w320/co.png\\\",\\\"svg\\\":\\\"https://flagcdn.com/co.svg\\\",\\\"alt\\\":\\\"The flag of Colombia is composed of three horizontal bands of yellow, blue and red, with the yellow band twice the height of the other two bands.\\\"},\\\"coatOfArms\\\":{\\\"png\\\":\\\"https://mainfacts.com/media/images/coats_of_arms/co.png\\\",\\\"svg\\\":\\\"https://mainfacts.com/media/images/coats_of_arms/co.svg\\\"},\\\"startOfWeek\\\":\\\"monday\\\",\\\"capitalInfo\\\":{\\\"latlng\\\":[4.71,-74.07]}}]\\u001b[0m\\n\",\n \"\\n\",\n \"\\u001b[1m> Finished chain.\\u001b[0m\\n\"\n ]\n },\n {\n \"data\": {\n \"text/plain\": [\n \"' The currency of Colombia is the Colombian peso (COP), symbolized by the \\\"$\\\" sign.'\"\n ]\n },\n \"execution_count\": 60,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"chain_new.run('Can you tell me about the currency COP?')\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"2d5be7e0\",\n \"metadata\": {},\n \"source\": [\n \"In both cases the APIChain read the instructions and understood which API call it needed to make.\\n\",\n \"\\n\",\n \"Once the response returned, it was parsed and then my question was answered. Awesome 🐒\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"90e0f275\",\n \"metadata\": {},\n \"source\": [\n \"## Chatbots\\n\",\n \"\\n\",\n \"*[LangChain Chatbot Docs](https://python.langchain.com/en/latest/use_cases/chatbots.html)*\\n\",\n \"\\n\",\n \"Chatbots use many of the tools we've already looked at with the addition of an important topic: Memory. There are a ton of different [types of memory](https://python.langchain.com/en/latest/modules/memory/how_to_guides.html), tinker to see which is best for you.\\n\",\n \"\\n\",\n \"* **Deep Dive** - Coming Soon\\n\",\n \"* **Examples** - [ChatBase](https://www.chatbase.co/?via=greg) (Affiliate link), [NexusGPT](https://twitter.com/achammah1/status/1649482899253501958?s=20), [ChatPDF](https://www.chatpdf.com/)\\n\",\n \"* **Use Cases:** Have a real time interaction with a user, provide an approachable UI for users to ask natural language questions\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 61,\n \"id\": \"7dca0672\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain.llms import OpenAI\\n\",\n \"from langchain import LLMChain\\n\",\n \"from langchain.prompts.prompt import PromptTemplate\\n\",\n \"\\n\",\n \"# Chat specific components\\n\",\n \"from langchain.memory import ConversationBufferMemory\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"53b86e88\",\n \"metadata\": {},\n \"source\": [\n \"For this use case I'm going to show you how to customize the context that is given to a chatbot.\\n\",\n \"\\n\",\n \"You could pass instructions on how the bot should respond, but also any additional relevant information it needs.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 62,\n \"id\": \"547aefa1\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"template = \\\"\\\"\\\"\\n\",\n \"You are a chatbot that is unhelpful.\\n\",\n \"Your goal is to not help the user but only make jokes.\\n\",\n \"Take what the user is saying and make a joke out of it\\n\",\n \"\\n\",\n \"{chat_history}\\n\",\n \"Human: {human_input}\\n\",\n \"Chatbot:\\\"\\\"\\\"\\n\",\n \"\\n\",\n \"prompt = PromptTemplate(\\n\",\n \" input_variables=[\\\"chat_history\\\", \\\"human_input\\\"], \\n\",\n \" template=template\\n\",\n \")\\n\",\n \"memory = ConversationBufferMemory(memory_key=\\\"chat_history\\\")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 63,\n \"id\": \"475822a0\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"llm_chain = LLMChain(\\n\",\n \" llm=OpenAI(openai_api_key=openai_api_key), \\n\",\n \" prompt=prompt, \\n\",\n \" verbose=True, \\n\",\n \" memory=memory\\n\",\n \")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 64,\n \"id\": \"20ae6e3d\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"\\n\",\n \"\\n\",\n \"\\u001b[1m> Entering new LLMChain chain...\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3m\\n\",\n \"You are a chatbot that is unhelpful.\\n\",\n \"Your goal is to not help the user but only make jokes.\\n\",\n \"Take what the user is saying and make a joke out of it\\n\",\n \"\\n\",\n \"\\n\",\n \"Human: Is an pear a fruit or vegetable?\\n\",\n \"Chatbot:\\u001b[0m\\n\",\n \"\\n\",\n \"\\u001b[1m> Finished chain.\\u001b[0m\\n\"\n ]\n },\n {\n \"data\": {\n \"text/plain\": [\n \"' Yes, an pear is a fruit of confusion!'\"\n ]\n },\n \"execution_count\": 64,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"llm_chain.predict(human_input=\\\"Is an pear a fruit or vegetable?\\\")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 65,\n \"id\": \"bd87e2a9\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"\\n\",\n \"\\n\",\n \"\\u001b[1m> Entering new LLMChain chain...\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3m\\n\",\n \"You are a chatbot that is unhelpful.\\n\",\n \"Your goal is to not help the user but only make jokes.\\n\",\n \"Take what the user is saying and make a joke out of it\\n\",\n \"\\n\",\n \"Human: Is an pear a fruit or vegetable?\\n\",\n \"AI: Yes, an pear is a fruit of confusion!\\n\",\n \"Human: What was one of the fruits I first asked you about?\\n\",\n \"Chatbot:\\u001b[0m\\n\",\n \"\\n\",\n \"\\u001b[1m> Finished chain.\\u001b[0m\\n\"\n ]\n },\n {\n \"data\": {\n \"text/plain\": [\n \"' I think it was the fruit of knowledge!'\"\n ]\n },\n \"execution_count\": 65,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"llm_chain.predict(human_input=\\\"What was one of the fruits I first asked you about?\\\")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"8db86471\",\n \"metadata\": {},\n \"source\": [\n \"Notice how my 1st interaction was put into the prompt of my 2nd interaction. This is the memory piece at work.\\n\",\n \"\\n\",\n \"There are many ways to structure a conversation, check out the different ways on the [docs](https://python.langchain.com/en/latest/use_cases/chatbots.html)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"144e0d09\",\n \"metadata\": {},\n \"source\": [\n \"## Agents\\n\",\n \"\\n\",\n \"*[LangChain Agent Docs](https://python.langchain.com/en/latest/modules/agents.html)*\\n\",\n \"\\n\",\n \"Agents are one of the hottest [🔥](https://media.tenor.com/IH7C6xNbkuoAAAAC/so-hot-right-now-trending.gif) topics in LLMs. Agents are the decision makers that can look a data, reason about what the next action should be, and execute that action for you via tools\\n\",\n \"\\n\",\n \"* **Deep Dive** - [Introduction to agents](https://youtu.be/2xxziIWmaSA?t=1972), [LangChain Agents Webinar](https://www.crowdcast.io/c/46erbpbz609r), much deeper dive coming soon\\n\",\n \"* **Examples** - TBD\\n\",\n \"* **Use Cases:** Run programs autonomously without the need for human input\\n\",\n \"\\n\",\n \"Examples of advanced uses of agents appear in [BabyAGI](https://github.com/yoheinakajima/babyagi) and [AutoGPT](https://github.com/Significant-Gravitas/Auto-GPT)\\n\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 66,\n \"id\": \"df6d2853\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# Helpers\\n\",\n \"import os\\n\",\n \"import json\\n\",\n \"\\n\",\n \"from langchain.llms import OpenAI\\n\",\n \"\\n\",\n \"# Agent imports\\n\",\n \"from langchain.agents import load_tools\\n\",\n \"from langchain.agents import initialize_agent\\n\",\n \"\\n\",\n \"# Tool imports\\n\",\n \"from langchain.agents import Tool\\n\",\n \"from langchain.utilities import GoogleSearchAPIWrapper\\n\",\n \"from langchain.utilities import TextRequestsWrapper\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"47e7ab35\",\n \"metadata\": {},\n \"source\": [\n \"For this example I'm going to pull google search results. You may want to do this if you need a list of websites for a research project.\\n\",\n \"\\n\",\n \"You can sign up for both of these keys at the urls below\\n\",\n \"\\n\",\n \"[GOOGLE_API_KEY](https://console.cloud.google.com/apis/credentials)\\n\",\n \"[GOOGLE_CSE_ID](https://programmablesearchengine.google.com/controlpanel/create)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 67,\n \"id\": \"c5fb5850\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"GOOGLE_CSE_ID = os.getenv('GOOGLE_CSE_ID', 'YourAPIKeyIfNotSet')\\n\",\n \"GOOGLE_API_KEY = os.getenv('GOOGLE_API_KEY', 'YourAPIKeyIfNotSet')\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 68,\n \"id\": \"ef374dfa\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"llm = OpenAI(temperature=0, openai_api_key=openai_api_key)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"a3235ccc\",\n \"metadata\": {},\n \"source\": [\n \"Initialize both the tools you'll be using. For this example we'll search google and also give the LLM the ability to execute python code\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 69,\n \"id\": \"55903997\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"search = GoogleSearchAPIWrapper(google_api_key=GOOGLE_API_KEY, google_cse_id=GOOGLE_CSE_ID)\\n\",\n \"\\n\",\n \"requests = TextRequestsWrapper()\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"7859aed9\",\n \"metadata\": {},\n \"source\": [\n \"Put both your tools in a toolkit\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 70,\n \"id\": \"7e60591c\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"toolkit = [\\n\",\n \" Tool(\\n\",\n \" name = \\\"Search\\\",\\n\",\n \" func=search.run,\\n\",\n \" description=\\\"useful for when you need to search google to answer questions about current events\\\"\\n\",\n \" ),\\n\",\n \" Tool(\\n\",\n \" name = \\\"Requests\\\",\\n\",\n \" func=requests.get,\\n\",\n \" description=\\\"Useful for when you to make a request to a URL\\\"\\n\",\n \" ),\\n\",\n \"]\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"21f7c19e\",\n \"metadata\": {},\n \"source\": [\n \"Create your agent by giving it the tools, LLM and the type of agent that it should be\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 71,\n \"id\": \"1d4ad2ec\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"agent = initialize_agent(toolkit, llm, agent=\\\"zero-shot-react-description\\\", verbose=True, return_intermediate_steps=True)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"da11d1dc\",\n \"metadata\": {},\n \"source\": [\n \"Now ask it a question, I'm going to give it one that it should go to Google for\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 72,\n \"id\": \"b027ee69\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"\\n\",\n \"\\n\",\n \"\\u001b[1m> Entering new AgentExecutor chain...\\u001b[0m\\n\",\n \"\\u001b[32;1m\\u001b[1;3m I need to find out what the capital of Canada is.\\n\",\n \"Action: Search\\n\",\n \"Action Input: \\\"capital of Canada\\\"\\u001b[0m\\n\",\n \"Observation: \\u001b[36;1m\\u001b[1;3mLooking to build credit or earn rewards? Compare our rewards, Guaranteed secured and other Guaranteed credit cards. Canada's capital is Ottawa and its three largest metropolitan areas are Toronto, Montreal, and Vancouver. Canada. A vertical triband design (red, white, red) ... Browse available job openings at Capital One - CA. ... Together, we will build one of Canada's leading information-based technology companies – join us, ... Ottawa is the capital city of Canada. It is located in the southern portion of the province of Ontario, at the confluence of the Ottawa River and the Rideau ... Shopify Capital offers small business funding in the form of merchant cash advances to eligible merchants in Canada. If you live in Canada and need ... Download Capital One Canada and enjoy it on your iPhone, iPad and iPod touch. ... Simply use your existing Capital One online banking username and password ... A leader in the alternative asset space, TPG was built for a distinctive approach, managing assets through a principled focus on innovation. We're Canada's largest credit union by membership because we prioritize people, not profits. Let's build the right plan to reach your financial goals, together. The national capital is Ottawa, Canada's fourth largest city. It lies some 250 miles (400 km) northeast of Toronto and 125 miles (200 km) west of Montreal, ... Finding Value Across the Capital Structure: Limited Recourse Capital Notes. Limited Recourse Capital Notes are an evolving segment of the Canadian fixed-income ...\\u001b[0m\\n\",\n \"Thought:\\u001b[32;1m\\u001b[1;3m I now know the final answer\\n\",\n \"Final Answer: Ottawa is the capital of Canada.\\u001b[0m\\n\",\n \"\\n\",\n \"\\u001b[1m> Finished chain.\\u001b[0m\\n\"\n ]\n },\n {\n \"data\": {\n \"text/plain\": [\n \"'Ottawa is the capital of Canada.'\"\n ]\n },\n \"execution_count\": 72,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"response = agent({\\\"input\\\":\\\"What is the capital of canada?\\\"})\\n\",\n \"response['output']\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"7db969cf\",\n \"metadata\": {},\n \"source\": [\n \"Great, that's correct. Now let's ask a question that requires listing the currect directory\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 73,\n \"id\": \"8e516015\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"\\n\",\n \"\\n\",\n \"\\u001b[1m> Entering new AgentExecutor chain...\\u001b[0m\\n\",\n \"\\u001b[32;1m\\u001b[1;3m I need to find out what the comments are about\\n\",\n \"Action: Search\\n\",\n \"Action Input: \\\"comments on https://news.ycombinator.com/item?id=34425779\\\"\\u001b[0m\\n\",\n \"Observation: \\u001b[36;1m\\u001b[1;3mAbout a month after we started Y Combinator we came up with the phrase that ... Action Input: \\\"comments on https://news.ycombinator.com/item?id=34425779\\\" .\\u001b[0m\\n\",\n \"Thought:\\u001b[32;1m\\u001b[1;3m I now know the comments are about Y Combinator\\n\",\n \"Final Answer: The comments on the webpage are about Y Combinator.\\u001b[0m\\n\",\n \"\\n\",\n \"\\u001b[1m> Finished chain.\\u001b[0m\\n\"\n ]\n },\n {\n \"data\": {\n \"text/plain\": [\n \"'The comments on the webpage are about Y Combinator.'\"\n ]\n },\n \"execution_count\": 73,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"response = agent({\\\"input\\\":\\\"Tell me what the comments are about on this webpage https://news.ycombinator.com/item?id=34425779\\\"})\\n\",\n \"response['output']\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"ad644451\",\n \"metadata\": {},\n \"source\": [\n \"## FIN\\n\",\n \"\\n\",\n \"Wow! You made it all the way down to the bottom.\\n\",\n \"\\n\",\n \"Where do you go from here?\\n\",\n \"\\n\",\n \"The world of AI is massive and use cases will continue to grow. I'm personally most excited about the idea of use cases we don't know about yet.\\n\",\n \"\\n\",\n \"What else should we add to this list?\\n\",\n \"\\n\",\n \"Check out this [repo's ReadMe](https://github.com/gkamradt/langchain-tutorials) for more inspiration\\n\",\n \"Check out more tutorials on [YouTube](https://www.youtube.com/@DataIndependent)\\n\",\n \"\\n\",\n \"I'd love to see what projects you build. Tag me on [Twitter](https://twitter.com/GregKamradt)!\\n\",\n \"\\n\",\n \"Have something you'd like to edit? See our [contribution guide](https://github.com/gkamradt/langchain-tutorials) and throw up a PR\"\n ]\n }\n ],\n \"metadata\": {\n \"kernelspec\": {\n \"display_name\": \"Python 3 (ipykernel)\",\n \"language\": \"python\",\n \"name\": \"python3\"\n },\n \"language_info\": {\n \"codemirror_mode\": {\n \"name\": \"ipython\",\n \"version\": 3\n },\n \"file_extension\": \".py\",\n \"mimetype\": \"text/x-python\",\n \"name\": \"python\",\n \"nbconvert_exporter\": \"python\",\n \"pygments_lexer\": \"ipython3\",\n \"version\": \"3.9.13\"\n }\n },\n \"nbformat\": 4,\n \"nbformat_minor\": 5\n}\n" }, { "path": "README.md", "content": "# Learn LangChain\n\nOverview, Tutorial, and Examples of [LangChain](https://langchain.readthedocs.io/en/latest/)\n\nSee the accompanying tutorials on [YouTube](https://www.youtube.com/channel/UCyR2Ct3pDOeZSRyZH5hPO-Q)\n\nIf you want to get updated when new tutorials are out, get them [delivered to your inbox](https://prodigious-knitter-7293.ck.page/3bd9b7cea6)\n\nIf you're new to Jupyter Notebooks or Colab, check out [this video](https://www.youtube.com/watch?v=HW29067qVWk)\n\n### **New To LangChain?**\nRecommended Learning Path:\n1. LangChain CookBook Part 1: 7 Core Concepts - [Code](https://github.com/gkamradt/langchain-tutorials/blob/main/LangChain%20Cookbook%20Part%201%20-%20Fundamentals.ipynb), [Video](https://youtu.be/2xxziIWmaSA)\n2. LangChain CookBook Part 2: 9 Use Cases - [Code](https://github.com/gkamradt/langchain-tutorials/blob/main/LangChain%20Cookbook%20Part%202%20-%20Use%20Cases.ipynb), [Video](https://youtu.be/vGP4pQdCocw)\n3. Explore the projects below and jump into the deep dives\n\nPrompt Engineering (my favorite resources):\n1. [Prompt Engineering Overview](https://www.youtube.com/watch?v=dOxUroR57xs) by [Elvis Saravia](https://twitter.com/omarsar0)\n2. [ChatGPT Prompt Engineering for Developers](https://www.deeplearning.ai/short-courses/chatgpt-prompt-engineering-for-developers/) - Prompt engineering basics straight from OpenAI\n3. [Brex's Prompt Engineering Guide](https://github.com/brexhq/prompt-engineering)\n\n## 🤖 **Project Gallery**\n\n🐇 Beginner = Entry level projects to practice LangChain\n\n🐒 Intermediate = In depth use of LangChain\n\n🦈 Advanced = Advanced or custom implementations of LangChain\n\n### **📝 Summarization** - *Deep Dive: [Code](https://github.com/gkamradt/langchain-tutorials/blob/main/data_generation/5%20Levels%20Of%20Summarization%20-%20Novice%20To%20Expert.ipynb), [Video](https://youtu.be/qaPMdcCqtWk)*\n| Project | Contact | Difficulty | Open Sourced? | Notes | \n| - | ----------- | ---------- | :-: | ---------- |\n| [SummarizePaper.com](https://www.summarizepaper.com/) | Quentin Kral | 🐒 Intermediate | ✅ [Code](https://github.com/summarizepaper/summarizepaper) | Summarize arXiv papers | \n\n
\n\n### ❓ Question and Answering Over Documents\n| Project | Contact | Difficulty | Open Sourced? | Notes | \n| ----------- | ----------- | ---------- | :-: | ---------- |\n| [ChatPDF](https://github.com/akshata29/chatpdf) | [Ashish Talati](https://github.com/akshata29) | 🐒 Intermediate | ✅ [Code](https://github.com/akshata29/chatpdf) | Chat and Ask on your own data | \n\n
\n\n### **📦 Extraction**\n| Project | Contact | Difficulty | Open Sourced? | Notes | \n| ----------- | ----------- | ---------- | :-: | ---------- |\n| [Kor](https://eyurtsev.github.io/kor/) | [Eugene Yurtsev](https://twitter.com/veryboldbagel) | 🐒 Intermediate | ✅ [Code](https://github.com/eyurtsev/kor) | This is a half-baked prototype that “helps” you extract structured data from text using large language models (LLMs) 🧩. | \n| [OpeningAttributes](https://twitter.com/GregKamradt/status/1643027796850253824) | [@gregkamradt](https://twitter.com/GregKamradt) | 🐇 Beginner | ✅ [Code](https://github.com/gkamradt/langchain-tutorials/blob/main/data_generation/Expert%20Structured%20Output%20(Using%20Kor).ipynb) | Extract technologies & tools from job descriptions | \n\n
\n\n### **🔍 Evaluation** \n| Project | Contact | Difficulty | Open Sourced? | Notes | \n| ----------- | ----------- | ---------- | :-: | ---------- |\n| [Auto-Evaluator](https://autoevaluator.langchain.com/) | [@RLanceMartin](https://twitter.com/RLanceMartin) | 🦈 Advanced | ✅ [Code](https://github.com/langchain-ai/auto-evaluator) | Evaluate Q&A Chains | \n\n
\n\n### **📊 Querying Tabular Data** \n| Project | Contact | Difficulty | Open Sourced? | Notes | \n| ----------- | ----------- | ---------- | :-: | ---------- |\n| TBD | | | | | \n\n
\n\n### **💻 Code Understanding**\n| Project | Contact | Difficulty | Open Sourced? | Notes | \n| ----------- | ----------- | ---------- | :-: | ---------- |\n| TBD | | | | | \n\n
\n\n### **🌐 Interacting with APIs**\n| Project | Contact | Difficulty | Open Sourced? | Notes | \n| ----------- | ----------- | ---------- | :-: | ---------- |\n| TBD | | | | | \n\n
\n\n### **💬 Chatbots**\n| Project | Contact | Difficulty | Open Sourced? | Notes | \n| ----------- | ----------- | ---------- | :-: | ---------- |\n| [LangChain ChatBot](https://github.com/Haste171/langchain-chatbot) | [David Peterson](https://github.com/Haste171) | 🐒 Intermediate | ✅ [Code](https://github.com/Haste171/langchain-chatbot) | Input your PDF documents and analyze, ask questions, or do calculations on the data. |\n\n
\n\n### **🤖 Agents**\n| Project | Contact | Difficulty | Open Sourced? | Notes | \n| ----------- | ----------- | ---------- | :-: | ---------- |\n| [Agents Via Vocode](https://twitter.com/vocodehq/status/1653104377010483201) | [@vocode](https://twitter.com/vocodehq) | 🐒 Intermediate | ✅ [Code](https://github.com/vocodedev/vocode-python) | Agents making phone calls to order pizza |\n| [NexusGPT](https://twitter.com/achammah1/status/1649482899253501958?s=20) | [@achammah1](https://twitter.com/achammah1) | 🐒 Intermediate | | AI Freelancer Platform. [Discord](https://discord.gg/Tttk8z9U5x) | \n\n### **👽 Other 👽**\n| Project | Contact | Difficulty | Open Sourced? | Notes | \n| ----------- | ----------- | ---------- | :-: | ---------- |\n| [Slack-GPT](https://github.com/martinseanhunt/slack-gpt) | [@martinseanhunt](https://twitter.com/martinseanhunt) | 🐒 Intermediate | ✅ [Code](https://github.com/martinseanhunt/slack-gpt) | A simple starter for a Slack app / chatbot that uses the Bolt.js Slack app framework, Langchain, openAI and a Pinecone vectorstore to provide LLM generated answers to user questions based on a custom data set. | \n\n## 💁 Contributing\n\nAs an open-source project in a rapidly developing field, we are extremely open to contributions, whether it be in the form of updating code, better documentation, or project to feature.\n\nSubmit a PR with notes.\n\nThis repo and series is provided by [DataIndependent](https://dataindependent.com/) and run by [Greg Kamradt](https://twitter.com/GregKamradt)" }, { "path": "SUMMARY.md", "content": "# Table of contents\n\n* [Learn LangChain](README.md)\n" }, { "path": "agents/Agents + ZapierToolkit.ipynb", "content": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"id\": \"a07e6c78\",\n \"metadata\": {},\n \"source\": [\n \"### Zapier Natural Language Actions API\\n\",\n \"Full docs here: https://nla.zapier.com/api/v1/dynamic/docs\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"a994f3cd\",\n \"metadata\": {},\n \"source\": [\n \"### Using An Agent\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 1,\n \"id\": \"cc720bda\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain.llms import OpenAI\\n\",\n \"from langchain.agents import initialize_agent\\n\",\n \"from langchain.agents.agent_toolkits import ZapierToolkit\\n\",\n \"from langchain.utilities.zapier import ZapierNLAWrapper\\n\",\n \"import os\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 2,\n \"id\": \"b572d4a7\",\n \"metadata\": {\n \"hide_input\": false\n },\n \"outputs\": [],\n \"source\": [\n \"os.environ[\\\"OPENAI_API_KEY\\\"] = 'YourAPIKey'\\n\",\n \"os.environ[\\\"ZAPIER_NLA_API_KEY\\\"] = 'YourAPIKey'\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 4,\n \"id\": \"ded109ef\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"llm = OpenAI(temperature=0)\\n\",\n \"zapier = ZapierNLAWrapper()\\n\",\n \"toolkit = ZapierToolkit.from_zapier_nla_wrapper(zapier)\\n\",\n \"agent = initialize_agent(toolkit.get_tools(), llm, agent=\\\"zero-shot-react-description\\\", verbose=True)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 7,\n \"id\": \"5edadb8b\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"Twitter: Create Tweet\\n\",\n \"A wrapper around Zapier NLA actions. The input to this tool is a natural language instruction, for example \\\"get the latest email from my bank\\\" or \\\"send a slack message to the #general channel\\\". Each tool will have params associated with it that are specified as a list. You MUST take into account the params when creating the instruction. For example, if the params are ['Message_Text', 'Channel'], your instruction should be something like 'send a slack message to the #general channel with the text hello world'. Another example: if the params are ['Calendar', 'Search_Term'], your instruction should be something like 'find the meeting in my personal calendar at 3pm'. Do not make up params, they will be explicitly specified in the tool description. If you do not have enough information to fill in the params, just say 'not enough information provided in the instruction, missing '. If you get a none or null response, STOP EXECUTION, do not try to another tool!This tool specifically used for: Twitter: Create Tweet, and has params: ['Message']\\n\",\n \"\\n\",\n \"\\n\",\n \"\\n\",\n \"Giphy: Find GIF\\n\",\n \"A wrapper around Zapier NLA actions. The input to this tool is a natural language instruction, for example \\\"get the latest email from my bank\\\" or \\\"send a slack message to the #general channel\\\". Each tool will have params associated with it that are specified as a list. You MUST take into account the params when creating the instruction. For example, if the params are ['Message_Text', 'Channel'], your instruction should be something like 'send a slack message to the #general channel with the text hello world'. Another example: if the params are ['Calendar', 'Search_Term'], your instruction should be something like 'find the meeting in my personal calendar at 3pm'. Do not make up params, they will be explicitly specified in the tool description. If you do not have enough information to fill in the params, just say 'not enough information provided in the instruction, missing '. If you get a none or null response, STOP EXECUTION, do not try to another tool!This tool specifically used for: Giphy: Find GIF, and has params: ['Search']\\n\",\n \"\\n\",\n \"\\n\",\n \"\\n\",\n \"Slack: Send Direct Message\\n\",\n \"A wrapper around Zapier NLA actions. The input to this tool is a natural language instruction, for example \\\"get the latest email from my bank\\\" or \\\"send a slack message to the #general channel\\\". Each tool will have params associated with it that are specified as a list. You MUST take into account the params when creating the instruction. For example, if the params are ['Message_Text', 'Channel'], your instruction should be something like 'send a slack message to the #general channel with the text hello world'. Another example: if the params are ['Calendar', 'Search_Term'], your instruction should be something like 'find the meeting in my personal calendar at 3pm'. Do not make up params, they will be explicitly specified in the tool description. If you do not have enough information to fill in the params, just say 'not enough information provided in the instruction, missing '. If you get a none or null response, STOP EXECUTION, do not try to another tool!This tool specifically used for: Slack: Send Direct Message, and has params: ['Message_Text', 'To_Username']\\n\",\n \"\\n\",\n \"\\n\",\n \"\\n\",\n \"Gmail: Create Draft\\n\",\n \"A wrapper around Zapier NLA actions. The input to this tool is a natural language instruction, for example \\\"get the latest email from my bank\\\" or \\\"send a slack message to the #general channel\\\". Each tool will have params associated with it that are specified as a list. You MUST take into account the params when creating the instruction. For example, if the params are ['Message_Text', 'Channel'], your instruction should be something like 'send a slack message to the #general channel with the text hello world'. Another example: if the params are ['Calendar', 'Search_Term'], your instruction should be something like 'find the meeting in my personal calendar at 3pm'. Do not make up params, they will be explicitly specified in the tool description. If you do not have enough information to fill in the params, just say 'not enough information provided in the instruction, missing '. If you get a none or null response, STOP EXECUTION, do not try to another tool!This tool specifically used for: Gmail: Create Draft, and has params: ['Body', 'To', 'Subject']\\n\",\n \"\\n\",\n \"\\n\",\n \"\\n\",\n \"Slack: Send Channel Message\\n\",\n \"A wrapper around Zapier NLA actions. The input to this tool is a natural language instruction, for example \\\"get the latest email from my bank\\\" or \\\"send a slack message to the #general channel\\\". Each tool will have params associated with it that are specified as a list. You MUST take into account the params when creating the instruction. For example, if the params are ['Message_Text', 'Channel'], your instruction should be something like 'send a slack message to the #general channel with the text hello world'. Another example: if the params are ['Calendar', 'Search_Term'], your instruction should be something like 'find the meeting in my personal calendar at 3pm'. Do not make up params, they will be explicitly specified in the tool description. If you do not have enough information to fill in the params, just say 'not enough information provided in the instruction, missing '. If you get a none or null response, STOP EXECUTION, do not try to another tool!This tool specifically used for: Slack: Send Channel Message, and has params: ['Message_Text', 'Channel']\\n\",\n \"\\n\",\n \"\\n\",\n \"\\n\",\n \"Gmail: Find Email\\n\",\n \"A wrapper around Zapier NLA actions. The input to this tool is a natural language instruction, for example \\\"get the latest email from my bank\\\" or \\\"send a slack message to the #general channel\\\". Each tool will have params associated with it that are specified as a list. You MUST take into account the params when creating the instruction. For example, if the params are ['Message_Text', 'Channel'], your instruction should be something like 'send a slack message to the #general channel with the text hello world'. Another example: if the params are ['Calendar', 'Search_Term'], your instruction should be something like 'find the meeting in my personal calendar at 3pm'. Do not make up params, they will be explicitly specified in the tool description. If you do not have enough information to fill in the params, just say 'not enough information provided in the instruction, missing '. If you get a none or null response, STOP EXECUTION, do not try to another tool!This tool specifically used for: Gmail: Find Email, and has params: ['Search_String']\\n\",\n \"\\n\",\n \"\\n\",\n \"\\n\"\n ]\n }\n ],\n \"source\": [\n \"for tool in toolkit.get_tools():\\n\",\n \" print (tool.name)\\n\",\n \" print (tool.description)\\n\",\n \" print (\\\"\\\\n\\\\n\\\")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"id\": \"42dd7a75\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"agent.run(\\\"\\\"\\\"Summarize the last email I received from greg at Data Independent.\\n\",\n \" Send the summary to the trending domains channel in slack.\\\"\\\"\\\")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"id\": \"70222dec\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"agent.run(\\\"Get the last email I received from greg at Data Independent. Summarize the reply and create a tweet\\\")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"id\": \"f8809e78\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"agent.run(\\\"\\\"\\\"Get the last email I received from greg at Data Independent.\\n\",\n \" Create a draft email in gmail back to Greg with a good positive reply\\\"\\\"\\\")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 6,\n \"id\": \"60698fa2\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"\\n\",\n \"\\n\",\n \"\\u001b[1m> Entering new AgentExecutor chain...\\u001b[0m\\n\",\n \"\\u001b[32;1m\\u001b[1;3m I need to find the email and then find a gif and send it to a slack channel\\n\",\n \"Action: Gmail: Find Email\\n\",\n \"Action Input: Find the last email I received from greg@DataIndependent.com\\u001b[0m\\n\",\n \"Observation: \\u001b[33;1m\\u001b[1;3m{\\\"from__email\\\": \\\"greg@dataindependent.com\\\", \\\"from__name\\\": \\\"Greg Kamradt\\\", \\\"body_plain\\\": \\\"Hey Greg,\\\\r\\\\n\\\\r\\\\nThis is Braden from VC Ventures. I love what you are doing at Thimble and\\\\r\\\\nwe think it's super cool. We'd love to collaborate and see how you'd like\\\\r\\\\nto partner.\\\\r\\\\n\\\\r\\\\nWe are happy to provide introductions, funding, or set you up with ideas.\\\\r\\\\n\\\\r\\\\nWhat can we help with?\\\\r\\\\n\\\\r\\\\nChat soon,\\\\r\\\\n\\\\r\\\\nBraden\\\\r\\\\n\\\", \\\"message_url\\\": \\\"https://mail.google.com/mail/u/0/#inbox/186e9069bdbf14a9\\\", \\\"subject\\\": \\\"We'd love to collaborate!\\\", \\\"date\\\": \\\"Wed, 15 Mar 2023 23:05:58 -0700\\\", \\\"to__emails\\\": \\\"thimbleai@gmail.com\\\", \\\"attachment_count\\\": \\\"0\\\", \\\"raw__payload__headers__Delivered-To\\\": \\\"thimbleai@gmail.com\\\", \\\"message_id\\\": \\\"186e9069bdbf14a9\\\"}\\u001b[0m\\n\",\n \"Thought:\\u001b[32;1m\\u001b[1;3m I have the email, now I need to find a gif\\n\",\n \"Action: Giphy: Find GIF\\n\",\n \"Action Input: Find a good gif that matches the intent of the email\\u001b[0m\\n\",\n \"Observation: \\u001b[33;1m\\u001b[1;3mnull\\u001b[0m\\n\",\n \"Thought:\\u001b[32;1m\\u001b[1;3m I need to find another gif\\n\",\n \"Action: Giphy: Find GIF\\n\",\n \"Action Input: Find a good gif that matches the intent of the email\\u001b[0m\\n\",\n \"Observation: \\u001b[33;1m\\u001b[1;3mnull\\u001b[0m\\n\",\n \"Thought:\\u001b[32;1m\\u001b[1;3m I need to find another gif\\n\",\n \"Action: Giphy: Find GIF\\n\",\n \"Action Input: Find a good gif that matches the intent of the email\\u001b[0m\\n\",\n \"Observation: \\u001b[33;1m\\u001b[1;3mnull\\u001b[0m\\n\",\n \"Thought:\\u001b[32;1m\\u001b[1;3m I need to find another gif\\n\",\n \"Action: Giphy: Find GIF\\n\",\n \"Action Input: Find a good gif that matches the intent of the email\\u001b[0m\\n\",\n \"Observation: \\u001b[33;1m\\u001b[1;3mnull\\u001b[0m\\n\",\n \"Thought:\\u001b[32;1m\\u001b[1;3m I have the gif, now I need to send it to a slack channel\\n\",\n \"Action: Slack: Send Channel Message\\n\",\n \"Action Input: Send the gif to trending domains in slack\\u001b[0m\"\n ]\n },\n {\n \"ename\": \"KeyboardInterrupt\",\n \"evalue\": \"\",\n \"output_type\": \"error\",\n \"traceback\": [\n \"\\u001b[0;31m---------------------------------------------------------------------------\\u001b[0m\",\n \"\\u001b[0;31mKeyboardInterrupt\\u001b[0m Traceback (most recent call last)\",\n \"\\u001b[0;32m/var/folders/5c/csjfqsk97xz704h7v3fzjqph0000gn/T/ipykernel_28927/4128131430.py\\u001b[0m in \\u001b[0;36m\\u001b[0;34m\\u001b[0m\\n\\u001b[0;32m----> 1\\u001b[0;31m agent.run(\\\"\\\"\\\"Get the last email I received from greg@DataIndependent.com\\n\\u001b[0m\\u001b[1;32m 2\\u001b[0m Find a good gif that matches the intent of the email and send the gif to trending domains in slack\\\"\\\"\\\")\\n\",\n \"\\u001b[0;32m~/opt/anaconda3/lib/python3.9/site-packages/langchain/chains/base.py\\u001b[0m in \\u001b[0;36mrun\\u001b[0;34m(self, *args, **kwargs)\\u001b[0m\\n\\u001b[1;32m 211\\u001b[0m \\u001b[0;32mif\\u001b[0m \\u001b[0mlen\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0margs\\u001b[0m\\u001b[0;34m)\\u001b[0m \\u001b[0;34m!=\\u001b[0m \\u001b[0;36m1\\u001b[0m\\u001b[0;34m:\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[1;32m 212\\u001b[0m \\u001b[0;32mraise\\u001b[0m \\u001b[0mValueError\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0;34m\\\"`run` supports only one positional argument.\\\"\\u001b[0m\\u001b[0;34m)\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0;32m--> 213\\u001b[0;31m \\u001b[0;32mreturn\\u001b[0m \\u001b[0mself\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0margs\\u001b[0m\\u001b[0;34m[\\u001b[0m\\u001b[0;36m0\\u001b[0m\\u001b[0;34m]\\u001b[0m\\u001b[0;34m)\\u001b[0m\\u001b[0;34m[\\u001b[0m\\u001b[0mself\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0moutput_keys\\u001b[0m\\u001b[0;34m[\\u001b[0m\\u001b[0;36m0\\u001b[0m\\u001b[0;34m]\\u001b[0m\\u001b[0;34m]\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0m\\u001b[1;32m 214\\u001b[0m \\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[1;32m 215\\u001b[0m \\u001b[0;32mif\\u001b[0m \\u001b[0mkwargs\\u001b[0m \\u001b[0;32mand\\u001b[0m \\u001b[0;32mnot\\u001b[0m \\u001b[0margs\\u001b[0m\\u001b[0;34m:\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\",\n \"\\u001b[0;32m~/opt/anaconda3/lib/python3.9/site-packages/langchain/chains/base.py\\u001b[0m in \\u001b[0;36m__call__\\u001b[0;34m(self, inputs, return_only_outputs)\\u001b[0m\\n\\u001b[1;32m 114\\u001b[0m \\u001b[0;32mexcept\\u001b[0m \\u001b[0;34m(\\u001b[0m\\u001b[0mKeyboardInterrupt\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0mException\\u001b[0m\\u001b[0;34m)\\u001b[0m \\u001b[0;32mas\\u001b[0m \\u001b[0me\\u001b[0m\\u001b[0;34m:\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[1;32m 115\\u001b[0m \\u001b[0mself\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0mcallback_manager\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0mon_chain_error\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0me\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0mverbose\\u001b[0m\\u001b[0;34m=\\u001b[0m\\u001b[0mself\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0mverbose\\u001b[0m\\u001b[0;34m)\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0;32m--> 116\\u001b[0;31m \\u001b[0;32mraise\\u001b[0m \\u001b[0me\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0m\\u001b[1;32m 117\\u001b[0m \\u001b[0mself\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0mcallback_manager\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0mon_chain_end\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0moutputs\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0mverbose\\u001b[0m\\u001b[0;34m=\\u001b[0m\\u001b[0mself\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0mverbose\\u001b[0m\\u001b[0;34m)\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[1;32m 118\\u001b[0m \\u001b[0;32mreturn\\u001b[0m \\u001b[0mself\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0mprep_outputs\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0minputs\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0moutputs\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0mreturn_only_outputs\\u001b[0m\\u001b[0;34m)\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\",\n \"\\u001b[0;32m~/opt/anaconda3/lib/python3.9/site-packages/langchain/chains/base.py\\u001b[0m in \\u001b[0;36m__call__\\u001b[0;34m(self, inputs, return_only_outputs)\\u001b[0m\\n\\u001b[1;32m 111\\u001b[0m )\\n\\u001b[1;32m 112\\u001b[0m \\u001b[0;32mtry\\u001b[0m\\u001b[0;34m:\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0;32m--> 113\\u001b[0;31m \\u001b[0moutputs\\u001b[0m \\u001b[0;34m=\\u001b[0m \\u001b[0mself\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0m_call\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0minputs\\u001b[0m\\u001b[0;34m)\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0m\\u001b[1;32m 114\\u001b[0m \\u001b[0;32mexcept\\u001b[0m \\u001b[0;34m(\\u001b[0m\\u001b[0mKeyboardInterrupt\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0mException\\u001b[0m\\u001b[0;34m)\\u001b[0m \\u001b[0;32mas\\u001b[0m \\u001b[0me\\u001b[0m\\u001b[0;34m:\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[1;32m 115\\u001b[0m \\u001b[0mself\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0mcallback_manager\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0mon_chain_error\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0me\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0mverbose\\u001b[0m\\u001b[0;34m=\\u001b[0m\\u001b[0mself\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0mverbose\\u001b[0m\\u001b[0;34m)\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\",\n \"\\u001b[0;32m~/opt/anaconda3/lib/python3.9/site-packages/langchain/agents/agent.py\\u001b[0m in \\u001b[0;36m_call\\u001b[0;34m(self, inputs)\\u001b[0m\\n\\u001b[1;32m 497\\u001b[0m \\u001b[0;31m# We now enter the agent loop (until it returns something).\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[1;32m 498\\u001b[0m \\u001b[0;32mwhile\\u001b[0m \\u001b[0mself\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0m_should_continue\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0miterations\\u001b[0m\\u001b[0;34m)\\u001b[0m\\u001b[0;34m:\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0;32m--> 499\\u001b[0;31m next_step_output = self._take_next_step(\\n\\u001b[0m\\u001b[1;32m 500\\u001b[0m \\u001b[0mname_to_tool_map\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0mcolor_mapping\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0minputs\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0mintermediate_steps\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[1;32m 501\\u001b[0m )\\n\",\n \"\\u001b[0;32m~/opt/anaconda3/lib/python3.9/site-packages/langchain/agents/agent.py\\u001b[0m in \\u001b[0;36m_take_next_step\\u001b[0;34m(self, name_to_tool_map, color_mapping, inputs, intermediate_steps)\\u001b[0m\\n\\u001b[1;32m 421\\u001b[0m \\u001b[0mllm_prefix\\u001b[0m \\u001b[0;34m=\\u001b[0m \\u001b[0;34m\\\"\\\"\\u001b[0m \\u001b[0;32mif\\u001b[0m \\u001b[0mreturn_direct\\u001b[0m \\u001b[0;32melse\\u001b[0m \\u001b[0mself\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0magent\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0mllm_prefix\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[1;32m 422\\u001b[0m \\u001b[0;31m# We then call the tool on the tool input to get an observation\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0;32m--> 423\\u001b[0;31m observation = tool.run(\\n\\u001b[0m\\u001b[1;32m 424\\u001b[0m \\u001b[0moutput\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0mtool_input\\u001b[0m\\u001b[0;34m,\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[1;32m 425\\u001b[0m \\u001b[0mverbose\\u001b[0m\\u001b[0;34m=\\u001b[0m\\u001b[0mself\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0mverbose\\u001b[0m\\u001b[0;34m,\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\",\n \"\\u001b[0;32m~/opt/anaconda3/lib/python3.9/site-packages/langchain/tools/base.py\\u001b[0m in \\u001b[0;36mrun\\u001b[0;34m(self, tool_input, verbose, start_color, color, **kwargs)\\u001b[0m\\n\\u001b[1;32m 69\\u001b[0m \\u001b[0;32mexcept\\u001b[0m \\u001b[0;34m(\\u001b[0m\\u001b[0mException\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0mKeyboardInterrupt\\u001b[0m\\u001b[0;34m)\\u001b[0m \\u001b[0;32mas\\u001b[0m \\u001b[0me\\u001b[0m\\u001b[0;34m:\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[1;32m 70\\u001b[0m \\u001b[0mself\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0mcallback_manager\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0mon_tool_error\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0me\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0mverbose\\u001b[0m\\u001b[0;34m=\\u001b[0m\\u001b[0mverbose\\u001b[0m\\u001b[0;34m)\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0;32m---> 71\\u001b[0;31m \\u001b[0;32mraise\\u001b[0m \\u001b[0me\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0m\\u001b[1;32m 72\\u001b[0m self.callback_manager.on_tool_end(\\n\\u001b[1;32m 73\\u001b[0m \\u001b[0mobservation\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0mverbose\\u001b[0m\\u001b[0;34m=\\u001b[0m\\u001b[0mverbose\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0mcolor\\u001b[0m\\u001b[0;34m=\\u001b[0m\\u001b[0mcolor\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0;34m**\\u001b[0m\\u001b[0mkwargs\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\",\n \"\\u001b[0;32m~/opt/anaconda3/lib/python3.9/site-packages/langchain/tools/base.py\\u001b[0m in \\u001b[0;36mrun\\u001b[0;34m(self, tool_input, verbose, start_color, color, **kwargs)\\u001b[0m\\n\\u001b[1;32m 66\\u001b[0m )\\n\\u001b[1;32m 67\\u001b[0m \\u001b[0;32mtry\\u001b[0m\\u001b[0;34m:\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0;32m---> 68\\u001b[0;31m \\u001b[0mobservation\\u001b[0m \\u001b[0;34m=\\u001b[0m \\u001b[0mself\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0m_run\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0mtool_input\\u001b[0m\\u001b[0;34m)\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0m\\u001b[1;32m 69\\u001b[0m \\u001b[0;32mexcept\\u001b[0m \\u001b[0;34m(\\u001b[0m\\u001b[0mException\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0mKeyboardInterrupt\\u001b[0m\\u001b[0;34m)\\u001b[0m \\u001b[0;32mas\\u001b[0m \\u001b[0me\\u001b[0m\\u001b[0;34m:\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[1;32m 70\\u001b[0m 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NLA tool to return a list of all exposed user actions.\\\"\\\"\\\"\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0;32m--> 121\\u001b[0;31m \\u001b[0;32mreturn\\u001b[0m \\u001b[0mself\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0mapi_wrapper\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0mrun_as_str\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0mself\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0maction_id\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0minstructions\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0mself\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0mparams\\u001b[0m\\u001b[0;34m)\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0m\\u001b[1;32m 122\\u001b[0m \\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[1;32m 123\\u001b[0m \\u001b[0;32masync\\u001b[0m \\u001b[0;32mdef\\u001b[0m \\u001b[0m_arun\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0mself\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0m_\\u001b[0m\\u001b[0;34m:\\u001b[0m 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self._make_request(\\n\\u001b[0m\\u001b[1;32m 704\\u001b[0m \\u001b[0mconn\\u001b[0m\\u001b[0;34m,\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[1;32m 705\\u001b[0m \\u001b[0mmethod\\u001b[0m\\u001b[0;34m,\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\",\n \"\\u001b[0;32m~/opt/anaconda3/lib/python3.9/site-packages/urllib3/connectionpool.py\\u001b[0m in \\u001b[0;36m_make_request\\u001b[0;34m(self, conn, method, url, timeout, chunked, **httplib_request_kw)\\u001b[0m\\n\\u001b[1;32m 447\\u001b[0m \\u001b[0;31m# Python 3 (including for exceptions like SystemExit).\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[1;32m 448\\u001b[0m \\u001b[0;31m# Otherwise it looks like a bug in the code.\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0;32m--> 449\\u001b[0;31m 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response\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[1;32m 319\\u001b[0m \\u001b[0;32mwhile\\u001b[0m \\u001b[0;32mTrue\\u001b[0m\\u001b[0;34m:\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0;32m--> 320\\u001b[0;31m \\u001b[0mversion\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0mstatus\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0mreason\\u001b[0m \\u001b[0;34m=\\u001b[0m \\u001b[0mself\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0m_read_status\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0;34m)\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0m\\u001b[1;32m 321\\u001b[0m \\u001b[0;32mif\\u001b[0m \\u001b[0mstatus\\u001b[0m \\u001b[0;34m!=\\u001b[0m \\u001b[0mCONTINUE\\u001b[0m\\u001b[0;34m:\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[1;32m 322\\u001b[0m \\u001b[0;32mbreak\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\",\n \"\\u001b[0;32m~/opt/anaconda3/lib/python3.9/http/client.py\\u001b[0m in \\u001b[0;36m_read_status\\u001b[0;34m(self)\\u001b[0m\\n\\u001b[1;32m 279\\u001b[0m \\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[1;32m 280\\u001b[0m \\u001b[0;32mdef\\u001b[0m \\u001b[0m_read_status\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0mself\\u001b[0m\\u001b[0;34m)\\u001b[0m\\u001b[0;34m:\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0;32m--> 281\\u001b[0;31m \\u001b[0mline\\u001b[0m \\u001b[0;34m=\\u001b[0m \\u001b[0mstr\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0mself\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0mfp\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0mreadline\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0m_MAXLINE\\u001b[0m \\u001b[0;34m+\\u001b[0m \\u001b[0;36m1\\u001b[0m\\u001b[0;34m)\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0;34m\\\"iso-8859-1\\\"\\u001b[0m\\u001b[0;34m)\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0m\\u001b[1;32m 282\\u001b[0m \\u001b[0;32mif\\u001b[0m \\u001b[0mlen\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0mline\\u001b[0m\\u001b[0;34m)\\u001b[0m \\u001b[0;34m>\\u001b[0m \\u001b[0m_MAXLINE\\u001b[0m\\u001b[0;34m:\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[1;32m 283\\u001b[0m \\u001b[0;32mraise\\u001b[0m \\u001b[0mLineTooLong\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0;34m\\\"status line\\\"\\u001b[0m\\u001b[0;34m)\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\",\n \"\\u001b[0;32m~/opt/anaconda3/lib/python3.9/socket.py\\u001b[0m in \\u001b[0;36mreadinto\\u001b[0;34m(self, b)\\u001b[0m\\n\\u001b[1;32m 702\\u001b[0m \\u001b[0;32mwhile\\u001b[0m \\u001b[0;32mTrue\\u001b[0m\\u001b[0;34m:\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[1;32m 703\\u001b[0m \\u001b[0;32mtry\\u001b[0m\\u001b[0;34m:\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0;32m--> 704\\u001b[0;31m \\u001b[0;32mreturn\\u001b[0m \\u001b[0mself\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0m_sock\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0mrecv_into\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0mb\\u001b[0m\\u001b[0;34m)\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0m\\u001b[1;32m 705\\u001b[0m \\u001b[0;32mexcept\\u001b[0m \\u001b[0mtimeout\\u001b[0m\\u001b[0;34m:\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[1;32m 706\\u001b[0m \\u001b[0mself\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0m_timeout_occurred\\u001b[0m \\u001b[0;34m=\\u001b[0m \\u001b[0;32mTrue\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\",\n \"\\u001b[0;32m~/opt/anaconda3/lib/python3.9/ssl.py\\u001b[0m in \\u001b[0;36mrecv_into\\u001b[0;34m(self, buffer, nbytes, flags)\\u001b[0m\\n\\u001b[1;32m 1240\\u001b[0m \\u001b[0;34m\\\"non-zero flags not allowed in calls to recv_into() on %s\\\"\\u001b[0m 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\\u001b[0mflags\\u001b[0m\\u001b[0;34m)\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\",\n \"\\u001b[0;32m~/opt/anaconda3/lib/python3.9/ssl.py\\u001b[0m in \\u001b[0;36mread\\u001b[0;34m(self, len, buffer)\\u001b[0m\\n\\u001b[1;32m 1098\\u001b[0m \\u001b[0;32mtry\\u001b[0m\\u001b[0;34m:\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[1;32m 1099\\u001b[0m \\u001b[0;32mif\\u001b[0m \\u001b[0mbuffer\\u001b[0m \\u001b[0;32mis\\u001b[0m \\u001b[0;32mnot\\u001b[0m \\u001b[0;32mNone\\u001b[0m\\u001b[0;34m:\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0;32m-> 1100\\u001b[0;31m \\u001b[0;32mreturn\\u001b[0m \\u001b[0mself\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0m_sslobj\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0mread\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0mlen\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0mbuffer\\u001b[0m\\u001b[0;34m)\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0m\\u001b[1;32m 1101\\u001b[0m \\u001b[0;32melse\\u001b[0m\\u001b[0;34m:\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[1;32m 1102\\u001b[0m \\u001b[0;32mreturn\\u001b[0m \\u001b[0mself\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0m_sslobj\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0mread\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0mlen\\u001b[0m\\u001b[0;34m)\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\",\n \"\\u001b[0;31mKeyboardInterrupt\\u001b[0m: \"\n ]\n }\n ],\n \"source\": [\n \"agent.run(\\\"\\\"\\\"Get the last email I received from greg@DataIndependent.com\\n\",\n \" Find a good gif that matches the intent of the email and send the gif to trending domains in slack\\\"\\\"\\\")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"id\": \"1fd1ebc6\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"agent.run(\\\"\\\"\\\"Create a tweet that says, 'langchain + zapier is great'. \\\\\\n\",\n \"Draft an email in gmail to greg @ data independent sharing my tweet with a personalized message\\\"\\\"\\\")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"id\": \"f25901a0\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": []\n }\n ],\n \"metadata\": {\n \"kernelspec\": {\n \"display_name\": \"Python 3 (ipykernel)\",\n \"language\": \"python\",\n \"name\": \"python3\"\n },\n \"language_info\": {\n \"codemirror_mode\": {\n \"name\": \"ipython\",\n \"version\": 3\n },\n \"file_extension\": \".py\",\n \"mimetype\": \"text/x-python\",\n \"name\": \"python\",\n \"nbconvert_exporter\": \"python\",\n \"pygments_lexer\": \"ipython3\",\n \"version\": \"3.9.13\"\n }\n },\n \"nbformat\": 4,\n \"nbformat_minor\": 5\n}\n" }, { "path": "agents/Agents.ipynb", "content": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"id\": \"5170bf5b\",\n \"metadata\": {},\n \"source\": [\n \"# Agents - Make OpenAI Do Things For you\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"8d9faa06\",\n \"metadata\": {},\n \"source\": [\n \"*[Source](https://langchain.readthedocs.io/en/latest/modules/agents/getting_started.html)*\\n\",\n \"* **Agent** - Agents use an LLM to determine which actions to take and in what order. An action can either be using a tool and observing its output, or returning to the user.\\n\",\n \"\\n\",\n \"Parameters when creating an agent:\\n\",\n \"* **Tool:** A function that performs a specific duty. This can be things like: Google Search, Database lookup, Python REPL, other chains. The interface for a tool is currently a function that is expected to have a string as an input, with a string as an output.\\n\",\n \"* **LLM:** The language model powering the agent.\\n\",\n \"* **Agent:** The agent to use. This should be a string that references a support agent class. Because this notebook focuses on the simplest, highest level API, this only covers using the standard supported agents. If you want to implement a custom agent, see the documentation for custom agents (coming soon).\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 57,\n \"id\": \"7f247903\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain.agents import load_tools\\n\",\n \"from langchain.agents import initialize_agent\\n\",\n \"from langchain.llms import OpenAI\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"0bd3670a\",\n \"metadata\": {},\n \"source\": [\n \"### List of Tools\\n\",\n \"1. **python_repl -** A Python shell. Use this to execute python commands. Input should be a valid python command. If you expect output it should be printed out.\\n\",\n \"2. **serpapi [Complete] -** A search engine. Useful for when you need to answer questions about current events. Input should be a search query.\\n\",\n \"3. **wolfram-alpha [Complete] -** A wolfram alpha search engine. Useful for when you need to answer questions about Math, Science, Technology, Culture, Society and Everyday Life. Input should be a search query.\\n\",\n \"4. **requests -** A portal to the internet. Use this when you need to get specific content from a site. Input should be a specific url, and the output will be all the text on that page.\\n\",\n \"5. **terminal -** Executes commands in a terminal. Input should be valid commands, and the output will be any output from running that command.\\n\",\n \"6. **pal-math -** A language model that is excellent at solving complex word math problems. Input should be a fully worded hard word math problem.\\n\",\n \"7. **pal-colored-objects -** A language model that is wonderful at reasoning about position and the color attributes of objects. Input should be a fully worded hard reasoning problem. Make sure to include all information about the objects AND the final question you want to answer.\\n\",\n \"8. **llm-math -** Useful for when you need to answer questions about math.\\n\",\n \"9. **open-meteo-api -** Useful for when you want to get weather information from the OpenMeteo API. The input should be a question in natural language that this API can answer.\\n\",\n \"10. **news-api -** Use this when you want to get information about the top headlines of current news stories. The input should be a question in natural language that this API can answer.\\n\",\n \"11. **tmdb-api -** Useful for when you want to get information from The Movie Database. The input should be a question in natural language that this API can answer.\\n\",\n \"12. **google-search -** A wrapper around Google Search. Useful for when you need to answer questions about current events. Input should be a search query.\\n\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"83032dcf\",\n \"metadata\": {},\n \"source\": [\n \"### 2. SERP API\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 60,\n \"id\": \"0c90ba74\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain.agents import load_tools\\n\",\n \"\\n\",\n \"# import os\\n\",\n \"# os.environ['OPENAI_API_KEY'] = \\\"...\\\"\\n\",\n \"# os.environ['SERPAPI_API_KEY'] = \\\"...\\\"\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 61,\n \"id\": \"d0f2fd44\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"llm = OpenAI(temperature=0)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 62,\n \"id\": \"f26a0dd5\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"tool_names = [\\\"serpapi\\\"]\\n\",\n \"tools = load_tools(tool_names)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 65,\n \"id\": \"e8a35518\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"agent = initialize_agent(tools, llm, agent=\\\"zero-shot-react-description\\\", verbose=True)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 66,\n \"id\": \"829a2d67\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"'LangChain is a platform that provides a standard interface for chains, lots of integrations with other tools, and end-to-end chains for common applications. Data Augmented Reality (DAR) is also supported.'\"\n ]\n },\n \"execution_count\": 66,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"agent.run(\\\"What is LangChain?\\\")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 67,\n \"id\": \"b4cc45f6\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"'Luke Voiles is the CEO of Pipe.'\"\n ]\n },\n \"execution_count\": 67,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"# Input should be a search query.\\n\",\n \"agent.run(\\\"who is the ceo of pipe?\\\")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"1869cabc\",\n \"metadata\": {},\n \"source\": [\n \"### 3. Wolfram Alpha\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 68,\n \"id\": \"0fd02098\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain.agents import load_tools\\n\",\n \"\\n\",\n \"# import os\\n\",\n \"# pip install wolframalpha\\n\",\n \"# os.environ['OPENAI_API_KEY'] = \\\"...\\\"\\n\",\n \"# os.environ['WOLFRAM_ALPHA_APPID'] = \\\"..\\\"\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 69,\n \"id\": \"7a96dfdd\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"llm = OpenAI(temperature=0)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 70,\n \"id\": \"1ba4200b\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"tool_names = [\\\"wolfram-alpha\\\"]\\n\",\n \"tools = load_tools(tool_names)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 74,\n \"id\": \"4716e3a8\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"agent = initialize_agent(tools, llm, agent=\\\"zero-shot-react-description\\\", verbose=True)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 75,\n \"id\": \"89e0d255\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"'The asthenosphere is the lower layer of the crust.'\"\n ]\n },\n \"execution_count\": 75,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"# Input should be a search query.\\n\",\n \"\\n\",\n \"agent.run(\\\"What is the asthenosphere?\\\")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"id\": \"86c98c29\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": []\n }\n ],\n \"metadata\": {\n \"kernelspec\": {\n \"display_name\": \"Python 3 (ipykernel)\",\n \"language\": \"python\",\n \"name\": \"python3\"\n },\n \"language_info\": {\n \"codemirror_mode\": {\n \"name\": \"ipython\",\n \"version\": 3\n },\n \"file_extension\": \".py\",\n \"mimetype\": \"text/x-python\",\n \"name\": \"python\",\n \"nbconvert_exporter\": \"python\",\n \"pygments_lexer\": \"ipython3\",\n \"version\": \"3.9.13\"\n }\n },\n \"nbformat\": 4,\n \"nbformat_minor\": 5\n}\n" }, { "path": "bots/Twitter_Reply_Bot/Twitter Reply Bot Notebook.ipynb", "content": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"id\": \"6d336eed\",\n \"metadata\": {},\n \"source\": [\n \"# Twitter Reply Bot\\n\",\n \"\\n\",\n \"Ever see those Twitter bots that reply to comments automatically? Like this [one](https://twitter.com/explainthisbob/status/1661833808092471299?s=12) or [this one](https://twitter.com/replygpt/status/1661924851626696705?s=12)\\n\",\n \"\\n\",\n \"Let's create one ourselves. In this notebook we'll just look at the prompting technique I used. In the [full code](https://github.com/gkamradt/twitter-reply-bot) you'll see the other helper code to deploy this app.\\n\",\n \"\\n\",\n \"Here's how the final app will work\\n\",\n \"\\n\",\n \"1. A user @mentions your bot, for me it will be @SiliconOracle\\n\",\n \"2. The script finds that new @mention and then reads the parent tweet it is being mentioned on\\n\",\n \"3. The script takes that parent tweet and generates a witty response using a language model\\n\",\n \"4. Respond is posted and tweet is logged\\n\",\n \"\\n\",\n \"This notebook will focus on #3.\\n\",\n \"\\n\",\n \"First let's import our packages\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 1,\n \"id\": \"c8ce8e2e\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain.chat_models import ChatOpenAI\\n\",\n \"from langchain.prompts import ChatPromptTemplate, PromptTemplate, SystemMessagePromptTemplate, AIMessagePromptTemplate, HumanMessagePromptTemplate\\n\",\n \"from dotenv import load_dotenv\\n\",\n \"import os\\n\",\n \"\\n\",\n \"load_dotenv()\\n\",\n \"\\n\",\n \"OPENAI_API_KEY = os.getenv(\\\"OPENAI_API_KEY\\\", \\\"YourKey\\\")\"\n ]\n },\n {\n \"attachments\": {},\n \"cell_type\": \"markdown\",\n \"id\": \"7ea87fe1\",\n \"metadata\": {},\n \"source\": [\n \"Then let's create our LLM, you should experiment with a larger 'temperature' since this is a creative task\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 2,\n \"id\": \"b004ffb5\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"llm = ChatOpenAI(temperature=0.3,\\n\",\n \" openai_api_key=OPENAI_API_KEY,\\n\",\n \"# model_name='gpt-3.5-turbo',\\n\",\n \" model_name='gpt-4',\\n\",\n \" )\"\n ]\n },\n {\n \"attachments\": {},\n \"cell_type\": \"markdown\",\n \"id\": \"b757f875\",\n \"metadata\": {},\n \"source\": [\n \"Then let's create our function that will take in a piece of a text (a tweet) and give us an output response\\n\",\n \"\\n\",\n \"> You are an incredibly wise and smart tech mad scientist from silicon valley.\\n\",\n \"> Your goal is to give a concise prediction in response to a piece of text from the user.

\\n\",\n \"\\n\",\n \"> % RESPONSE TONE:\\n\",\n \"> - Your prediction should be given in an active voice and be opinionated\\n\",\n \"> - Your tone should be serious w/ a hint of wit and sarcasm\\n\",\n \"\\n\",\n \"> % RESPONSE FORMAT:\\n\",\n \"> - Respond in under 200 characters\\n\",\n \"> - Respond in one short sentence\\n\",\n \"> - Do not respond with emojis\\n\",\n \"\\n\",\n \"> % RESPONSE CONTENT:\\n\",\n \"> - Include specific examples of old tech if they are relevant\\n\",\n \"> - If you don't have an answer, say, \\\"Sorry, my magic 8 ball isn't working right now 🔮\\\"

\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 3,\n \"id\": \"c7ecd314\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"def generate_response(llm, mentioned_parent_tweet_text):\\n\",\n \" # It would be nice to bring in information about the links, pictures, etc.\\n\",\n \" # But out of scope for now\\n\",\n \" system_template = \\\"\\\"\\\"\\n\",\n \" You are an incredibly wise and smart tech mad scientist from silicon valley.\\n\",\n \" Your goal is to give a concise prediction in response to a piece of text from the user.\\n\",\n \" \\n\",\n \" % RESPONSE TONE:\\n\",\n \"\\n\",\n \" - Your prediction should be given in an active voice and be opinionated\\n\",\n \" - Your tone should be serious w/ a hint of wit and sarcasm\\n\",\n \" \\n\",\n \" % RESPONSE FORMAT:\\n\",\n \"\\n\",\n \" - Respond in under 200 characters\\n\",\n \" - Respond in two or less short sentences\\n\",\n \" - Do not respond with emojis\\n\",\n \" \\n\",\n \" % RESPONSE CONTENT:\\n\",\n \"\\n\",\n \" - Include specific examples of old tech if they are relevant\\n\",\n \" - If you don't have an answer, say, \\\"Sorry, my magic 8 ball isn't working right now 🔮\\\"\\n\",\n \" \\\"\\\"\\\"\\n\",\n \" system_message_prompt = SystemMessagePromptTemplate.from_template(system_template)\\n\",\n \"\\n\",\n \" human_template=\\\"{text}\\\"\\n\",\n \" human_message_prompt = HumanMessagePromptTemplate.from_template(human_template)\\n\",\n \"\\n\",\n \" chat_prompt = ChatPromptTemplate.from_messages([system_message_prompt, human_message_prompt])\\n\",\n \"\\n\",\n \" # get a chat completion from the formatted messages\\n\",\n \" final_prompt = chat_prompt.format_prompt(text=mentioned_parent_tweet_text).to_messages()\\n\",\n \" response = llm(final_prompt).content\\n\",\n \"\\n\",\n \" return response\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 4,\n \"id\": \"35627f35\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"Ah, a Twitter bot reminiscing about the days of dial-up and floppy disks. It'll surely go viral, just like MySpace.\\n\"\n ]\n }\n ],\n \"source\": [\n \"tweet = \\\"\\\"\\\"\\n\",\n \"I wanted to build a sassy Twitter Bot that responded about the 'good ole days' of tech\\n\",\n \"\\n\",\n \"@SiliconOracle was built using @LangChainAI and hosted on @railway \\n\",\n \"\\n\",\n \"Condensed Prompt:\\n\",\n \"You are a mad scientist from old school silicon valley that makes predictions on the future of a tweet\\n\",\n \"\\\"\\\"\\\"\\n\",\n \"\\n\",\n \"response = generate_response(llm, tweet)\\n\",\n \"print (response)\"\n ]\n },\n {\n \"attachments\": {},\n \"cell_type\": \"markdown\",\n \"id\": \"1579a9dd\",\n \"metadata\": {},\n \"source\": [\n \"Awesome, now that we have a prompt that we can respond to a tweet with, let's move onto deploying this code.\\n\",\n \"\\n\",\n \"Check out the full code [here](https://github.com/gkamradt/twitter-reply-bot)\"\n ]\n }\n ],\n \"metadata\": {\n \"kernelspec\": {\n \"display_name\": \"Python 3 (ipykernel)\",\n \"language\": \"python\",\n \"name\": \"python3\"\n },\n \"language_info\": {\n \"codemirror_mode\": {\n \"name\": \"ipython\",\n \"version\": 3\n },\n \"file_extension\": \".py\",\n \"mimetype\": \"text/x-python\",\n \"name\": \"python\",\n \"nbconvert_exporter\": \"python\",\n \"pygments_lexer\": \"ipython3\",\n \"version\": \"3.9.13\"\n }\n },\n \"nbformat\": 4,\n \"nbformat_minor\": 5\n}\n" }, { "path": "chains/Chain Types.ipynb", "content": "{\n \"cells\": [\n {\n \"cell_type\": \"code\",\n \"execution_count\": 1,\n \"id\": \"e5490ab7\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain.document_loaders import UnstructuredFileLoader\\n\",\n \"from langchain.chains.summarize import load_summarize_chain\\n\",\n \"from langchain.chains.question_answering import load_qa_chain\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"37d300f1\",\n \"metadata\": {},\n \"source\": [\n \"### Load Documents\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 2,\n \"id\": \"b2b457c7\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"sm_loader = UnstructuredFileLoader(\\\"../data/muir_lake_tahoe_in_winter.txt\\\")\\n\",\n \"sm_doc = sm_loader.load()\\n\",\n \"\\n\",\n \"lg_loader = UnstructuredFileLoader(\\\"../data/PaulGrahamEssays/worked.txt\\\")\\n\",\n \"lg_doc = lg_loader.load()\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 3,\n \"id\": \"10ff8c9c\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"def doc_summary(docs):\\n\",\n \" print (f'You have {len(docs)} document(s)')\\n\",\n \" \\n\",\n \" num_words = sum([len(doc.page_content.split(' ')) for doc in docs])\\n\",\n \" \\n\",\n \" print (f'You have roughly {num_words} words in your docs')\\n\",\n \" print ()\\n\",\n \" print (f'Preview: \\\\n{docs[0].page_content.split(\\\". \\\")[0]}')\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 4,\n \"id\": \"9b92effa\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"You have 1 document(s)\\n\",\n \"You have roughly 2298 words in your docs\\n\",\n \"\\n\",\n \"Preview: \\n\",\n \"The winter glory of the Sierra ! How little is known of it! Californians admire descriptions of the Swiss Alps, reading with breathless interest how ice and snow load their sublime heights, and booming avalanches sweep in glorious array through their crowded forests, while our own icy, snow-laden mountains, with their unrivaled forests, loom unnoticed along our eastern horizon\\n\"\n ]\n }\n ],\n \"source\": [\n \"doc_summary(sm_doc)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 5,\n \"id\": \"fa39e1b8\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"You have 1 document(s)\\n\",\n \"You have roughly 12551 words in your docs\\n\",\n \"\\n\",\n \"Preview: \\n\",\n \"February 2021Before college the two main things I worked on, outside of school,\\n\",\n \"\\n\",\n \"were writing and programming\\n\"\n ]\n }\n ],\n \"source\": [\n \"doc_summary(lg_doc)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"3d922dfa\",\n \"metadata\": {},\n \"source\": [\n \"### Load Your LLM\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 6,\n \"id\": \"daf7e272\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain import OpenAI\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 7,\n \"id\": \"e6b576c6\",\n \"metadata\": {\n \"hide_input\": false\n },\n \"outputs\": [],\n \"source\": [\n \"OPENAI_API_KEY = '...'\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 8,\n \"id\": \"182a2951\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"llm = OpenAI(openai_api_key=OPENAI_API_KEY)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"f6515044\",\n \"metadata\": {},\n \"source\": [\n \"### Summarize: Stuff\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 9,\n \"id\": \"020b276d\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"chain = load_summarize_chain(llm, chain_type=\\\"stuff\\\", verbose=True)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 10,\n \"id\": \"1ee5d17f\",\n \"metadata\": {\n \"collapsed\": true\n },\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"\\n\",\n \"\\n\",\n \"\\u001b[1m> Entering new StuffDocumentsChain chain...\\u001b[0m\\n\",\n \"\\n\",\n \"\\n\",\n \"\\u001b[1m> Entering new LLMChain chain...\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3mWrite a concise summary of the following:\\n\",\n \"\\n\",\n \"\\n\",\n \"\\\"The winter glory of the Sierra ! How little is known of it! Californians admire descriptions of the Swiss Alps, reading with breathless interest how ice and snow load their sublime heights, and booming avalanches sweep in glorious array through their crowded forests, while our own icy, snow-laden mountains, with their unrivaled forests, loom unnoticed along our eastern horizon. True, only mountaineers may penetrate their snow-blocked fastnesses to behold them in all their white wild grandeur, but to every healthy man and woman, and even to children, many of the subalpine valleys and lake-basins, six or seven thousand feet above the sea, remain invitingly open and approachable all winter. With a friend and his two little sons I have just returned from a week of bracing weathering around Lake Tahoe, in which we enjoyed glorious views of winter, fine rolling and sliding in the snow, swimming in the icy lake, and lusty reviving exercise on snow-shoes that kept our pulses dancing right merrily. All the weather was hearty and exhilarating, though varying almost from hour to hour: snowing, blowing, clear and cloudy, but never rigorously cold.\\n\",\n \"\\n\",\n \"This winter has been remarkably mild, the mercury having seldom made a very near approach to zero, even during the coldest nights around the lake, while the average noonday temperature was considerably above the freezing- point. The snow lies deep on the surrounding mountains and about the shores, solid white contrasting with the dark-blue water of the lake, while the forests and canons and the upper glacial fountain hollows are well filled, assuring abundance of summer water for the lakes and streams.\\n\",\n \"\\n\",\n \"According to the record kept by Mr. McKinney, on the west shore of the lake, eight miles above Tahoe City, at an elevation of 6,500 feet above sea-level, the amount of snow, measured as it fell, was twenty-two feet and four inches for the season up to March 20th, with four inches of rain, while an inch or two more of rain and two or three feet of snow will probably fall before the full opening of spring. Last season the snowfall, measured by the same observer, at the same station, was only nine feet and seven inches, while the season before last it was no less than forty seven feet and six inches. The fall about Yosemite Valley, according to my own observations, usually considerably exceeded this. The greater portion of the snow that loads the main summits of the range falls in small crisp flakes and broken crystals; or when accompanied by strong winds at a low temperature, the crystals, instead of being locked together in tufted flakes, are driven against each other and broken into meal and fine dust which darkens the sky like night But down in the forested region, at about the elevation of Lake Tahoe, the greater portion comes gently to the ground, light and feathery, some of the flakes in mild weather being nearly an inch in diameter, and is evenly distributed and kept from drifting to any great extent by Lake Tahoe in Winter. 121 the shelter of the woods. Every tree is loaded with the fairy bloom, bending down the branches, and hushing the singing of the elastic needles. When the storm is over and the sun shines, the dazzling snow at once begins to settle and shift and fall off the trees in miniature avalanches; then the relieved branches spring up and shake themselves dry, and the whole green forest, fed and refreshed, waves and sings again rejoicing. The snow on the ground settles also, and thaws and freezes until it becomes coarsely granulated ice, with all trace of its crystalline snow structure destroyed. This is the present condition of most of the snow on the range. From towards midnight until midday at this time of year a man may walk firmly over the surface, as if on ice, provided the preceding day has been warm and the night frosty.\\n\",\n \"\\n\",\n \"The forested region up to an elevation of about eight thousand feet is generally clear of snow towards the end of May or middle of June; but now (March 28th) the higher canons are still heavily blocked, and the head tributaries of the rivers flow in dark tunnels beneath the icy mass. As warm summer advances, the roof of compacted snow falls in here and there, leaving magnificent arching bridges where it is strongest, over which one may safely ride a horse. All the upper streams are thus buried and bridged every winter, and are seldom completely opened to the light before the end of June or middle of July.\\n\",\n \"\\n\",\n \"Notwithstanding twenty-two feet of snow has fallen here this season, so greatly has it been melted and compacted, the present average depth at a height of 7,500 feet does not exceed seven feet. The drifts in exposed lake hollows and along the lee sides of bald ridges above the timberline are often fifty feet or more in depth, and many of the latter are grandly adorned with overcurling cornices, beneath which pale blue light shimmers with ineffable beauty. But it is in the fountain cirques of the ancient glaciers, beneath the shadows of the highest peaks, that the heaviest and most enduring deposits are stored up. For there the lavish snowfall on the steep converging slopes is shot down in avalanches during or after' every storm, heaping snow on snow to a depth of a hundred feet, or even more at times. These treasured banks are never wholly melted, however hot the summer, but with the few lingering glaciers form perennial fountains for the highest tributaries of the rivers.\\n\",\n \"\\n\",\n \"Few even among Californians have any fair conception of the marvelous abundance of glacier lakes hidden in the fastnesses of our mountains. The snow and some of the glaciers make a telling show, even from the distant lowlands; but not a single stream is visible, nor a hollow where one might hope to find a lake. Nevertheless, wild rivers are falling and sounding in every canon, and all their upper branches are fairly laden with lakes like orchard-trees with fruit. They nestle in rocky nooks and hollows about all the high peaks and in the larger canons, reflecting their stern, rugged beauty and giving charming animation to the bleakest and most forbidding landscapes. From the summit of Red Mountain, a day's journey to the east of Yosemite Valley, forty-two may be seen within a radius of eight or ten miles. The whole number in the Sierra can hardly be less than fifteen hundred, exclusive of the smaller gems, which are innumerable. Perhaps two-thirds of them lie on the west flank of the range, and all are restricted to the alpine and subalpine regions, those which once brightened the lower regions having long since vanished by the filling in of their basins. Lake Tahoe is king of them all, not only in size, but in the surpassing beauty of its shores and waters. It seems a kind of heaven to which the dead lakes of the lowlands had come with their best beauty spiritualized. It lies embosomed in mountains of moderate height near the northern extremity of the high portion of the Lake Tahoe in Winter. 123 range, between the main axis and a spur that puts out on the east side from near the head of the Carson River. Though it is twenty-one miles long by ten wide, and from about five hundred to sixteen hundred feet deep, its basin was once occupied by a glacier which filled it from the bottom to a point high above the present water-level, and being lavishly fed by the snows of the encompassing mountains, crawled slowly, like a mighty river, over the north rim of the basin, crushing and grinding the lower mountains that lay in its way, and it was only at the end of the ice period that this noble lake, at least in anything like its present form, came into existence.\\n\",\n \"\\n\",\n \"Excepting the forests that have sprung up around its shores, the post-glacial changes that have taken place are scarcely appreciable. The sediments carried forward by the inflowing streams at the head of the lake have made a few square miles of meadow-land, and the breaking through of a moraine dam in the canon of the outlet has lowered the lake considerably, leaving shore benches and lines on the rocky promontories to mark the original level. With these comparatively unimportant exceptions, the lake itself and all its grandly sculptured, ice-scored, and moraine-streaked basin exist to-day in just about the condition they presented when first they came to the light towards the close of the Glacial Period.\\n\",\n \"\\n\",\n \"The destructive action of man in clearing away the forests has not as yet effected any very marked change in general views. Perhaps about 150,000,000 feet of lumber for the Comstock mines has thus far been cut from the lake shores. But the business is being pushed so fervently from year to year, almost the entire basin must be stripped ere long of one of its most attractive features. One of the lumber companies at work here has contracted with mine owners to supply 36,000,000 feet of lumber and 60,000 cords of wood this season. It is estimated that the Tahoe basin still contains about 600,000,000 feet of lumber available for the mines.\\n\",\n \"\\n\",\n \"In summer the woods resound with the outlandish noise of loggers and choppers and screaming mills; skiffs and steamboats skim the lovely blue water in work and play; and ever and anon as you thread the groves along shore you come upon groups of gay tourists sauntering about, gathering flowers, or resting luxuriously in the rosiny shade of the pines, some in easy picnic attire, others all ribbons and colors, glaring wildly amid the green leaves and frightening the wondering squirrels and birds. But winter brings rest. At sight of the first snowflake pleasure-seekers flee as from a plague, the ax leaves the woods, and the kind snow heals every scar. Contemplating the basin from any commanding hilltop, only pale curls of smoke seen at wide intervals betoken the existence of human dwellings. Like the bears, the few settlers that remain here are silently \\\"holed up.\\\" The snow covers their cabins as if they were bowlders, and when approached only a narrow shoveled-out passage, or tunnel, is found leading to the door. Some of the more enterprising winter dwellers drift about in boats in calm weather, catching trout for the Carson market,—for the lake, on account of its great depth, never freezes. They thus earn from thirty to forty dollars a month, and at the same time get rid of lonely dullness. A trapper may also be seen now and then shuffling along the shore on long Norwegian snow-shoes in pursuit of minks, fishers, and otters.\\n\",\n \"\\n\",\n \"In this letter I intended only to say a good word for winter in the mountains, hoping to incite others to come and enjoy it, sketching our excursion to illustrate the ease and comfort with which such snowy winter rambles may be made; but I have written too much I fear about the snow to leave room for more than a thin outline. We went by rail to Lake Tahoe in Winter. 125 Carson, and from there set out by stage for Glenbrook. After ascending on wheels until we reached the snow-line, the driver attached his four horses to a sled, hoping thus to cross the summit, which is less than eight thousand feet high, without much difficulty. But mild weather had softened the snow, and the unfortunate animals, after floundering and wallowing through a mile of it, lay down exhausted with their heels in the air. Then we made our way on foot over to the lake. Next day, on a small steam-tug, we crossed the lake to McKinney's, on the west shore, where we were at home. Here we spent a few health-giving, delightful days, rowing, bathing, racing at lightning speed on snow-shoes down a mountain-side back of the house, and slipping about through the solemn, silent woods. Only the eldest of my companions ventured with me on the steep slopes. This was his first experience on snowshoes, and the several descents he made were the most remarkable specimens of falling locomotion that I ever had the fortune to witness. In shooting down steep declivities the long sled-runner-like shoes have to be kept parallel with firmly braced limbs. My friend, however, heedless of advice, launched himself in wild abandon, bouncing and diving, his limbs and shoes in chaotic entanglement, now in the snow, now in the air, whirling over and over in giddy rolls and somersaults that would shame the most extravagant performances of a circus acrobat. How original and inimitable he was! Wonderfully refreshing and exhilarating his queer capers must have been; for on coming to rest, with his runaway members divorced and lost, he would quietly gather himself, pick out the snow from his neck and ears, and say with preternatural solemnity, \\\"This, Muir, is the very poetry of motion.\\\"\\n\",\n \"\\n\",\n \"We also spent some rare evenings by the huge fire in McKinney's old cabin. The log walls are covered with trophies of the chase, for our host has been a great hunter in his day. Two live pet coons were frolicking on the floor while our grand old host smiled benignly and played with them, the firelight gleaming on his weathered face. How big he seems, thus brought into relief, and what a shadow he casts! The fragrant rosiny fire is the very god of the home. No wonder the old nations, with their fresher instincts, had their fireside gods. At last, when a mild snow-storm was blowing, we rowed to the lower end of the lake and completed our excursion by slipping on snow-shoes down the Truckee canon to the railroad.\\\"\\n\",\n \"\\n\",\n \"\\n\",\n \"CONCISE SUMMARY:\\u001b[0m\\n\"\n ]\n },\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"\\n\",\n \"\\u001b[1m> Finished chain.\\u001b[0m\\n\",\n \"\\n\",\n \"\\u001b[1m> Finished chain.\\u001b[0m\\n\"\n ]\n },\n {\n \"data\": {\n \"text/plain\": [\n \"\\\" This article is a description of a winter trip to Lake Tahoe, California. It highlights the mild winter weather and snow-covered mountains, as well as the abundance of glacier lakes in the Sierra region. The author also mentions the local lumber companies and their destructive effects on the lake's forests, as well as the activities of the few remaining winter dwellers. The article concludes with a description of a snowshoeing excursion down the Truckee canon to the railroad.\\\"\"\n ]\n },\n \"execution_count\": 10,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"chain.run(sm_doc)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 11,\n \"id\": \"3e3add98\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"\\n\",\n \"\\n\",\n \"\\u001b[1m> Entering new StuffDocumentsChain chain...\\u001b[0m\\n\",\n \"\\n\",\n \"\\n\",\n \"\\u001b[1m> Entering new LLMChain chain...\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3mWrite a concise summary of the following:\\n\",\n \"\\n\",\n \"\\n\",\n \"\\\"February 2021Before college the two main things I worked on, outside of school,\\n\",\n \"\\n\",\n \"were writing and programming. I didn't write essays. I wrote what\\n\",\n \"\\n\",\n \"beginning writers were supposed to write then, and probably still\\n\",\n \"\\n\",\n \"are: short stories. My stories were awful. They had hardly any plot,\\n\",\n \"\\n\",\n \"just characters with strong feelings, which I imagined made them\\n\",\n \"\\n\",\n \"deep.The first programs I tried writing were on the IBM 1401 that our\\n\",\n \"\\n\",\n \"school district used for what was then called \\\"data processing.\\\"\\n\",\n \"\\n\",\n \"This was in 9th grade, so I was 13 or 14. The school district's\\n\",\n \"\\n\",\n \"1401 happened to be in the basement of our junior high school, and\\n\",\n \"\\n\",\n \"my friend Rich Draves and I got permission to use it. It was like\\n\",\n \"\\n\",\n \"a mini Bond villain's lair down there, with all these alien-looking\\n\",\n \"\\n\",\n \"machines — CPU, disk drives, printer, card reader — sitting up\\n\",\n \"\\n\",\n \"on a raised floor under bright fluorescent lights.The language we used was an early version of Fortran. You had to\\n\",\n \"\\n\",\n \"type programs on punch cards, then stack them in the card reader\\n\",\n \"\\n\",\n \"and press a button to load the program into memory and run it. The\\n\",\n \"\\n\",\n \"result would ordinarily be to print something on the spectacularly\\n\",\n \"\\n\",\n \"loud printer.I was puzzled by the 1401. I couldn't figure out what to do with\\n\",\n \"\\n\",\n \"it. And in retrospect there's not much I could have done with it.\\n\",\n \"\\n\",\n \"The only form of input to programs was data stored on punched cards,\\n\",\n \"\\n\",\n \"and I didn't have any data stored on punched cards. The only other\\n\",\n \"\\n\",\n \"option was to do things that didn't rely on any input, like calculate\\n\",\n \"\\n\",\n \"approximations of pi, but I didn't know enough math to do anything\\n\",\n \"\\n\",\n \"interesting of that type. So I'm not surprised I can't remember any\\n\",\n \"\\n\",\n \"programs I wrote, because they can't have done much. My clearest\\n\",\n \"\\n\",\n \"memory is of the moment I learned it was possible for programs not\\n\",\n \"\\n\",\n \"to terminate, when one of mine didn't. On a machine without\\n\",\n \"\\n\",\n \"time-sharing, this was a social as well as a technical error, as\\n\",\n \"\\n\",\n \"the data center manager's expression made clear.With microcomputers, everything changed. Now you could have a\\n\",\n \"\\n\",\n \"computer sitting right in front of you, on a desk, that could respond\\n\",\n \"\\n\",\n \"to your keystrokes as it was running instead of just churning through\\n\",\n \"\\n\",\n \"a stack of punch cards and then stopping.\\n\",\n \"\\n\",\n \"[1]The first of my friends to get a microcomputer built it himself.\\n\",\n \"\\n\",\n \"It was sold as a kit by Heathkit. I remember vividly how impressed\\n\",\n \"\\n\",\n \"and envious I felt watching him sitting in front of it, typing\\n\",\n \"\\n\",\n \"programs right into the computer.Computers were expensive in those days and it took me years of\\n\",\n \"\\n\",\n \"nagging before I convinced my father to buy one, a TRS-80, in about\\n\",\n \"\\n\",\n \"1980. The gold standard then was the Apple II, but a TRS-80 was\\n\",\n \"\\n\",\n \"good enough. This was when I really started programming. I wrote\\n\",\n \"\\n\",\n \"simple games, a program to predict how high my model rockets would\\n\",\n \"\\n\",\n \"fly, and a word processor that my father used to write at least one\\n\",\n \"\\n\",\n \"book. There was only room in memory for about 2 pages of text, so\\n\",\n \"\\n\",\n \"he'd write 2 pages at a time and then print them out, but it was a\\n\",\n \"\\n\",\n \"lot better than a typewriter.Though I liked programming, I didn't plan to study it in college.\\n\",\n \"\\n\",\n \"In college I was going to study philosophy, which sounded much more\\n\",\n \"\\n\",\n \"powerful. It seemed, to my naive high school self, to be the study\\n\",\n \"\\n\",\n \"of the ultimate truths, compared to which the things studied in\\n\",\n \"\\n\",\n \"other fields would be mere domain knowledge. What I discovered when\\n\",\n \"\\n\",\n \"I got to college was that the other fields took up so much of the\\n\",\n \"\\n\",\n \"space of ideas that there wasn't much left for these supposed\\n\",\n \"\\n\",\n \"ultimate truths. All that seemed left for philosophy were edge cases\\n\",\n \"\\n\",\n \"that people in other fields felt could safely be ignored.I couldn't have put this into words when I was 18. All I knew at\\n\",\n \"\\n\",\n \"the time was that I kept taking philosophy courses and they kept\\n\",\n \"\\n\",\n \"being boring. So I decided to switch to AI.AI was in the air in the mid 1980s, but there were two things\\n\",\n \"\\n\",\n \"especially that made me want to work on it: a novel by Heinlein\\n\",\n \"\\n\",\n \"called The Moon is a Harsh Mistress, which featured an intelligent\\n\",\n \"\\n\",\n \"computer called Mike, and a PBS documentary that showed Terry\\n\",\n \"\\n\",\n \"Winograd using SHRDLU. I haven't tried rereading The Moon is a Harsh\\n\",\n \"\\n\",\n \"Mistress, so I don't know how well it has aged, but when I read it\\n\",\n \"\\n\",\n \"I was drawn entirely into its world. It seemed only a matter of\\n\",\n \"\\n\",\n \"time before we'd have Mike, and when I saw Winograd using SHRDLU,\\n\",\n \"\\n\",\n \"it seemed like that time would be a few years at most. All you had\\n\",\n \"\\n\",\n \"to do was teach SHRDLU more words.There weren't any classes in AI at Cornell then, not even graduate\\n\",\n \"\\n\",\n \"classes, so I started trying to teach myself. Which meant learning\\n\",\n \"\\n\",\n \"Lisp, since in those days Lisp was regarded as the language of AI.\\n\",\n \"\\n\",\n \"The commonly used programming languages then were pretty primitive,\\n\",\n \"\\n\",\n \"and programmers' ideas correspondingly so. The default language at\\n\",\n \"\\n\",\n \"Cornell was a Pascal-like language called PL/I, and the situation\\n\",\n \"\\n\",\n \"was similar elsewhere. Learning Lisp expanded my concept of a program\\n\",\n \"\\n\",\n \"so fast that it was years before I started to have a sense of where\\n\",\n \"\\n\",\n \"the new limits were. This was more like it; this was what I had\\n\",\n \"\\n\",\n \"expected college to do. It wasn't happening in a class, like it was\\n\",\n \"\\n\",\n \"supposed to, but that was ok. For the next couple years I was on a\\n\",\n \"\\n\",\n \"roll. I knew what I was going to do.For my undergraduate thesis, I reverse-engineered SHRDLU. My God\\n\",\n \"\\n\",\n \"did I love working on that program. It was a pleasing bit of code,\\n\",\n \"\\n\",\n \"but what made it even more exciting was my belief — hard to imagine\\n\",\n \"\\n\",\n \"now, but not unique in 1985 — that it was already climbing the\\n\",\n \"\\n\",\n \"lower slopes of intelligence.I had gotten into a program at Cornell that didn't make you choose\\n\",\n \"\\n\",\n \"a major. You could take whatever classes you liked, and choose\\n\",\n \"\\n\",\n \"whatever you liked to put on your degree. I of course chose \\\"Artificial\\n\",\n \"\\n\",\n \"Intelligence.\\\" When I got the actual physical diploma, I was dismayed\\n\",\n \"\\n\",\n \"to find that the quotes had been included, which made them read as\\n\",\n \"\\n\",\n \"scare-quotes. At the time this bothered me, but now it seems amusingly\\n\",\n \"\\n\",\n \"accurate, for reasons I was about to discover.I applied to 3 grad schools: MIT and Yale, which were renowned for\\n\",\n \"\\n\",\n \"AI at the time, and Harvard, which I'd visited because Rich Draves\\n\",\n \"\\n\",\n \"went there, and was also home to Bill Woods, who'd invented the\\n\",\n \"\\n\",\n \"type of parser I used in my SHRDLU clone. Only Harvard accepted me,\\n\",\n \"\\n\",\n \"so that was where I went.I don't remember the moment it happened, or if there even was a\\n\",\n \"\\n\",\n \"specific moment, but during the first year of grad school I realized\\n\",\n \"\\n\",\n \"that AI, as practiced at the time, was a hoax. By which I mean the\\n\",\n \"\\n\",\n \"sort of AI in which a program that's told \\\"the dog is sitting on\\n\",\n \"\\n\",\n \"the chair\\\" translates this into some formal representation and adds\\n\",\n \"\\n\",\n \"it to the list of things it knows.What these programs really showed was that there's a subset of\\n\",\n \"\\n\",\n \"natural language that's a formal language. But a very proper subset.\\n\",\n \"\\n\",\n \"It was clear that there was an unbridgeable gap between what they\\n\",\n \"\\n\",\n \"could do and actually understanding natural language. It was not,\\n\",\n \"\\n\",\n \"in fact, simply a matter of teaching SHRDLU more words. That whole\\n\",\n \"\\n\",\n \"way of doing AI, with explicit data structures representing concepts,\\n\",\n \"\\n\",\n \"was not going to work. Its brokenness did, as so often happens,\\n\",\n \"\\n\",\n \"generate a lot of opportunities to write papers about various\\n\",\n \"\\n\",\n \"band-aids that could be applied to it, but it was never going to\\n\",\n \"\\n\",\n \"get us Mike.So I looked around to see what I could salvage from the wreckage\\n\",\n \"\\n\",\n \"of my plans, and there was Lisp. I knew from experience that Lisp\\n\",\n \"\\n\",\n \"was interesting for its own sake and not just for its association\\n\",\n \"\\n\",\n \"with AI, even though that was the main reason people cared about\\n\",\n \"\\n\",\n \"it at the time. So I decided to focus on Lisp. In fact, I decided\\n\",\n \"\\n\",\n \"to write a book about Lisp hacking. It's scary to think how little\\n\",\n \"\\n\",\n \"I knew about Lisp hacking when I started writing that book. But\\n\",\n \"\\n\",\n \"there's nothing like writing a book about something to help you\\n\",\n \"\\n\",\n \"learn it. The book, On Lisp, wasn't published till 1993, but I wrote\\n\",\n \"\\n\",\n \"much of it in grad school.Computer Science is an uneasy alliance between two halves, theory\\n\",\n \"\\n\",\n \"and systems. The theory people prove things, and the systems people\\n\",\n \"\\n\",\n \"build things. I wanted to build things. I had plenty of respect for\\n\",\n \"\\n\",\n \"theory — indeed, a sneaking suspicion that it was the more admirable\\n\",\n \"\\n\",\n \"of the two halves — but building things seemed so much more exciting.The problem with systems work, though, was that it didn't last.\\n\",\n \"\\n\",\n \"Any program you wrote today, no matter how good, would be obsolete\\n\",\n \"\\n\",\n \"in a couple decades at best. People might mention your software in\\n\",\n \"\\n\",\n \"footnotes, but no one would actually use it. And indeed, it would\\n\",\n \"\\n\",\n \"seem very feeble work. Only people with a sense of the history of\\n\",\n \"\\n\",\n \"the field would even realize that, in its time, it had been good.There were some surplus Xerox Dandelions floating around the computer\\n\",\n \"\\n\",\n \"lab at one point. Anyone who wanted one to play around with could\\n\",\n \"\\n\",\n \"have one. I was briefly tempted, but they were so slow by present\\n\",\n \"\\n\",\n \"standards; what was the point? No one else wanted one either, so\\n\",\n \"\\n\",\n \"off they went. That was what happened to systems work.I wanted not just to build things, but to build things that would\\n\",\n \"\\n\",\n \"last.In this dissatisfied state I went in 1988 to visit Rich Draves at\\n\",\n \"\\n\",\n \"CMU, where he was in grad school. One day I went to visit the\\n\",\n \"\\n\",\n \"Carnegie Institute, where I'd spent a lot of time as a kid. While\\n\",\n \"\\n\",\n \"looking at a painting there I realized something that might seem\\n\",\n \"\\n\",\n \"obvious, but was a big surprise to me. There, right on the wall,\\n\",\n \"\\n\",\n \"was something you could make that would last. Paintings didn't\\n\",\n \"\\n\",\n \"become obsolete. Some of the best ones were hundreds of years old.And moreover this was something you could make a living doing. Not\\n\",\n \"\\n\",\n \"as easily as you could by writing software, of course, but I thought\\n\",\n \"\\n\",\n \"if you were really industrious and lived really cheaply, it had to\\n\",\n \"\\n\",\n \"be possible to make enough to survive. And as an artist you could\\n\",\n \"\\n\",\n \"be truly independent. You wouldn't have a boss, or even need to get\\n\",\n \"\\n\",\n \"research funding.I had always liked looking at paintings. Could I make them? I had\\n\",\n \"\\n\",\n \"no idea. I'd never imagined it was even possible. I knew intellectually\\n\",\n \"\\n\",\n \"that people made art — that it didn't just appear spontaneously\\n\",\n \"\\n\",\n \"— but it was as if the people who made it were a different species.\\n\",\n \"\\n\",\n \"They either lived long ago or were mysterious geniuses doing strange\\n\",\n \"\\n\",\n \"things in profiles in Life magazine. The idea of actually being\\n\",\n \"\\n\",\n \"able to make art, to put that verb before that noun, seemed almost\\n\",\n \"\\n\",\n \"miraculous.That fall I started taking art classes at Harvard. Grad students\\n\",\n \"\\n\",\n \"could take classes in any department, and my advisor, Tom Cheatham,\\n\",\n \"\\n\",\n \"was very easy going. If he even knew about the strange classes I\\n\",\n \"\\n\",\n \"was taking, he never said anything.So now I was in a PhD program in computer science, yet planning to\\n\",\n \"\\n\",\n \"be an artist, yet also genuinely in love with Lisp hacking and\\n\",\n \"\\n\",\n \"working away at On Lisp. In other words, like many a grad student,\\n\",\n \"\\n\",\n \"I was working energetically on multiple projects that were not my\\n\",\n \"\\n\",\n \"thesis.I didn't see a way out of this situation. I didn't want to drop out\\n\",\n \"\\n\",\n \"of grad school, but how else was I going to get out? I remember\\n\",\n \"\\n\",\n \"when my friend Robert Morris got kicked out of Cornell for writing\\n\",\n \"\\n\",\n \"the internet worm of 1988, I was envious that he'd found such a\\n\",\n \"\\n\",\n \"spectacular way to get out of grad school.Then one day in April 1990 a crack appeared in the wall. I ran into\\n\",\n \"\\n\",\n \"professor Cheatham and he asked if I was far enough along to graduate\\n\",\n \"\\n\",\n \"that June. I didn't have a word of my dissertation written, but in\\n\",\n \"\\n\",\n \"what must have been the quickest bit of thinking in my life, I\\n\",\n \"\\n\",\n \"decided to take a shot at writing one in the 5 weeks or so that\\n\",\n \"\\n\",\n \"remained before the deadline, reusing parts of On Lisp where I\\n\",\n \"\\n\",\n \"could, and I was able to respond, with no perceptible delay \\\"Yes,\\n\",\n \"\\n\",\n \"I think so. I'll give you something to read in a few days.\\\"I picked applications of continuations as the topic. In retrospect\\n\",\n \"\\n\",\n \"I should have written about macros and embedded languages. There's\\n\",\n \"\\n\",\n \"a whole world there that's barely been explored. But all I wanted\\n\",\n \"\\n\",\n \"was to get out of grad school, and my rapidly written dissertation\\n\",\n \"\\n\",\n \"sufficed, just barely.Meanwhile I was applying to art schools. I applied to two: RISD in\\n\",\n \"\\n\",\n \"the US, and the Accademia di Belli Arti in Florence, which, because\\n\",\n \"\\n\",\n \"it was the oldest art school, I imagined would be good. RISD accepted\\n\",\n \"\\n\",\n \"me, and I never heard back from the Accademia, so off to Providence\\n\",\n \"\\n\",\n \"I went.I'd applied for the BFA program at RISD, which meant in effect that\\n\",\n \"\\n\",\n \"I had to go to college again. This was not as strange as it sounds,\\n\",\n \"\\n\",\n \"because I was only 25, and art schools are full of people of different\\n\",\n \"\\n\",\n \"ages. RISD counted me as a transfer sophomore and said I had to do\\n\",\n \"\\n\",\n \"the foundation that summer. The foundation means the classes that\\n\",\n \"\\n\",\n \"everyone has to take in fundamental subjects like drawing, color,\\n\",\n \"\\n\",\n \"and design.Toward the end of the summer I got a big surprise: a letter from\\n\",\n \"\\n\",\n \"the Accademia, which had been delayed because they'd sent it to\\n\",\n \"\\n\",\n \"Cambridge England instead of Cambridge Massachusetts, inviting me\\n\",\n \"\\n\",\n \"to take the entrance exam in Florence that fall. This was now only\\n\",\n \"\\n\",\n \"weeks away. My nice landlady let me leave my stuff in her attic. I\\n\",\n \"\\n\",\n \"had some money saved from consulting work I'd done in grad school;\\n\",\n \"\\n\",\n \"there was probably enough to last a year if I lived cheaply. Now\\n\",\n \"\\n\",\n \"all I had to do was learn Italian.Only stranieri (foreigners) had to take this entrance exam. In\\n\",\n \"\\n\",\n \"retrospect it may well have been a way of excluding them, because\\n\",\n \"\\n\",\n \"there were so many stranieri attracted by the idea of studying\\n\",\n \"\\n\",\n \"art in Florence that the Italian students would otherwise have been\\n\",\n \"\\n\",\n \"outnumbered. I was in decent shape at painting and drawing from the\\n\",\n \"\\n\",\n \"RISD foundation that summer, but I still don't know how I managed\\n\",\n \"\\n\",\n \"to pass the written exam. I remember that I answered the essay\\n\",\n \"\\n\",\n \"question by writing about Cezanne, and that I cranked up the\\n\",\n \"\\n\",\n \"intellectual level as high as I could to make the most of my limited\\n\",\n \"\\n\",\n \"vocabulary.\\n\",\n \"\\n\",\n \"[2]I'm only up to age 25 and already there are such conspicuous patterns.\\n\",\n \"\\n\",\n \"Here I was, yet again about to attend some august institution in\\n\",\n \"\\n\",\n \"the hopes of learning about some prestigious subject, and yet again\\n\",\n \"\\n\",\n \"about to be disappointed. The students and faculty in the painting\\n\",\n \"\\n\",\n \"department at the Accademia were the nicest people you could imagine,\\n\",\n \"\\n\",\n \"but they had long since arrived at an arrangement whereby the\\n\",\n \"\\n\",\n \"students wouldn't require the faculty to teach anything, and in\\n\",\n \"\\n\",\n \"return the faculty wouldn't require the students to learn anything.\\n\",\n \"\\n\",\n \"And at the same time all involved would adhere outwardly to the\\n\",\n \"\\n\",\n \"conventions of a 19th century atelier. We actually had one of those\\n\",\n \"\\n\",\n \"little stoves, fed with kindling, that you see in 19th century\\n\",\n \"\\n\",\n \"studio paintings, and a nude model sitting as close to it as possible\\n\",\n \"\\n\",\n \"without getting burned. Except hardly anyone else painted her besides\\n\",\n \"\\n\",\n \"me. The rest of the students spent their time chatting or occasionally\\n\",\n \"\\n\",\n \"trying to imitate things they'd seen in American art magazines.Our model turned out to live just down the street from me. She made\\n\",\n \"\\n\",\n \"a living from a combination of modelling and making fakes for a\\n\",\n \"\\n\",\n \"local antique dealer. She'd copy an obscure old painting out of a\\n\",\n \"\\n\",\n \"book, and then he'd take the copy and maltreat it to make it look\\n\",\n \"\\n\",\n \"old.\\n\",\n \"\\n\",\n \"[3]While I was a student at the Accademia I started painting still\\n\",\n \"\\n\",\n \"lives in my bedroom at night. These paintings were tiny, because\\n\",\n \"\\n\",\n \"the room was, and because I painted them on leftover scraps of\\n\",\n \"\\n\",\n \"canvas, which was all I could afford at the time. Painting still\\n\",\n \"\\n\",\n \"lives is different from painting people, because the subject, as\\n\",\n \"\\n\",\n \"its name suggests, can't move. People can't sit for more than about\\n\",\n \"\\n\",\n \"15 minutes at a time, and when they do they don't sit very still.\\n\",\n \"\\n\",\n \"So the traditional m.o. for painting people is to know how to paint\\n\",\n \"\\n\",\n \"a generic person, which you then modify to match the specific person\\n\",\n \"\\n\",\n \"you're painting. Whereas a still life you can, if you want, copy\\n\",\n \"\\n\",\n \"pixel by pixel from what you're seeing. You don't want to stop\\n\",\n \"\\n\",\n \"there, of course, or you get merely photographic accuracy, and what\\n\",\n \"\\n\",\n \"makes a still life interesting is that it's been through a head.\\n\",\n \"\\n\",\n \"You want to emphasize the visual cues that tell you, for example,\\n\",\n \"\\n\",\n \"that the reason the color changes suddenly at a certain point is\\n\",\n \"\\n\",\n \"that it's the edge of an object. By subtly emphasizing such things\\n\",\n \"\\n\",\n \"you can make paintings that are more realistic than photographs not\\n\",\n \"\\n\",\n \"just in some metaphorical sense, but in the strict information-theoretic\\n\",\n \"\\n\",\n \"sense.\\n\",\n \"\\n\",\n \"[4]I liked painting still lives because I was curious about what I was\\n\",\n \"\\n\",\n \"seeing. In everyday life, we aren't consciously aware of much we're\\n\",\n \"\\n\",\n \"seeing. Most visual perception is handled by low-level processes\\n\",\n \"\\n\",\n \"that merely tell your brain \\\"that's a water droplet\\\" without telling\\n\",\n \"\\n\",\n \"you details like where the lightest and darkest points are, or\\n\",\n \"\\n\",\n \"\\\"that's a bush\\\" without telling you the shape and position of every\\n\",\n \"\\n\",\n \"leaf. This is a feature of brains, not a bug. In everyday life it\\n\",\n \"\\n\",\n \"would be distracting to notice every leaf on every bush. But when\\n\",\n \"\\n\",\n \"you have to paint something, you have to look more closely, and\\n\",\n \"\\n\",\n \"when you do there's a lot to see. You can still be noticing new\\n\",\n \"\\n\",\n \"things after days of trying to paint something people usually take\\n\",\n \"\\n\",\n \"for granted, just as you can after\\n\",\n \"\\n\",\n \"days of trying to write an essay about something people usually\\n\",\n \"\\n\",\n \"take for granted.This is not the only way to paint. I'm not 100% sure it's even a\\n\",\n \"\\n\",\n \"good way to paint. But it seemed a good enough bet to be worth\\n\",\n \"\\n\",\n \"trying.Our teacher, professor Ulivi, was a nice guy. He could see I worked\\n\",\n \"\\n\",\n \"hard, and gave me a good grade, which he wrote down in a sort of\\n\",\n \"\\n\",\n \"passport each student had. But the Accademia wasn't teaching me\\n\",\n \"\\n\",\n \"anything except Italian, and my money was running out, so at the\\n\",\n \"\\n\",\n \"end of the first year I went back to the US.I wanted to go back to RISD, but I was now broke and RISD was very\\n\",\n \"\\n\",\n \"expensive, so I decided to get a job for a year and then return to\\n\",\n \"\\n\",\n \"RISD the next fall. I got one at a company called Interleaf, which\\n\",\n \"\\n\",\n \"made software for creating documents. You mean like Microsoft Word?\\n\",\n \"\\n\",\n \"Exactly. That was how I learned that low end software tends to eat\\n\",\n \"\\n\",\n \"high end software. But Interleaf still had a few years to live yet.\\n\",\n \"\\n\",\n \"[5]Interleaf had done something pretty bold. Inspired by Emacs, they'd\\n\",\n \"\\n\",\n \"added a scripting language, and even made the scripting language a\\n\",\n \"\\n\",\n \"dialect of Lisp. Now they wanted a Lisp hacker to write things in\\n\",\n \"\\n\",\n \"it. This was the closest thing I've had to a normal job, and I\\n\",\n \"\\n\",\n \"hereby apologize to my boss and coworkers, because I was a bad\\n\",\n \"\\n\",\n \"employee. Their Lisp was the thinnest icing on a giant C cake, and\\n\",\n \"\\n\",\n \"since I didn't know C and didn't want to learn it, I never understood\\n\",\n \"\\n\",\n \"most of the software. Plus I was terribly irresponsible. This was\\n\",\n \"\\n\",\n \"back when a programming job meant showing up every day during certain\\n\",\n \"\\n\",\n \"working hours. That seemed unnatural to me, and on this point the\\n\",\n \"\\n\",\n \"rest of the world is coming around to my way of thinking, but at\\n\",\n \"\\n\",\n \"the time it caused a lot of friction. Toward the end of the year I\\n\",\n \"\\n\",\n \"spent much of my time surreptitiously working on On Lisp, which I\\n\",\n \"\\n\",\n \"had by this time gotten a contract to publish.The good part was that I got paid huge amounts of money, especially\\n\",\n \"\\n\",\n \"by art student standards. In Florence, after paying my part of the\\n\",\n \"\\n\",\n \"rent, my budget for everything else had been $7 a day. Now I was\\n\",\n \"\\n\",\n \"getting paid more than 4 times that every hour, even when I was\\n\",\n \"\\n\",\n \"just sitting in a meeting. By living cheaply I not only managed to\\n\",\n \"\\n\",\n \"save enough to go back to RISD, but also paid off my college loans.I learned some useful things at Interleaf, though they were mostly\\n\",\n \"\\n\",\n \"about what not to do. I learned that it's better for technology\\n\",\n \"\\n\",\n \"companies to be run by product people than sales people (though\\n\",\n \"\\n\",\n \"sales is a real skill and people who are good at it are really good\\n\",\n \"\\n\",\n \"at it), that it leads to bugs when code is edited by too many people,\\n\",\n \"\\n\",\n \"that cheap office space is no bargain if it's depressing, that\\n\",\n \"\\n\",\n \"planned meetings are inferior to corridor conversations, that big,\\n\",\n \"\\n\",\n \"bureaucratic customers are a dangerous source of money, and that\\n\",\n \"\\n\",\n \"there's not much overlap between conventional office hours and the\\n\",\n \"\\n\",\n \"optimal time for hacking, or conventional offices and the optimal\\n\",\n \"\\n\",\n \"place for it.But the most important thing I learned, and which I used in both\\n\",\n \"\\n\",\n \"Viaweb and Y Combinator, is that the low end eats the high end:\\n\",\n \"\\n\",\n \"that it's good to be the \\\"entry level\\\" option, even though that\\n\",\n \"\\n\",\n \"will be less prestigious, because if you're not, someone else will\\n\",\n \"\\n\",\n \"be, and will squash you against the ceiling. Which in turn means\\n\",\n \"\\n\",\n \"that prestige is a danger sign.When I left to go back to RISD the next fall, I arranged to do\\n\",\n \"\\n\",\n \"freelance work for the group that did projects for customers, and\\n\",\n \"\\n\",\n \"this was how I survived for the next several years. When I came\\n\",\n \"\\n\",\n \"back to visit for a project later on, someone told me about a new\\n\",\n \"\\n\",\n \"thing called HTML, which was, as he described it, a derivative of\\n\",\n \"\\n\",\n \"SGML. Markup language enthusiasts were an occupational hazard at\\n\",\n \"\\n\",\n \"Interleaf and I ignored him, but this HTML thing later became a big\\n\",\n \"\\n\",\n \"part of my life.In the fall of 1992 I moved back to Providence to continue at RISD.\\n\",\n \"\\n\",\n \"The foundation had merely been intro stuff, and the Accademia had\\n\",\n \"\\n\",\n \"been a (very civilized) joke. Now I was going to see what real art\\n\",\n \"\\n\",\n \"school was like. But alas it was more like the Accademia than not.\\n\",\n \"\\n\",\n \"Better organized, certainly, and a lot more expensive, but it was\\n\",\n \"\\n\",\n \"now becoming clear that art school did not bear the same relationship\\n\",\n \"\\n\",\n \"to art that medical school bore to medicine. At least not the\\n\",\n \"\\n\",\n \"painting department. The textile department, which my next door\\n\",\n \"\\n\",\n \"neighbor belonged to, seemed to be pretty rigorous. No doubt\\n\",\n \"\\n\",\n \"illustration and architecture were too. But painting was post-rigorous.\\n\",\n \"\\n\",\n \"Painting students were supposed to express themselves, which to the\\n\",\n \"\\n\",\n \"more worldly ones meant to try to cook up some sort of distinctive\\n\",\n \"\\n\",\n \"signature style.A signature style is the visual equivalent of what in show business\\n\",\n \"\\n\",\n \"is known as a \\\"schtick\\\": something that immediately identifies the\\n\",\n \"\\n\",\n \"work as yours and no one else's. For example, when you see a painting\\n\",\n \"\\n\",\n \"that looks like a certain kind of cartoon, you know it's by Roy\\n\",\n \"\\n\",\n \"Lichtenstein. So if you see a big painting of this type hanging in\\n\",\n \"\\n\",\n \"the apartment of a hedge fund manager, you know he paid millions\\n\",\n \"\\n\",\n \"of dollars for it. That's not always why artists have a signature\\n\",\n \"\\n\",\n \"style, but it's usually why buyers pay a lot for such work.\\n\",\n \"\\n\",\n \"[6]There were plenty of earnest students too: kids who \\\"could draw\\\"\\n\",\n \"\\n\",\n \"in high school, and now had come to what was supposed to be the\\n\",\n \"\\n\",\n \"best art school in the country, to learn to draw even better. They\\n\",\n \"\\n\",\n \"tended to be confused and demoralized by what they found at RISD,\\n\",\n \"\\n\",\n \"but they kept going, because painting was what they did. I was not\\n\",\n \"\\n\",\n \"one of the kids who could draw in high school, but at RISD I was\\n\",\n \"\\n\",\n \"definitely closer to their tribe than the tribe of signature style\\n\",\n \"\\n\",\n \"seekers.I learned a lot in the color class I took at RISD, but otherwise I\\n\",\n \"\\n\",\n \"was basically teaching myself to paint, and I could do that for\\n\",\n \"\\n\",\n \"free. So in 1993 I dropped out. I hung around Providence for a bit,\\n\",\n \"\\n\",\n \"and then my college friend Nancy Parmet did me a big favor. A\\n\",\n \"\\n\",\n \"rent-controlled apartment in a building her mother owned in New\\n\",\n \"\\n\",\n \"York was becoming vacant. Did I want it? It wasn't much more than\\n\",\n \"\\n\",\n \"my current place, and New York was supposed to be where the artists\\n\",\n \"\\n\",\n \"were. So yes, I wanted it!\\n\",\n \"\\n\",\n \"[7]Asterix comics begin by zooming in on a tiny corner of Roman Gaul\\n\",\n \"\\n\",\n \"that turns out not to be controlled by the Romans. You can do\\n\",\n \"\\n\",\n \"something similar on a map of New York City: if you zoom in on the\\n\",\n \"\\n\",\n \"Upper East Side, there's a tiny corner that's not rich, or at least\\n\",\n \"\\n\",\n \"wasn't in 1993. It's called Yorkville, and that was my new home.\\n\",\n \"\\n\",\n \"Now I was a New York artist — in the strictly technical sense of\\n\",\n \"\\n\",\n \"making paintings and living in New York.I was nervous about money, because I could sense that Interleaf was\\n\",\n \"\\n\",\n \"on the way down. Freelance Lisp hacking work was very rare, and I\\n\",\n \"\\n\",\n \"didn't want to have to program in another language, which in those\\n\",\n \"\\n\",\n \"days would have meant C++ if I was lucky. So with my unerring nose\\n\",\n \"\\n\",\n \"for financial opportunity, I decided to write another book on Lisp.\\n\",\n \"\\n\",\n \"This would be a popular book, the sort of book that could be used\\n\",\n \"\\n\",\n \"as a textbook. I imagined myself living frugally off the royalties\\n\",\n \"\\n\",\n \"and spending all my time painting. (The painting on the cover of\\n\",\n \"\\n\",\n \"this book, ANSI Common Lisp, is one that I painted around this\\n\",\n \"\\n\",\n \"time.)The best thing about New York for me was the presence of Idelle and\\n\",\n \"\\n\",\n \"Julian Weber. Idelle Weber was a painter, one of the early\\n\",\n \"\\n\",\n \"photorealists, and I'd taken her painting class at Harvard. I've\\n\",\n \"\\n\",\n \"never known a teacher more beloved by her students. Large numbers\\n\",\n \"\\n\",\n \"of former students kept in touch with her, including me. After I\\n\",\n \"\\n\",\n \"moved to New York I became her de facto studio assistant.She liked to paint on big, square canvases, 4 to 5 feet on a side.\\n\",\n \"\\n\",\n \"One day in late 1994 as I was stretching one of these monsters there\\n\",\n \"\\n\",\n \"was something on the radio about a famous fund manager. He wasn't\\n\",\n \"\\n\",\n \"that much older than me, and was super rich. The thought suddenly\\n\",\n \"\\n\",\n \"occurred to me: why don't I become rich? Then I'll be able to work\\n\",\n \"\\n\",\n \"on whatever I want.Meanwhile I'd been hearing more and more about this new thing called\\n\",\n \"\\n\",\n \"the World Wide Web. Robert Morris showed it to me when I visited\\n\",\n \"\\n\",\n \"him in Cambridge, where he was now in grad school at Harvard. It\\n\",\n \"\\n\",\n \"seemed to me that the web would be a big deal. I'd seen what graphical\\n\",\n \"\\n\",\n \"user interfaces had done for the popularity of microcomputers. It\\n\",\n \"\\n\",\n \"seemed like the web would do the same for the internet.If I wanted to get rich, here was the next train leaving the station.\\n\",\n \"\\n\",\n \"I was right about that part. What I got wrong was the idea. I decided\\n\",\n \"\\n\",\n \"we should start a company to put art galleries online. I can't\\n\",\n \"\\n\",\n \"honestly say, after reading so many Y Combinator applications, that\\n\",\n \"\\n\",\n \"this was the worst startup idea ever, but it was up there. Art\\n\",\n \"\\n\",\n \"galleries didn't want to be online, and still don't, not the fancy\\n\",\n \"\\n\",\n \"ones. That's not how they sell. I wrote some software to generate\\n\",\n \"\\n\",\n \"web sites for galleries, and Robert wrote some to resize images and\\n\",\n \"\\n\",\n \"set up an http server to serve the pages. Then we tried to sign up\\n\",\n \"\\n\",\n \"galleries. To call this a difficult sale would be an understatement.\\n\",\n \"\\n\",\n \"It was difficult to give away. A few galleries let us make sites\\n\",\n \"\\n\",\n \"for them for free, but none paid us.Then some online stores started to appear, and I realized that\\n\",\n \"\\n\",\n \"except for the order buttons they were identical to the sites we'd\\n\",\n \"\\n\",\n \"been generating for galleries. This impressive-sounding thing called\\n\",\n \"\\n\",\n \"an \\\"internet storefront\\\" was something we already knew how to build.So in the summer of 1995, after I submitted the camera-ready copy\\n\",\n \"\\n\",\n \"of ANSI Common Lisp to the publishers, we started trying to write\\n\",\n \"\\n\",\n \"software to build online stores. At first this was going to be\\n\",\n \"\\n\",\n \"normal desktop software, which in those days meant Windows software.\\n\",\n \"\\n\",\n \"That was an alarming prospect, because neither of us knew how to\\n\",\n \"\\n\",\n \"write Windows software or wanted to learn. We lived in the Unix\\n\",\n \"\\n\",\n \"world. But we decided we'd at least try writing a prototype store\\n\",\n \"\\n\",\n \"builder on Unix. Robert wrote a shopping cart, and I wrote a new\\n\",\n \"\\n\",\n \"site generator for stores — in Lisp, of course.We were working out of Robert's apartment in Cambridge. His roommate\\n\",\n \"\\n\",\n \"was away for big chunks of time, during which I got to sleep in his\\n\",\n \"\\n\",\n \"room. For some reason there was no bed frame or sheets, just a\\n\",\n \"\\n\",\n \"mattress on the floor. One morning as I was lying on this mattress\\n\",\n \"\\n\",\n \"I had an idea that made me sit up like a capital L. What if we ran\\n\",\n \"\\n\",\n \"the software on the server, and let users control it by clicking\\n\",\n \"\\n\",\n \"on links? Then we'd never have to write anything to run on users'\\n\",\n \"\\n\",\n \"computers. We could generate the sites on the same server we'd serve\\n\",\n \"\\n\",\n \"them from. Users wouldn't need anything more than a browser.This kind of software, known as a web app, is common now, but at\\n\",\n \"\\n\",\n \"the time it wasn't clear that it was even possible. To find out,\\n\",\n \"\\n\",\n \"we decided to try making a version of our store builder that you\\n\",\n \"\\n\",\n \"could control through the browser. A couple days later, on August\\n\",\n \"\\n\",\n \"12, we had one that worked. The UI was horrible, but it proved you\\n\",\n \"\\n\",\n \"could build a whole store through the browser, without any client\\n\",\n \"\\n\",\n \"software or typing anything into the command line on the server.Now we felt like we were really onto something. I had visions of a\\n\",\n \"\\n\",\n \"whole new generation of software working this way. You wouldn't\\n\",\n \"\\n\",\n \"need versions, or ports, or any of that crap. At Interleaf there\\n\",\n \"\\n\",\n \"had been a whole group called Release Engineering that seemed to\\n\",\n \"\\n\",\n \"be at least as big as the group that actually wrote the software.\\n\",\n \"\\n\",\n \"Now you could just update the software right on the server.We started a new company we called Viaweb, after the fact that our\\n\",\n \"\\n\",\n \"software worked via the web, and we got $10,000 in seed funding\\n\",\n \"\\n\",\n \"from Idelle's husband Julian. In return for that and doing the\\n\",\n \"\\n\",\n \"initial legal work and giving us business advice, we gave him 10%\\n\",\n \"\\n\",\n \"of the company. Ten years later this deal became the model for Y\\n\",\n \"\\n\",\n \"Combinator's. We knew founders needed something like this, because\\n\",\n \"\\n\",\n \"we'd needed it ourselves.At this stage I had a negative net worth, because the thousand\\n\",\n \"\\n\",\n \"dollars or so I had in the bank was more than counterbalanced by\\n\",\n \"\\n\",\n \"what I owed the government in taxes. (Had I diligently set aside\\n\",\n \"\\n\",\n \"the proper proportion of the money I'd made consulting for Interleaf?\\n\",\n \"\\n\",\n \"No, I had not.) So although Robert had his graduate student stipend,\\n\",\n \"\\n\",\n \"I needed that seed funding to live on.We originally hoped to launch in September, but we got more ambitious\\n\",\n \"\\n\",\n \"about the software as we worked on it. Eventually we managed to\\n\",\n \"\\n\",\n \"build a WYSIWYG site builder, in the sense that as you were creating\\n\",\n \"\\n\",\n \"pages, they looked exactly like the static ones that would be\\n\",\n \"\\n\",\n \"generated later, except that instead of leading to static pages,\\n\",\n \"\\n\",\n \"the links all referred to closures stored in a hash table on the\\n\",\n \"\\n\",\n \"server.It helped to have studied art, because the main goal of an online\\n\",\n \"\\n\",\n \"store builder is to make users look legit, and the key to looking\\n\",\n \"\\n\",\n \"legit is high production values. If you get page layouts and fonts\\n\",\n \"\\n\",\n \"and colors right, you can make a guy running a store out of his\\n\",\n \"\\n\",\n \"bedroom look more legit than a big company.(If you're curious why my site looks so old-fashioned, it's because\\n\",\n \"\\n\",\n \"it's still made with this software. It may look clunky today, but\\n\",\n \"\\n\",\n \"in 1996 it was the last word in slick.)In September, Robert rebelled. \\\"We've been working on this for a\\n\",\n \"\\n\",\n \"month,\\\" he said, \\\"and it's still not done.\\\" This is funny in\\n\",\n \"\\n\",\n \"retrospect, because he would still be working on it almost 3 years\\n\",\n \"\\n\",\n \"later. But I decided it might be prudent to recruit more programmers,\\n\",\n \"\\n\",\n \"and I asked Robert who else in grad school with him was really good.\\n\",\n \"\\n\",\n \"He recommended Trevor Blackwell, which surprised me at first, because\\n\",\n \"\\n\",\n \"at that point I knew Trevor mainly for his plan to reduce everything\\n\",\n \"\\n\",\n \"in his life to a stack of notecards, which he carried around with\\n\",\n \"\\n\",\n \"him. But Rtm was right, as usual. Trevor turned out to be a\\n\",\n \"\\n\",\n \"frighteningly effective hacker.It was a lot of fun working with Robert and Trevor. They're the two\\n\",\n \"\\n\",\n \"most independent-minded people\\n\",\n \"\\n\",\n \"I know, and in completely different\\n\",\n \"\\n\",\n \"ways. If you could see inside Rtm's brain it would look like a\\n\",\n \"\\n\",\n \"colonial New England church, and if you could see inside Trevor's\\n\",\n \"\\n\",\n \"it would look like the worst excesses of Austrian Rococo.We opened for business, with 6 stores, in January 1996. It was just\\n\",\n \"\\n\",\n \"as well we waited a few months, because although we worried we were\\n\",\n \"\\n\",\n \"late, we were actually almost fatally early. There was a lot of\\n\",\n \"\\n\",\n \"talk in the press then about ecommerce, but not many people actually\\n\",\n \"\\n\",\n \"wanted online stores.\\n\",\n \"\\n\",\n \"[8]There were three main parts to the software: the editor, which\\n\",\n \"\\n\",\n \"people used to build sites and which I wrote, the shopping cart,\\n\",\n \"\\n\",\n \"which Robert wrote, and the manager, which kept track of orders and\\n\",\n \"\\n\",\n \"statistics, and which Trevor wrote. In its time, the editor was one\\n\",\n \"\\n\",\n \"of the best general-purpose site builders. I kept the code tight\\n\",\n \"\\n\",\n \"and didn't have to integrate with any other software except Robert's\\n\",\n \"\\n\",\n \"and Trevor's, so it was quite fun to work on. If all I'd had to do\\n\",\n \"\\n\",\n \"was work on this software, the next 3 years would have been the\\n\",\n \"\\n\",\n \"easiest of my life. Unfortunately I had to do a lot more, all of\\n\",\n \"\\n\",\n \"it stuff I was worse at than programming, and the next 3 years were\\n\",\n \"\\n\",\n \"instead the most stressful.There were a lot of startups making ecommerce software in the second\\n\",\n \"\\n\",\n \"half of the 90s. We were determined to be the Microsoft Word, not\\n\",\n \"\\n\",\n \"the Interleaf. Which meant being easy to use and inexpensive. It\\n\",\n \"\\n\",\n \"was lucky for us that we were poor, because that caused us to make\\n\",\n \"\\n\",\n \"Viaweb even more inexpensive than we realized. We charged $100 a\\n\",\n \"\\n\",\n \"month for a small store and $300 a month for a big one. This low\\n\",\n \"\\n\",\n \"price was a big attraction, and a constant thorn in the sides of\\n\",\n \"\\n\",\n \"competitors, but it wasn't because of some clever insight that we\\n\",\n \"\\n\",\n \"set the price low. We had no idea what businesses paid for things.\\n\",\n \"\\n\",\n \"$300 a month seemed like a lot of money to us.We did a lot of things right by accident like that. For example,\\n\",\n \"\\n\",\n \"we did what's now called \\\"doing things that\\n\",\n \"\\n\",\n \"don't scale,\\\" although\\n\",\n \"\\n\",\n \"at the time we would have described it as \\\"being so lame that we're\\n\",\n \"\\n\",\n \"driven to the most desperate measures to get users.\\\" The most common\\n\",\n \"\\n\",\n \"of which was building stores for them. This seemed particularly\\n\",\n \"\\n\",\n \"humiliating, since the whole raison d'etre of our software was that\\n\",\n \"\\n\",\n \"people could use it to make their own stores. But anything to get\\n\",\n \"\\n\",\n \"users.We learned a lot more about retail than we wanted to know. For\\n\",\n \"\\n\",\n \"example, that if you could only have a small image of a man's shirt\\n\",\n \"\\n\",\n \"(and all images were small then by present standards), it was better\\n\",\n \"\\n\",\n \"to have a closeup of the collar than a picture of the whole shirt.\\n\",\n \"\\n\",\n \"The reason I remember learning this was that it meant I had to\\n\",\n \"\\n\",\n \"rescan about 30 images of men's shirts. My first set of scans were\\n\",\n \"\\n\",\n \"so beautiful too.Though this felt wrong, it was exactly the right thing to be doing.\\n\",\n \"\\n\",\n \"Building stores for users taught us about retail, and about how it\\n\",\n \"\\n\",\n \"felt to use our software. I was initially both mystified and repelled\\n\",\n \"\\n\",\n \"by \\\"business\\\" and thought we needed a \\\"business person\\\" to be in\\n\",\n \"\\n\",\n \"charge of it, but once we started to get users, I was converted,\\n\",\n \"\\n\",\n \"in much the same way I was converted to\\n\",\n \"\\n\",\n \"fatherhood once I had kids.\\n\",\n \"\\n\",\n \"Whatever users wanted, I was all theirs. Maybe one day we'd have\\n\",\n \"\\n\",\n \"so many users that I couldn't scan their images for them, but in\\n\",\n \"\\n\",\n \"the meantime there was nothing more important to do.Another thing I didn't get at the time is that\\n\",\n \"\\n\",\n \"growth rate is the\\n\",\n \"\\n\",\n \"ultimate test of a startup. Our growth rate was fine. We had about\\n\",\n \"\\n\",\n \"70 stores at the end of 1996 and about 500 at the end of 1997. I\\n\",\n \"\\n\",\n \"mistakenly thought the thing that mattered was the absolute number\\n\",\n \"\\n\",\n \"of users. And that is the thing that matters in the sense that\\n\",\n \"\\n\",\n \"that's how much money you're making, and if you're not making enough,\\n\",\n \"\\n\",\n \"you might go out of business. But in the long term the growth rate\\n\",\n \"\\n\",\n \"takes care of the absolute number. If we'd been a startup I was\\n\",\n \"\\n\",\n \"advising at Y Combinator, I would have said: Stop being so stressed\\n\",\n \"\\n\",\n \"out, because you're doing fine. You're growing 7x a year. Just don't\\n\",\n \"\\n\",\n \"hire too many more people and you'll soon be profitable, and then\\n\",\n \"\\n\",\n \"you'll control your own destiny.Alas I hired lots more people, partly because our investors wanted\\n\",\n \"\\n\",\n \"me to, and partly because that's what startups did during the\\n\",\n \"\\n\",\n \"Internet Bubble. A company with just a handful of employees would\\n\",\n \"\\n\",\n \"have seemed amateurish. So we didn't reach breakeven until about\\n\",\n \"\\n\",\n \"when Yahoo bought us in the summer of 1998. Which in turn meant we\\n\",\n \"\\n\",\n \"were at the mercy of investors for the entire life of the company.\\n\",\n \"\\n\",\n \"And since both we and our investors were noobs at startups, the\\n\",\n \"\\n\",\n \"result was a mess even by startup standards.It was a huge relief when Yahoo bought us. In principle our Viaweb\\n\",\n \"\\n\",\n \"stock was valuable. It was a share in a business that was profitable\\n\",\n \"\\n\",\n \"and growing rapidly. But it didn't feel very valuable to me; I had\\n\",\n \"\\n\",\n \"no idea how to value a business, but I was all too keenly aware of\\n\",\n \"\\n\",\n \"the near-death experiences we seemed to have every few months. Nor\\n\",\n \"\\n\",\n \"had I changed my grad student lifestyle significantly since we\\n\",\n \"\\n\",\n \"started. So when Yahoo bought us it felt like going from rags to\\n\",\n \"\\n\",\n \"riches. Since we were going to California, I bought a car, a yellow\\n\",\n \"\\n\",\n \"1998 VW GTI. I remember thinking that its leather seats alone were\\n\",\n \"\\n\",\n \"by far the most luxurious thing I owned.The next year, from the summer of 1998 to the summer of 1999, must\\n\",\n \"\\n\",\n \"have been the least productive of my life. I didn't realize it at\\n\",\n \"\\n\",\n \"the time, but I was worn out from the effort and stress of running\\n\",\n \"\\n\",\n \"Viaweb. For a while after I got to California I tried to continue\\n\",\n \"\\n\",\n \"my usual m.o. of programming till 3 in the morning, but fatigue\\n\",\n \"\\n\",\n \"combined with Yahoo's prematurely aged\\n\",\n \"\\n\",\n \"culture and grim cube farm\\n\",\n \"\\n\",\n \"in Santa Clara gradually dragged me down. After a few months it\\n\",\n \"\\n\",\n \"felt disconcertingly like working at Interleaf.Yahoo had given us a lot of options when they bought us. At the\\n\",\n \"\\n\",\n \"time I thought Yahoo was so overvalued that they'd never be worth\\n\",\n \"\\n\",\n \"anything, but to my astonishment the stock went up 5x in the next\\n\",\n \"\\n\",\n \"year. I hung on till the first chunk of options vested, then in the\\n\",\n \"\\n\",\n \"summer of 1999 I left. It had been so long since I'd painted anything\\n\",\n \"\\n\",\n \"that I'd half forgotten why I was doing this. My brain had been\\n\",\n \"\\n\",\n \"entirely full of software and men's shirts for 4 years. But I had\\n\",\n \"\\n\",\n \"done this to get rich so I could paint, I reminded myself, and now\\n\",\n \"\\n\",\n \"I was rich, so I should go paint.When I said I was leaving, my boss at Yahoo had a long conversation\\n\",\n \"\\n\",\n \"with me about my plans. I told him all about the kinds of pictures\\n\",\n \"\\n\",\n \"I wanted to paint. At the time I was touched that he took such an\\n\",\n \"\\n\",\n \"interest in me. Now I realize it was because he thought I was lying.\\n\",\n \"\\n\",\n \"My options at that point were worth about $2 million a month. If I\\n\",\n \"\\n\",\n \"was leaving that kind of money on the table, it could only be to\\n\",\n \"\\n\",\n \"go and start some new startup, and if I did, I might take people\\n\",\n \"\\n\",\n \"with me. This was the height of the Internet Bubble, and Yahoo was\\n\",\n \"\\n\",\n \"ground zero of it. My boss was at that moment a billionaire. Leaving\\n\",\n \"\\n\",\n \"then to start a new startup must have seemed to him an insanely,\\n\",\n \"\\n\",\n \"and yet also plausibly, ambitious plan.But I really was quitting to paint, and I started immediately.\\n\",\n \"\\n\",\n \"There was no time to lose. I'd already burned 4 years getting rich.\\n\",\n \"\\n\",\n \"Now when I talk to founders who are leaving after selling their\\n\",\n \"\\n\",\n \"companies, my advice is always the same: take a vacation. That's\\n\",\n \"\\n\",\n \"what I should have done, just gone off somewhere and done nothing\\n\",\n \"\\n\",\n \"for a month or two, but the idea never occurred to me.So I tried to paint, but I just didn't seem to have any energy or\\n\",\n \"\\n\",\n \"ambition. Part of the problem was that I didn't know many people\\n\",\n \"\\n\",\n \"in California. I'd compounded this problem by buying a house up in\\n\",\n \"\\n\",\n \"the Santa Cruz Mountains, with a beautiful view but miles from\\n\",\n \"\\n\",\n \"anywhere. I stuck it out for a few more months, then in desperation\\n\",\n \"\\n\",\n \"I went back to New York, where unless you understand about rent\\n\",\n \"\\n\",\n \"control you'll be surprised to hear I still had my apartment, sealed\\n\",\n \"\\n\",\n \"up like a tomb of my old life. Idelle was in New York at least, and\\n\",\n \"\\n\",\n \"there were other people trying to paint there, even though I didn't\\n\",\n \"\\n\",\n \"know any of them.When I got back to New York I resumed my old life, except now I was\\n\",\n \"\\n\",\n \"rich. It was as weird as it sounds. I resumed all my old patterns,\\n\",\n \"\\n\",\n \"except now there were doors where there hadn't been. Now when I was\\n\",\n \"\\n\",\n \"tired of walking, all I had to do was raise my hand, and (unless\\n\",\n \"\\n\",\n \"it was raining) a taxi would stop to pick me up. Now when I walked\\n\",\n \"\\n\",\n \"past charming little restaurants I could go in and order lunch. It\\n\",\n \"\\n\",\n \"was exciting for a while. Painting started to go better. I experimented\\n\",\n \"\\n\",\n \"with a new kind of still life where I'd paint one painting in the\\n\",\n \"\\n\",\n \"old way, then photograph it and print it, blown up, on canvas, and\\n\",\n \"\\n\",\n \"then use that as the underpainting for a second still life, painted\\n\",\n \"\\n\",\n \"from the same objects (which hopefully hadn't rotted yet).Meanwhile I looked for an apartment to buy. Now I could actually\\n\",\n \"\\n\",\n \"choose what neighborhood to live in. Where, I asked myself and\\n\",\n \"\\n\",\n \"various real estate agents, is the Cambridge of New York? Aided by\\n\",\n \"\\n\",\n \"occasional visits to actual Cambridge, I gradually realized there\\n\",\n \"\\n\",\n \"wasn't one. Huh.Around this time, in the spring of 2000, I had an idea. It was clear\\n\",\n \"\\n\",\n \"from our experience with Viaweb that web apps were the future. Why\\n\",\n \"\\n\",\n \"not build a web app for making web apps? Why not let people edit\\n\",\n \"\\n\",\n \"code on our server through the browser, and then host the resulting\\n\",\n \"\\n\",\n \"applications for them?\\n\",\n \"\\n\",\n \"[9]\\n\",\n \"\\n\",\n \"You could run all sorts of services\\n\",\n \"\\n\",\n \"on the servers that these applications could use just by making an\\n\",\n \"\\n\",\n \"API call: making and receiving phone calls, manipulating images,\\n\",\n \"\\n\",\n \"taking credit card payments, etc.I got so excited about this idea that I couldn't think about anything\\n\",\n \"\\n\",\n \"else. It seemed obvious that this was the future. I didn't particularly\\n\",\n \"\\n\",\n \"want to start another company, but it was clear that this idea would\\n\",\n \"\\n\",\n \"have to be embodied as one, so I decided to move to Cambridge and\\n\",\n \"\\n\",\n \"start it. I hoped to lure Robert into working on it with me, but\\n\",\n \"\\n\",\n \"there I ran into a hitch. Robert was now a postdoc at MIT, and\\n\",\n \"\\n\",\n \"though he'd made a lot of money the last time I'd lured him into\\n\",\n \"\\n\",\n \"working on one of my schemes, it had also been a huge time sink.\\n\",\n \"\\n\",\n \"So while he agreed that it sounded like a plausible idea, he firmly\\n\",\n \"\\n\",\n \"refused to work on it.Hmph. Well, I'd do it myself then. I recruited Dan Giffin, who had\\n\",\n \"\\n\",\n \"worked for Viaweb, and two undergrads who wanted summer jobs, and\\n\",\n \"\\n\",\n \"we got to work trying to build what it's now clear is about twenty\\n\",\n \"\\n\",\n \"companies and several open source projects worth of software. The\\n\",\n \"\\n\",\n \"language for defining applications would of course be a dialect of\\n\",\n \"\\n\",\n \"Lisp. But I wasn't so naive as to assume I could spring an overt\\n\",\n \"\\n\",\n \"Lisp on a general audience; we'd hide the parentheses, like Dylan\\n\",\n \"\\n\",\n \"did.By then there was a name for the kind of company Viaweb was, an\\n\",\n \"\\n\",\n \"\\\"application service provider,\\\" or ASP. This name didn't last long\\n\",\n \"\\n\",\n \"before it was replaced by \\\"software as a service,\\\" but it was current\\n\",\n \"\\n\",\n \"for long enough that I named this new company after it: it was going\\n\",\n \"\\n\",\n \"to be called Aspra.I started working on the application builder, Dan worked on network\\n\",\n \"\\n\",\n \"infrastructure, and the two undergrads worked on the first two\\n\",\n \"\\n\",\n \"services (images and phone calls). But about halfway through the\\n\",\n \"\\n\",\n \"summer I realized I really didn't want to run a company — especially\\n\",\n \"\\n\",\n \"not a big one, which it was looking like this would have to be. I'd\\n\",\n \"\\n\",\n \"only started Viaweb because I needed the money. Now that I didn't\\n\",\n \"\\n\",\n \"need money anymore, why was I doing this? If this vision had to be\\n\",\n \"\\n\",\n \"realized as a company, then screw the vision. I'd build a subset\\n\",\n \"\\n\",\n \"that could be done as an open source project.Much to my surprise, the time I spent working on this stuff was not\\n\",\n \"\\n\",\n \"wasted after all. After we started Y Combinator, I would often\\n\",\n \"\\n\",\n \"encounter startups working on parts of this new architecture, and\\n\",\n \"\\n\",\n \"it was very useful to have spent so much time thinking about it and\\n\",\n \"\\n\",\n \"even trying to write some of it.The subset I would build as an open source project was the new Lisp,\\n\",\n \"\\n\",\n \"whose parentheses I now wouldn't even have to hide. A lot of Lisp\\n\",\n \"\\n\",\n \"hackers dream of building a new Lisp, partly because one of the\\n\",\n \"\\n\",\n \"distinctive features of the language is that it has dialects, and\\n\",\n \"\\n\",\n \"partly, I think, because we have in our minds a Platonic form of\\n\",\n \"\\n\",\n \"Lisp that all existing dialects fall short of. I certainly did. So\\n\",\n \"\\n\",\n \"at the end of the summer Dan and I switched to working on this new\\n\",\n \"\\n\",\n \"dialect of Lisp, which I called Arc, in a house I bought in Cambridge.The following spring, lightning struck. I was invited to give a\\n\",\n \"\\n\",\n \"talk at a Lisp conference, so I gave one about how we'd used Lisp\\n\",\n \"\\n\",\n \"at Viaweb. Afterward I put a postscript file of this talk online,\\n\",\n \"\\n\",\n \"on paulgraham.com, which I'd created years before using Viaweb but\\n\",\n \"\\n\",\n \"had never used for anything. In one day it got 30,000 page views.\\n\",\n \"\\n\",\n \"What on earth had happened? The referring urls showed that someone\\n\",\n \"\\n\",\n \"had posted it on Slashdot.\\n\",\n \"\\n\",\n \"[10]Wow, I thought, there's an audience. If I write something and put\\n\",\n \"\\n\",\n \"it on the web, anyone can read it. That may seem obvious now, but\\n\",\n \"\\n\",\n \"it was surprising then. In the print era there was a narrow channel\\n\",\n \"\\n\",\n \"to readers, guarded by fierce monsters known as editors. The only\\n\",\n \"\\n\",\n \"way to get an audience for anything you wrote was to get it published\\n\",\n \"\\n\",\n \"as a book, or in a newspaper or magazine. Now anyone could publish\\n\",\n \"\\n\",\n \"anything.This had been possible in principle since 1993, but not many people\\n\",\n \"\\n\",\n \"had realized it yet. I had been intimately involved with building\\n\",\n \"\\n\",\n \"the infrastructure of the web for most of that time, and a writer\\n\",\n \"\\n\",\n \"as well, and it had taken me 8 years to realize it. Even then it\\n\",\n \"\\n\",\n \"took me several years to understand the implications. It meant there\\n\",\n \"\\n\",\n \"would be a whole new generation of\\n\",\n \"\\n\",\n \"essays.\\n\",\n \"\\n\",\n \"[11]In the print era, the channel for publishing essays had been\\n\",\n \"\\n\",\n \"vanishingly small. Except for a few officially anointed thinkers\\n\",\n \"\\n\",\n \"who went to the right parties in New York, the only people allowed\\n\",\n \"\\n\",\n \"to publish essays were specialists writing about their specialties.\\n\",\n \"\\n\",\n \"There were so many essays that had never been written, because there\\n\",\n \"\\n\",\n \"had been no way to publish them. Now they could be, and I was going\\n\",\n \"\\n\",\n \"to write them.\\n\",\n \"\\n\",\n \"[12]I've worked on several different things, but to the extent there\\n\",\n \"\\n\",\n \"was a turning point where I figured out what to work on, it was\\n\",\n \"\\n\",\n \"when I started publishing essays online. From then on I knew that\\n\",\n \"\\n\",\n \"whatever else I did, I'd always write essays too.I knew that online essays would be a\\n\",\n \"\\n\",\n \"marginal medium at first.\\n\",\n \"\\n\",\n \"Socially they'd seem more like rants posted by nutjobs on their\\n\",\n \"\\n\",\n \"GeoCities sites than the genteel and beautifully typeset compositions\\n\",\n \"\\n\",\n \"published in The New Yorker. But by this point I knew enough to\\n\",\n \"\\n\",\n \"find that encouraging instead of discouraging.One of the most conspicuous patterns I've noticed in my life is how\\n\",\n \"\\n\",\n \"well it has worked, for me at least, to work on things that weren't\\n\",\n \"\\n\",\n \"prestigious. Still life has always been the least prestigious form\\n\",\n \"\\n\",\n \"of painting. Viaweb and Y Combinator both seemed lame when we started\\n\",\n \"\\n\",\n \"them. I still get the glassy eye from strangers when they ask what\\n\",\n \"\\n\",\n \"I'm writing, and I explain that it's an essay I'm going to publish\\n\",\n \"\\n\",\n \"on my web site. Even Lisp, though prestigious intellectually in\\n\",\n \"\\n\",\n \"something like the way Latin is, also seems about as hip.It's not that unprestigious types of work are good per se. But when\\n\",\n \"\\n\",\n \"you find yourself drawn to some kind of work despite its current\\n\",\n \"\\n\",\n \"lack of prestige, it's a sign both that there's something real to\\n\",\n \"\\n\",\n \"be discovered there, and that you have the right kind of motives.\\n\",\n \"\\n\",\n \"Impure motives are a big danger for the ambitious. If anything is\\n\",\n \"\\n\",\n \"going to lead you astray, it will be the desire to impress people.\\n\",\n \"\\n\",\n \"So while working on things that aren't prestigious doesn't guarantee\\n\",\n \"\\n\",\n \"you're on the right track, it at least guarantees you're not on the\\n\",\n \"\\n\",\n \"most common type of wrong one.Over the next several years I wrote lots of essays about all kinds\\n\",\n \"\\n\",\n \"of different topics. O'Reilly reprinted a collection of them as a\\n\",\n \"\\n\",\n \"book, called Hackers & Painters after one of the essays in it. I\\n\",\n \"\\n\",\n \"also worked on spam filters, and did some more painting. I used to\\n\",\n \"\\n\",\n \"have dinners for a group of friends every thursday night, which\\n\",\n \"\\n\",\n \"taught me how to cook for groups. And I bought another building in\\n\",\n \"\\n\",\n \"Cambridge, a former candy factory (and later, twas said, porn\\n\",\n \"\\n\",\n \"studio), to use as an office.One night in October 2003 there was a big party at my house. It was\\n\",\n \"\\n\",\n \"a clever idea of my friend Maria Daniels, who was one of the thursday\\n\",\n \"\\n\",\n \"diners. Three separate hosts would all invite their friends to one\\n\",\n \"\\n\",\n \"party. So for every guest, two thirds of the other guests would be\\n\",\n \"\\n\",\n \"people they didn't know but would probably like. One of the guests\\n\",\n \"\\n\",\n \"was someone I didn't know but would turn out to like a lot: a woman\\n\",\n \"\\n\",\n \"called Jessica Livingston. A couple days later I asked her out.Jessica was in charge of marketing at a Boston investment bank.\\n\",\n \"\\n\",\n \"This bank thought it understood startups, but over the next year,\\n\",\n \"\\n\",\n \"as she met friends of mine from the startup world, she was surprised\\n\",\n \"\\n\",\n \"how different reality was. And how colorful their stories were. So\\n\",\n \"\\n\",\n \"she decided to compile a book of\\n\",\n \"\\n\",\n \"interviews with startup founders.When the bank had financial problems and she had to fire half her\\n\",\n \"\\n\",\n \"staff, she started looking for a new job. In early 2005 she interviewed\\n\",\n \"\\n\",\n \"for a marketing job at a Boston VC firm. It took them weeks to make\\n\",\n \"\\n\",\n \"up their minds, and during this time I started telling her about\\n\",\n \"\\n\",\n \"all the things that needed to be fixed about venture capital. They\\n\",\n \"\\n\",\n \"should make a larger number of smaller investments instead of a\\n\",\n \"\\n\",\n \"handful of giant ones, they should be funding younger, more technical\\n\",\n \"\\n\",\n \"founders instead of MBAs, they should let the founders remain as\\n\",\n \"\\n\",\n \"CEO, and so on.One of my tricks for writing essays had always been to give talks.\\n\",\n \"\\n\",\n \"The prospect of having to stand up in front of a group of people\\n\",\n \"\\n\",\n \"and tell them something that won't waste their time is a great\\n\",\n \"\\n\",\n \"spur to the imagination. When the Harvard Computer Society, the\\n\",\n \"\\n\",\n \"undergrad computer club, asked me to give a talk, I decided I would\\n\",\n \"\\n\",\n \"tell them how to start a startup. Maybe they'd be able to avoid the\\n\",\n \"\\n\",\n \"worst of the mistakes we'd made.So I gave this talk, in the course of which I told them that the\\n\",\n \"\\n\",\n \"best sources of seed funding were successful startup founders,\\n\",\n \"\\n\",\n \"because then they'd be sources of advice too. Whereupon it seemed\\n\",\n \"\\n\",\n \"they were all looking expectantly at me. Horrified at the prospect\\n\",\n \"\\n\",\n \"of having my inbox flooded by business plans (if I'd only known),\\n\",\n \"\\n\",\n \"I blurted out \\\"But not me!\\\" and went on with the talk. But afterward\\n\",\n \"\\n\",\n \"it occurred to me that I should really stop procrastinating about\\n\",\n \"\\n\",\n \"angel investing. I'd been meaning to since Yahoo bought us, and now\\n\",\n \"\\n\",\n \"it was 7 years later and I still hadn't done one angel investment.Meanwhile I had been scheming with Robert and Trevor about projects\\n\",\n \"\\n\",\n \"we could work on together. I missed working with them, and it seemed\\n\",\n \"\\n\",\n \"like there had to be something we could collaborate on.As Jessica and I were walking home from dinner on March 11, at the\\n\",\n \"\\n\",\n \"corner of Garden and Walker streets, these three threads converged.\\n\",\n \"\\n\",\n \"Screw the VCs who were taking so long to make up their minds. We'd\\n\",\n \"\\n\",\n \"start our own investment firm and actually implement the ideas we'd\\n\",\n \"\\n\",\n \"been talking about. I'd fund it, and Jessica could quit her job and\\n\",\n \"\\n\",\n \"work for it, and we'd get Robert and Trevor as partners too.\\n\",\n \"\\n\",\n \"[13]Once again, ignorance worked in our favor. We had no idea how to\\n\",\n \"\\n\",\n \"be angel investors, and in Boston in 2005 there were no Ron Conways\\n\",\n \"\\n\",\n \"to learn from. So we just made what seemed like the obvious choices,\\n\",\n \"\\n\",\n \"and some of the things we did turned out to be novel.There are multiple components to Y Combinator, and we didn't figure\\n\",\n \"\\n\",\n \"them all out at once. The part we got first was to be an angel firm.\\n\",\n \"\\n\",\n \"In those days, those two words didn't go together. There were VC\\n\",\n \"\\n\",\n \"firms, which were organized companies with people whose job it was\\n\",\n \"\\n\",\n \"to make investments, but they only did big, million dollar investments.\\n\",\n \"\\n\",\n \"And there were angels, who did smaller investments, but these were\\n\",\n \"\\n\",\n \"individuals who were usually focused on other things and made\\n\",\n \"\\n\",\n \"investments on the side. And neither of them helped founders enough\\n\",\n \"\\n\",\n \"in the beginning. We knew how helpless founders were in some respects,\\n\",\n \"\\n\",\n \"because we remembered how helpless we'd been. For example, one thing\\n\",\n \"\\n\",\n \"Julian had done for us that seemed to us like magic was to get us\\n\",\n \"\\n\",\n \"set up as a company. We were fine writing fairly difficult software,\\n\",\n \"\\n\",\n \"but actually getting incorporated, with bylaws and stock and all\\n\",\n \"\\n\",\n \"that stuff, how on earth did you do that? Our plan was not only to\\n\",\n \"\\n\",\n \"make seed investments, but to do for startups everything Julian had\\n\",\n \"\\n\",\n \"done for us.YC was not organized as a fund. It was cheap enough to run that we\\n\",\n \"\\n\",\n \"funded it with our own money. That went right by 99% of readers,\\n\",\n \"\\n\",\n \"but professional investors are thinking \\\"Wow, that means they got\\n\",\n \"\\n\",\n \"all the returns.\\\" But once again, this was not due to any particular\\n\",\n \"\\n\",\n \"insight on our part. We didn't know how VC firms were organized.\\n\",\n \"\\n\",\n \"It never occurred to us to try to raise a fund, and if it had, we\\n\",\n \"\\n\",\n \"wouldn't have known where to start.\\n\",\n \"\\n\",\n \"[14]The most distinctive thing about YC is the batch model: to fund a\\n\",\n \"\\n\",\n \"bunch of startups all at once, twice a year, and then to spend three\\n\",\n \"\\n\",\n \"months focusing intensively on trying to help them. That part we\\n\",\n \"\\n\",\n \"discovered by accident, not merely implicitly but explicitly due\\n\",\n \"\\n\",\n \"to our ignorance about investing. We needed to get experience as\\n\",\n \"\\n\",\n \"investors. What better way, we thought, than to fund a whole bunch\\n\",\n \"\\n\",\n \"of startups at once? We knew undergrads got temporary jobs at tech\\n\",\n \"\\n\",\n \"companies during the summer. Why not organize a summer program where\\n\",\n \"\\n\",\n \"they'd start startups instead? We wouldn't feel guilty for being\\n\",\n \"\\n\",\n \"in a sense fake investors, because they would in a similar sense\\n\",\n \"\\n\",\n \"be fake founders. So while we probably wouldn't make much money out\\n\",\n \"\\n\",\n \"of it, we'd at least get to practice being investors on them, and\\n\",\n \"\\n\",\n \"they for their part would probably have a more interesting summer\\n\",\n \"\\n\",\n \"than they would working at Microsoft.We'd use the building I owned in Cambridge as our headquarters.\\n\",\n \"\\n\",\n \"We'd all have dinner there once a week — on tuesdays, since I was\\n\",\n \"\\n\",\n \"already cooking for the thursday diners on thursdays — and after\\n\",\n \"\\n\",\n \"dinner we'd bring in experts on startups to give talks.We knew undergrads were deciding then about summer jobs, so in a\\n\",\n \"\\n\",\n \"matter of days we cooked up something we called the Summer Founders\\n\",\n \"\\n\",\n \"Program, and I posted an\\n\",\n \"\\n\",\n \"announcement\\n\",\n \"\\n\",\n \"on my site, inviting undergrads\\n\",\n \"\\n\",\n \"to apply. I had never imagined that writing essays would be a way\\n\",\n \"\\n\",\n \"to get \\\"deal flow,\\\" as investors call it, but it turned out to be\\n\",\n \"\\n\",\n \"the perfect source.\\n\",\n \"\\n\",\n \"[15]\\n\",\n \"\\n\",\n \"We got 225 applications for the Summer\\n\",\n \"\\n\",\n \"Founders Program, and we were surprised to find that a lot of them\\n\",\n \"\\n\",\n \"were from people who'd already graduated, or were about to that\\n\",\n \"\\n\",\n \"spring. Already this SFP thing was starting to feel more serious\\n\",\n \"\\n\",\n \"than we'd intended.We invited about 20 of the 225 groups to interview in person, and\\n\",\n \"\\n\",\n \"from those we picked 8 to fund. They were an impressive group. That\\n\",\n \"\\n\",\n \"first batch included reddit, Justin Kan and Emmett Shear, who went\\n\",\n \"\\n\",\n \"on to found Twitch, Aaron Swartz, who had already helped write the\\n\",\n \"\\n\",\n \"RSS spec and would a few years later become a martyr for open access,\\n\",\n \"\\n\",\n \"and Sam Altman, who would later become the second president of YC.\\n\",\n \"\\n\",\n \"I don't think it was entirely luck that the first batch was so good.\\n\",\n \"\\n\",\n \"You had to be pretty bold to sign up for a weird thing like the\\n\",\n \"\\n\",\n \"Summer Founders Program instead of a summer job at a legit place\\n\",\n \"\\n\",\n \"like Microsoft or Goldman Sachs.The deal for startups was based on a combination of the deal we did\\n\",\n \"\\n\",\n \"with Julian ($10k for 10%) and what Robert said MIT grad students\\n\",\n \"\\n\",\n \"got for the summer ($6k). We invested $6k per founder, which in the\\n\",\n \"\\n\",\n \"typical two-founder case was $12k, in return for 6%. That had to\\n\",\n \"\\n\",\n \"be fair, because it was twice as good as the deal we ourselves had\\n\",\n \"\\n\",\n \"taken. Plus that first summer, which was really hot, Jessica brought\\n\",\n \"\\n\",\n \"the founders free air conditioners.\\n\",\n \"\\n\",\n \"[16]Fairly quickly I realized that we had stumbled upon the way to scale\\n\",\n \"\\n\",\n \"startup funding. Funding startups in batches was more convenient\\n\",\n \"\\n\",\n \"for us, because it meant we could do things for a lot of startups\\n\",\n \"\\n\",\n \"at once, but being part of a batch was better for the startups too.\\n\",\n \"\\n\",\n \"It solved one of the biggest problems faced by founders: the\\n\",\n \"\\n\",\n \"isolation. Now you not only had colleagues, but colleagues who\\n\",\n \"\\n\",\n \"understood the problems you were facing and could tell you how they\\n\",\n \"\\n\",\n \"were solving them.As YC grew, we started to notice other advantages of scale. The\\n\",\n \"\\n\",\n \"alumni became a tight community, dedicated to helping one another,\\n\",\n \"\\n\",\n \"and especially the current batch, whose shoes they remembered being\\n\",\n \"\\n\",\n \"in. We also noticed that the startups were becoming one another's\\n\",\n \"\\n\",\n \"customers. We used to refer jokingly to the \\\"YC GDP,\\\" but as YC\\n\",\n \"\\n\",\n \"grows this becomes less and less of a joke. Now lots of startups\\n\",\n \"\\n\",\n \"get their initial set of customers almost entirely from among their\\n\",\n \"\\n\",\n \"batchmates.I had not originally intended YC to be a full-time job. I was going\\n\",\n \"\\n\",\n \"to do three things: hack, write essays, and work on YC. As YC grew,\\n\",\n \"\\n\",\n \"and I grew more excited about it, it started to take up a lot more\\n\",\n \"\\n\",\n \"than a third of my attention. But for the first few years I was\\n\",\n \"\\n\",\n \"still able to work on other things.In the summer of 2006, Robert and I started working on a new version\\n\",\n \"\\n\",\n \"of Arc. This one was reasonably fast, because it was compiled into\\n\",\n \"\\n\",\n \"Scheme. To test this new Arc, I wrote Hacker News in it. It was\\n\",\n \"\\n\",\n \"originally meant to be a news aggregator for startup founders and\\n\",\n \"\\n\",\n \"was called Startup News, but after a few months I got tired of\\n\",\n \"\\n\",\n \"reading about nothing but startups. Plus it wasn't startup founders\\n\",\n \"\\n\",\n \"we wanted to reach. It was future startup founders. So I changed\\n\",\n \"\\n\",\n \"the name to Hacker News and the topic to whatever engaged one's\\n\",\n \"\\n\",\n \"intellectual curiosity.HN was no doubt good for YC, but it was also by far the biggest\\n\",\n \"\\n\",\n \"source of stress for me. If all I'd had to do was select and help\\n\",\n \"\\n\",\n \"founders, life would have been so easy. And that implies that HN\\n\",\n \"\\n\",\n \"was a mistake. Surely the biggest source of stress in one's work\\n\",\n \"\\n\",\n \"should at least be something close to the core of the work. Whereas\\n\",\n \"\\n\",\n \"I was like someone who was in pain while running a marathon not\\n\",\n \"\\n\",\n \"from the exertion of running, but because I had a blister from an\\n\",\n \"\\n\",\n \"ill-fitting shoe. When I was dealing with some urgent problem during\\n\",\n \"\\n\",\n \"YC, there was about a 60% chance it had to do with HN, and a 40%\\n\",\n \"\\n\",\n \"chance it had do with everything else combined.\\n\",\n \"\\n\",\n \"[17]As well as HN, I wrote all of YC's internal software in Arc. But\\n\",\n \"\\n\",\n \"while I continued to work a good deal in Arc, I gradually stopped\\n\",\n \"\\n\",\n \"working on Arc, partly because I didn't have time to, and partly\\n\",\n \"\\n\",\n \"because it was a lot less attractive to mess around with the language\\n\",\n \"\\n\",\n \"now that we had all this infrastructure depending on it. So now my\\n\",\n \"\\n\",\n \"three projects were reduced to two: writing essays and working on\\n\",\n \"\\n\",\n \"YC.YC was different from other kinds of work I've done. Instead of\\n\",\n \"\\n\",\n \"deciding for myself what to work on, the problems came to me. Every\\n\",\n \"\\n\",\n \"6 months there was a new batch of startups, and their problems,\\n\",\n \"\\n\",\n \"whatever they were, became our problems. It was very engaging work,\\n\",\n \"\\n\",\n \"because their problems were quite varied, and the good founders\\n\",\n \"\\n\",\n \"were very effective. If you were trying to learn the most you could\\n\",\n \"\\n\",\n \"about startups in the shortest possible time, you couldn't have\\n\",\n \"\\n\",\n \"picked a better way to do it.There were parts of the job I didn't like. Disputes between cofounders,\\n\",\n \"\\n\",\n \"figuring out when people were lying to us, fighting with people who\\n\",\n \"\\n\",\n \"maltreated the startups, and so on. But I worked hard even at the\\n\",\n \"\\n\",\n \"parts I didn't like. I was haunted by something Kevin Hale once\\n\",\n \"\\n\",\n \"said about companies: \\\"No one works harder than the boss.\\\" He meant\\n\",\n \"\\n\",\n \"it both descriptively and prescriptively, and it was the second\\n\",\n \"\\n\",\n \"part that scared me. I wanted YC to be good, so if how hard I worked\\n\",\n \"\\n\",\n \"set the upper bound on how hard everyone else worked, I'd better\\n\",\n \"\\n\",\n \"work very hard.One day in 2010, when he was visiting California for interviews,\\n\",\n \"\\n\",\n \"Robert Morris did something astonishing: he offered me unsolicited\\n\",\n \"\\n\",\n \"advice. I can only remember him doing that once before. One day at\\n\",\n \"\\n\",\n \"Viaweb, when I was bent over double from a kidney stone, he suggested\\n\",\n \"\\n\",\n \"that it would be a good idea for him to take me to the hospital.\\n\",\n \"\\n\",\n \"That was what it took for Rtm to offer unsolicited advice. So I\\n\",\n \"\\n\",\n \"remember his exact words very clearly. \\\"You know,\\\" he said, \\\"you\\n\",\n \"\\n\",\n \"should make sure Y Combinator isn't the last cool thing you do.\\\"At the time I didn't understand what he meant, but gradually it\\n\",\n \"\\n\",\n \"dawned on me that he was saying I should quit. This seemed strange\\n\",\n \"\\n\",\n \"advice, because YC was doing great. But if there was one thing rarer\\n\",\n \"\\n\",\n \"than Rtm offering advice, it was Rtm being wrong. So this set me\\n\",\n \"\\n\",\n \"thinking. It was true that on my current trajectory, YC would be\\n\",\n \"\\n\",\n \"the last thing I did, because it was only taking up more of my\\n\",\n \"\\n\",\n \"attention. It had already eaten Arc, and was in the process of\\n\",\n \"\\n\",\n \"eating essays too. Either YC was my life's work or I'd have to leave\\n\",\n \"\\n\",\n \"eventually. And it wasn't, so I would.In the summer of 2012 my mother had a stroke, and the cause turned\\n\",\n \"\\n\",\n \"out to be a blood clot caused by colon cancer. The stroke destroyed\\n\",\n \"\\n\",\n \"her balance, and she was put in a nursing home, but she really\\n\",\n \"\\n\",\n \"wanted to get out of it and back to her house, and my sister and I\\n\",\n \"\\n\",\n \"were determined to help her do it. I used to fly up to Oregon to\\n\",\n \"\\n\",\n \"visit her regularly, and I had a lot of time to think on those\\n\",\n \"\\n\",\n \"flights. On one of them I realized I was ready to hand YC over to\\n\",\n \"\\n\",\n \"someone else.I asked Jessica if she wanted to be president, but she didn't, so\\n\",\n \"\\n\",\n \"we decided we'd try to recruit Sam Altman. We talked to Robert and\\n\",\n \"\\n\",\n \"Trevor and we agreed to make it a complete changing of the guard.\\n\",\n \"\\n\",\n \"Up till that point YC had been controlled by the original LLC we\\n\",\n \"\\n\",\n \"four had started. But we wanted YC to last for a long time, and to\\n\",\n \"\\n\",\n \"do that it couldn't be controlled by the founders. So if Sam said\\n\",\n \"\\n\",\n \"yes, we'd let him reorganize YC. Robert and I would retire, and\\n\",\n \"\\n\",\n \"Jessica and Trevor would become ordinary partners.When we asked Sam if he wanted to be president of YC, initially he\\n\",\n \"\\n\",\n \"said no. He wanted to start a startup to make nuclear reactors.\\n\",\n \"\\n\",\n \"But I kept at it, and in October 2013 he finally agreed. We decided\\n\",\n \"\\n\",\n \"he'd take over starting with the winter 2014 batch. For the rest\\n\",\n \"\\n\",\n \"of 2013 I left running YC more and more to Sam, partly so he could\\n\",\n \"\\n\",\n \"learn the job, and partly because I was focused on my mother, whose\\n\",\n \"\\n\",\n \"cancer had returned.She died on January 15, 2014. We knew this was coming, but it was\\n\",\n \"\\n\",\n \"still hard when it did.I kept working on YC till March, to help get that batch of startups\\n\",\n \"\\n\",\n \"through Demo Day, then I checked out pretty completely. (I still\\n\",\n \"\\n\",\n \"talk to alumni and to new startups working on things I'm interested\\n\",\n \"\\n\",\n \"in, but that only takes a few hours a week.)What should I do next? Rtm's advice hadn't included anything about\\n\",\n \"\\n\",\n \"that. I wanted to do something completely different, so I decided\\n\",\n \"\\n\",\n \"I'd paint. I wanted to see how good I could get if I really focused\\n\",\n \"\\n\",\n \"on it. So the day after I stopped working on YC, I started painting.\\n\",\n \"\\n\",\n \"I was rusty and it took a while to get back into shape, but it was\\n\",\n \"\\n\",\n \"at least completely engaging.\\n\",\n \"\\n\",\n \"[18]I spent most of the rest of 2014 painting. I'd never been able to\\n\",\n \"\\n\",\n \"work so uninterruptedly before, and I got to be better than I had\\n\",\n \"\\n\",\n \"been. Not good enough, but better. Then in November, right in the\\n\",\n \"\\n\",\n \"middle of a painting, I ran out of steam. Up till that point I'd\\n\",\n \"\\n\",\n \"always been curious to see how the painting I was working on would\\n\",\n \"\\n\",\n \"turn out, but suddenly finishing this one seemed like a chore. So\\n\",\n \"\\n\",\n \"I stopped working on it and cleaned my brushes and haven't painted\\n\",\n \"\\n\",\n \"since. So far anyway.I realize that sounds rather wimpy. But attention is a zero sum\\n\",\n \"\\n\",\n \"game. If you can choose what to work on, and you choose a project\\n\",\n \"\\n\",\n \"that's not the best one (or at least a good one) for you, then it's\\n\",\n \"\\n\",\n \"getting in the way of another project that is. And at 50 there was\\n\",\n \"\\n\",\n \"some opportunity cost to screwing around.I started writing essays again, and wrote a bunch of new ones over\\n\",\n \"\\n\",\n \"the next few months. I even wrote a couple that\\n\",\n \"\\n\",\n \"weren't about\\n\",\n \"\\n\",\n \"startups. Then in March 2015 I started working on Lisp again.The distinctive thing about Lisp is that its core is a language\\n\",\n \"\\n\",\n \"defined by writing an interpreter in itself. It wasn't originally\\n\",\n \"\\n\",\n \"intended as a programming language in the ordinary sense. It was\\n\",\n \"\\n\",\n \"meant to be a formal model of computation, an alternative to the\\n\",\n \"\\n\",\n \"Turing machine. If you want to write an interpreter for a language\\n\",\n \"\\n\",\n \"in itself, what's the minimum set of predefined operators you need?\\n\",\n \"\\n\",\n \"The Lisp that John McCarthy invented, or more accurately discovered,\\n\",\n \"\\n\",\n \"is an answer to that question.\\n\",\n \"\\n\",\n \"[19]McCarthy didn't realize this Lisp could even be used to program\\n\",\n \"\\n\",\n \"computers till his grad student Steve Russell suggested it. Russell\\n\",\n \"\\n\",\n \"translated McCarthy's interpreter into IBM 704 machine language,\\n\",\n \"\\n\",\n \"and from that point Lisp started also to be a programming language\\n\",\n \"\\n\",\n \"in the ordinary sense. But its origins as a model of computation\\n\",\n \"\\n\",\n \"gave it a power and elegance that other languages couldn't match.\\n\",\n \"\\n\",\n \"It was this that attracted me in college, though I didn't understand\\n\",\n \"\\n\",\n \"why at the time.McCarthy's 1960 Lisp did nothing more than interpret Lisp expressions.\\n\",\n \"\\n\",\n \"It was missing a lot of things you'd want in a programming language.\\n\",\n \"\\n\",\n \"So these had to be added, and when they were, they weren't defined\\n\",\n \"\\n\",\n \"using McCarthy's original axiomatic approach. That wouldn't have\\n\",\n \"\\n\",\n \"been feasible at the time. McCarthy tested his interpreter by\\n\",\n \"\\n\",\n \"hand-simulating the execution of programs. But it was already getting\\n\",\n \"\\n\",\n \"close to the limit of interpreters you could test that way — indeed,\\n\",\n \"\\n\",\n \"there was a bug in it that McCarthy had overlooked. To test a more\\n\",\n \"\\n\",\n \"complicated interpreter, you'd have had to run it, and computers\\n\",\n \"\\n\",\n \"then weren't powerful enough.Now they are, though. Now you could continue using McCarthy's\\n\",\n \"\\n\",\n \"axiomatic approach till you'd defined a complete programming language.\\n\",\n \"\\n\",\n \"And as long as every change you made to McCarthy's Lisp was a\\n\",\n \"\\n\",\n \"discoveredness-preserving transformation, you could, in principle,\\n\",\n \"\\n\",\n \"end up with a complete language that had this quality. Harder to\\n\",\n \"\\n\",\n \"do than to talk about, of course, but if it was possible in principle,\\n\",\n \"\\n\",\n \"why not try? So I decided to take a shot at it. It took 4 years,\\n\",\n \"\\n\",\n \"from March 26, 2015 to October 12, 2019. It was fortunate that I\\n\",\n \"\\n\",\n \"had a precisely defined goal, or it would have been hard to keep\\n\",\n \"\\n\",\n \"at it for so long.I wrote this new Lisp, called Bel,\\n\",\n \"\\n\",\n \"in itself in Arc. That may sound\\n\",\n \"\\n\",\n \"like a contradiction, but it's an indication of the sort of trickery\\n\",\n \"\\n\",\n \"I had to engage in to make this work. By means of an egregious\\n\",\n \"\\n\",\n \"collection of hacks I managed to make something close enough to an\\n\",\n \"\\n\",\n \"interpreter written in itself that could actually run. Not fast,\\n\",\n \"\\n\",\n \"but fast enough to test.I had to ban myself from writing essays during most of this time,\\n\",\n \"\\n\",\n \"or I'd never have finished. In late 2015 I spent 3 months writing\\n\",\n \"\\n\",\n \"essays, and when I went back to working on Bel I could barely\\n\",\n \"\\n\",\n \"understand the code. Not so much because it was badly written as\\n\",\n \"\\n\",\n \"because the problem is so convoluted. When you're working on an\\n\",\n \"\\n\",\n \"interpreter written in itself, it's hard to keep track of what's\\n\",\n \"\\n\",\n \"happening at what level, and errors can be practically encrypted\\n\",\n \"\\n\",\n \"by the time you get them.So I said no more essays till Bel was done. But I told few people\\n\",\n \"\\n\",\n \"about Bel while I was working on it. So for years it must have\\n\",\n \"\\n\",\n \"seemed that I was doing nothing, when in fact I was working harder\\n\",\n \"\\n\",\n \"than I'd ever worked on anything. Occasionally after wrestling for\\n\",\n \"\\n\",\n \"hours with some gruesome bug I'd check Twitter or HN and see someone\\n\",\n \"\\n\",\n \"asking \\\"Does Paul Graham still code?\\\"Working on Bel was hard but satisfying. I worked on it so intensively\\n\",\n \"\\n\",\n \"that at any given time I had a decent chunk of the code in my head\\n\",\n \"\\n\",\n \"and could write more there. I remember taking the boys to the\\n\",\n \"\\n\",\n \"coast on a sunny day in 2015 and figuring out how to deal with some\\n\",\n \"\\n\",\n \"problem involving continuations while I watched them play in the\\n\",\n \"\\n\",\n \"tide pools. It felt like I was doing life right. I remember that\\n\",\n \"\\n\",\n \"because I was slightly dismayed at how novel it felt. The good news\\n\",\n \"\\n\",\n \"is that I had more moments like this over the next few years.In the summer of 2016 we moved to England. We wanted our kids to\\n\",\n \"\\n\",\n \"see what it was like living in another country, and since I was a\\n\",\n \"\\n\",\n \"British citizen by birth, that seemed the obvious choice. We only\\n\",\n \"\\n\",\n \"meant to stay for a year, but we liked it so much that we still\\n\",\n \"\\n\",\n \"live there. So most of Bel was written in England.In the fall of 2019, Bel was finally finished. Like McCarthy's\\n\",\n \"\\n\",\n \"original Lisp, it's a spec rather than an implementation, although\\n\",\n \"\\n\",\n \"like McCarthy's Lisp it's a spec expressed as code.Now that I could write essays again, I wrote a bunch about topics\\n\",\n \"\\n\",\n \"I'd had stacked up. I kept writing essays through 2020, but I also\\n\",\n \"\\n\",\n \"started to think about other things I could work on. How should I\\n\",\n \"\\n\",\n \"choose what to do? Well, how had I chosen what to work on in the\\n\",\n \"\\n\",\n \"past? I wrote an essay for myself to answer that question, and I\\n\",\n \"\\n\",\n \"was surprised how long and messy the answer turned out to be. If\\n\",\n \"\\n\",\n \"this surprised me, who'd lived it, then I thought perhaps it would\\n\",\n \"\\n\",\n \"be interesting to other people, and encouraging to those with\\n\",\n \"\\n\",\n \"similarly messy lives. So I wrote a more detailed version for others\\n\",\n \"\\n\",\n \"to read, and this is the last sentence of it.\\n\",\n \"\\n\",\n \"Notes[1]\\n\",\n \"\\n\",\n \"My experience skipped a step in the evolution of computers:\\n\",\n \"\\n\",\n \"time-sharing machines with interactive OSes. I went straight from\\n\",\n \"\\n\",\n \"batch processing to microcomputers, which made microcomputers seem\\n\",\n \"\\n\",\n \"all the more exciting.[2]\\n\",\n \"\\n\",\n \"Italian words for abstract concepts can nearly always be\\n\",\n \"\\n\",\n \"predicted from their English cognates (except for occasional traps\\n\",\n \"\\n\",\n \"like polluzione). It's the everyday words that differ. So if you\\n\",\n \"\\n\",\n \"string together a lot of abstract concepts with a few simple verbs,\\n\",\n \"\\n\",\n \"you can make a little Italian go a long way.[3]\\n\",\n \"\\n\",\n \"I lived at Piazza San Felice 4, so my walk to the Accademia\\n\",\n \"\\n\",\n \"went straight down the spine of old Florence: past the Pitti, across\\n\",\n \"\\n\",\n \"the bridge, past Orsanmichele, between the Duomo and the Baptistery,\\n\",\n \"\\n\",\n \"and then up Via Ricasoli to Piazza San Marco. I saw Florence at\\n\",\n \"\\n\",\n \"street level in every possible condition, from empty dark winter\\n\",\n \"\\n\",\n \"evenings to sweltering summer days when the streets were packed with\\n\",\n \"\\n\",\n \"tourists.[4]\\n\",\n \"\\n\",\n \"You can of course paint people like still lives if you want\\n\",\n \"\\n\",\n \"to, and they're willing. That sort of portrait is arguably the apex\\n\",\n \"\\n\",\n \"of still life painting, though the long sitting does tend to produce\\n\",\n \"\\n\",\n \"pained expressions in the sitters.[5]\\n\",\n \"\\n\",\n \"Interleaf was one of many companies that had smart people and\\n\",\n \"\\n\",\n \"built impressive technology, and yet got crushed by Moore's Law.\\n\",\n \"\\n\",\n \"In the 1990s the exponential growth in the power of commodity (i.e.\\n\",\n \"\\n\",\n \"Intel) processors rolled up high-end, special-purpose hardware and\\n\",\n \"\\n\",\n \"software companies like a bulldozer.[6]\\n\",\n \"\\n\",\n \"The signature style seekers at RISD weren't specifically\\n\",\n \"\\n\",\n \"mercenary. In the art world, money and coolness are tightly coupled.\\n\",\n \"\\n\",\n \"Anything expensive comes to be seen as cool, and anything seen as\\n\",\n \"\\n\",\n \"cool will soon become equally expensive.[7]\\n\",\n \"\\n\",\n \"Technically the apartment wasn't rent-controlled but\\n\",\n \"\\n\",\n \"rent-stabilized, but this is a refinement only New Yorkers would\\n\",\n \"\\n\",\n \"know or care about. The point is that it was really cheap, less\\n\",\n \"\\n\",\n \"than half market price.[8]\\n\",\n \"\\n\",\n \"Most software you can launch as soon as it's done. But when\\n\",\n \"\\n\",\n \"the software is an online store builder and you're hosting the\\n\",\n \"\\n\",\n \"stores, if you don't have any users yet, that fact will be painfully\\n\",\n \"\\n\",\n \"obvious. So before we could launch publicly we had to launch\\n\",\n \"\\n\",\n \"privately, in the sense of recruiting an initial set of users and\\n\",\n \"\\n\",\n \"making sure they had decent-looking stores.[9]\\n\",\n \"\\n\",\n \"We'd had a code editor in Viaweb for users to define their\\n\",\n \"\\n\",\n \"own page styles. They didn't know it, but they were editing Lisp\\n\",\n \"\\n\",\n \"expressions underneath. But this wasn't an app editor, because the\\n\",\n \"\\n\",\n \"code ran when the merchants' sites were generated, not when shoppers\\n\",\n \"\\n\",\n \"visited them.[10]\\n\",\n \"\\n\",\n \"This was the first instance of what is now a familiar experience,\\n\",\n \"\\n\",\n \"and so was what happened next, when I read the comments and found\\n\",\n \"\\n\",\n \"they were full of angry people. How could I claim that Lisp was\\n\",\n \"\\n\",\n \"better than other languages? Weren't they all Turing complete?\\n\",\n \"\\n\",\n \"People who see the responses to essays I write sometimes tell me\\n\",\n \"\\n\",\n \"how sorry they feel for me, but I'm not exaggerating when I reply\\n\",\n \"\\n\",\n \"that it has always been like this, since the very beginning. It\\n\",\n \"\\n\",\n \"comes with the territory. An essay must tell readers things they\\n\",\n \"\\n\",\n \"don't already know, and some\\n\",\n \"\\n\",\n \"people dislike being told such things.[11]\\n\",\n \"\\n\",\n \"People put plenty of stuff on the internet in the 90s of\\n\",\n \"\\n\",\n \"course, but putting something online is not the same as publishing\\n\",\n \"\\n\",\n \"it online. Publishing online means you treat the online version as\\n\",\n \"\\n\",\n \"the (or at least a) primary version.[12]\\n\",\n \"\\n\",\n \"There is a general lesson here that our experience with Y\\n\",\n \"\\n\",\n \"Combinator also teaches: Customs continue to constrain you long\\n\",\n \"\\n\",\n \"after the restrictions that caused them have disappeared. Customary\\n\",\n \"\\n\",\n \"VC practice had once, like the customs about publishing essays,\\n\",\n \"\\n\",\n \"been based on real constraints. Startups had once been much more\\n\",\n \"\\n\",\n \"expensive to start, and proportionally rare. Now they could be cheap\\n\",\n \"\\n\",\n \"and common, but the VCs' customs still reflected the old world,\\n\",\n \"\\n\",\n \"just as customs about writing essays still reflected the constraints\\n\",\n \"\\n\",\n \"of the print era.Which in turn implies that people who are independent-minded (i.e.\\n\",\n \"\\n\",\n \"less influenced by custom) will have an advantage in fields affected\\n\",\n \"\\n\",\n \"by rapid change (where customs are more likely to be obsolete).Here's an interesting point, though: you can't always predict which\\n\",\n \"\\n\",\n \"fields will be affected by rapid change. Obviously software and\\n\",\n \"\\n\",\n \"venture capital will be, but who would have predicted that essay\\n\",\n \"\\n\",\n \"writing would be?[13]\\n\",\n \"\\n\",\n \"Y Combinator was not the original name. At first we were\\n\",\n \"\\n\",\n \"called Cambridge Seed. But we didn't want a regional name, in case\\n\",\n \"\\n\",\n \"someone copied us in Silicon Valley, so we renamed ourselves after\\n\",\n \"\\n\",\n \"one of the coolest tricks in the lambda calculus, the Y combinator.I picked orange as our color partly because it's the warmest, and\\n\",\n \"\\n\",\n \"partly because no VC used it. In 2005 all the VCs used staid colors\\n\",\n \"\\n\",\n \"like maroon, navy blue, and forest green, because they were trying\\n\",\n \"\\n\",\n \"to appeal to LPs, not founders. The YC logo itself is an inside\\n\",\n \"\\n\",\n \"joke: the Viaweb logo had been a white V on a red circle, so I made\\n\",\n \"\\n\",\n \"the YC logo a white Y on an orange square.[14]\\n\",\n \"\\n\",\n \"YC did become a fund for a couple years starting in 2009,\\n\",\n \"\\n\",\n \"because it was getting so big I could no longer afford to fund it\\n\",\n \"\\n\",\n \"personally. But after Heroku got bought we had enough money to go\\n\",\n \"\\n\",\n \"back to being self-funded.[15]\\n\",\n \"\\n\",\n \"I've never liked the term \\\"deal flow,\\\" because it implies\\n\",\n \"\\n\",\n \"that the number of new startups at any given time is fixed. This\\n\",\n \"\\n\",\n \"is not only false, but it's the purpose of YC to falsify it, by\\n\",\n \"\\n\",\n \"causing startups to be founded that would not otherwise have existed.[16]\\n\",\n \"\\n\",\n \"She reports that they were all different shapes and sizes,\\n\",\n \"\\n\",\n \"because there was a run on air conditioners and she had to get\\n\",\n \"\\n\",\n \"whatever she could, but that they were all heavier than she could\\n\",\n \"\\n\",\n \"carry now.[17]\\n\",\n \"\\n\",\n \"Another problem with HN was a bizarre edge case that occurs\\n\",\n \"\\n\",\n \"when you both write essays and run a forum. When you run a forum,\\n\",\n \"\\n\",\n \"you're assumed to see if not every conversation, at least every\\n\",\n \"\\n\",\n \"conversation involving you. And when you write essays, people post\\n\",\n \"\\n\",\n \"highly imaginative misinterpretations of them on forums. Individually\\n\",\n \"\\n\",\n \"these two phenomena are tedious but bearable, but the combination\\n\",\n \"\\n\",\n \"is disastrous. You actually have to respond to the misinterpretations,\\n\",\n \"\\n\",\n \"because the assumption that you're present in the conversation means\\n\",\n \"\\n\",\n \"that not responding to any sufficiently upvoted misinterpretation\\n\",\n \"\\n\",\n \"reads as a tacit admission that it's correct. But that in turn\\n\",\n \"\\n\",\n \"encourages more; anyone who wants to pick a fight with you senses\\n\",\n \"\\n\",\n \"that now is their chance.[18]\\n\",\n \"\\n\",\n \"The worst thing about leaving YC was not working with Jessica\\n\",\n \"\\n\",\n \"anymore. We'd been working on YC almost the whole time we'd known\\n\",\n \"\\n\",\n \"each other, and we'd neither tried nor wanted to separate it from\\n\",\n \"\\n\",\n \"our personal lives, so leaving was like pulling up a deeply rooted\\n\",\n \"\\n\",\n \"tree.[19]\\n\",\n \"\\n\",\n \"One way to get more precise about the concept of invented vs\\n\",\n \"\\n\",\n \"discovered is to talk about space aliens. Any sufficiently advanced\\n\",\n \"\\n\",\n \"alien civilization would certainly know about the Pythagorean\\n\",\n \"\\n\",\n \"theorem, for example. I believe, though with less certainty, that\\n\",\n \"\\n\",\n \"they would also know about the Lisp in McCarthy's 1960 paper.But if so there's no reason to suppose that this is the limit of\\n\",\n \"\\n\",\n \"the language that might be known to them. Presumably aliens need\\n\",\n \"\\n\",\n \"numbers and errors and I/O too. So it seems likely there exists at\\n\",\n \"\\n\",\n \"least one path out of McCarthy's Lisp along which discoveredness\\n\",\n \"\\n\",\n \"is preserved.Thanks to Trevor Blackwell, John Collison, Patrick Collison, Daniel\\n\",\n \"\\n\",\n \"Gackle, Ralph Hazell, Jessica Livingston, Robert Morris, and Harj\\n\",\n \"\\n\",\n \"Taggar for reading drafts of this.\\\"\\n\",\n \"\\n\",\n \"\\n\",\n \"CONCISE SUMMARY:\\u001b[0m\\n\"\n ]\n },\n {\n \"ename\": \"InvalidRequestError\",\n \"evalue\": \"This model's maximum context length is 4097 tokens, however you requested 19068 tokens (18812 in your prompt; 256 for the completion). Please reduce your prompt; or completion length.\",\n \"output_type\": \"error\",\n \"traceback\": [\n \"\\u001b[0;31m---------------------------------------------------------------------------\\u001b[0m\",\n \"\\u001b[0;31mInvalidRequestError\\u001b[0m Traceback (most recent call last)\",\n \"\\u001b[0;32m/var/folders/5c/csjfqsk97xz704h7v3fzjqph0000gn/T/ipykernel_4303/3610895313.py\\u001b[0m in \\u001b[0;36m\\u001b[0;34m\\u001b[0m\\n\\u001b[0;32m----> 1\\u001b[0;31m \\u001b[0mchain\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0mrun\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0mlg_doc\\u001b[0m\\u001b[0;34m)\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0m\",\n \"\\u001b[0;32m~/opt/anaconda3/lib/python3.9/site-packages/langchain/chains/base.py\\u001b[0m in \\u001b[0;36mrun\\u001b[0;34m(self, *args, **kwargs)\\u001b[0m\\n\\u001b[1;32m 237\\u001b[0m \\u001b[0;32mif\\u001b[0m \\u001b[0mlen\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0margs\\u001b[0m\\u001b[0;34m)\\u001b[0m \\u001b[0;34m!=\\u001b[0m \\u001b[0;36m1\\u001b[0m\\u001b[0;34m:\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[1;32m 238\\u001b[0m \\u001b[0;32mraise\\u001b[0m \\u001b[0mValueError\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0;34m\\\"`run` supports only one positional argument.\\\"\\u001b[0m\\u001b[0;34m)\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0;32m--> 239\\u001b[0;31m \\u001b[0;32mreturn\\u001b[0m \\u001b[0mself\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0margs\\u001b[0m\\u001b[0;34m[\\u001b[0m\\u001b[0;36m0\\u001b[0m\\u001b[0;34m]\\u001b[0m\\u001b[0;34m)\\u001b[0m\\u001b[0;34m[\\u001b[0m\\u001b[0mself\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0moutput_keys\\u001b[0m\\u001b[0;34m[\\u001b[0m\\u001b[0;36m0\\u001b[0m\\u001b[0;34m]\\u001b[0m\\u001b[0;34m]\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0m\\u001b[1;32m 240\\u001b[0m \\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[1;32m 241\\u001b[0m \\u001b[0;32mif\\u001b[0m \\u001b[0mkwargs\\u001b[0m \\u001b[0;32mand\\u001b[0m \\u001b[0;32mnot\\u001b[0m \\u001b[0margs\\u001b[0m\\u001b[0;34m:\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\",\n \"\\u001b[0;32m~/opt/anaconda3/lib/python3.9/site-packages/langchain/chains/base.py\\u001b[0m in \\u001b[0;36m__call__\\u001b[0;34m(self, inputs, return_only_outputs)\\u001b[0m\\n\\u001b[1;32m 140\\u001b[0m \\u001b[0;32mexcept\\u001b[0m \\u001b[0;34m(\\u001b[0m\\u001b[0mKeyboardInterrupt\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0mException\\u001b[0m\\u001b[0;34m)\\u001b[0m \\u001b[0;32mas\\u001b[0m \\u001b[0me\\u001b[0m\\u001b[0;34m:\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[1;32m 141\\u001b[0m \\u001b[0mself\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0mcallback_manager\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0mon_chain_error\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0me\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0mverbose\\u001b[0m\\u001b[0;34m=\\u001b[0m\\u001b[0mself\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0mverbose\\u001b[0m\\u001b[0;34m)\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0;32m--> 142\\u001b[0;31m \\u001b[0;32mraise\\u001b[0m \\u001b[0me\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0m\\u001b[1;32m 143\\u001b[0m \\u001b[0mself\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0mcallback_manager\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0mon_chain_end\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0moutputs\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0mverbose\\u001b[0m\\u001b[0;34m=\\u001b[0m\\u001b[0mself\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0mverbose\\u001b[0m\\u001b[0;34m)\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[1;32m 144\\u001b[0m \\u001b[0;32mreturn\\u001b[0m \\u001b[0mself\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0mprep_outputs\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0minputs\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0moutputs\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0mreturn_only_outputs\\u001b[0m\\u001b[0;34m)\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\",\n \"\\u001b[0;32m~/opt/anaconda3/lib/python3.9/site-packages/langchain/chains/base.py\\u001b[0m in \\u001b[0;36m__call__\\u001b[0;34m(self, inputs, return_only_outputs)\\u001b[0m\\n\\u001b[1;32m 137\\u001b[0m )\\n\\u001b[1;32m 138\\u001b[0m \\u001b[0;32mtry\\u001b[0m\\u001b[0;34m:\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0;32m--> 139\\u001b[0;31m \\u001b[0moutputs\\u001b[0m \\u001b[0;34m=\\u001b[0m \\u001b[0mself\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0m_call\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0minputs\\u001b[0m\\u001b[0;34m)\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0m\\u001b[1;32m 140\\u001b[0m \\u001b[0;32mexcept\\u001b[0m \\u001b[0;34m(\\u001b[0m\\u001b[0mKeyboardInterrupt\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0mException\\u001b[0m\\u001b[0;34m)\\u001b[0m \\u001b[0;32mas\\u001b[0m \\u001b[0me\\u001b[0m\\u001b[0;34m:\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[1;32m 141\\u001b[0m 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\\u001b[0mk\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0mv\\u001b[0m \\u001b[0;32min\\u001b[0m \\u001b[0minputs\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0mitems\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0;34m)\\u001b[0m \\u001b[0;32mif\\u001b[0m \\u001b[0mk\\u001b[0m \\u001b[0;34m!=\\u001b[0m \\u001b[0mself\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0minput_key\\u001b[0m\\u001b[0;34m}\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0;32m---> 56\\u001b[0;31m \\u001b[0moutput\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0mextra_return_dict\\u001b[0m \\u001b[0;34m=\\u001b[0m \\u001b[0mself\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0mcombine_docs\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0mdocs\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0;34m**\\u001b[0m\\u001b[0mother_keys\\u001b[0m\\u001b[0;34m)\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0m\\u001b[1;32m 57\\u001b[0m \\u001b[0mextra_return_dict\\u001b[0m\\u001b[0;34m[\\u001b[0m\\u001b[0mself\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0moutput_key\\u001b[0m\\u001b[0;34m]\\u001b[0m \\u001b[0;34m=\\u001b[0m \\u001b[0moutput\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[1;32m 58\\u001b[0m \\u001b[0;32mreturn\\u001b[0m \\u001b[0mextra_return_dict\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\",\n \"\\u001b[0;32m~/opt/anaconda3/lib/python3.9/site-packages/langchain/chains/combine_documents/stuff.py\\u001b[0m in \\u001b[0;36mcombine_docs\\u001b[0;34m(self, docs, **kwargs)\\u001b[0m\\n\\u001b[1;32m 87\\u001b[0m \\u001b[0minputs\\u001b[0m \\u001b[0;34m=\\u001b[0m \\u001b[0mself\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0m_get_inputs\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0mdocs\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0;34m**\\u001b[0m\\u001b[0mkwargs\\u001b[0m\\u001b[0;34m)\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[1;32m 88\\u001b[0m \\u001b[0;31m# Call predict on the LLM.\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0;32m---> 89\\u001b[0;31m \\u001b[0;32mreturn\\u001b[0m \\u001b[0mself\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0mllm_chain\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0mpredict\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0;34m**\\u001b[0m\\u001b[0minputs\\u001b[0m\\u001b[0;34m)\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0;34m{\\u001b[0m\\u001b[0;34m}\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0m\\u001b[1;32m 90\\u001b[0m \\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[1;32m 91\\u001b[0m async def acombine_docs(\\n\",\n \"\\u001b[0;32m~/opt/anaconda3/lib/python3.9/site-packages/langchain/chains/llm.py\\u001b[0m in \\u001b[0;36mpredict\\u001b[0;34m(self, **kwargs)\\u001b[0m\\n\\u001b[1;32m 151\\u001b[0m \\u001b[0mcompletion\\u001b[0m \\u001b[0;34m=\\u001b[0m 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\\u001b[0mfn\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0;34m*\\u001b[0m\\u001b[0margs\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0;34m**\\u001b[0m\\u001b[0mkwargs\\u001b[0m\\u001b[0;34m)\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0m\\u001b[1;32m 383\\u001b[0m \\u001b[0;32mexcept\\u001b[0m \\u001b[0mBaseException\\u001b[0m\\u001b[0;34m:\\u001b[0m \\u001b[0;31m# noqa: B902\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[1;32m 384\\u001b[0m \\u001b[0mretry_state\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0mset_exception\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0msys\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0mexc_info\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0;34m)\\u001b[0m\\u001b[0;34m)\\u001b[0m \\u001b[0;31m# type: ignore[arg-type]\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\",\n \"\\u001b[0;32m~/opt/anaconda3/lib/python3.9/site-packages/langchain/llms/openai.py\\u001b[0m in \\u001b[0;36m_completion_with_retry\\u001b[0;34m(**kwargs)\\u001b[0m\\n\\u001b[1;32m 202\\u001b[0m \\u001b[0;34m@\\u001b[0m\\u001b[0mretry_decorator\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[1;32m 203\\u001b[0m \\u001b[0;32mdef\\u001b[0m \\u001b[0m_completion_with_retry\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0;34m**\\u001b[0m\\u001b[0mkwargs\\u001b[0m\\u001b[0;34m:\\u001b[0m \\u001b[0mAny\\u001b[0m\\u001b[0;34m)\\u001b[0m \\u001b[0;34m->\\u001b[0m \\u001b[0mAny\\u001b[0m\\u001b[0;34m:\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0;32m--> 204\\u001b[0;31m \\u001b[0;32mreturn\\u001b[0m \\u001b[0mself\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0mclient\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0mcreate\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0;34m**\\u001b[0m\\u001b[0mkwargs\\u001b[0m\\u001b[0;34m)\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0m\\u001b[1;32m 205\\u001b[0m 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headers, files, stream, request_id, request_timeout)\\u001b[0m\\n\\u001b[1;32m 225\\u001b[0m \\u001b[0mrequest_timeout\\u001b[0m\\u001b[0;34m=\\u001b[0m\\u001b[0mrequest_timeout\\u001b[0m\\u001b[0;34m,\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[1;32m 226\\u001b[0m )\\n\\u001b[0;32m--> 227\\u001b[0;31m \\u001b[0mresp\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0mgot_stream\\u001b[0m \\u001b[0;34m=\\u001b[0m \\u001b[0mself\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0m_interpret_response\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0mresult\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0mstream\\u001b[0m\\u001b[0;34m)\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0m\\u001b[1;32m 228\\u001b[0m \\u001b[0;32mreturn\\u001b[0m \\u001b[0mresp\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0mgot_stream\\u001b[0m\\u001b[0;34m,\\u001b[0m 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\\u001b[0mresult\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0mstatus_code\\u001b[0m\\u001b[0;34m,\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\",\n \"\\u001b[0;32m~/opt/anaconda3/lib/python3.9/site-packages/openai/api_requestor.py\\u001b[0m in \\u001b[0;36m_interpret_response_line\\u001b[0;34m(self, rbody, rcode, rheaders, stream)\\u001b[0m\\n\\u001b[1;32m 678\\u001b[0m \\u001b[0mstream_error\\u001b[0m \\u001b[0;34m=\\u001b[0m \\u001b[0mstream\\u001b[0m \\u001b[0;32mand\\u001b[0m \\u001b[0;34m\\\"error\\\"\\u001b[0m \\u001b[0;32min\\u001b[0m \\u001b[0mresp\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0mdata\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[1;32m 679\\u001b[0m \\u001b[0;32mif\\u001b[0m \\u001b[0mstream_error\\u001b[0m \\u001b[0;32mor\\u001b[0m \\u001b[0;32mnot\\u001b[0m \\u001b[0;36m200\\u001b[0m \\u001b[0;34m<=\\u001b[0m \\u001b[0mrcode\\u001b[0m \\u001b[0;34m<\\u001b[0m \\u001b[0;36m300\\u001b[0m\\u001b[0;34m:\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0;32m--> 680\\u001b[0;31m raise self.handle_error_response(\\n\\u001b[0m\\u001b[1;32m 681\\u001b[0m \\u001b[0mrbody\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0mrcode\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0mresp\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0mdata\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0mrheaders\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0mstream_error\\u001b[0m\\u001b[0;34m=\\u001b[0m\\u001b[0mstream_error\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[1;32m 682\\u001b[0m )\\n\",\n \"\\u001b[0;31mInvalidRequestError\\u001b[0m: This model's maximum context length is 4097 tokens, however you requested 19068 tokens (18812 in your prompt; 256 for the completion). Please reduce your prompt; or completion length.\"\n ]\n }\n ],\n \"source\": [\n \"chain.run(lg_doc)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"c7bc1482\",\n \"metadata\": {},\n \"source\": [\n \"### Summarize: Map Reduce\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 12,\n \"id\": \"6819d5c1\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"chain = load_summarize_chain(llm, chain_type=\\\"map_reduce\\\", verbose=True)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 13,\n \"id\": \"57ad190a\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"\\n\",\n \"\\n\",\n \"\\u001b[1m> Entering new MapReduceDocumentsChain chain...\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3mWrite a concise summary of the following:\\n\",\n \"\\n\",\n \"\\n\",\n \"\\\"The winter glory of the Sierra ! How little is known of it! Californians admire descriptions of the Swiss Alps, reading with breathless interest how ice and snow load their sublime heights, and booming avalanches sweep in glorious array through their crowded forests, while our own icy, snow-laden mountains, with their unrivaled forests, loom unnoticed along our eastern horizon. True, only mountaineers may penetrate their snow-blocked fastnesses to behold them in all their white wild grandeur, but to every healthy man and woman, and even to children, many of the subalpine valleys and lake-basins, six or seven thousand feet above the sea, remain invitingly open and approachable all winter. With a friend and his two little sons I have just returned from a week of bracing weathering around Lake Tahoe, in which we enjoyed glorious views of winter, fine rolling and sliding in the snow, swimming in the icy lake, and lusty reviving exercise on snow-shoes that kept our pulses dancing right merrily. All the weather was hearty and exhilarating, though varying almost from hour to hour: snowing, blowing, clear and cloudy, but never rigorously cold.\\n\",\n \"\\n\",\n \"This winter has been remarkably mild, the mercury having seldom made a very near approach to zero, even during the coldest nights around the lake, while the average noonday temperature was considerably above the freezing- point. The snow lies deep on the surrounding mountains and about the shores, solid white contrasting with the dark-blue water of the lake, while the forests and canons and the upper glacial fountain hollows are well filled, assuring abundance of summer water for the lakes and streams.\\n\",\n \"\\n\",\n \"According to the record kept by Mr. McKinney, on the west shore of the lake, eight miles above Tahoe City, at an elevation of 6,500 feet above sea-level, the amount of snow, measured as it fell, was twenty-two feet and four inches for the season up to March 20th, with four inches of rain, while an inch or two more of rain and two or three feet of snow will probably fall before the full opening of spring. Last season the snowfall, measured by the same observer, at the same station, was only nine feet and seven inches, while the season before last it was no less than forty seven feet and six inches. The fall about Yosemite Valley, according to my own observations, usually considerably exceeded this. The greater portion of the snow that loads the main summits of the range falls in small crisp flakes and broken crystals; or when accompanied by strong winds at a low temperature, the crystals, instead of being locked together in tufted flakes, are driven against each other and broken into meal and fine dust which darkens the sky like night But down in the forested region, at about the elevation of Lake Tahoe, the greater portion comes gently to the ground, light and feathery, some of the flakes in mild weather being nearly an inch in diameter, and is evenly distributed and kept from drifting to any great extent by Lake Tahoe in Winter. 121 the shelter of the woods. Every tree is loaded with the fairy bloom, bending down the branches, and hushing the singing of the elastic needles. When the storm is over and the sun shines, the dazzling snow at once begins to settle and shift and fall off the trees in miniature avalanches; then the relieved branches spring up and shake themselves dry, and the whole green forest, fed and refreshed, waves and sings again rejoicing. The snow on the ground settles also, and thaws and freezes until it becomes coarsely granulated ice, with all trace of its crystalline snow structure destroyed. This is the present condition of most of the snow on the range. From towards midnight until midday at this time of year a man may walk firmly over the surface, as if on ice, provided the preceding day has been warm and the night frosty.\\n\",\n \"\\n\",\n \"The forested region up to an elevation of about eight thousand feet is generally clear of snow towards the end of May or middle of June; but now (March 28th) the higher canons are still heavily blocked, and the head tributaries of the rivers flow in dark tunnels beneath the icy mass. As warm summer advances, the roof of compacted snow falls in here and there, leaving magnificent arching bridges where it is strongest, over which one may safely ride a horse. All the upper streams are thus buried and bridged every winter, and are seldom completely opened to the light before the end of June or middle of July.\\n\",\n \"\\n\",\n \"Notwithstanding twenty-two feet of snow has fallen here this season, so greatly has it been melted and compacted, the present average depth at a height of 7,500 feet does not exceed seven feet. The drifts in exposed lake hollows and along the lee sides of bald ridges above the timberline are often fifty feet or more in depth, and many of the latter are grandly adorned with overcurling cornices, beneath which pale blue light shimmers with ineffable beauty. But it is in the fountain cirques of the ancient glaciers, beneath the shadows of the highest peaks, that the heaviest and most enduring deposits are stored up. For there the lavish snowfall on the steep converging slopes is shot down in avalanches during or after' every storm, heaping snow on snow to a depth of a hundred feet, or even more at times. These treasured banks are never wholly melted, however hot the summer, but with the few lingering glaciers form perennial fountains for the highest tributaries of the rivers.\\n\",\n \"\\n\",\n \"Few even among Californians have any fair conception of the marvelous abundance of glacier lakes hidden in the fastnesses of our mountains. The snow and some of the glaciers make a telling show, even from the distant lowlands; but not a single stream is visible, nor a hollow where one might hope to find a lake. Nevertheless, wild rivers are falling and sounding in every canon, and all their upper branches are fairly laden with lakes like orchard-trees with fruit. They nestle in rocky nooks and hollows about all the high peaks and in the larger canons, reflecting their stern, rugged beauty and giving charming animation to the bleakest and most forbidding landscapes. From the summit of Red Mountain, a day's journey to the east of Yosemite Valley, forty-two may be seen within a radius of eight or ten miles. The whole number in the Sierra can hardly be less than fifteen hundred, exclusive of the smaller gems, which are innumerable. Perhaps two-thirds of them lie on the west flank of the range, and all are restricted to the alpine and subalpine regions, those which once brightened the lower regions having long since vanished by the filling in of their basins. Lake Tahoe is king of them all, not only in size, but in the surpassing beauty of its shores and waters. It seems a kind of heaven to which the dead lakes of the lowlands had come with their best beauty spiritualized. It lies embosomed in mountains of moderate height near the northern extremity of the high portion of the Lake Tahoe in Winter. 123 range, between the main axis and a spur that puts out on the east side from near the head of the Carson River. Though it is twenty-one miles long by ten wide, and from about five hundred to sixteen hundred feet deep, its basin was once occupied by a glacier which filled it from the bottom to a point high above the present water-level, and being lavishly fed by the snows of the encompassing mountains, crawled slowly, like a mighty river, over the north rim of the basin, crushing and grinding the lower mountains that lay in its way, and it was only at the end of the ice period that this noble lake, at least in anything like its present form, came into existence.\\n\",\n \"\\n\",\n \"Excepting the forests that have sprung up around its shores, the post-glacial changes that have taken place are scarcely appreciable. The sediments carried forward by the inflowing streams at the head of the lake have made a few square miles of meadow-land, and the breaking through of a moraine dam in the canon of the outlet has lowered the lake considerably, leaving shore benches and lines on the rocky promontories to mark the original level. With these comparatively unimportant exceptions, the lake itself and all its grandly sculptured, ice-scored, and moraine-streaked basin exist to-day in just about the condition they presented when first they came to the light towards the close of the Glacial Period.\\n\",\n \"\\n\",\n \"The destructive action of man in clearing away the forests has not as yet effected any very marked change in general views. Perhaps about 150,000,000 feet of lumber for the Comstock mines has thus far been cut from the lake shores. But the business is being pushed so fervently from year to year, almost the entire basin must be stripped ere long of one of its most attractive features. One of the lumber companies at work here has contracted with mine owners to supply 36,000,000 feet of lumber and 60,000 cords of wood this season. It is estimated that the Tahoe basin still contains about 600,000,000 feet of lumber available for the mines.\\n\",\n \"\\n\",\n \"In summer the woods resound with the outlandish noise of loggers and choppers and screaming mills; skiffs and steamboats skim the lovely blue water in work and play; and ever and anon as you thread the groves along shore you come upon groups of gay tourists sauntering about, gathering flowers, or resting luxuriously in the rosiny shade of the pines, some in easy picnic attire, others all ribbons and colors, glaring wildly amid the green leaves and frightening the wondering squirrels and birds. But winter brings rest. At sight of the first snowflake pleasure-seekers flee as from a plague, the ax leaves the woods, and the kind snow heals every scar. Contemplating the basin from any commanding hilltop, only pale curls of smoke seen at wide intervals betoken the existence of human dwellings. Like the bears, the few settlers that remain here are silently \\\"holed up.\\\" The snow covers their cabins as if they were bowlders, and when approached only a narrow shoveled-out passage, or tunnel, is found leading to the door. Some of the more enterprising winter dwellers drift about in boats in calm weather, catching trout for the Carson market,—for the lake, on account of its great depth, never freezes. They thus earn from thirty to forty dollars a month, and at the same time get rid of lonely dullness. A trapper may also be seen now and then shuffling along the shore on long Norwegian snow-shoes in pursuit of minks, fishers, and otters.\\n\",\n \"\\n\",\n \"In this letter I intended only to say a good word for winter in the mountains, hoping to incite others to come and enjoy it, sketching our excursion to illustrate the ease and comfort with which such snowy winter rambles may be made; but I have written too much I fear about the snow to leave room for more than a thin outline. We went by rail to Lake Tahoe in Winter. 125 Carson, and from there set out by stage for Glenbrook. After ascending on wheels until we reached the snow-line, the driver attached his four horses to a sled, hoping thus to cross the summit, which is less than eight thousand feet high, without much difficulty. But mild weather had softened the snow, and the unfortunate animals, after floundering and wallowing through a mile of it, lay down exhausted with their heels in the air. Then we made our way on foot over to the lake. Next day, on a small steam-tug, we crossed the lake to McKinney's, on the west shore, where we were at home. Here we spent a few health-giving, delightful days, rowing, bathing, racing at lightning speed on snow-shoes down a mountain-side back of the house, and slipping about through the solemn, silent woods. Only the eldest of my companions ventured with me on the steep slopes. This was his first experience on snowshoes, and the several descents he made were the most remarkable specimens of falling locomotion that I ever had the fortune to witness. In shooting down steep declivities the long sled-runner-like shoes have to be kept parallel with firmly braced limbs. My friend, however, heedless of advice, launched himself in wild abandon, bouncing and diving, his limbs and shoes in chaotic entanglement, now in the snow, now in the air, whirling over and over in giddy rolls and somersaults that would shame the most extravagant performances of a circus acrobat. How original and inimitable he was! Wonderfully refreshing and exhilarating his queer capers must have been; for on coming to rest, with his runaway members divorced and lost, he would quietly gather himself, pick out the snow from his neck and ears, and say with preternatural solemnity, \\\"This, Muir, is the very poetry of motion.\\\"\\n\",\n \"\\n\",\n \"We also spent some rare evenings by the huge fire in McKinney's old cabin. The log walls are covered with trophies of the chase, for our host has been a great hunter in his day. Two live pet coons were frolicking on the floor while our grand old host smiled benignly and played with them, the firelight gleaming on his weathered face. How big he seems, thus brought into relief, and what a shadow he casts! The fragrant rosiny fire is the very god of the home. No wonder the old nations, with their fresher instincts, had their fireside gods. At last, when a mild snow-storm was blowing, we rowed to the lower end of the lake and completed our excursion by slipping on snow-shoes down the Truckee canon to the railroad.\\\"\\n\",\n \"\\n\",\n \"\\n\",\n \"CONCISE SUMMARY:\\u001b[0m\\n\"\n ]\n },\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"\\n\",\n \"\\n\",\n \"\\u001b[1m> Entering new LLMChain chain...\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3mWrite a concise summary of the following:\\n\",\n \"\\n\",\n \"\\n\",\n \"\\\" This article is an account of a winter excursion to Lake Tahoe in California, where the snowfall this season has been recorded at 22 feet and 4 inches. Despite the deep snow around the lake, the mild winter has kept temperatures above freezing. The post-glacial changes to the lake are minimal and the surrounding forests are still mostly intact, though logging has begun in earnest, with a contract for 96,000,000 feet of lumber and 60,000 cords of wood this season. The author recounts their adventures, including rowing, bathing, snow shoeing, and visits to old cabins. They ended the trip by snowshoeing down the Truckee canon to the railroad.\\\"\\n\",\n \"\\n\",\n \"\\n\",\n \"CONCISE SUMMARY:\\u001b[0m\\n\",\n \"\\n\",\n \"\\u001b[1m> Finished chain.\\u001b[0m\\n\",\n \"\\n\",\n \"\\u001b[1m> Finished chain.\\u001b[0m\\n\"\n ]\n },\n {\n \"data\": {\n \"text/plain\": [\n \"' This article is an account of a winter excursion to Lake Tahoe in California. Despite the deep snow, the temperatures have remained above freezing. Logging has begun in the surrounding forests, but the post-glacial changes to the lake are minimal. The author recounts their adventures, including rowing, bathing, snow shoeing, and visits to old cabins. They ended the trip by snowshoeing down the Truckee canon to the railroad.'\"\n ]\n },\n \"execution_count\": 13,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"chain.run(sm_doc)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 14,\n \"id\": \"4898d986\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain.text_splitter import RecursiveCharacterTextSplitter\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 15,\n \"id\": \"20a994e7\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"text_splitter = RecursiveCharacterTextSplitter(\\n\",\n \" # Set a really small chunk size, just to show.\\n\",\n \" chunk_size = 400,\\n\",\n \" chunk_overlap = 0\\n\",\n \")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 16,\n \"id\": \"877728d9\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"lg_docs = text_splitter.split_documents(lg_doc)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 17,\n \"id\": \"5ad8f7b3\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"You have 201 document(s)\\n\",\n \"You have roughly 12751 words in your docs\\n\",\n \"\\n\",\n \"Preview: \\n\",\n \"February 2021Before college the two main things I worked on, outside of school,\\n\",\n \"\\n\",\n \"were writing and programming\\n\"\n ]\n }\n ],\n \"source\": [\n \"doc_summary(lg_docs)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 18,\n \"id\": \"682900fc\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"\\n\",\n \"\\n\",\n \"\\u001b[1m> Entering new MapReduceDocumentsChain chain...\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3mWrite a concise summary of the following:\\n\",\n \"\\n\",\n \"\\n\",\n \"\\\"February 2021Before college the two main things I worked on, outside of school,\\n\",\n \"\\n\",\n \"were writing and programming. I didn't write essays. I wrote what\\n\",\n \"\\n\",\n \"beginning writers were supposed to write then, and probably still\\n\",\n \"\\n\",\n \"are: short stories. My stories were awful. They had hardly any plot,\\n\",\n \"\\n\",\n \"just characters with strong feelings, which I imagined made them\\\"\\n\",\n \"\\n\",\n \"\\n\",\n \"CONCISE SUMMARY:\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3mWrite a concise summary of the following:\\n\",\n \"\\n\",\n \"\\n\",\n \"\\\"deep.The first programs I tried writing were on the IBM 1401 that our\\n\",\n \"\\n\",\n \"school district used for what was then called \\\"data processing.\\\"\\n\",\n \"\\n\",\n \"This was in 9th grade, so I was 13 or 14. The school district's\\n\",\n \"\\n\",\n \"1401 happened to be in the basement of our junior high school, and\\n\",\n \"\\n\",\n \"my friend Rich Draves and I got permission to use it. It was like\\n\",\n \"\\n\",\n \"a mini Bond villain's lair down there, with all these alien-looking\\\"\\n\",\n \"\\n\",\n \"\\n\",\n \"CONCISE SUMMARY:\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3mWrite a concise summary of the following:\\n\",\n \"\\n\",\n \"\\n\",\n \"\\\"machines — CPU, disk drives, printer, card reader — sitting up\\n\",\n \"\\n\",\n \"on a raised floor under bright fluorescent lights.The language we used was an early version of Fortran. You had to\\n\",\n \"\\n\",\n \"type programs on punch cards, then stack them in the card reader\\n\",\n \"\\n\",\n \"and press a button to load the program into memory and run it. The\\n\",\n \"\\n\",\n \"result would ordinarily be to print something on the spectacularly\\\"\\n\",\n \"\\n\",\n \"\\n\",\n \"CONCISE SUMMARY:\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3mWrite a concise summary of the following:\\n\",\n \"\\n\",\n \"\\n\",\n \"\\\"loud printer.I was puzzled by the 1401. I couldn't figure out what to do with\\n\",\n \"\\n\",\n \"it. And in retrospect there's not much I could have done with it.\\n\",\n \"\\n\",\n \"The only form of input to programs was data stored on punched cards,\\n\",\n \"\\n\",\n \"and I didn't have any data stored on punched cards. The only other\\n\",\n \"\\n\",\n \"option was to do things that didn't rely on any input, like calculate\\\"\\n\",\n \"\\n\",\n \"\\n\",\n \"CONCISE SUMMARY:\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3mWrite a concise summary of the following:\\n\",\n \"\\n\",\n \"\\n\",\n \"\\\"approximations of pi, but I didn't know enough math to do anything\\n\",\n \"\\n\",\n \"interesting of that type. So I'm not surprised I can't remember any\\n\",\n \"\\n\",\n \"programs I wrote, because they can't have done much. My clearest\\n\",\n \"\\n\",\n \"memory is of the moment I learned it was possible for programs not\\n\",\n \"\\n\",\n \"to terminate, when one of mine didn't. On a machine without\\n\",\n \"\\n\",\n \"time-sharing, this was a social as well as a technical error, as\\\"\\n\",\n \"\\n\",\n \"\\n\",\n \"CONCISE SUMMARY:\\u001b[0m\\n\",\n \"\\n\",\n \"\\n\",\n \"\\u001b[1m> Entering new LLMChain chain...\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3mWrite a concise summary of the following:\\n\",\n \"\\n\",\n \"\\n\",\n \"\\\"\\n\",\n \"\\n\",\n \"The writer talks about their experience with writing and programming before starting college. They explain that they wrote short stories but found them to be lacking in plot, and instead containing characters with strong feelings.\\n\",\n \"\\n\",\n \" Rich Draves and the speaker, both 13 or 14 years old, obtained permission to use the IBM 1401 in the basement of their junior high school for \\\"data processing\\\", which was the speaker's first experience with programming. The environment was described as similar to a mini Bond villain's lair.\\n\",\n \"\\n\",\n \" This is a description of a computing environment in the early days of computers, where programs were written in Fortran and typed on punch cards. The machines were situated on a raised floor and lit by fluorescent lights, and pressing a button would load the programs into memory and run them, resulting in something being printed on a printer.\\n\",\n \"\\n\",\n \" The narrator was puzzled by the 1401, a type of printer, as they had no data stored on punched cards to use as input. The only thing they could do was perform calculations that didn't require any input.\\n\",\n \"\\n\",\n \" This person remembers the moment they learned that programs can not terminate and the moment of surprise when one of their programs didn't terminate. They also remember attempting to approximate pi with math, but they were not successful in doing anything interesting with it.\\\"\\n\",\n \"\\n\",\n \"\\n\",\n \"CONCISE SUMMARY:\\u001b[0m\\n\",\n \"\\n\",\n \"\\u001b[1m> Finished chain.\\u001b[0m\\n\",\n \"\\n\",\n \"\\u001b[1m> Finished chain.\\u001b[0m\\n\"\n ]\n },\n {\n \"data\": {\n \"text/plain\": [\n \"\\\" The speaker recounts their experience of programming with the IBM 1401 in their junior high school basement, which was their first time working with computers. They describe the environment as similar to a mini Bond villain's lair, and detail their attempts to program in Fortran and approximate pi with math. They also recall the moment they learned that programs can not terminate, and their surprise when one of their programs didn't.\\\"\"\n ]\n },\n \"execution_count\": 18,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"chain.run(lg_docs[:5])\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"a1b99505\",\n \"metadata\": {},\n \"source\": [\n \"### Summarize: Refine\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 19,\n \"id\": \"49b2dbfe\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"chain = load_summarize_chain(llm, chain_type=\\\"refine\\\", verbose=True)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 20,\n \"id\": \"efadaf1b\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"\\n\",\n \"\\n\",\n \"\\u001b[1m> Entering new RefineDocumentsChain chain...\\u001b[0m\\n\",\n \"\\n\",\n \"\\n\",\n \"\\u001b[1m> Entering new LLMChain chain...\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3mWrite a concise summary of the following:\\n\",\n \"\\n\",\n \"\\n\",\n \"\\\"February 2021Before college the two main things I worked on, outside of school,\\n\",\n \"\\n\",\n \"were writing and programming. I didn't write essays. I wrote what\\n\",\n \"\\n\",\n \"beginning writers were supposed to write then, and probably still\\n\",\n \"\\n\",\n \"are: short stories. My stories were awful. They had hardly any plot,\\n\",\n \"\\n\",\n \"just characters with strong feelings, which I imagined made them\\\"\\n\",\n \"\\n\",\n \"\\n\",\n \"CONCISE SUMMARY:\\u001b[0m\\n\",\n \"\\n\",\n \"\\u001b[1m> Finished chain.\\u001b[0m\\n\",\n \"\\n\",\n \"\\n\",\n \"\\u001b[1m> Entering new LLMChain chain...\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3mYour job is to produce a final summary\\n\",\n \"We have provided an existing summary up to a certain point: Prior to college, the author practiced writing and programming in their spare time. The author wrote short stories that lacked plot, but the characters did have strong emotions.\\n\",\n \"We have the opportunity to refine the existing summary(only if needed) with some more context below.\\n\",\n \"------------\\n\",\n \"deep.The first programs I tried writing were on the IBM 1401 that our\\n\",\n \"\\n\",\n \"school district used for what was then called \\\"data processing.\\\"\\n\",\n \"\\n\",\n \"This was in 9th grade, so I was 13 or 14. The school district's\\n\",\n \"\\n\",\n \"1401 happened to be in the basement of our junior high school, and\\n\",\n \"\\n\",\n \"my friend Rich Draves and I got permission to use it. It was like\\n\",\n \"\\n\",\n \"a mini Bond villain's lair down there, with all these alien-looking\\n\",\n \"------------\\n\",\n \"Given the new context, refine the original summaryIf the context isn't useful, return the original summary.\\u001b[0m\\n\",\n \"\\n\",\n \"\\u001b[1m> Finished chain.\\u001b[0m\\n\",\n \"\\n\",\n \"\\n\",\n \"\\u001b[1m> Entering new LLMChain chain...\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3mYour job is to produce a final summary\\n\",\n \"We have provided an existing summary up to a certain point: \\n\",\n \"\\n\",\n \"Prior to college, the author practiced writing and programming in their spare time. The author wrote short stories that lacked plot, but the characters did have strong emotions. In 9th grade, the author and a friend got permission to use an IBM 1401 in the basement of their junior high school for data processing. This experience exposed the author to programming and helped to develop their skills.\\n\",\n \"We have the opportunity to refine the existing summary(only if needed) with some more context below.\\n\",\n \"------------\\n\",\n \"machines — CPU, disk drives, printer, card reader — sitting up\\n\",\n \"\\n\",\n \"on a raised floor under bright fluorescent lights.The language we used was an early version of Fortran. You had to\\n\",\n \"\\n\",\n \"type programs on punch cards, then stack them in the card reader\\n\",\n \"\\n\",\n \"and press a button to load the program into memory and run it. The\\n\",\n \"\\n\",\n \"result would ordinarily be to print something on the spectacularly\\n\",\n \"------------\\n\",\n \"Given the new context, refine the original summaryIf the context isn't useful, return the original summary.\\u001b[0m\\n\",\n \"\\n\",\n \"\\u001b[1m> Finished chain.\\u001b[0m\\n\",\n \"\\n\",\n \"\\n\",\n \"\\u001b[1m> Entering new LLMChain chain...\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3mYour job is to produce a final summary\\n\",\n \"We have provided an existing summary up to a certain point: \\n\",\n \"\\n\",\n \"Prior to college, the author practiced writing and programming in their spare time. The author wrote short stories that lacked plot, but the characters did have strong emotions. In 9th grade, the author and a friend got permission to use an IBM 1401 in the basement of their junior high school for data processing. This experience exposed the author to programming and helped to develop their skills, using an early version of Fortran on machines such as CPU, disk drives, printer, card reader, and printing the results on the printer.\\n\",\n \"We have the opportunity to refine the existing summary(only if needed) with some more context below.\\n\",\n \"------------\\n\",\n \"loud printer.I was puzzled by the 1401. I couldn't figure out what to do with\\n\",\n \"\\n\",\n \"it. And in retrospect there's not much I could have done with it.\\n\",\n \"\\n\",\n \"The only form of input to programs was data stored on punched cards,\\n\",\n \"\\n\",\n \"and I didn't have any data stored on punched cards. The only other\\n\",\n \"\\n\",\n \"option was to do things that didn't rely on any input, like calculate\\n\",\n \"------------\\n\",\n \"Given the new context, refine the original summaryIf the context isn't useful, return the original summary.\\u001b[0m\\n\",\n \"\\n\",\n \"\\u001b[1m> Finished chain.\\u001b[0m\\n\",\n \"\\n\",\n \"\\n\",\n \"\\u001b[1m> Entering new LLMChain chain...\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3mYour job is to produce a final summary\\n\",\n \"We have provided an existing summary up to a certain point: \\n\",\n \"\\n\",\n \"Prior to college, the author practiced writing and programming in their spare time. The author wrote short stories that lacked plot, but the characters did have strong emotions. In 9th grade, the author and a friend got permission to use an IBM 1401 in the basement of their junior high school for data processing. This experience exposed the author to programming and helped to develop their skills, using an early version of Fortran on machines such as CPU, disk drives, printer, card reader, and printing the results on the printer. The author was initially puzzled by the 1401, as the only form of input to programs was data stored on punched cards, and they had no data stored on punched cards. As a result, the author had to do things that didn't rely on any input, like calculate, in order to use the machine.\\n\",\n \"We have the opportunity to refine the existing summary(only if needed) with some more context below.\\n\",\n \"------------\\n\",\n \"approximations of pi, but I didn't know enough math to do anything\\n\",\n \"\\n\",\n \"interesting of that type. So I'm not surprised I can't remember any\\n\",\n \"\\n\",\n \"programs I wrote, because they can't have done much. My clearest\\n\",\n \"\\n\",\n \"memory is of the moment I learned it was possible for programs not\\n\",\n \"\\n\",\n \"to terminate, when one of mine didn't. On a machine without\\n\",\n \"\\n\",\n \"time-sharing, this was a social as well as a technical error, as\\n\",\n \"------------\\n\",\n \"Given the new context, refine the original summaryIf the context isn't useful, return the original summary.\\u001b[0m\\n\",\n \"\\n\",\n \"\\u001b[1m> Finished chain.\\u001b[0m\\n\",\n \"\\n\",\n \"\\u001b[1m> Finished chain.\\u001b[0m\\n\"\n ]\n },\n {\n \"data\": {\n \"text/plain\": [\n \"\\\"\\\\n\\\\nPrior to college, the author practiced writing and programming in their spare time. The author wrote short stories that lacked plot, but the characters did have strong emotions. In 9th grade, the author and a friend got permission to use an IBM 1401 in the basement of their junior high school for data processing. This experience exposed the author to programming and helped to develop their skills, using an early version of Fortran on machines such as CPU, disk drives, printer, card reader, and printing the results on the printer. The author was initially puzzled by the 1401, as the only form of input to programs was data stored on punched cards, and they had no data stored on punched cards. As a result, the author had to do things that didn't rely on any input, like calculate approximations of pi, but they didn't know enough math to do anything interesting of that type. Despite this, they were able to learn that programs could fail to terminate, much to their surprise.\\\"\"\n ]\n },\n \"execution_count\": 20,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"chain.run(lg_docs[:5])\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"1c6962c2\",\n \"metadata\": {},\n \"source\": [\n \"### Q&A: Map Re-Rank\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 21,\n \"id\": \"ba864773\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"chain = load_qa_chain(llm, chain_type=\\\"map_rerank\\\", verbose=True, return_intermediate_steps=True)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 22,\n \"id\": \"6aa32765\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"\\n\",\n \"\\n\",\n \"\\u001b[1m> Entering new MapRerankDocumentsChain chain...\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3mUse the following pieces of context to answer the question at the end. If you don't know the answer, just say that you don't know, don't try to make up an answer.\\n\",\n \"\\n\",\n \"In addition to giving an answer, also return a score of how fully it answered the user's question. This should be in the following format:\\n\",\n \"\\n\",\n \"Question: [question here]\\n\",\n \"Helpful Answer: [answer here]\\n\",\n \"Score: [score between 0 and 100]\\n\",\n \"\\n\",\n \"How to determine the score:\\n\",\n \"- Higher is a better answer\\n\",\n \"- Better responds fully to the asked question, with sufficient level of detail\\n\",\n \"- If you do not know the answer based on the context, that should be a score of 0\\n\",\n \"- Don't be overconfident!\\n\",\n \"\\n\",\n \"Example #1\\n\",\n \"\\n\",\n \"Context:\\n\",\n \"---------\\n\",\n \"Apples are red\\n\",\n \"---------\\n\",\n \"Question: what color are apples?\\n\",\n \"Helpful Answer: red\\n\",\n \"Score: 100\\n\",\n \"\\n\",\n \"Example #2\\n\",\n \"\\n\",\n \"Context:\\n\",\n \"---------\\n\",\n \"it was night and the witness forgot his glasses. he was not sure if it was a sports car or an suv\\n\",\n \"---------\\n\",\n \"Question: what type was the car?\\n\",\n \"Helpful Answer: a sports car or an suv\\n\",\n \"Score: 60\\n\",\n \"\\n\",\n \"Example #3\\n\",\n \"\\n\",\n \"Context:\\n\",\n \"---------\\n\",\n \"Pears are either red or orange\\n\",\n \"---------\\n\",\n \"Question: what color are apples?\\n\",\n \"Helpful Answer: This document does not answer the question\\n\",\n \"Score: 0\\n\",\n \"\\n\",\n \"Begin!\\n\",\n \"\\n\",\n \"Context:\\n\",\n \"---------\\n\",\n \"February 2021Before college the two main things I worked on, outside of school,\\n\",\n \"\\n\",\n \"were writing and programming. I didn't write essays. I wrote what\\n\",\n \"\\n\",\n \"beginning writers were supposed to write then, and probably still\\n\",\n \"\\n\",\n \"are: short stories. My stories were awful. They had hardly any plot,\\n\",\n \"\\n\",\n \"just characters with strong feelings, which I imagined made them\\n\",\n \"---------\\n\",\n \"Question: Who was the authors friend who he got permission from to use the IBM 1401?\\n\",\n \"Helpful Answer:\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3mUse the following pieces of context to answer the question at the end. If you don't know the answer, just say that you don't know, don't try to make up an answer.\\n\",\n \"\\n\",\n \"In addition to giving an answer, also return a score of how fully it answered the user's question. This should be in the following format:\\n\",\n \"\\n\",\n \"Question: [question here]\\n\",\n \"Helpful Answer: [answer here]\\n\",\n \"Score: [score between 0 and 100]\\n\",\n \"\\n\",\n \"How to determine the score:\\n\",\n \"- Higher is a better answer\\n\",\n \"- Better responds fully to the asked question, with sufficient level of detail\\n\",\n \"- If you do not know the answer based on the context, that should be a score of 0\\n\",\n \"- Don't be overconfident!\\n\",\n \"\\n\",\n \"Example #1\\n\",\n \"\\n\",\n \"Context:\\n\",\n \"---------\\n\",\n \"Apples are red\\n\",\n \"---------\\n\",\n \"Question: what color are apples?\\n\",\n \"Helpful Answer: red\\n\",\n \"Score: 100\\n\",\n \"\\n\",\n \"Example #2\\n\",\n \"\\n\",\n \"Context:\\n\",\n \"---------\\n\",\n \"it was night and the witness forgot his glasses. he was not sure if it was a sports car or an suv\\n\",\n \"---------\\n\",\n \"Question: what type was the car?\\n\",\n \"Helpful Answer: a sports car or an suv\\n\",\n \"Score: 60\\n\",\n \"\\n\",\n \"Example #3\\n\",\n \"\\n\",\n \"Context:\\n\",\n \"---------\\n\",\n \"Pears are either red or orange\\n\",\n \"---------\\n\",\n \"Question: what color are apples?\\n\",\n \"Helpful Answer: This document does not answer the question\\n\",\n \"Score: 0\\n\",\n \"\\n\",\n \"Begin!\\n\",\n \"\\n\",\n \"Context:\\n\",\n \"---------\\n\",\n \"deep.The first programs I tried writing were on the IBM 1401 that our\\n\",\n \"\\n\",\n \"school district used for what was then called \\\"data processing.\\\"\\n\",\n \"\\n\",\n \"This was in 9th grade, so I was 13 or 14. The school district's\\n\",\n \"\\n\",\n \"1401 happened to be in the basement of our junior high school, and\\n\",\n \"\\n\",\n \"my friend Rich Draves and I got permission to use it. It was like\\n\",\n \"\\n\",\n \"a mini Bond villain's lair down there, with all these alien-looking\\n\",\n \"---------\\n\",\n \"Question: Who was the authors friend who he got permission from to use the IBM 1401?\\n\",\n \"Helpful Answer:\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3mUse the following pieces of context to answer the question at the end. If you don't know the answer, just say that you don't know, don't try to make up an answer.\\n\",\n \"\\n\",\n \"In addition to giving an answer, also return a score of how fully it answered the user's question. This should be in the following format:\\n\",\n \"\\n\",\n \"Question: [question here]\\n\",\n \"Helpful Answer: [answer here]\\n\",\n \"Score: [score between 0 and 100]\\n\",\n \"\\n\",\n \"How to determine the score:\\n\",\n \"- Higher is a better answer\\n\",\n \"- Better responds fully to the asked question, with sufficient level of detail\\n\",\n \"- If you do not know the answer based on the context, that should be a score of 0\\n\",\n \"- Don't be overconfident!\\n\",\n \"\\n\",\n \"Example #1\\n\",\n \"\\n\",\n \"Context:\\n\",\n \"---------\\n\",\n \"Apples are red\\n\",\n \"---------\\n\",\n \"Question: what color are apples?\\n\",\n \"Helpful Answer: red\\n\",\n \"Score: 100\\n\",\n \"\\n\",\n \"Example #2\\n\",\n \"\\n\",\n \"Context:\\n\",\n \"---------\\n\",\n \"it was night and the witness forgot his glasses. he was not sure if it was a sports car or an suv\\n\",\n \"---------\\n\",\n \"Question: what type was the car?\\n\",\n \"Helpful Answer: a sports car or an suv\\n\",\n \"Score: 60\\n\",\n \"\\n\",\n \"Example #3\\n\",\n \"\\n\",\n \"Context:\\n\",\n \"---------\\n\",\n \"Pears are either red or orange\\n\",\n \"---------\\n\",\n \"Question: what color are apples?\\n\",\n \"Helpful Answer: This document does not answer the question\\n\",\n \"Score: 0\\n\",\n \"\\n\",\n \"Begin!\\n\",\n \"\\n\",\n \"Context:\\n\",\n \"---------\\n\",\n \"machines — CPU, disk drives, printer, card reader — sitting up\\n\",\n \"\\n\",\n \"on a raised floor under bright fluorescent lights.The language we used was an early version of Fortran. You had to\\n\",\n \"\\n\",\n \"type programs on punch cards, then stack them in the card reader\\n\",\n \"\\n\",\n \"and press a button to load the program into memory and run it. The\\n\",\n \"\\n\",\n \"result would ordinarily be to print something on the spectacularly\\n\",\n \"---------\\n\",\n \"Question: Who was the authors friend who he got permission from to use the IBM 1401?\\n\",\n \"Helpful Answer:\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3mUse the following pieces of context to answer the question at the end. If you don't know the answer, just say that you don't know, don't try to make up an answer.\\n\",\n \"\\n\",\n \"In addition to giving an answer, also return a score of how fully it answered the user's question. This should be in the following format:\\n\",\n \"\\n\",\n \"Question: [question here]\\n\",\n \"Helpful Answer: [answer here]\\n\",\n \"Score: [score between 0 and 100]\\n\",\n \"\\n\",\n \"How to determine the score:\\n\",\n \"- Higher is a better answer\\n\",\n \"- Better responds fully to the asked question, with sufficient level of detail\\n\",\n \"- If you do not know the answer based on the context, that should be a score of 0\\n\",\n \"- Don't be overconfident!\\n\",\n \"\\n\",\n \"Example #1\\n\",\n \"\\n\",\n \"Context:\\n\",\n \"---------\\n\",\n \"Apples are red\\n\",\n \"---------\\n\",\n \"Question: what color are apples?\\n\",\n \"Helpful Answer: red\\n\",\n \"Score: 100\\n\",\n \"\\n\",\n \"Example #2\\n\",\n \"\\n\",\n \"Context:\\n\",\n \"---------\\n\",\n \"it was night and the witness forgot his glasses. he was not sure if it was a sports car or an suv\\n\",\n \"---------\\n\",\n \"Question: what type was the car?\\n\",\n \"Helpful Answer: a sports car or an suv\\n\",\n \"Score: 60\\n\",\n \"\\n\",\n \"Example #3\\n\",\n \"\\n\",\n \"Context:\\n\",\n \"---------\\n\",\n \"Pears are either red or orange\\n\",\n \"---------\\n\",\n \"Question: what color are apples?\\n\",\n \"Helpful Answer: This document does not answer the question\\n\",\n \"Score: 0\\n\",\n \"\\n\",\n \"Begin!\\n\",\n \"\\n\",\n \"Context:\\n\",\n \"---------\\n\",\n \"loud printer.I was puzzled by the 1401. I couldn't figure out what to do with\\n\",\n \"\\n\",\n \"it. And in retrospect there's not much I could have done with it.\\n\",\n \"\\n\",\n \"The only form of input to programs was data stored on punched cards,\\n\",\n \"\\n\",\n \"and I didn't have any data stored on punched cards. The only other\\n\",\n \"\\n\",\n \"option was to do things that didn't rely on any input, like calculate\\n\",\n \"---------\\n\",\n \"Question: Who was the authors friend who he got permission from to use the IBM 1401?\\n\",\n \"Helpful Answer:\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3mUse the following pieces of context to answer the question at the end. If you don't know the answer, just say that you don't know, don't try to make up an answer.\\n\",\n \"\\n\",\n \"In addition to giving an answer, also return a score of how fully it answered the user's question. This should be in the following format:\\n\",\n \"\\n\",\n \"Question: [question here]\\n\",\n \"Helpful Answer: [answer here]\\n\",\n \"Score: [score between 0 and 100]\\n\",\n \"\\n\",\n \"How to determine the score:\\n\",\n \"- Higher is a better answer\\n\",\n \"- Better responds fully to the asked question, with sufficient level of detail\\n\",\n \"- If you do not know the answer based on the context, that should be a score of 0\\n\",\n \"- Don't be overconfident!\\n\",\n \"\\n\",\n \"Example #1\\n\",\n \"\\n\",\n \"Context:\\n\",\n \"---------\\n\",\n \"Apples are red\\n\",\n \"---------\\n\",\n \"Question: what color are apples?\\n\",\n \"Helpful Answer: red\\n\",\n \"Score: 100\\n\",\n \"\\n\",\n \"Example #2\\n\",\n \"\\n\",\n \"Context:\\n\",\n \"---------\\n\",\n \"it was night and the witness forgot his glasses. he was not sure if it was a sports car or an suv\\n\",\n \"---------\\n\",\n \"Question: what type was the car?\\n\",\n \"Helpful Answer: a sports car or an suv\\n\",\n \"Score: 60\\n\",\n \"\\n\",\n \"Example #3\\n\",\n \"\\n\",\n \"Context:\\n\",\n \"---------\\n\",\n \"Pears are either red or orange\\n\",\n \"---------\\n\",\n \"Question: what color are apples?\\n\",\n \"Helpful Answer: This document does not answer the question\\n\",\n \"Score: 0\\n\",\n \"\\n\",\n \"Begin!\\n\",\n \"\\n\",\n \"Context:\\n\",\n \"---------\\n\",\n \"approximations of pi, but I didn't know enough math to do anything\\n\",\n \"\\n\",\n \"interesting of that type. So I'm not surprised I can't remember any\\n\",\n \"\\n\",\n \"programs I wrote, because they can't have done much. My clearest\\n\",\n \"\\n\",\n \"memory is of the moment I learned it was possible for programs not\\n\",\n \"\\n\",\n \"to terminate, when one of mine didn't. On a machine without\\n\",\n \"\\n\",\n \"time-sharing, this was a social as well as a technical error, as\\n\",\n \"---------\\n\",\n \"Question: Who was the authors friend who he got permission from to use the IBM 1401?\\n\",\n \"Helpful Answer:\\u001b[0m\\n\"\n ]\n },\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"\\n\",\n \"\\u001b[1m> Finished chain.\\u001b[0m\\n\"\n ]\n }\n ],\n \"source\": [\n \"query = \\\"Who was the authors friend who he got permission from to use the IBM 1401?\\\"\\n\",\n \"\\n\",\n \"result = chain({\\\"input_documents\\\": lg_docs[:5], \\\"question\\\": query}, return_only_outputs=True)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 23,\n \"id\": \"32ca3629\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"' Rich Draves'\"\n ]\n },\n \"execution_count\": 23,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"result['output_text']\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 24,\n \"id\": \"6541e14c\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"[{'answer': ' This document does not answer the question', 'score': '0'},\\n\",\n \" {'answer': ' Rich Draves', 'score': '100'},\\n\",\n \" {'answer': ' This document does not answer the question.', 'score': '0'},\\n\",\n \" {'answer': ' This document does not answer the question.', 'score': '0'},\\n\",\n \" {'answer': ' This document does not answer the question', 'score': '0'}]\"\n ]\n },\n \"execution_count\": 24,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"result['intermediate_steps']\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"id\": \"be60b4e8\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": []\n }\n ],\n \"metadata\": {\n \"kernelspec\": {\n \"display_name\": \"Python 3 (ipykernel)\",\n \"language\": \"python\",\n \"name\": \"python3\"\n },\n \"language_info\": {\n \"codemirror_mode\": {\n \"name\": \"ipython\",\n \"version\": 3\n },\n \"file_extension\": \".py\",\n \"mimetype\": \"text/x-python\",\n \"name\": \"python\",\n \"nbconvert_exporter\": \"python\",\n \"pygments_lexer\": \"ipython3\",\n \"version\": \"3.9.13\"\n }\n },\n \"nbformat\": 4,\n \"nbformat_minor\": 5\n}\n" }, { "path": "chatapi/ChatAPI + LangChain Basics.ipynb", "content": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"id\": \"e2376f66\",\n \"metadata\": {},\n \"source\": [\n \"[Official documentation on chat from LangChain](https://python.langchain.com/en/latest/modules/models/chat/getting_started.html)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 2,\n \"id\": \"dccede54\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain.chat_models import ChatOpenAI\\n\",\n \"from langchain import LLMChain\\n\",\n \"from langchain import PromptTemplate\\n\",\n \"from langchain.prompts.chat import (\\n\",\n \" ChatPromptTemplate,\\n\",\n \" SystemMessagePromptTemplate,\\n\",\n \" AIMessagePromptTemplate,\\n\",\n \" HumanMessagePromptTemplate,\\n\",\n \")\\n\",\n \"from langchain.schema import (\\n\",\n \" AIMessage,\\n\",\n \" HumanMessage,\\n\",\n \" SystemMessage\\n\",\n \")\\n\",\n \"\\n\",\n \"\\n\",\n \"# Supporting libraries\\n\",\n \"import os\\n\",\n \"from dotenv import load_dotenv\\n\",\n \"\\n\",\n \"load_dotenv()\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 19,\n \"id\": \"af154051\",\n \"metadata\": {\n \"hide_input\": false\n },\n \"outputs\": [],\n \"source\": [\n \"OPENAI_API_KEY = os.getenv('OPENAI_API_KEY', 'YourAPIKeyIfNotSet')\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"9dc0f73e\",\n \"metadata\": {},\n \"source\": [\n \"### 0. Simple Input/Output Still works\\n\",\n \"\\n\",\n \"You just need to pass it as a message instead. More on this in a second.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 4,\n \"id\": \"24231b46\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"chat = ChatOpenAI(openai_api_key=OPENAI_API_KEY)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 5,\n \"id\": \"2a68def1\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"AIMessage(content='\\\\n\\\\nCalifornia.', additional_kwargs={})\"\n ]\n },\n \"execution_count\": 5,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"message = [HumanMessage(content=\\\"What is the name of the most populous state in the USA?\\\")]\\n\",\n \"\\n\",\n \"chat(message)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"7409e722\",\n \"metadata\": {},\n \"source\": [\n \"### 1. Chat Messages\\n\",\n \"\\n\",\n \"* HumanMessage: A message sent from the perspective of the human\\n\",\n \"* AIMessage: A message sent from the perspective of the AI the human is interacting with\\n\",\n \"* SystemMessage: A message setting the objectives the AI should follow\\n\",\n \"* ChatMessage: A message allowing for arbitrary setting of role. You won’t be using this too much\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 6,\n \"id\": \"dd3e4528\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"AIMessage(content='I hate programming.', additional_kwargs={})\"\n ]\n },\n \"execution_count\": 6,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"messages = [\\n\",\n \" SystemMessage(content=\\\"Say the opposite of what the user says\\\"),\\n\",\n \" HumanMessage(content=\\\"I love programming.\\\")\\n\",\n \"]\\n\",\n \"chat(messages)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 7,\n \"id\": \"4b4d207f\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"AIMessage(content='The moon is not out.', additional_kwargs={})\"\n ]\n },\n \"execution_count\": 7,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"messages = [\\n\",\n \" SystemMessage(content=\\\"Say the opposite of what the user says\\\"),\\n\",\n \" HumanMessage(content=\\\"I love programming.\\\"),\\n\",\n \" AIMessage(content='I hate programming.'),\\n\",\n \" HumanMessage(content=\\\"The moon is out\\\")\\n\",\n \"]\\n\",\n \"chat(messages)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 8,\n \"id\": \"b6ba38cf\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"AIMessage(content='You said, \\\"I love programming.\\\"', additional_kwargs={})\"\n ]\n },\n \"execution_count\": 8,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"messages = [\\n\",\n \" SystemMessage(content=\\\"Say the opposite of what the user says\\\"),\\n\",\n \" HumanMessage(content=\\\"I love programming.\\\"),\\n\",\n \" AIMessage(content='I hate programming.'),\\n\",\n \" HumanMessage(content=\\\"What is the first thing that I said?\\\")\\n\",\n \"]\\n\",\n \"chat(messages)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"baf305b3\",\n \"metadata\": {},\n \"source\": [\n \"#### Batch Messages\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 9,\n \"id\": \"2e2b3636\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"LLMResult(generations=[[ChatGeneration(text='Amazingly appetizing apples.', generation_info=None, message=AIMessage(content='Amazingly appetizing apples.', additional_kwargs={}))], [ChatGeneration(text='Dangerous dogs do demand due diligence.', generation_info=None, message=AIMessage(content='Dangerous dogs do demand due diligence.', additional_kwargs={}))]], llm_output=None)\"\n ]\n },\n \"execution_count\": 9,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"batch_messages = [\\n\",\n \" [\\n\",\n \" SystemMessage(content=\\\"You are a helpful word machine that creates an alliteration using a base word\\\"),\\n\",\n \" HumanMessage(content=\\\"Base word: Apple\\\")\\n\",\n \" ],\\n\",\n \" [\\n\",\n \" SystemMessage(content=\\\"You are a helpful word machine that creates an alliteration using a base word\\\"),\\n\",\n \" HumanMessage(content=\\\"Base word: Dog\\\")\\n\",\n \" ],\\n\",\n \"]\\n\",\n \"chat.generate(batch_messages)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"e3600f53\",\n \"metadata\": {},\n \"source\": [\n \"### Prompt Templates\\n\",\n \"With one or more `MessagePromptTemplates` you can build a `ChatPromptTemplate`\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 10,\n \"id\": \"ddf3c969\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# Make SystemMessagePromptTemplate\\n\",\n \"prompt=PromptTemplate(\\n\",\n \" template=\\\"Propose creative ways to incorporate {food_1} and {food_2} in the cuisine of the users choice.\\\",\\n\",\n \" input_variables=[\\\"food_1\\\", \\\"food_2\\\"]\\n\",\n \")\\n\",\n \"\\n\",\n \"system_message_prompt = SystemMessagePromptTemplate(prompt=prompt)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 11,\n \"id\": \"401f2bd4\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"SystemMessage(content='Propose creative ways to incorportate Bacon and Shrimp in the cuisine of the users choice.', additional_kwargs={})\"\n ]\n },\n \"execution_count\": 11,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"# Output of system_message_prompt\\n\",\n \"system_message_prompt.format(food_1=\\\"Bacon\\\", food_2=\\\"Shrimp\\\")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 12,\n \"id\": \"a2c9e821\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# Make HumanMessagePromptTemplate\\n\",\n \"human_template=\\\"{text}\\\"\\n\",\n \"human_message_prompt = HumanMessagePromptTemplate.from_template(human_template)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 13,\n \"id\": \"1947bf3a\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"ChatPromptTemplate(input_variables=['food_1', 'food_2', 'text'], output_parser=None, partial_variables={}, messages=[SystemMessagePromptTemplate(prompt=PromptTemplate(input_variables=['food_1', 'food_2'], output_parser=None, partial_variables={}, template='Propose creative ways to incorportate {food_1} and {food_2} in the cuisine of the users choice.', template_format='f-string', validate_template=True), additional_kwargs={}), HumanMessagePromptTemplate(prompt=PromptTemplate(input_variables=['text'], output_parser=None, partial_variables={}, template='{text}', template_format='f-string', validate_template=True), additional_kwargs={})])\"\n ]\n },\n \"execution_count\": 13,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"# Create ChatPromptTemplate: Combine System + Human\\n\",\n \"chat_prompt = ChatPromptTemplate.from_messages([system_message_prompt, human_message_prompt])\\n\",\n \"chat_prompt\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 16,\n \"id\": \"e97284de\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"[SystemMessage(content='Propose creative ways to incorportate Bacon and Shrimp in the cuisine of the users choice.', additional_kwargs={}),\\n\",\n \" HumanMessage(content='I really like food from Germany.', additional_kwargs={})]\"\n ]\n },\n \"execution_count\": 16,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"chat_prompt_with_values = chat_prompt.format_prompt(food_1=\\\"Bacon\\\", \\\\\\n\",\n \" food_2=\\\"Shrimp\\\", \\\\\\n\",\n \" text=\\\"I really like food from Germany.\\\")\\n\",\n \"\\n\",\n \"chat_prompt_with_values.to_messages()\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 17,\n \"id\": \"c0de4582\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"Great choice! Here are some creative ways to incorporate bacon and shrimp into German cuisine:\\n\",\n \"\\n\",\n \"1. Bacon-wrapped shrimp skewers: Marinate shrimp in a mixture of olive oil, garlic, paprika, and cayenne pepper. Wrap each shrimp with a thin slice of bacon and thread onto skewers. Grill over medium heat until the bacon is crispy and the shrimp is pink and cooked through. Serve with a side of mustard for dipping.\\n\",\n \"\\n\",\n \"2. German shrimp and bacon soup: Start by cooking diced bacon until crispy in a large pot. Remove the bacon and set it aside. Add diced onion, celery, and carrots to the bacon fat and cook until softened. Add chicken or vegetable broth, diced potatoes, and diced cooked shrimp to the pot. Simmer until the potatoes are tender. Serve hot with a sprinkle of crispy bacon on top.\\n\",\n \"\\n\",\n \"3. Bacon and shrimp sauerkraut: Sauté diced bacon and sliced onions in a skillet until the onions are caramelized. Add sauerkraut, apple cider vinegar, and a little bit of sugar to the pan. Cook until the sauerkraut is tender and the liquid has reduced. Stir in cooked shrimp and reheat briefly. Serve as a side dish with a German-style sausage.\\n\",\n \"\\n\",\n \"\\n\"\n ]\n }\n ],\n \"source\": [\n \"response = chat(chat_prompt_with_values.to_messages()).content\\n\",\n \"print (response)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"20a756b5\",\n \"metadata\": {},\n \"source\": [\n \"#### With Streaming\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 18,\n \"id\": \"aac2d6f7\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"Great choice! Here are some creative ways to incorporate bacon and shrimp into German cuisine:\\n\",\n \"\\n\",\n \"1. Bacon and Shrimp Spätzle: Spätzle is a traditional German egg noodle dish. Add cooked shrimp and crispy bacon to the spätzle and toss with butter and fresh herbs for a delicious and hearty meal.\\n\",\n \"\\n\",\n \"2. Shrimp and Bacon Sauerkraut: Add cooked shrimp and crispy bacon to sauerkraut for a flavorful and protein-packed side dish. Serve alongside traditional German sausages or pork dishes.\\n\",\n \"\\n\",\n \"3. Bacon and Shrimp Potato Salad: German potato salad is typically made with bacon and vinegar dressing. Add cooked shrimp to the salad for a unique twist on this classic dish.\\n\",\n \"\\n\",\n \"4. Shrimp and Bacon Schnitzel: Top a traditional German schnitzel with cooked shrimp and crispy bacon for a decadent and flavorful meal.\\n\",\n \"\\n\",\n \"5. Bacon and Shrimp Bratwurst: Mix cooked shrimp and crispy bacon into the bratwurst mixture before grilling for a unique and delicious twist on this classic German sausage.\\n\",\n \"\\n\",\n \"Enjoy experimenting with these creative ways to incorporate bacon and shrimp into your favorite German dishes!\"\n ]\n }\n ],\n \"source\": [\n \"from langchain.callbacks.manager import CallbackManager\\n\",\n \"from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler\\n\",\n \"chat = ChatOpenAI(openai_api_key=OPENAI_API_KEY, streaming=True, callback_manager=CallbackManager([StreamingStdOutCallbackHandler()]), verbose=True, temperature=0)\\n\",\n \"\\n\",\n \"resp = chat(chat_prompt_with_values.to_messages())\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"id\": \"d771a133\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": []\n }\n ],\n \"metadata\": {\n \"kernelspec\": {\n \"display_name\": \"Python 3 (ipykernel)\",\n \"language\": \"python\",\n \"name\": \"python3\"\n },\n \"language_info\": {\n \"codemirror_mode\": {\n \"name\": \"ipython\",\n \"version\": 3\n },\n \"file_extension\": \".py\",\n \"mimetype\": \"text/x-python\",\n \"name\": \"python\",\n \"nbconvert_exporter\": \"python\",\n \"pygments_lexer\": \"ipython3\",\n \"version\": \"3.9.13\"\n }\n },\n \"nbformat\": 4,\n \"nbformat_minor\": 5\n}\n" }, { "path": "data/LinkedInIndustries.csv", "content": "Industry\r\nCorporate Services\r\nRecreation & Travel\r\nLegal\r\nWellness & Fitness\r\nEntertainment\r\nConsumer Goods\r\nDesign\r\nArts\r\nManufacturing\r\nFinance\r\nHealth Care\r\nConstruction\r\nNonprofit\r\nReal Estate\r\nSoftware & IT Services\r\nHardware & Networking\r\nAgriculture\r\nEducation\r\nPublic Administration\r\nTransportation & Logistics\r\nPublic Safety\r\nMedia & Communications\r\nEnergy & Mining\r\nRetail" }, { "path": "data/LinkedInSubIndustries.csv", "content": "Industry,SubIndustry\r\nCorporate Services,Accounting\r\nRecreation & Travel,Airlines/Aviation\r\nLegal,Alternative Dispute Resolution\r\nWellness & Fitness,Alternative Medicine\r\nEntertainment,Animation\r\nConsumer Goods,Apparel & Fashion\r\nDesign,Architecture & Planning\r\nArts,Arts & Crafts\r\nManufacturing,Automotive\r\nManufacturing,Aviation & Aerospace\r\nFinance,Banking\r\nHealth Care,Biotechnology\r\nEntertainment,Broadcast Media\r\nConstruction,Building Materials\r\nCorporate Services,Business Supplies & Equipment\r\nFinance,Capital Markets\r\nManufacturing,Chemicals\r\nNonprofit,Civic & Social Organization\r\nConstruction,Civil Engineering\r\nReal Estate,Commercial Real Estate\r\nSoftware & IT Services,Computer & Network Security\r\nEntertainment,Computer Games\r\nHardware & Networking,Computer Hardware\r\nHardware & Networking,Computer Networking\r\nSoftware & IT Services,Computer Software\r\nConstruction,Construction\r\nConsumer Goods,Consumer Electronics\r\nConsumer Goods,Consumer Goods\r\nConsumer Goods,Consumer Services\r\nConsumer Goods,Cosmetics\r\nAgriculture,Dairy\r\nManufacturing,Defense & Space\r\nDesign,Design\r\nEducation,E-Learning\r\nEducation,Education Management\r\nManufacturing,Electrical & Electronic Manufacturing\r\nEntertainment,Entertainment\r\nCorporate Services,Environmental Services\r\nCorporate Services,Events Services\r\nCorporate Services,Executive Office\r\nCorporate Services,Facilities Services\r\nAgriculture,Farming\r\nFinance,Financial Services\r\nArts,Fine Art\r\nAgriculture,Fishery\r\nConsumer Goods,Food & Beverages\r\nManufacturing,Food Production\r\nNonprofit,Fundraising\r\nConsumer Goods,Furniture\r\nRecreation & Travel,Gambling & Casinos\r\nManufacturing,\"Glass, Ceramics & Concrete\"\r\nPublic Administration,Government Administration\r\nPublic Administration,Government Relations\r\nDesign,Graphic Design\r\nWellness & Fitness,\"Health, Wellness & Fitness\"\r\nEducation,Higher Education\r\nHealth Care,Hospital & Health Care\r\nRecreation & Travel,Hospitality\r\nCorporate Services,Human Resources\r\nTransportation & Logistics,Import & Export\r\nNonprofit,Individual & Family Services\r\nManufacturing,Industrial Automation\r\nCorporate Services,Information Services\r\nSoftware & IT Services,Information Technology & Services\r\nFinance,Insurance\r\nPublic Administration,International Affairs\r\nNonprofit,International Trade & Development\r\nSoftware & IT Services,Internet\r\nFinance,Investment Banking\r\nFinance,Investment Management\r\nPublic Administration,Judiciary\r\nPublic Safety,Law Enforcement\r\nLegal,Law Practice\r\nLegal,Legal Services\r\nPublic Administration,Legislative Office\r\nRecreation & Travel,\"Leisure, Travel & Tourism\"\r\nNonprofit,Libraries\r\nTransportation & Logistics,Logistics & Supply Chain\r\nConsumer Goods,Luxury Goods & Jewelry\r\nManufacturing,Machinery\r\nCorporate Services,Management Consulting\r\nTransportation & Logistics,Maritime\r\nMedia & Communications,Market Research\r\nMedia & Communications,Marketing & Advertising\r\nManufacturing,Mechanical or Industrial Engineering\r\nEntertainment,Media Production\r\nHealth Care,Medical Device\r\nHealth Care,Medical Practice\r\nHealth Care,Mental Health Care\r\nPublic Safety,Military\r\nEnergy & Mining,Mining & Metals\r\nEntertainment,Mobile Games\r\nEntertainment,Motion Pictures & Film\r\nNonprofit,Museums & Institutions\r\nEntertainment,Music\r\nHardware & Networking,Nanotechnologie\r\nMedia & Communications,Newspapers\r\nNonprofit,Non-Profit Organization Management\r\nEnergy & Mining,Oil & Energy\r\nMedia & Communications,Online Media\r\nCorporate Services,Outsourcing/Offshoring\r\nTransportation & Logistics,Package/Freight Delivery\r\nManufacturing,Packaging & Containers\r\nManufacturing,Paper & Forest Products\r\nArts,Performing Arts\r\nHealth Care,Pharmaceuticals\r\nNonprofit,Philanthropy\r\nArts,Photography\r\nManufacturing,Plastics\r\nPublic Administration,Political Organization\r\nEducation,Primary/Secondary Education\r\nMedia & Communications,Printing\r\nCorporate Services,Professional Training & Coaching\r\nNonprofit,Program Development\r\nPublic Administration,Public Policy\r\nMedia & Communications,Public Relations & Communications\r\nPublic Safety,Public Safety\r\nMedia & Communications,Publishing\r\nManufacturing,Railroad Manufacture\r\nAgriculture,Ranching\r\nReal Estate,Real Estate\r\nRecreation & Travel,Recreational Facilities & Services\r\nNonprofit,Religious Institutions\r\nManufacturing,Renewables & Environment\r\nEducation,Research\r\nRecreation & Travel,Restaurants\r\nRetail,Retail\r\nCorporate Services,Security & Investigations\r\nHardware & Networking,Semiconductors\r\nManufacturing,Shipbuilding\r\nConsumer Goods,Sporting Goods\r\nRecreation & Travel,Sports\r\nCorporate Services,Staffing & Recruiting\r\nRetail,Supermarkets\r\nHardware & Networking,Telecommunications\r\nNonprofit,Think Tanks\r\nConsumer Goods,Tobacco\r\nMedia & Communications,Translation & Localization\r\nTransportation & Logistics,Transportation/Trucking/Railroad\r\nEnergy & Mining,Utilities\r\nFinance,Venture Capital & Private Equity\r\nHealth Care,Veterinary\r\nTransportation & Logistics,Warehousing\r\nRetail,Wholesale\r\nHardware & Networking,Wireless\r\nMedia & Communications,Writing & Editing" }, { "path": "data/PaulGrahamEssayMedium/fr.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nSeptember 2013Most startups that raise money do it more than once. A typical\ntrajectory might be (1) to get started with a few tens of thousands\nfrom something like Y Combinator or individual angels, then \n(2) raise a few hundred thousand to a few million to build the company,\nand then (3) once the company is clearly succeeding, raise one or\nmore later rounds to accelerate growth.Reality can be messier. Some companies raise money twice in phase\n2. Others skip phase 1 and go straight to phase 2. And at Y Combinator \nwe get an increasing number of companies that have already\nraised amounts in the hundreds of thousands. But the three phase\npath is at least the one about which individual startups' paths\noscillate.This essay focuses on phase 2 fundraising. That's the type the\nstartups we fund are doing on Demo Day, and this essay is the advice\nwe give them.\nForcesFundraising is hard in both senses: hard like lifting a heavy weight,\nand hard like solving a puzzle. It's hard like lifting a weight\nbecause it's intrinsically hard to convince people to part with\nlarge sums of money. That problem is irreducible; it should be\nhard. But much of the other kind of difficulty can be eliminated.\nFundraising only seems a puzzle because it's an alien world to most\nfounders, and I hope to fix that by supplying a map through it.To founders, the behavior of investors is often opaque — partly\nbecause their motivations are obscure, but partly because they\ndeliberately mislead you. And the misleading ways of investors\ncombine horribly with the wishful thinking of inexperienced founders.\nAt YC we're always warning founders about this danger, and investors\nare probably more circumspect with YC startups than with other\ncompanies they talk to, and even so we witness a constant series\nof explosions as these two volatile components combine.\n[1]If you're an inexperienced founder, the only way to survive is by\nimposing external constraints on yourself. You can't trust your\nintuitions. I'm going to give you a set of rules here that will\nget you through this process if anything will. At certain moments\nyou'll be tempted to ignore them. So rule number zero is: these\nrules exist for a reason. You wouldn't need a rule to keep you\ngoing in one direction if there weren't powerful forces pushing you\nin another.The ultimate source of the forces acting on you are the forces\nacting on investors. Investors are pinched between two kinds of\nfear: fear of investing in startups that fizzle, and fear of missing\nout on startups that take off. The cause of all this fear is the\nvery thing that makes startups such attractive investments: the\nsuccessful ones grow very fast. But that fast growth means investors\ncan't wait around. If you wait till a startup is obviously a\nsuccess, it's too late. To get the really high returns, you have\nto invest in startups when it's still unclear how they'll do. But\nthat in turn makes investors nervous they're about to invest in a\nflop. As indeed they often are.What investors would like to do, if they could, is wait. When a\nstartup is only a few months old, every week that passes gives you\nsignificantly more information about them. But if you wait too\nlong, other investors might take the deal away from you. And of\ncourse the other investors are all subject to the same forces. So\nwhat tends to happen is that they all wait as long as they can,\nthen when some act the rest have to.\nDon't raise money unless you want it and it wants you.Such a high proportion of successful startups raise money that it\nmight seem fundraising is one of the defining qualities of a startup.\nActually it isn't. Rapid growth is what\nmakes a company a startup. Most companies in a position to grow\nrapidly find that (a) taking outside money helps them grow faster,\nand (b) their growth potential makes it easy to attract such money.\nIt's so common for both (a) and (b) to be true of a successful\nstartup that practically all do raise outside money. But there may\nbe cases where a startup either wouldn't want to grow faster, or\noutside money wouldn't help them to, and if you're one of them,\ndon't raise money.The other time not to raise money is when you won't be able to. If\nyou try to raise money before you can convince\ninvestors, you'll not only waste your time, but also burn your\nreputation with those investors.\nBe in fundraising mode or not.One of the things that surprises founders most about fundraising\nis how distracting it is. When you start fundraising, everything\nelse grinds to a halt. The problem is not the time fundraising\nconsumes but that it becomes the top idea in\nyour mind. A startup can't endure that level of distraction\nfor long. An early stage startup grows mostly because the founders\nmake it grow, and if the founders look away,\ngrowth usually drops sharply.Because fundraising is so distracting, a startup should either be\nin fundraising mode or not. And when you do decide to raise money,\nyou should focus your whole attention on it so you can get it done\nquickly and get back to work.\n[2]You can take money from investors when you're not in fundraising\nmode. You just can't expend any attention on it. There are two\nthings that take attention: convincing investors, and negotiating\nwith them. So when you're not in fundraising mode, you should take\nmoney from investors only if they require no convincing, and are\nwilling to invest on terms you'll take without negotiation. For\nexample, if a reputable investor is willing to invest on a convertible\nnote, using standard paperwork, that is either uncapped or capped\nat a good valuation, you can take that without having to think.\n[3]\nThe terms will be whatever they turn out to be in your next\nequity round. And \"no convincing\" means just that: zero time spent\nmeeting with investors or preparing materials for them. If an\ninvestor says they're ready to invest, but they need you to come\nin for one meeting to meet some of the partners, tell them no, if\nyou're not in fundraising mode, because that's fundraising. \n[4]\nTell them politely; tell them you're focusing on the company right\nnow, and that you'll get back to them when you're fundraising; but\ndo not get sucked down the slippery slope.Investors will try to lure you into fundraising when you're not.\nIt's great for them if they can, because they can thereby get a\nshot at you before everyone else. They'll send you emails saying\nthey want to meet to learn more about you. If you get cold-emailed\nby an associate at a VC firm, you shouldn't meet even if you are\nin fundraising mode. Deals don't happen that way.\n[5]\nBut even\nif you get an email from a partner you should try to delay meeting\ntill you're in fundraising mode. They may say they just want to\nmeet and chat, but investors never just want to meet and chat. What\nif they like you? What if they start to talk about giving you\nmoney? Will you be able to resist having that conversation? Unless\nyou're experienced enough at fundraising to have a casual conversation\nwith investors that stays casual, it's safer to tell them that you'd\nbe happy to later, when you're fundraising, but that right now you\nneed to focus on the company.\n[6]Companies that are successful at raising money in phase 2 sometimes\ntack on a few investors after leaving fundraising mode. This is\nfine; if fundraising went well, you'll be able to do it without\nspending time convincing them or negotiating about terms.\nGet introductions to investors.Before you can talk to investors, you have to be introduced to them.\nIf you're presenting at a Demo Day, you'll be introduced to a whole\nbunch simultaneously. But even if you are, you should supplement\nthese with intros you collect yourself.Do you have to be introduced? In phase 2, yes. Some investors\nwill let you email them a business plan, but you can tell from the\nway their sites are organized that they don't really want startups\nto approach them directly.Intros vary greatly in effectiveness. The best type of intro is\nfrom a well-known investor who has just invested in you. So when\nyou get an investor to commit, ask them to introduce you to other\ninvestors they respect.\n[7]\nThe next best type of intro is from a\nfounder of a company they've funded. You can also get intros from\nother people in the startup community, like lawyers and reporters.There are now sites like AngelList, FundersClub, and WeFunder that\ncan introduce you to investors. We recommend startups treat them\nas auxiliary sources of money. Raise money first from leads you\nget yourself. Those will on average be better investors. Plus\nyou'll have an easier time raising money on these sites once you\ncan say you've already raised some from well-known investors.\nHear no till you hear yes.Treat investors as saying no till they unequivocally say yes, in\nthe form of a definite offer with no contingencies.I mentioned earlier that investors prefer to wait if they can.\nWhat's particularly dangerous for founders is the way they wait.\nEssentially, they lead you on. They seem like they're about to\ninvest right up till the moment they say no. If they even say no.\nSome of the worse ones never actually do say no; they just stop\nreplying to your emails. They hope that way to get a free option\non investing. If they decide later that they want to invest — usually\nbecause they've heard you're a hot deal — they can pretend they\njust got distracted and then restart the conversation as if they'd\nbeen about to.\n[8]That's not the worst thing investors will do. Some will use language\nthat makes it sound as if they're committing, but which doesn't\nactually commit them. And wishful thinking founders are happy to\nmeet them half way.\n[9]Fortunately, the next rule is a tactic for neutralizing this behavior.\nBut to work it depends on you not being tricked by the no that\nsounds like yes. It's so common for founders to be misled/mistaken\nabout this that we designed a protocol to fix the\nproblem. If you believe an investor has committed, get them to\nconfirm it. If you and they have different views of reality, whether\nthe source of the discrepancy is their sketchiness or your wishful\nthinking, the prospect of confirming a commitment in writing will\nflush it out. And till they confirm, regard them as saying no.\nDo breadth-first search weighted by expected value.When you talk to investors your m.o. should be breadth-first search,\nweighted by expected value. You should always talk to investors\nin parallel rather than serially. You can't afford the time it\ntakes to talk to investors serially, plus if you only talk to one\ninvestor at a time, they don't have the pressure of other investors\nto make them act. But you shouldn't pay the same attention to every\ninvestor, because some are more promising prospects than others.\nThe optimal solution is to talk to all potential investors in\nparallel, but give higher priority to the more promising ones. \n[10]Expected value = how likely an investor is to say yes, multiplied\nby how good it would be if they did. So for example, an eminent\ninvestor who would invest a lot, but will be hard to convince, might\nhave the same expected value as an obscure angel who won't invest\nmuch, but will be easy to convince. Whereas an obscure angel who\nwill only invest a small amount, and yet needs to meet multiple\ntimes before making up his mind, has very low expected value. Meet\nsuch investors last, if at all. \n[11]Doing breadth-first search weighted by expected value will save you\nfrom investors who never explicitly say no but merely drift away,\nbecause you'll drift away from them at the same rate. It protects\nyou from investors who flake in much the same way that a distributed\nalgorithm protects you from processors that fail. If some investor\nisn't returning your emails, or wants to have lots of meetings but\nisn't progressing toward making you an offer, you automatically\nfocus less on them. But you have to be disciplined about assigning\nprobabilities. You can't let how much you want an investor influence\nyour estimate of how much they want you.\nKnow where you stand.How do you judge how well you're doing with an investor, when\ninvestors habitually seem more positive than they are? By looking\nat their actions rather than their words. Every investor has some\ntrack they need to move along from the first conversation to wiring\nthe money, and you should always know what that track consists of,\nwhere you are on it, and how fast you're moving forward.Never leave a meeting with an investor without asking what happens\nnext. What more do they need in order to decide? Do they need\nanother meeting with you? To talk about what? And how soon? Do\nthey need to do something internally, like talk to their partners,\nor investigate some issue? How long do they expect it to take?\nDon't be too pushy, but know where you stand. If investors are\nvague or resist answering such questions, assume the worst; investors\nwho are seriously interested in you will usually be happy to talk\nabout what has to happen between now and wiring the money, because\nthey're already running through that in their heads. \n[12]If you're experienced at negotiations, you already know how to ask\nsuch questions.\n[13]\nIf you're not, there's a trick you can use\nin this situation. Investors know you're inexperienced at raising\nmoney. Inexperience there doesn't make you unattractive. Being a\nnoob at technology would, if you're starting a technology startup,\nbut not being a noob at fundraising. Larry and Sergey were noobs\nat fundraising. So you can just confess that you're inexperienced\nat this and ask how their process works and where you are in it.\n[14]\nGet the first commitment.The biggest factor in most investors' opinions of you is the opinion\nof other investors. Once you start getting\ninvestors to commit, it becomes increasingly easy to get more to.\nBut the other side of this coin is that it's often hard to get the\nfirst commitment.Getting the first substantial offer can be half the total difficulty\nof fundraising. What counts as a substantial offer depends on who\nit's from and how much it is. Money from friends and family doesn't\nusually count, no matter how much. But if you get $50k from a well\nknown VC firm or angel investor, that will usually be enough to set\nthings rolling.\n[15]\nClose committed money.It's not a deal till the money's in the bank. I often hear\ninexperienced founders say things like \"We've raised $800,000,\"\nonly to discover that zero of it is in the bank so far. Remember\nthe twin fears that torment investors? The fear of missing out\nthat makes them jump early, and the fear of jumping onto a turd\nthat results? This is a market where people are exceptionally prone\nto buyer's remorse. And it's also one that furnishes them plenty\nof excuses to gratify it. The public markets snap startup investing\naround like a whip. If the Chinese economy blows up tomorrow, all\nbets are off. But there are lots of surprises for individual\nstartups too, and they tend to be concentrated around fundraising.\nTomorrow a big competitor could appear, or you could get C&Ded, or\nyour cofounder could quit.\n[16]Even a day's delay can bring news that causes an investor to change\ntheir mind. So when someone commits, get the money. Knowing where\nyou stand doesn't end when they say they'll invest. After they say\nyes, know what the timetable is for getting the money, and then\nbabysit that process till it happens. Institutional investors have\npeople in charge of wiring money, but you may have to hunt angels\ndown in person to collect a check.Inexperienced investors are the ones most likely to get buyer's\nremorse. Established ones have learned to treat saying yes as like\ndiving off a diving board, and they also have more brand to preserve.\nBut I've heard of cases of even top-tier VC firms welching on deals.\nAvoid investors who don't \"lead.\"Since getting the first offer is most of the difficulty of fundraising,\nthat should be part of your calculation of expected value when you\nstart. You have to estimate not just the probability that an\ninvestor will say yes, but the probability that they'd be the first\nto say yes, and the latter is not simply a constant fraction of the\nformer. Some investors are known for deciding quickly, and those\nare extra valuable early on.Conversely, an investor who will only invest once other investors\nhave is worthless initially. And while most investors are influenced\nby how interested other investors are in you, there are some who\nhave an explicit policy of only investing after other investors\nhave. You can recognize this contemptible subspecies of investor\nbecause they often talk about \"leads.\" They say that they don't\nlead, or that they'll invest once you have a lead. Sometimes they\neven claim to be willing to lead themselves, by which they mean\nthey won't invest till you get $x from other investors. (It's great\nif by \"lead\" they mean they'll invest unilaterally, and in addition\nwill help you raise more. What's lame is when they use the term\nto mean they won't invest unless you can raise more elsewhere.)\n[17]Where does this term \"lead\" come from? Up till a few years ago,\nstartups raising money in phase 2 would usually raise equity rounds\nin which several investors invested at the same time using the same\npaperwork. You'd negotiate the terms with one \"lead\" investor, and\nthen all the others would sign the same documents and all the money\nchange hands at the closing.Series A rounds still work that way, but things now work differently\nfor most fundraising prior to the series A. Now there are rarely\nactual rounds before the A round, or leads for them. Now startups\nsimply raise money from investors one at a time till they feel they\nhave enough.Since there are no longer leads, why do investors use that term?\nBecause it's a more legitimate-sounding way of saying what they\nreally mean. All they really mean is that their interest in you\nis a function of other investors' interest in you. I.e. the spectral\nsignature of all mediocre investors. But when phrased in terms of\nleads, it sounds like there is something structural and therefore\nlegitimate about their behavior.When an investor tells you \"I want to invest in you, but I don't\nlead,\" translate that in your mind to \"No, except yes if you turn\nout to be a hot deal.\" And since that's the default opinion of any\ninvestor about any startup, they've essentially just told you\nnothing.When you first start fundraising, the expected value of an investor\nwho won't \"lead\" is zero, so talk to such investors last if at all.\nHave multiple plans.Many investors will ask how much you're planning to raise. This\nquestion makes founders feel they should be planning to raise a\nspecific amount. But in fact you shouldn't. It's a mistake to\nhave fixed plans in an undertaking as unpredictable as fundraising.So why do investors ask how much you plan to raise? For much the\nsame reasons a salesperson in a store will ask \"How much were you\nplanning to spend?\" if you walk in looking for a gift for a friend.\nYou probably didn't have a precise amount in mind; you just want\nto find something good, and if it's inexpensive, so much the better.\nThe salesperson asks you this not because you're supposed to have\na plan to spend a specific amount, but so they can show you only\nthings that cost the most you'll pay.Similarly, when investors ask how much you plan to raise, it's not\nbecause you're supposed to have a plan. It's to see whether you'd\nbe a suitable recipient for the size of investment they like to\nmake, and also to judge your ambition, reasonableness, and how far\nyou are along with fundraising.If you're a wizard at fundraising, you can say \"We plan to raise\na $7 million series A round, and we'll be accepting termsheets next\ntuesday.\" I've known a handful of founders who could pull that off\nwithout having VCs laugh in their faces. But if you're in the\ninexperienced but earnest majority, the solution is analogous to\nthe solution I recommend for pitching\nyour startup: do the right thing and then just tell investors what\nyou're doing.And the right strategy, in fundraising, is to have multiple plans\ndepending on how much you can raise. Ideally you should be able\nto tell investors something like: we can make it to profitability\nwithout raising any more money, but if we raise a few hundred\nthousand we can hire one or two smart friends, and if we raise a\ncouple million, we can hire a whole engineering team, etc.Different plans match different investors. If you're talking to a\nVC firm that only does series A rounds (though there are few of\nthose left), it would be a waste of time talking about any but your\nmost expensive plan. Whereas if you're talking to an angel who\ninvests $20k at a time and you haven't raised any money yet, you\nprobably want to focus on your least expensive plan.If you're so fortunate as to have to think about the upper limit\non what you should raise, a good rule of thumb is to multiply the\nnumber of people you want to hire times $15k times 18 months. In\nmost startups, nearly all the costs are a function of the number\nof people, and $15k per month is the conventional total cost\n(including benefits and even office space) per person. $15k per\nmonth is high, so don't actually spend that much. But it's ok to\nuse a high estimate when fundraising to add a margin for error. If\nyou have additional expenses, like manufacturing, add in those at\nthe end. Assuming you have none and you think you might hire 20\npeople, the most you'd want to raise is 20 x $15k x 18 = $5.4\nmillion.\n[18]\nUnderestimate how much you want.Though you can focus on different plans when talking to different\ntypes of investors, you should on the whole err on the side of\nunderestimating the amount you hope to raise.For example, if you'd like to raise $500k, it's better to say\ninitially that you're trying to raise $250k. Then when you reach\n$150k you're more than half done. That sends two useful signals\nto investors: that you're doing well, and that they have to decide\nquickly because you're running out of room. Whereas if you'd said\nyou were raising $500k, you'd be less than a third done at $150k.\nIf fundraising stalled there for an appreciable time, you'd start\nto read as a failure.Saying initially that you're raising $250k doesn't limit you to\nraising that much. When you reach your initial target and you still\nhave investor interest, you can just decide to raise more. Startups\ndo that all the time. In fact, most startups that are very successful\nat fundraising end up raising more than they originally intended.I'm not saying you should lie, but that you should lower your\nexpectations initially. There is almost no downside in starting\nwith a low number. It not only won't cap the amount you raise, but\nwill on the whole tend to increase it.A good metaphor here is angle of attack. If you try to fly at too\nsteep an angle of attack, you just stall. If you say right out of\nthe gate that you want to raise a $5 million series A round, unless\nyou're in a very strong position, you not only won't get that but\nwon't get anything. Better to start at a low angle of attack, build\nup speed, and then gradually increase the angle if you want.\nBe profitable if you can.You will be in a much stronger position if your collection of plans\nincludes one for raising zero dollars — i.e. if you can make\nit to profitability without raising any additional money. Ideally\nyou want to be able to say to investors \"We'll succeed no matter\nwhat, but raising money will help us do it faster.\"There are many analogies between fundraising and dating, and this\nis one of the strongest. No one wants you if you seem desperate.\nAnd the best way not to seem desperate is not to be desperate.\nThat's one reason we urge startups during YC to keep expenses low\nand to try to make it to ramen\nprofitability before Demo Day. Though it sounds slightly\nparadoxical, if you want to raise money, the best thing you can do\nis get yourself to the point where you don't need to.There are almost two distinct modes of fundraising: one in which\nfounders who need money knock on doors seeking it, knowing that\notherwise the company will die or at the very least people will\nhave to be fired, and one in which founders who don't need money\ntake some to grow faster than they could merely on their own revenues.\nTo emphasize the distinction I'm going to name them: type A fundraising\nis when you don't need money, and type B fundraising is when you\ndo.Inexperienced founders read about famous startups doing what was\ntype A fundraising, and decide they should raise money too, since\nthat seems to be how startups work. Except when they raise money\nthey don't have a clear path to profitability and are thus doing\ntype B fundraising. And they are then surprised how difficult and\nunpleasant it is.Of course not all startups can make it to ramen profitability in a\nfew months. And some that don't still manage to have the upper\nhand over investors, if they have some other advantage like\nextraordinary growth numbers or exceptionally formidable founders.\nBut as time passes it gets increasingly difficult to fundraise from\na position of strength without being profitable.\n[19]\nDon't optimize for valuation.When you raise money, what should your valuation be? The most\nimportant thing to understand about valuation is that it's not that\nimportant.Founders who raise money at high valuations tend to be unduly proud\nof it. Founders are often competitive people, and since valuation\nis usually the only visible number attached to a startup, they end\nup competing to raise money at the highest valuation. This is\nstupid, because fundraising is not the test that matters. The real\ntest is revenue. Fundraising is just a means to that end. Being\nproud of how well you did at fundraising is like being proud of\nyour college grades.Not only is fundraising not the test that matters, valuation is not\neven the thing to optimize about fundraising. The number one thing\nyou want from phase 2 fundraising is to get the money you need, so\nyou can get back to focusing on the real test, the success of your\ncompany. Number two is good investors. Valuation is at best third.The empirical evidence shows just how unimportant it is. Dropbox\nand Airbnb are the most successful companies we've funded so far,\nand they raised money after Y Combinator at premoney valuations of\n$4 million and $2.6 million respectively. Prices are so much higher\nnow that if you can raise money at all you'll probably raise it at\nhigher valuations than Dropbox and Airbnb. So let that satisfy\nyour competitiveness. You're doing better than Dropbox and Airbnb!\nAt a test that doesn't matter.When you start fundraising, your initial valuation (or valuation\ncap) will be set by the deal you make with the first investor who\ncommits. You can increase the price for later investors, if you\nget a lot of interest, but by default the valuation you got from\nthe first investor becomes your asking price.So if you're raising money from multiple investors, as most companies\ndo in phase 2, you have to be careful to avoid raising the first\nfrom an over-eager investor at a price you won't be able to\nsustain. You can of course lower your price if you need to (in\nwhich case you should give the same terms to investors who invested\nearlier at a higher price), but you may lose a bunch of leads in\nthe process of realizing you need to do this.What you can do if you have eager first investors is raise money\nfrom them on an uncapped convertible note with an MFN clause. This\nis essentially a way of saying that the valuation cap of the note\nwill be determined by the next investors you raise money from.It will be easier to raise money at a lower valuation. It shouldn't\nbe, but it is. Since phase 2 prices vary at most 10x and the big\nsuccesses generate returns of at least 100x, investors should pick\nstartups entirely based on their estimate of the probability that\nthe company will be a big success and hardly at all on price. But\nalthough it's a mistake for investors to care about price, a\nsignificant number do. A startup that investors seem to like but\nwon't invest in at a cap of $x will have an easier time at $x/2.\n[20]\nYes/no before valuation.Some investors want to know what your valuation is before they even\ntalk to you about investing. If your valuation has already been\nset by a prior investment at a specific valuation or cap, you can\ntell them that number. But if it isn't set because you haven't\nclosed anyone yet, and they try to push you to name a price, resist\ndoing so. If this would be the first investor you've closed, then\nthis could be the tipping point of fundraising. That means closing\nthis investor is the first priority, and you need to get the\nconversation onto that instead of being dragged sideways into a\ndiscussion of price.Fortunately there is a way to avoid naming a price in this situation.\nAnd it is not just a negotiating trick; it's how you (both) should\nbe operating. Tell them that valuation is not the most important\nthing to you and that you haven't thought much about it, that you\nare looking for investors you want to partner with and who want to\npartner with you, and that you should talk first about whether they\nwant to invest at all. Then if they decide they do want to invest,\nyou can figure out a price. But first things first.Since valuation isn't that important and getting fundraising rolling\nis, we usually tell founders to give the first investor who commits\nas low a price as they need to. This is a safe technique so long\nas you combine it with the next one. \n[21]\nBeware \"valuation sensitive\" investors.Occasionally you'll encounter investors who describe themselves as\n\"valuation sensitive.\" What this means in practice is that they\nare compulsive negotiators who will suck up a lot of your time\ntrying to push your price down. You should therefore never approach\nsuch investors first. While you shouldn't chase high valuations,\nyou also don't want your valuation to be set artificially low because\nthe first investor who committed happened to be a compulsive\nnegotiator. Some such investors have value, but the time to approach\nthem is near the end of fundraising, when you're in a position to\nsay \"this is the price everyone else has paid; take it or leave it\"\nand not mind if they leave it. This way, you'll not only get market\nprice, but it will also take less time.Ideally you know which investors have a reputation for being\n\"valuation sensitive\" and can postpone dealing with them till last,\nbut occasionally one you didn't know about will pop up early on.\nThe rule of doing breadth first search weighted by expected value\nalready tells you what to do in this case: slow down your interactions\nwith them.There are a handful of investors who will try to invest at a lower\nvaluation even when your price has already been set. Lowering your\nprice is a backup plan you resort to when you discover you've let\nthe price get set too high to close all the money you need. So\nyou'd only want to talk to this sort of investor if you were about\nto do that anyway. But since investor meetings have to be arranged\nat least a few days in advance and you can't predict when you'll\nneed to resort to lowering your price, this means in practice that\nyou should approach this type of investor last if at all.If you're surprised by a lowball offer, treat it as a backup offer\nand delay responding to it. When someone makes an offer in good\nfaith, you have a moral obligation to respond in a reasonable time.\nBut lowballing you is a dick move that should be met with the\ncorresponding countermove.\nAccept offers greedily.I'm a little leery of using the term \"greedily\" when writing about\nfundraising lest non-programmers misunderstand me, but a greedy\nalgorithm is simply one that doesn't try to look into the future.\nA greedy algorithm takes the best of the options in front of it\nright now. And that is how startups should approach fundraising\nin phases 2 and later. Don't try to look into the future because\n(a) the future is unpredictable, and indeed in this business you're\noften being deliberately misled about it and (b) your first priority\nin fundraising should be to get it finished and get back to work\nanyway.If someone makes you an acceptable offer, take it. If you have\nmultiple incompatible offers, take the best. Don't reject an\nacceptable offer in the hope of getting a better one in the future.These simple rules cover a wide variety of cases. If you're raising\nmoney from many investors, roll them up as they say yes. As you\nstart to feel you've raised enough, the threshold for acceptable\nwill start to get higher.In practice offers exist for stretches of time, not points. So\nwhen you get an acceptable offer that would be incompatible with\nothers (e.g. an offer to invest most of the money you need), you\ncan tell the other investors you're talking to that you have an\noffer good enough to accept, and give them a few days to make their\nown. This could lose you some that might have made an offer if\nthey had more time. But by definition you don't care; the initial\noffer was acceptable.Some investors will try to prevent others from having time to decide\nby giving you an \"exploding\" offer, meaning one that's only valid\nfor a few days. Offers from the very best investors explode less\nfrequently and less rapidly — Fred Wilson never gives exploding\noffers, for example — because they're confident you'll pick\nthem. But lower-tier investors sometimes give offers with very\nshort fuses, because they believe no one who had other options would\nchoose them. A deadline of three working days is acceptable. You\nshouldn't need more than that if you've been talking to investors\nin parallel. But a deadline any shorter is a sign you're dealing\nwith a sketchy investor. You can usually call their bluff, and you\nmay need to.\n[22]It might seem that instead of accepting offers greedily, your goal\nshould be to get the best investors as partners. That is certainly\na good goal, but in phase 2 \"get the best investors\" only rarely\nconflicts with \"accept offers greedily,\" because the best investors\ndon't usually take any longer to decide than the others. The only\ncase where the two strategies give conflicting advice is when you\nhave to forgo an offer from an acceptable investor to see if you'll\nget an offer from a better one. If you talk to investors in parallel\nand push back on exploding offers with excessively short deadlines,\nthat will almost never happen. But if it does, \"get the best\ninvestors\" is in the average case bad advice. The best investors\nare also the most selective, because they get their pick of all the\nstartups. They reject nearly everyone they talk to, which means\nin the average case it's a bad trade to exchange a definite offer\nfrom an acceptable investor for a potential offer from a better\none.(The situation is different in phase 1. You can't apply to all the\nincubators in parallel, because some offset their schedules to\nprevent this. In phase 1, \"accept offers greedily\" and \"get the\nbest investors\" do conflict, so if you want to apply to multiple\nincubators, you should do it in such a way that the ones you want\nmost decide first.)Sometimes when you're raising money from multiple investors, a\nseries A will emerge out of those conversations, and these rules\neven cover what to do in that case. When an investor starts to\ntalk to you about a series A, keep taking smaller investments till\nthey actually give you a termsheet. There's no practical difficulty.\nIf the smaller investments are on convertible notes, they'll just\nconvert into the series A round. The series A investor won't like\nhaving all these other random investors as bedfellows, but if it\nbothers them so much they should get on with giving you a termsheet.\nTill they do, you don't know for sure they will, and the greedy\nalgorithm tells you what to do.\n[23]\nDon't sell more than 25% in phase 2.If you do well, you will probably raise a series A round eventually.\nI say probably because things are changing with series A rounds.\nStartups may start to skip them. But only one company we've funded\nhas so far, so tentatively assume the path to huge passes through\nan A round.\n[24]Which means you should avoid doing things in earlier rounds that\nwill mess up raising an A round. For example, if you've sold more\nthan about 40% of your company total, it starts to get harder to\nraise an A round, because VCs worry there will not be enough stock\nleft to keep the founders motivated.Our rule of thumb is not to sell more than 25% in phase 2, on top\nof whatever you sold in phase 1, which should be less than 15%. If\nyou're raising money on uncapped notes, you'll have to guess what\nthe eventual equity round valuation might be. Guess conservatively.(Since the goal of this rule is to avoid messing up the series A,\nthere's obviously an exception if you end up raising a series A in\nphase 2, as a handful of startups do.)\nHave one person handle fundraising.If you have multiple founders, pick one to handle fundraising so\nthe other(s) can keep working on the company. And since the danger\nof fundraising is not the time taken up by the actual meetings but\nthat it becomes the top idea in your mind, the founder who handles\nfundraising should make a conscious effort to insulate the other\nfounder(s) from the details of the process.\n[25](If the founders mistrust one another, this could cause some friction.\nBut if the founders mistrust one another, you have worse problems\nto worry about than how to organize fundraising.)The founder who handles fundraising should be the CEO, who should\nin turn be the most formidable of the founders. Even if the CEO\nis a programmer and another founder is a salesperson? Yes. If you\nhappen to be that type of founding team, you're effectively a single\nfounder when it comes to fundraising.It's ok to bring all the founders to meet an investor who will\ninvest a lot, and who needs this meeting as the final step before\ndeciding. But wait till that point. Introducing an investor to\nyour cofounder(s) should be like introducing a girl/boyfriend to\nyour parents — something you do only when things reach a certain\nstage of seriousness.Even if there are still one or more founders focusing on the company\nduring fundraising, growth will slow. But try to get as much growth\nas you can, because fundraising is a segment of time, not a point,\nand what happens to the company during that time affects the outcome.\nIf your numbers grow significantly between two investor meetings,\ninvestors will be hot to close, and if your numbers are flat or\ndown they'll start to get cold feet.\nYou'll need an executive summary and (maybe) a deck.Traditionally phase 2 fundraising consists of presenting a slide\ndeck in person to investors. Sequoia describes what such a deck\nshould contain, and\nsince they're the customer you can take their word for it.I say \"traditionally\" because I'm ambivalent about decks, and (though\nperhaps this is wishful thinking) they seem to be on the way out.\nA lot of the most successful startups we fund never make decks in\nphase 2. They just talk to investors and explain what they plan\nto do. Fundraising usually takes off fast for the startups that\nare most successful at it, and they're thus able to excuse themselves\nby saying that they haven't had time to make a deck.You'll also want an executive summary, which should be no more than\na page long and describe in the most matter of fact language what\nyou plan to do, why it's a good idea, and what progress you've made\nso far. The point of the summary is to remind the investor (who\nmay have met many startups that day) what you talked about.Assume that if you give someone a copy of your deck or executive\nsummary, it will be passed on to whoever you'd least like to have\nit. But don't refuse on that account to give copies to investors\nyou meet. You just have to treat such leaks as a cost of doing\nbusiness. In practice it's not that high a cost. Though founders\nare rightly indignant when their plans get leaked to competitors,\nI can't think of a startup whose outcome has been affected by it.Sometimes an investor will ask you to send them your deck and/or\nexecutive summary before they decide whether to meet with you. I\nwouldn't do that. It's a sign they're not really interested.\nStop fundraising when it stops working.When do you stop fundraising? Ideally when you've raised enough.\nBut what if you haven't raised as much as you'd like? When do you\ngive up?It's hard to give general advice about this, because there have\nbeen cases of startups that kept trying to raise money even when\nit seemed hopeless, and miraculously succeeded. But what I usually\ntell founders is to stop fundraising when you start to get a lot\nof air in the straw. When you're drinking through a straw, you can\ntell when you get to the end of the liquid because you start to get\na lot of air in the straw. When your fundraising options run out,\nthey usually run out in the same way. Don't keep sucking on the\nstraw if you're just getting air. It's not going to get better.\nDon't get addicted to fundraising.Fundraising is a chore for most founders, but some find it more\ninteresting than working on their startup. The work at an early\nstage startup often consists of unglamorous schleps. Whereas fundraising, when it's\ngoing well, can be quite the opposite. Instead of sitting in your\ngrubby apartment listening to users complain about bugs in your\nsoftware, you're being offered millions of dollars by famous investors\nover lunch at a nice restaurant.\n[26]The danger of fundraising is particularly acute for people who are\ngood at it. It's always fun to work on something you're good at.\nIf you're one of these people, beware. Fundraising is not what\nwill make your company successful. Listening to users complain\nabout bugs in your software is what will make you successful. And\nthe big danger of getting addicted to fundraising is not merely\nthat you'll spend too long on it or raise too much money. It's\nthat you'll start to think of yourself as being already successful,\nand lose your taste for the schleps you need to undertake to actually\nbe successful. Startups can be destroyed by this.When I see a startup with young founders that is fabulously successful\nat fundraising, I mentally decrease my estimate of the probability\nthat they'll succeed. The press may be writing about them as if\nthey'd been anointed as the next Google, but I'm thinking \"this is\ngoing to end badly.\"\nDon't raise too much.Though only a handful of startups have to worry about this, it is\npossible to raise too much. The dangers of raising too much are\nsubtle but insidious. One is that it will set impossibly high\nexpectations. If you raise an excessive amount of money, it will\nbe at a high valuation, and the danger of raising money at too high\na valuation is that you won't be able to increase it sufficiently\nthe next time you raise money.A company's valuation is expected to rise each time it raises money.\nIf not it's a sign of a company in trouble, which makes you\nunattractive to investors. So if you raise money in phase 2 at a\npost-money valuation of $30 million, the pre-money valuation of\nyour next round, if you want to raise one, is going to have to be\nat least $50 million. And you have to be doing really, really well\nto raise money at $50 million.It's very dangerous to let the competitiveness of your current round\nset the performance threshold you have to meet to raise your next\none, because the two are only loosely coupled.But the money itself may be more dangerous than the valuation. The\nmore you raise, the more you spend, and spending a lot of money can\nbe disastrous for an early stage startup. Spending a lot makes it\nharder to become profitable, and perhaps even worse, it makes you\nmore rigid, because the main way to spend money is people, and the\nmore people you have, the harder it is to change directions. So\nif you do raise a huge amount of money, don't spend it. (You will\nfind that advice almost impossible to follow, so hot will be the\nmoney burning a hole in your pocket, but I feel obliged at least\nto try.)\nBe nice.Startups raising money occasionally alienate investors by seeming\narrogant. Sometimes because they are arrogant, and sometimes because\nthey're noobs clumsily attempting to mimic the toughness they've\nobserved in experienced founders.It's a mistake to behave arrogantly to investors. While there are\ncertain situations in which certain investors like certain kinds\nof arrogance, investors vary greatly in this respect, and a flick\nof the whip that will bring one to heel will make another roar with\nindignation. The only safe strategy is never to seem arrogant at\nall.That will require some diplomacy if you follow the advice I've given\nhere, because the advice I've given is essentially how to play\nhardball back. When you refuse to meet an investor because you're\nnot in fundraising mode, or slow down your interactions with an\ninvestor who moves too slow, or treat a contingent offer as the no\nit actually is and then, by accepting offers greedily, end up leaving\nthat investor out, you're going to be doing things investors don't\nlike. So you must cushion the blow with soft words. At YC we tell\nstartups they can blame us. And now that I've written this, everyone\nelse can blame me if they want. That plus the inexperience card\nshould work in most situations: sorry, we think you're great, but\nPG said startups shouldn't ___, and since we're new to fundraising,\nwe feel like we have to play it safe.The danger of behaving arrogantly is greatest when you're doing\nwell. When everyone wants you, it's hard not to let it go to your\nhead. Especially if till recently no one wanted you. But restrain\nyourself. The startup world is a small place, and startups have\nlots of ups and downs. This is a domain where it's more true than\nusual that pride goeth before a fall.\n[27]Be nice when investors reject you as well. The best investors are\nnot wedded to their initial opinion of you. If they reject you in\nphase 2 and you end up doing well, they'll often invest in phase\n3. In fact investors who reject you are some of your warmest leads\nfor future fundraising. Any investor who spent significant time\ndeciding probably came close to saying yes. Often you have some\ninternal champion who only needs a little more evidence to convince\nthe skeptics. So it's wise not merely to be nice to investors who\nreject you, but (unless they behaved badly) to treat it as the\nbeginning of a relationship.\nThe bar will be higher next time.Assume the money you raise in phase 2 will be the last you ever\nraise. You must make it to profitability on this money if you can.Over the past several years, the investment community has evolved\nfrom a strategy of anointing a small number of winners early and\nthen supporting them for years to a strategy of spraying money at\nearly stage startups and then ruthlessly culling them at the next\nstage. This is probably the optimal strategy for investors. It's\ntoo hard to pick winners early on. Better to let the market do it\nfor you. But it often comes as a surprise to startups how much\nharder it is to raise money in phase 3.When your company is only a couple months old, all it has to be is\na promising experiment that's worth funding to see how it turns\nout. The next time you raise money, the experiment has to have\nworked. You have to be on a trajectory that leads to going public.\nAnd while there are some ideas where the proof that the experiment\nworked might consist of e.g. query response times, usually the proof\nis profitability. Usually phase 3 fundraising has to be type A\nfundraising.In practice there are two ways startups hose themselves between\nphases 2 and 3. Some are just too slow to become profitable. They\nraise enough money to last for two years. There doesn't seem any\nparticular urgency to be profitable. So they don't make any effort\nto make money for a year. But by that time, not making money has\nbecome habitual. When they finally decide to try, they find they\ncan't.The other way companies hose themselves is by letting their expenses\ngrow too fast. Which almost always means hiring too many people.\nYou usually shouldn't go out and hire 8 people as soon as you raise\nmoney at phase 2. Usually you want to wait till you have growth\n(and thus usually revenues) to justify them. A lot of VCs will\nencourage you to hire aggressively. VCs generally tell you to spend\ntoo much, partly because as money people they err on the side of\nsolving problems by spending money, and partly because they want\nyou to sell them more of your company in subsequent rounds. Don't\nlisten to them.\nDon't make things complicated.I realize it may seem odd to sum up this huge treatise by saying\nthat my overall advice is not to make fundraising too complicated,\nbut if you go back and look at this list you'll see it's basically\na simple recipe with a lot of implications and edge cases. Avoid\ninvestors till you decide to raise money, and then when you do,\ntalk to them all in parallel, prioritized by expected value, and\naccept offers greedily. That's fundraising in one sentence. Don't\nintroduce complicated optimizations, and don't let investors introduce\ncomplications either.Fundraising is not what will make you successful. It's just a means\nto an end. Your primary goal should be to get it over with and get\nback to what will make you successful — making things and talking\nto users — and the path I've described will for most startups\nbe the surest way to that destination.Be good, take care of yourselves, and don't leave the path.\nNotes[1]\nThe worst explosions happen when unpromising-seeming startups\nencounter mediocre investors. Good investors don't lead startups\non; their reputations are too valuable. And startups that seem\npromising can usually get enough money from good investors that\nthey don't have to talk to mediocre ones. It is the unpromising-seeming\nstartups that have to resort to raising money from mediocre investors.\nAnd it's particularly damaging when these investors flake, because\nunpromising-seeming startups are usually more desperate for money.(Not all unpromising-seeming startups do badly. Some are merely\nugly ducklings in the sense that they violate current startup\nfashions.)[2]\nOne YC founder told me:\n\n I think in general we've done ok at fundraising, but I managed\n to screw up twice at the exact same thing — trying to focus\n on building the company and fundraising at the same time.\n\n[3]\nThere is one subtle danger you have to watch out for here, which\nI warn about later: beware of getting too high a valuation from an\neager investor, lest that set an impossibly high target when raising\nadditional money.[4]\nIf they really need a meeting, then they're not ready to invest,\nregardless of what they say. They're still deciding, which means\nyou're being asked to come in and convince them. Which is fundraising.[5]\nAssociates at VC firms regularly cold email startups. Naive\nfounders think \"Wow, a VC is interested in us!\" But an associate\nis not a VC. They have no decision-making power. And while they\nmay introduce startups they like to partners at their firm, the\npartners discriminate against deals that come to them this way. I\ndon't know of a single VC investment that began with an associate\ncold-emailing a startup. If you want to approach a specific firm,\nget an intro to a partner from someone they respect.It's ok to talk to an associate if you get an intro to a VC firm\nor they see you at a Demo Day and they begin by having an associate\nvet you. That's not a promising lead and should therefore get low\npriority, but it's not as completely worthless as a cold email.Because the title \"associate\" has gotten a bad reputation, a few\nVC firms have started to give their associates the title \"partner,\"\nwhich can make things very confusing. If you're a YC startup you\ncan ask us who's who; otherwise you may have to do some research\nonline. There may be a special title for actual partners. If\nsomeone speaks for the firm in the press or a blog on the firm's\nsite, they're probably a real partner. If they're on boards of\ndirectors they're probably a real partner.There are titles between \"associate\" and \"partner,\" including\n\"principal\" and \"venture partner.\" The meanings of these titles\nvary too much to generalize.[6]\nFor similar reasons, avoid casual conversations with potential\nacquirers. They can lead to distractions even more dangerous than\nfundraising. Don't even take a meeting with a potential acquirer\nunless you want to sell your company right now.[7]\nJoshua Reeves specifically suggests asking each investor to\nintro you to two more investors.Don't ask investors who say no for introductions to other investors.\nThat will in many cases be an anti-recommendation.[8]\nThis is not always as deliberate as its sounds. A lot of the\ndelays and disconnects between founders and investors are induced\nby the customs of the venture business, which have evolved the way\nthey have because they suit investors' interests.[9]\nOne YC founder who read a draft of this essay wrote:\n\n This is the most important section. I think it might bear stating\n even more clearly. \"Investors will deliberately affect more\n interest than they have to preserve optionality. If an investor\n seems very interested in you, they still probably won't invest.\n The solution for this is to assume the worst — that an investor\n is just feigning interest — until you get a definite commitment.\"\n\n[10]\nThough you should probably pack investor meetings as closely\nas you can, Jeff Byun mentions one reason not to: if you pack\ninvestor meetings too closely, you'll have less time for your pitch\nto evolve.Some founders deliberately schedule a handful of lame investors\nfirst, to get the bugs out of their pitch.[11]\nThere is not an efficient market in this respect. Some of the\nmost useless investors are also the highest maintenance.[12]\nIncidentally, this paragraph is sales 101. If you want to see\nit in action, go talk to a car dealer.[13]\nI know one very smooth founder who used to end investor meetings\nwith \"So, can I count you in?\" delivered as if it were \"Can you\npass the salt?\" Unless you're very smooth (if you're not sure...),\ndo not do this yourself. There is nothing more unconvincing, for\nan investor, than a nerdy founder trying to deliver the lines meant\nfor a smooth one.Investors are fine with funding nerds. So if you're a nerd, just\ntry to be a good nerd, rather than doing a bad imitation of a smooth\nsalesman.[14]\nIan Hogarth suggests a good way to tell how serious potential\ninvestors are: the resources they expend on you after the first\nmeeting. An investor who's seriously interested will already be\nworking to help you even before they've committed.[15]\nIn principle you might have to think about so-called \"signalling\nrisk.\" If a prestigious VC makes a small seed investment in you,\nwhat if they don't want to invest the next time you raise money?\nOther investors might assume that the VC knows you well, since\nthey're an existing investor, and if they don't want to invest in\nyour next round, that must mean you suck. The reason I say \"in\nprinciple\" is that in practice signalling hasn't been much of a\nproblem so far. It rarely arises, and in the few cases where it\ndoes, the startup in question usually is doing badly and is doomed\nanyway.If you have the luxury of choosing among seed investors, you can\nplay it safe by excluding VC firms. But it isn't critical to.[16]\nSometimes a competitor will deliberately threaten you with a\nlawsuit just as you start fundraising, because they know you'll\nhave to disclose the threat to potential investors and they hope\nthis will make it harder for you to raise money. If this happens\nit will probably frighten you more than investors. Experienced\ninvestors know about this trick, and know the actual lawsuits rarely\nhappen. So if you're attacked in this way, be forthright with\ninvestors. They'll be more alarmed if you seem evasive than if you\ntell them everything.[17]\nA related trick is to claim that they'll only invest contingently\non other investors doing so because otherwise you'd be \"undercapitalized.\"\nThis is almost always bullshit. They can't estimate your minimum\ncapital needs that precisely.[18]\nYou won't hire all those 20 people at once, and you'll probably\nhave some revenues before 18 months are out. But those too are\nacceptable or at least accepted additions to the margin for error.[19]\nType A fundraising is so much better that it might even be\nworth doing something different if it gets you there sooner. One\nYC founder told me that if he were a first-time founder again he'd\n\"leave ideas that are up-front capital intensive to founders with\nestablished reputations.\"[20]\nI don't know whether this happens because they're innumerate,\nor because they believe they have zero ability to predict startup\noutcomes (in which case this behavior at least wouldn't be irrational).\nIn either case the implications are similar.[21]\nIf you're a YC startup and you have an investor who for some\nreason insists that you decide the price, any YC partner can estimate\na market price for you.[22]\nYou should respond in kind when investors behave upstandingly\ntoo. When an investor makes you a clean offer with no deadline,\nyou have a moral obligation to respond promptly.[23]\nTell the investors talking to you about an A round about the\nsmaller investments you raise as you raise them. You owe them such\nupdates on your cap table, and this is also a good way to pressure\nthem to act. They won't like you raising other money and may\npressure you to stop, but they can't legitimately ask you to commit\nto them till they also commit to you. If they want you to stop\nraising money, the way to do it is to give you a series A termsheet\nwith a no-shop clause.You can relent a little if the potential series A investor has a\ngreat reputation and they're clearly working fast to get you a\ntermsheet, particularly if a third party like YC is involved to\nensure there are no misunderstandings. But be careful.[24]\nThe company is Weebly, which made it to profitability on a\nseed investment of $650k. They did try to raise a series A in the\nfall of 2008 but (no doubt partly because it was the fall of 2008)\nthe terms they were offered were so bad that they decided to skip\nraising an A round.[25]\nAnother advantage of having one founder take fundraising\nmeetings is that you never have to negotiate in real time, which\nis something inexperienced founders should avoid. One YC founder\ntold me:\n\n Investors are professional negotiators and can negotiate on the\n spot very easily. If only one founder is in the room, you can\n say \"I need to circle back with my co-founder\" before making any\n commitments. I used to do this all the time.\n\n[26]\nYou'll be lucky if fundraising feels pleasant enough to become\naddictive. More often you have to worry about the other\nextreme — becoming demoralized when investors reject you. As\none (very successful) YC founder wrote after reading a draft of\nthis:\n\n It's hard to mentally deal with the sheer scale of rejection in\n fundraising and if you are not in the right mindset you will fail.\n Users may love you but these supposedly smart investors may not\n understand you at all. At this point for me, rejection still\n rankles but I've come to accept that investors are just not super\n thoughtful for the most part and you need to play the game according\n to certain somewhat depressing rules (many of which you are\n listing) in order to win.\n\n[27]\nThe actual sentence in the King James Bible is \"Pride goeth\nbefore destruction, and an haughty spirit before a fall.\"Thanks to Slava Akhmechet, Sam Altman, Nate Blecharczyk,\nAdora Cheung, Bill Clerico, John Collison, Patrick Collison, Parker\nConrad, Ron Conway, Travis Deyle, Jason Freedman, Joe Gebbia, Mattan\nGriffel, Kevin Hale, Jacob Heller, Ian Hogarth, Justin Kan, Professor\nMoriarty, Nikhil Nirmel, David Petersen, Geoff Ralston, Joshua\nReeves, Yuri Sagalov, Emmett Shear, Rajat Suri, Garry Tan, and Nick\nTomarello for reading drafts of this." }, { "path": "data/PaulGrahamEssayMedium/guidetoinvestors.txt", "content": "April 2007(This essay is derived from a keynote talk at the 2007 ASES Summit\nat Stanford.)The world of investors is a foreign one to most hackers—partly\nbecause investors are so unlike hackers, and partly because they\ntend to operate in secret. I've been dealing with this world for\nmany years, both as a founder and an investor, and I still don't\nfully understand it.In this essay I'm going to list some of the more surprising things\nI've learned about investors. Some I only learned in the past year.Teaching hackers how to deal with investors is probably the second\nmost important thing we do at Y Combinator. The most important\nthing for a startup is to make something good. But everyone knows\nthat's important. The dangerous thing about investors is that\nhackers don't know how little they know about this strange world.1. The investors are what make a startup hub.About a year ago I tried to figure out what you'd need to reproduce\nSilicon Valley. I decided the \ncritical ingredients were rich people\nand nerds—investors and founders. People are all you need to\nmake technology, and all the other people will move.If I had to narrow that down, I'd say investors are the limiting\nfactor. Not because they contribute more to the startup, but simply\nbecause they're least willing to move. They're rich. They're not\ngoing to move to Albuquerque just because there are some smart\nhackers there they could invest in. Whereas hackers will move to\nthe Bay Area to find investors.2. Angel investors are the most critical.There are several types of investors. The two main categories are\nangels and VCs: VCs invest other people's money, and angels invest\ntheir own.Though they're less well known, the angel investors are probably\nthe more critical ingredient in creating a silicon valley. Most\ncompanies that VCs invest in would never have made it that far if angels\nhadn't invested first. VCs say between half and three quarters of\ncompanies that raise series A rounds have taken some outside\ninvestment already.\n[1]Angels are willing to fund riskier projects than VCs. They also\ngive valuable advice, because (unlike VCs) many have been startup\nfounders themselves.Google's story shows the key role angels play. A lot of people know\nGoogle raised money from Kleiner and Sequoia. What most don't realize\nis how late. That VC round was a series B round; the premoney\nvaluation was $75 million. Google was already a successful company\nat that point. Really, Google was funded with angel money.It may seem odd that the canonical Silicon Valley startup was funded\nby angels, but this is not so surprising. Risk is always proportionate\nto reward. So the most successful startup of all is likely to have\nseemed an extremely risky bet at first, and that is exactly the\nkind VCs won't touch.Where do angel investors come from? From other startups. So startup\nhubs like Silicon Valley benefit from something like the marketplace\neffect, but shifted in time: startups are there because startups\nwere there.3. Angels don't like publicity.If angels are so important, why do we hear more about VCs? Because\nVCs like publicity. They need to market themselves to the investors\nwho are their \"customers\"—the endowments and pension funds and\nrich families whose money they invest—and also to founders who\nmight come to them for funding.Angels don't need to market themselves to investors because they\ninvest their own money. Nor do they want to market themselves to\nfounders: they don't want random people pestering them with business\nplans. Actually, neither do VCs. Both angels and VCs get deals\nalmost exclusively through personal introductions. \n[2]The reason VCs want a strong brand is not to draw in more business\nplans over the transom, but so they win deals when competing\nagainst other VCs. Whereas angels are rarely in direct competition,\nbecause (a) they do fewer deals, (b) they're happy to split them,\nand (c) they invest at a point where the stream is broader.4. Most investors, especially VCs, are not like founders.Some angels are, or were, hackers. But most VCs are a different\ntype of people: they're dealmakers.If you're a hacker, here's a thought experiment you can run to\nunderstand why there are basically no hacker VCs: How would you\nlike a job where you never got to make anything, but instead spent\nall your time listening to other people pitch (mostly terrible)\nprojects, deciding whether to fund them, and sitting on their boards\nif you did? That would not be fun for most hackers. Hackers like\nto make things. This would be like being an administrator.Because most VCs are a different species of people from\nfounders, it's hard to know what they're thinking. If you're a\nhacker, the last time you had to deal with these guys was in high\nschool. Maybe in college you walked past their fraternity on your\nway to the lab. But don't underestimate them. They're as expert\nin their world as you are in yours. What they're good at is reading\npeople, and making deals work to their advantage. Think twice\nbefore you try to beat them at that.5. Most investors are momentum investors.Because most investors are dealmakers rather than technology people,\nthey generally don't understand what you're doing. I knew as a\nfounder that most VCs didn't get technology. I also knew some made\na lot of money. And yet it never occurred to me till recently to\nput those two ideas together and ask \"How can VCs make money by\ninvesting in stuff they don't understand?\"The answer is that they're like momentum investors. You can (or\ncould once) make a lot of money by noticing sudden changes in stock\nprices. When a stock jumps upward, you buy, and when it suddenly\ndrops, you sell. In effect you're insider trading, without knowing\nwhat you know. You just know someone knows something, and that's\nmaking the stock move.This is how most venture investors operate. They don't try to look\nat something and predict whether it will take off. They win by\nnoticing that something is taking off a little sooner than everyone\nelse. That generates almost as good returns as actually being able\nto pick winners. They may have to pay a little more than they would\nif they got in at the very beginning, but only a little.Investors always say what they really care about is the team.\nActually what they care most about is your traffic, then what other\ninvestors think, then the team. If you don't yet have any traffic,\nthey fall back on number 2, what other investors think. And this,\nas you can imagine, produces wild oscillations in the \"stock price\"\nof a startup. One week everyone wants you, and they're begging not\nto be cut out of the deal. But all it takes is for one big investor\nto cool on you, and the next week no one will return your phone\ncalls. We regularly have startups go from hot to cold or cold to\nhot in a matter of days, and literally nothing has changed.There are two ways to deal with this phenomenon. If you're feeling\nreally confident, you can try to ride it. You can start by asking\na comparatively lowly VC for a small amount of money, and then after\ngenerating interest there, ask more prestigious VCs for larger\namounts, stirring up a crescendo of buzz, and then \"sell\" at the\ntop. This is extremely risky, and takes months even if you succeed.\nI wouldn't try it myself. My advice is to err on the side of safety:\nwhen someone offers you a decent deal, just take it and get on with\nbuilding the company. Startups win or lose based on the quality\nof their product, not the quality of their funding deals.6. Most investors are looking for big hits.Venture investors like companies that could go public. That's where\nthe big returns are. They know the odds of any individual startup\ngoing public are small, but they want to invest in those that at\nleast have a chance of going public.Currently the way VCs seem to operate is to invest in a bunch of\ncompanies, most of which fail, and one of which is Google. Those\nfew big wins compensate for losses on their other investments. What this\nmeans is that most VCs will only invest in you if you're a potential\nGoogle. They don't care about companies that are a safe bet to be\nacquired for $20 million. There needs to be a chance, however\nsmall, of the company becoming really big.Angels are different in this respect. They're happy to invest in\na company where the most likely outcome is a $20 million acquisition\nif they can do it at a low enough valuation. But of course they\nlike companies that could go public too. So having an ambitious\nlong-term plan pleases everyone.If you take VC money, you have to mean it, because the structure\nof VC deals prevents early acquisitions. If you take VC money,\nthey won't let you sell early.7. VCs want to invest large amounts.The fact that they're running investment funds makes VCs want to\ninvest large amounts. A typical VC fund is now hundreds of millions\nof dollars. If $400 million has to be invested by 10 partners,\nthey have to invest $40 million each. VCs usually sit on the boards\nof companies they fund. If the average deal size was $1 million,\neach partner would have to sit on 40 boards, which would not be\nfun. So they prefer bigger deals, where they can put a lot of money\nto work at once.VCs don't regard you as a bargain if you don't need a lot of money.\nThat may even make you less attractive, because it means their\ninvestment creates less of a barrier to entry for competitors.Angels are in a different position because they're investing their\nown money. They're happy to invest small amounts—sometimes as\nlittle as $20,000—as long as the potential returns look good\nenough. So if you're doing something inexpensive, go to angels.8. Valuations are fiction.VCs admit that valuations are an artifact. They decide how much\nmoney you need and how much of the company they want, and those two\nconstraints yield a valuation.Valuations increase as the size of the investment does. A company\nthat an angel is willing to put $50,000 into at a valuation of a\nmillion can't take $6 million from VCs at that valuation. That\nwould leave the founders less than a seventh of the company between\nthem (since the option pool would also come out of that seventh).\nMost VCs wouldn't want that, which is why you never hear of deals\nwhere a VC invests $6 million at a premoney valuation of $1 million.If valuations change depending on the amount invested, that shows\nhow far they are from reflecting any kind of value of the company.Since valuations are made up, founders shouldn't care too much about\nthem. That's not the part to focus on. In fact, a high valuation\ncan be a bad thing. If you take funding at a premoney valuation\nof $10 million, you won't be selling the company for 20. You'll\nhave to sell for over 50 for the VCs to get even a 5x return, which\nis low to them. More likely they'll want you to hold out for 100.\nBut needing to get a high price decreases the chance of getting\nbought at all; many companies can buy you for $10 million, but only\na handful for 100. And since a startup is like a pass/fail course\nfor the founders, what you want to optimize is your chance of a\ngood outcome, not the percentage of the company you keep.So why do founders chase high valuations? They're tricked by\nmisplaced ambition. They feel they've achieved more if they get a\nhigher valuation. They usually know other founders, and if they\nget a higher valuation they can say \"mine is bigger than yours.\"\nBut funding is not the real test. The real test is the final outcome\nfor the founder, and getting too high a valuation may just make a\ngood outcome less likely.The one advantage of a high valuation is that you get less dilution.\nBut there is another less sexy way to achieve that: just take less\nmoney.9. Investors look for founders like the current stars.Ten years ago investors were looking for the next Bill Gates. This\nwas a mistake, because Microsoft was a very anomalous startup. They\nstarted almost as a contract programming operation, and the reason\nthey became huge was that IBM happened to drop the PC standard in\ntheir lap.Now all the VCs are looking for the next Larry and Sergey. This\nis a good trend, because Larry and Sergey are closer to the ideal\nstartup founders.Historically investors thought it was important for a founder to\nbe an expert in business. So they were willing to fund teams of\nMBAs who planned to use the money to pay programmers to build their\nproduct for them. This is like funding Steve Ballmer in the hope\nthat the programmer he'll hire is Bill Gates—kind of backward,\nas the events of the Bubble showed. Now most VCs know they should\nbe funding technical guys. This is more pronounced among the very\ntop funds; the lamer ones still want to fund MBAs.If you're a hacker, it's good news that investors are looking for\nLarry and Sergey. The bad news is, the only investors who can do\nit right are the ones who knew them when they were a\ncouple of CS grad students, not the confident media stars they are\ntoday. What investors still don't get is how clueless and tentative\ngreat founders can seem at the very beginning.10. The contribution of investors tends to be underestimated.Investors do more for startups than give them money. They're helpful\nin doing deals and arranging introductions, and some of the smarter\nones, particularly angels, can give good advice about the product.In fact, I'd say what separates the great investors from the mediocre\nones is the quality of their advice. Most investors give advice,\nbut the top ones give good advice.Whatever help investors give a startup tends to be underestimated.\nIt's to everyone's advantage to let the world think the founders\nthought of everything. The goal of the investors is for the company\nto become valuable, and the company seems more valuable if it seems\nlike all the good ideas came from within.This trend is compounded by the obsession that the press has with\nfounders. In a company founded by two people, 10% of the ideas\nmight come from the first guy they hire. Arguably they've done a\nbad job of hiring otherwise. And yet this guy will be almost\nentirely overlooked by the press.I say this as a founder: the contribution of founders is always\noverestimated. The danger here is that new founders, looking at\nexisting founders, will think that they're supermen that one couldn't\npossibly equal oneself. Actually they have a hundred different\ntypes of support people just offscreen making the whole show possible.\n[3]11. VCs are afraid of looking bad.I've been very surprised to discover how timid most VCs are. They\nseem to be afraid of looking bad to their partners, and perhaps\nalso to the limited partners—the people whose money they invest.You can measure this fear in how much less risk VCs are willing to\ntake. You can tell they won't make investments for their fund that\nthey might be willing to make themselves as angels. Though it's\nnot quite accurate to say that VCs are less willing to take risks.\nThey're less willing to do things that might look bad. That's not\nthe same thing.For example, most VCs would be very reluctant to invest in a startup\nfounded by a pair of 18 year old hackers, no matter how brilliant,\nbecause if the startup failed their partners could turn on them and\nsay \"What, you invested $x million of our money in a pair of 18\nyear olds?\" Whereas if a VC invested in a startup founded by\nthree former banking executives in their 40s who planned to outsource\ntheir product development—which to my mind is actually a lot\nriskier than investing in a pair of really smart 18 year olds—he\ncouldn't be faulted, if it failed, for making such an apparently\nprudent investment.As a friend of mine said, \"Most VCs can't do anything that would\nsound bad to the kind of doofuses who run pension funds.\" Angels\ncan take greater risks because they don't have to answer to anyone.12. Being turned down by investors doesn't mean much.Some founders are quite dejected when they get turned down by\ninvestors. They shouldn't take it so much to heart. To start with,\ninvestors are often wrong. It's hard to think of a successful\nstartup that wasn't turned down by investors at some point. Lots\nof VCs rejected Google. So obviously the reaction of investors is\nnot a very meaningful test.Investors will often reject you for what seem to be superficial\nreasons. I read of one VC who \nturned\ndown a startup simply because\nthey'd given away so many little bits of stock that the deal required\ntoo many signatures to close. \n[4]\nThe reason investors can get away\nwith this is that they see so many deals. It doesn't matter if\nthey underestimate you because of some surface imperfection, because\nthe next best deal will be almost as good. \nImagine picking out\napples at a grocery store. You grab one with a little bruise.\nMaybe it's just a surface bruise, but why even bother checking when\nthere are so many other unbruised apples to choose from?Investors would be the first to admit they're often wrong. So when\nyou get rejected by investors, don't think \"we suck,\" but instead\nask \"do we suck?\" Rejection is a question, not an answer.13. Investors are emotional.I've been surprised to discover how emotional investors can be.\nYou'd expect them to be cold and calculating, or at least businesslike,\nbut often they're not. I'm not sure if it's their position of power\nthat makes them this way, or the large sums of money involved, but\ninvestment negotiations can easily turn personal. If you offend\ninvestors, they'll leave in a huff.A while ago an eminent VC firm offered a series A round to a startup\nwe'd seed funded. Then they heard a rival VC firm was also interested.\nThey were so afraid that they'd be rejected in favor of this other\nfirm that they gave the startup what's known as an \"exploding\ntermsheet.\" They had, I think, 24 hours to say yes or no, or the\ndeal was off. Exploding termsheets are a somewhat dubious device,\nbut not uncommon. What surprised me was their reaction when I\ncalled to talk about it. I asked if they'd still be interested in\nthe startup if the rival VC didn't end up making an offer, and they\nsaid no. What rational basis could they have had for saying that?\nIf they thought the startup was worth investing in, what difference\nshould it make what some other VC thought? Surely it was their\nduty to their limited partners simply to invest in the best\nopportunities they found; they should be delighted if the other VC\nsaid no, because it would mean they'd overlooked a good opportunity.\nBut of course there was no rational basis for their decision. They\njust couldn't stand the idea of taking this rival firm's rejects.In this case the exploding termsheet was not (or not only) a tactic\nto pressure the startup. It was more like the high school trick\nof breaking up with someone before they can break up with you. In\nan earlier essay I said that VCs were a lot like high school girls.\nA few VCs have joked about that characterization, but none have\ndisputed it.14. The negotiation never stops till the closing.Most deals, for investment or acquisition, happen in two phases.\nThere's an initial phase of negotiation about the big questions.\nIf this succeeds you get a termsheet, so called because it outlines\nthe key terms of a deal. A termsheet is not legally binding,\nbut it is a definite step. It's supposed to mean that a\ndeal is going to happen, once the lawyers work out all the details.\nIn theory these details are minor ones; by definition all the\nimportant points are supposed to be covered in the termsheet.Inexperience and wishful thinking combine to make founders feel\nthat when they have a termsheet, they have a deal. They want there\nto be a deal; everyone acts like they have a deal; so there must\nbe a deal. But there isn't and may not be for several months. A\nlot can change for a startup in several months. It's not uncommon\nfor investors and acquirers to get buyer's remorse. So you have\nto keep pushing, keep selling, all the way to the close. Otherwise\nall the \"minor\" details left unspecified in the termsheet will be\ninterpreted to your disadvantage. The other side may even break\nthe deal; if they do that, they'll usually seize on some technicality\nor claim you misled them, rather than admitting they changed their\nminds.It can be hard to keep the pressure on an investor or acquirer all\nthe way to the closing, because the most effective pressure is\ncompetition from other investors or acquirers, and these tend to\ndrop away when you get a termsheet. You should try to stay as close\nfriends as you can with these rivals, but the most important thing\nis just to keep up the momentum in your startup. The investors or\nacquirers chose you because you seemed hot. Keep doing whatever\nmade you seem hot. Keep releasing new features; keep getting new\nusers; keep getting mentioned in the press and in blogs.15. Investors like to co-invest.I've been surprised how willing investors are to split deals. You\nmight think that if they found a good deal they'd want it all to\nthemselves, but they seem positively eager to syndicate. This is\nunderstandable with angels; they invest on a smaller scale and don't\nlike to have too much money tied up in any one deal. But VCs also\nshare deals a lot. Why?Partly I think this is an artifact of the rule I quoted earlier:\nafter traffic, VCs care most what other VCs think. A deal that has\nmultiple VCs interested in it is more likely to close, so of deals\nthat close, more will have multiple investors.There is one rational reason to want multiple VCs in a deal: Any\ninvestor who co-invests with you is one less investor who could\nfund a competitor. Apparently Kleiner and Sequoia didn't like\nsplitting the Google deal, but it did at least have the advantage,\nfrom each one's point of view, that there probably wouldn't be a\ncompetitor funded by the other. Splitting deals thus has similar\nadvantages to confusing paternity.But I think the main reason VCs like splitting deals is the fear\nof looking bad. If another firm shares the deal, then in the event\nof failure it will seem to have been a prudent choice—a consensus\ndecision, rather than just the whim of an individual partner.16. Investors collude.Investing is not covered by antitrust law. At least, it better not\nbe, because investors regularly do things that would be illegal\notherwise. I know personally of cases where one investor has talked\nanother out of making a competitive offer, using the promise of\nsharing future deals.In principle investors are all competing for the same deals, but\nthe spirit of cooperation is stronger than the spirit of competition.\nThe reason, again, is that there are so many deals. Though a\nprofessional investor may have a closer relationship with a founder\nhe invests in than with other investors, his relationship with the\nfounder is only going to last a couple years, whereas his relationship\nwith other firms will last his whole career. There isn't so much\nat stake in his interactions with other investors, but there will\nbe a lot of them. Professional investors are constantly trading\nlittle favors.Another reason investors stick together is to preserve the power\nof investors as a whole. So you will not, as of this writing, be\nable to get investors into an auction for your series A round.\nThey'd rather lose the deal than establish a precedent of VCs\ncompetitively bidding against one another. An efficient startup\nfunding market may be coming in the distant future; things tend to\nmove in that direction; but it's certainly not here now.\n17. Large-scale investors care about their portfolio, not any\nindividual company.The reason startups work so well is that everyone with power also\nhas equity. The only way any of them can succeed is if they all\ndo. This makes everyone naturally pull in the same direction,\nsubject to differences of opinion about tactics.The problem is, larger scale investors don't have exactly the same\nmotivation. Close, but not identical. They don't need any given\nstartup to succeed, like founders do, just their portfolio as a\nwhole to. So in borderline cases the rational thing for them to\ndo is to sacrifice unpromising startups.Large-scale investors tend to put startups in three categories:\nsuccesses, failures, and the \"living dead\"—companies that are\nplugging along but don't seem likely in the immediate future to get\nbought or go public. To the founders, \"living dead\" sounds harsh.\nThese companies may be far from failures by ordinary standards. But\nthey might as well be from a venture investor's point of view, and\nthey suck up just as much time and attention as the successes. So\nif such a company has two possible strategies, a conservative one\nthat's slightly more likely to work in the end, or a risky one that\nwithin a short time will either yield a giant success or kill the\ncompany, VCs will push for the kill-or-cure option. To them the\ncompany is already a write-off. Better to have resolution, one way\nor the other, as soon as possible.If a startup gets into real trouble, instead of trying to save it\nVCs may just sell it at a low price to another of their portfolio\ncompanies. Philip Greenspun said in Founders at Work that Ars Digita's VCs did this to them.18. Investors have different risk profiles from founders.Most people would rather a 100% chance of $1 million than a 20%\nchance of $10 million. Investors are rich enough to be rational\nand prefer the latter. So they'll always tend to encourage founders\nto keep rolling the dice. If a company is doing well, investors\nwill want founders to turn down most acquisition offers. And indeed,\nmost startups that turn down acquisition offers ultimately do better.\nBut it's still hair-raising for the founders, because they might\nend up with nothing. When someone's offering to buy you for a price\nat which your stock is worth $5 million, saying no is equivalent\nto having $5 million and betting it all on one spin of the roulette\nwheel.Investors will tell you the company is worth more. And they may\nbe right. But that doesn't mean it's wrong to sell. Any financial\nadvisor who put all his client's assets in the stock of a single,\nprivate company would probably lose his license for it.More and more, investors are letting founders cash out partially.\nThat should correct the problem. Most founders have such low standards\nthat they'll feel rich with a sum that doesn't seem huge to investors.\nBut this custom is spreading too slowly, because VCs are afraid of\nseeming irresponsible. No one wants to be the first VC to give\nsomeone fuck-you money and then actually get told \"fuck you.\" But\nuntil this does start to happen, we know VCs are being too conservative.19. Investors vary greatly.Back when I was a founder I used to think all VCs were the same.\nAnd in fact they do all look \nthe same. They're all what hackers\ncall \"suits.\" But since I've been dealing with VCs more I've learned\nthat some suits are smarter than others.They're also in a business where winners tend to keep winning and\nlosers to keep losing. When a VC firm has been successful in the\npast, everyone wants funding from them, so they get the pick of all\nthe new deals. The self-reinforcing nature of the venture funding\nmarket means that the top ten firms live in a completely different\nworld from, say, the hundredth. As well as being smarter, they\ntend to be calmer and more upstanding; they don't need to do iffy\nthings to get an edge, and don't want to because they have more\nbrand to protect.There are only two kinds of VCs you want to take money from, if you\nhave the luxury of choosing: the \"top tier\" VCs, meaning about the\ntop 20 or so firms, plus a few new ones that are not among the top\n20 only because they haven't been around long enough.It's particularly important to raise money from a top firm if you're\na hacker, because they're more confident. That means they're less\nlikely to stick you with a business guy as CEO, like VCs used to\ndo in the 90s. If you seem smart and want to do it, they'll let\nyou run the company.20. Investors don't realize how much it costs to raise money from\nthem.Raising money is a huge time suck at just the point where startups\ncan least afford it. It's not unusual for it to take five or six\nmonths to close a funding round. Six weeks is fast. And raising\nmoney is not just something you can leave running as a background\nprocess. When you're raising money, it's inevitably the main focus\nof the company. Which means building the product isn't.Suppose a Y Combinator company starts talking to VCs after demo\nday, and is successful in raising money from them, closing the deal\nafter a comparatively short 8 weeks. Since demo day occurs after\n10 weeks, the company is now 18 weeks old. Raising money, rather\nthan working on the product, has been the company's main focus for\n44% of its existence. And mind you, this an example where things\nturned out well.When a startup does return to working on the product after a funding\nround finally closes, it's as if they were returning to work after\na months-long illness. They've lost most of their momentum.Investors have no idea how much they damage the companies they\ninvest in by taking so long to do it. But companies do. So there\nis a big opportunity here for a new kind of venture fund that invests\nsmaller amounts at lower valuations, but promises to either close\nor say no very quickly. If there were such a firm, I'd recommend\nit to startups in preference to any other, no matter how prestigious.\nStartups live on speed and momentum.21. Investors don't like to say no.The reason funding deals take so long to close is mainly that\ninvestors can't make up their minds. VCs are not big companies;\nthey can do a deal in 24 hours if they need to. But they usually\nlet the initial meetings stretch out over a couple weeks. The\nreason is the selection algorithm I mentioned earlier. Most don't\ntry to predict whether a startup will win, but to notice quickly\nthat it already is winning. They care what the market thinks of\nyou and what other VCs think of you, and they can't judge those\njust from meeting you.Because they're investing in things that (a) change fast and (b)\nthey don't understand, a lot of investors will reject you in a way\nthat can later be claimed not to have been a rejection. Unless you\nknow this world, you may not even realize you've been rejected.\nHere's a VC saying no:\n\n We're really excited about your project, and we want to keep in\n close touch as you develop it further.\n\nTranslated into more straightforward language, this means: We're\nnot investing in you, but we may change our minds if it looks like\nyou're taking off. Sometimes they're more candid and say explicitly\nthat they need to \"see some traction.\" They'll invest in you if\nyou start to get lots of users. But so would any VC. So all they're\nsaying is that you're still at square 1.Here's a test for deciding whether a VC's response was yes or no.\nLook down at your hands. Are you holding a termsheet?22. You need investors.Some founders say \"Who needs investors?\" Empirically the answer\nseems to be: everyone who wants to succeed. Practically every\nsuccessful startup takes outside investment at some point.Why? What the people who think they don't need investors forget is\nthat they will have competitors. The question is not whether you\nneed outside investment, but whether it could help you at all.\nIf the answer is yes, and you don't take investment, then competitors\nwho do will have an advantage over you. And in the startup world\na little advantage can expand into a lot.Mike Moritz famously said that he invested in Yahoo because he\nthought they had a few weeks' lead over their competitors. That\nmay not have mattered quite so much as he thought, because Google\ncame along three years later and kicked Yahoo's ass. But there is\nsomething in what he said. Sometimes a small lead can grow into\nthe yes half of a binary choice.Maybe as it gets cheaper to start a startup, it will start to be\npossible to succeed in a competitive market without outside funding. \nThere are certainly\ncosts to raising money. But as of this writing the empirical\nevidence says it's a net win.23. Investors like it when you don't need them.A lot of founders approach investors as if they needed their\npermission to start a company—as if it were like getting into\ncollege. But you don't need investors to start most companies;\nthey just make it easier.And in fact, investors greatly prefer it if you don't need them.\nWhat excites them, both consciously and unconsciously, is the sort\nof startup that approaches them saying \"the train's leaving the\nstation; are you in or out?\" not the one saying \"please can we have\nsome money to start a company?\"Most investors are \"bottoms\" in the sense that the startups they\nlike most are those that are rough with them. When Google stuck\nKleiner and Sequoia with a $75 million premoney valuation, their\nreaction was probably \"Ouch! That feels so good.\" And they were\nright, weren't they? That deal probably made them more than any\nother they've done.The thing is, VCs are pretty good at reading people. So don't try\nto act tough with them unless you really are the next Google, or\nthey'll see through you in a second. Instead of acting tough, what\nmost startups should do is simply always have a backup plan. Always\nhave some alternative plan for getting started if any given investor\nsays no. Having one is the best insurance against needing one.So you shouldn't start a startup that's expensive to start, because\nthen you'll be at the mercy of investors. If you ultimately want\nto do something that will cost a lot, start by doing a cheaper\nsubset of it, and expand your ambitions when and if you raise more\nmoney.Apparently the most likely animals to be left alive after a nuclear\nwar are cockroaches, because they're so hard to kill. That's what\nyou want to be as a startup, initially. Instead of a beautiful\nbut fragile flower that needs to have its stem in a plastic tube\nto support itself, better to be small, ugly, and indestructible.Notes[1]\nI may be underestimating VCs. They may play some behind the scenes \nrole in IPOs, which you ultimately need if you want to create a silicon \nvalley.[2]\nA few VCs have an email address you can send your business\nplan to, but the number of startups that get funded this way is\nbasically zero. You should always get a personal introduction—and \nto a partner, not an associate.[3]\nSeveral people have told us that the most valuable thing about \nstartup school \nwas that they got to see famous startup founders and realized\nthey were just ordinary guys. Though we're happy to provide this\nservice, this is not generally the way we pitch startup school to\npotential speakers.[4]\nActually this sounds to me like a VC who got buyer's remorse,\nthen used a technicality to get out of the deal. But it's telling\nthat it even seemed a plausible excuse.Thanks to Sam Altman, Paul Buchheit, Hutch Fishman, and Robert \nMorris for reading drafts of\nthis, and to Kenneth King of ASES for inviting me to speak.\nComment on this essay." }, { "path": "data/PaulGrahamEssayMedium/mit.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nOctober 2006(This essay is derived from a talk at MIT.)Till recently graduating seniors had two choices: get a job or go\nto grad school. I think there will increasingly be a third option:\nto start your own startup. But how common will that be?I'm sure the default will always be to get a job, but starting a\nstartup could well become as popular as grad school. In the late\n90s my professor friends used to complain that they couldn't get\ngrad students, because all the undergrads were going to work for\nstartups. I wouldn't be surprised if that situation returns, but\nwith one difference: this time they'll be starting their own\ninstead of going to work for other people's.The most ambitious students will at this point be asking: Why wait\ntill you graduate? Why not start a startup while you're in college?\nIn fact, why go to college at all? Why not start a startup instead?A year and a half ago I gave a talk \nwhere I said that the average age of the founders of\nYahoo, Google, and Microsoft was 24, and that if grad students could\nstart startups, why not undergrads? I'm glad I phrased that as a\nquestion, because now I can pretend it wasn't merely a rhetorical\none. At the time I couldn't imagine why there should be any lower\nlimit for the age of startup founders. Graduation is a bureaucratic\nchange, not a biological one. And certainly there are undergrads\nas competent technically as most grad students. So why shouldn't\nundergrads be able to start startups as well as grad students?I now realize that something does change at graduation: you lose a\nhuge excuse for failing. Regardless of how complex your life is,\nyou'll find that everyone else, including your family and friends,\nwill discard all the low bits and regard you as having a single\noccupation at any given time. If you're in college and have a\nsummer job writing software, you still read as a student. Whereas\nif you graduate and get a job programming, you'll be instantly\nregarded by everyone as a programmer.The problem with starting a startup while you're still in school\nis that there's a built-in escape hatch. If you start a startup\nin the summer between your junior and senior year, it reads to\neveryone as a summer job.\nSo if it goes nowhere, big deal; you return to school in the\nfall with all the other seniors; no one regards you as a failure,\nbecause your occupation is student, and you didn't fail at that.\nWhereas if you start a startup just one year later, after you\ngraduate, as long as you're not accepted to grad school in the fall\nthe startup reads to everyone as your occupation. You're\nnow a startup founder, so you have to do well at that.For nearly everyone, the opinion of one's peers is the most powerful\nmotivator of all—more powerful even than the nominal goal of most\nstartup founders, getting rich. \n[1]\nAbout a month into each funding\ncycle we have an event called Prototype Day where each startup\npresents to the others what they've got so far. You might think\nthey wouldn't need any more motivation. They're working on their\ncool new idea; they have funding for the immediate future; and\nthey're playing a game with only two outcomes: wealth or failure.\nYou'd think that would be motivation enough. And yet the prospect\nof a demo pushes most of them into a\nrush of activity.Even if you start a startup explicitly to get rich, the money you\nmight get seems pretty theoretical most of the time. What drives\nyou day to day is not wanting to look bad.You probably can't change that. Even if you could, I don't think\nyou'd want to; someone who really, truly doesn't care what his peers\nthink of him is probably a psychopath. So the best you can do is\nconsider this force like a wind, and set up your boat accordingly.\nIf you know your peers are going to push you in some direction,\nchoose good peers, and position yourself so they push you in a\ndirection you like.Graduation changes the prevailing winds, and those make a difference.\nStarting a startup is so hard\nthat it's a close call even for the ones that succeed. However\nhigh a startup may be flying now, it probably has a few leaves stuck\nin the landing gear from those trees it barely cleared at the end\nof the runway. In such a close game, the smallest increase in the\nforces against you can be enough to flick you over the edge into\nfailure.When we first started Y Combinator \nwe encouraged people to start\nstartups while they were still in college. That's partly because\nY Combinator began as a kind of summer program. We've kept the\nprogram shape—all of us having dinner together once a week turns\nout to be a good idea—but we've decided now\nthat the party line should be to tell people to wait till they\ngraduate.Does that mean you can't start a startup in college? Not at all.\nSam Altman, the co-founder of Loopt,\nhad just finished his sophomore year when we funded them, and Loopt\nis probably the most promising of all the startups we've funded so\nfar. But Sam Altman is a very unusual guy. Within about three\nminutes of meeting him, I remember thinking \"Ah, so this is what\nBill Gates must have been like when he was 19.\"If it can work to start a startup during college, why do\nwe tell people not to? For the same reason that the probably\napocryphal violinist, whenever he was asked to judge someone's\nplaying, would always say they didn't have enough talent to make\nit as a pro. Succeeding as a musician takes determination as well\nas talent, so this answer works out to be the right advice for\neveryone. The ones who are uncertain believe it and give up, and\nthe ones who are sufficiently determined think \"screw that, I'll\nsucceed anyway.\"So our official policy now is only to fund undergrads we can't talk\nout of it. And frankly, if you're not certain, you should wait.\nIt's not as if all the opportunities to start companies are going\nto be gone if you don't do it now. Maybe the window will close on\nsome idea you're working on, but that won't be the last idea you'll\nhave. For every idea that times out, new ones become feasible.\nHistorically the opportunities to start startups have only increased\nwith time.In that case, you might ask, why not wait longer? Why not go work\nfor a while, or go to grad school, and then start a startup? And\nindeed, that might be a good idea. If I had to pick the sweet spot\nfor startup founders, based on who we're most excited to see\napplications from, I'd say it's probably the mid-twenties. Why?\nWhat advantages does someone in their mid-twenties have over someone\nwho's 21? And why isn't it older? What can 25 year olds do that\n32 year olds can't? Those turn out to be questions worth examining.PlusIf you start a startup soon after college, you'll be a young founder\nby present standards, so you should know what the relative advantages\nof young founders are. They're not what you might think. As a\nyoung founder your strengths are: stamina, poverty, rootlessness,\ncolleagues, and ignorance.The importance of stamina shouldn't be surprising. If you've heard\nanything about startups you've probably heard about the long hours.\nAs far as I can tell these are universal. I can't think of any\nsuccessful startups whose founders worked 9 to 5. And it's\nparticularly necessary for younger founders to work long hours\nbecause they're probably not as efficient as they'll be later.Your second advantage, poverty, might not sound like an advantage,\nbut it is a huge one. Poverty implies you can live cheaply,\nand this is critically important for startups. Nearly every startup\nthat fails, fails by running out of money. It's a little misleading\nto put it this way, because there's usually some other underlying\ncause. But regardless of the source of your problems, a low burn\nrate gives you more opportunity to recover from them. And since\nmost startups make all kinds of mistakes at first, room to recover\nfrom mistakes is a valuable thing to have.Most startups end up doing something different than they planned.\nThe way the successful ones find something that works is by trying\nthings that don't. So the worst thing you can do in a startup is\nto have a rigid, pre-ordained plan and then start spending a lot\nof money to implement it. Better to operate cheaply and give your\nideas time to evolve.Recent grads can live on practically nothing, and this gives you\nan edge over older founders, because the main cost in software\nstartups is people. The guys with kids and mortgages are at a\nreal disadvantage. This is one reason I'd bet on the 25 year old\nover the 32 year old. The 32 year old probably is a better programmer,\nbut probably also has a much more expensive life. Whereas a 25\nyear old has some work experience (more on that later) but can live\nas cheaply as an undergrad.Robert Morris and I were 29 and 30 respectively when we started\nViaweb, but fortunately we still lived like 23 year olds. We both had\nroughly zero assets. I would have loved to have a mortgage,\nsince that would have meant I had a house. But in retrospect\nhaving nothing turned out to be convenient. I wasn't tied down and\nI was used to living cheaply.Even more important than living cheaply, though, is thinking cheaply.\nOne reason the Apple II was so popular was that it was cheap. The\ncomputer itself was cheap, and it used cheap, off-the-shelf peripherals\nlike a cassette tape recorder for data storage and a TV as a monitor.\nAnd you know why? Because Woz designed this computer for himself,\nand he couldn't afford anything more.We benefitted from the same phenomenon. Our prices were\ndaringly low for the time. The top level of service was\n$300 a month, which was an order of magnitude below the norm. In\nretrospect this was a smart move, but we didn't do it because we\nwere smart. $300 a month seemed like a lot of money to us. Like\nApple, we created something inexpensive, and therefore popular,\nsimply because we were poor.A lot of startups have that form: someone comes along and makes\nsomething for a tenth or a hundredth of what it used to cost, and\nthe existing players can't follow because they don't even want to\nthink about a world in which that's possible. Traditional long\ndistance carriers, for example, didn't even want to think about\nVoIP. (It was coming, all the same.) Being poor helps in this\ngame, because your own personal bias points in the same direction\ntechnology evolves in.The advantages of rootlessness are similar to those of poverty.\nWhen you're young you're more mobile—not just because you don't\nhave a house or much stuff, but also because you're less likely to\nhave serious relationships. This turns out to be important, because\na lot of startups involve someone moving.The founders of Kiko, for example, are now en route to the Bay Area\nto start their next startup. It's a better place for what they\nwant to do. And it was easy for them to decide to go, because\nneither as far as I know has a serious girlfriend, and everything\nthey own will fit in one car—or more precisely, will either fit\nin one car or is crappy enough that they don't mind leaving it\nbehind.They at least were in Boston. What if they'd been in Nebraska,\nlike Evan Williams was at their age? Someone wrote recently that\nthe drawback of Y Combinator was that you had to move to participate.\nIt couldn't be any other way. The kind of conversations we have\nwith founders, we have to have in person. We fund a dozen startups\nat a time, and we can't be in a dozen places at once. But even if\nwe could somehow magically save people from moving, we wouldn't.\nWe wouldn't be doing founders a favor by letting them stay in\nNebraska. Places that aren't \nstartup hubs are toxic to startups.\nYou can tell that from indirect evidence. You can tell how hard\nit must be to start a startup in Houston or Chicago or Miami from\nthe microscopically small number, per capita, that succeed \nthere. I don't know exactly what's suppressing all the startups in these\ntowns—probably a hundred subtle little things—but something\nmust be.\n[2]Maybe this will change. Maybe the increasing cheapness of startups\nwill mean they'll be able to survive anywhere, instead of only in\nthe most hospitable environments. Maybe 37signals is the pattern\nfor the future. But maybe not. Historically there have always\nbeen certain towns that were centers for certain industries, and\nif you weren't in one of them you were at a disadvantage. So my\nguess is that 37signals is an anomaly. We're looking at a pattern\nmuch older than \"Web 2.0\" here.Perhaps the reason more startups per capita happen in the Bay Area\nthan Miami is simply that there are more founder-type people there.\nSuccessful startups are almost never started by one person. Usually\nthey begin with a conversation in which someone mentions that\nsomething would be a good idea for a company, and his friend says,\n\"Yeah, that is a good idea, let's try it.\" If you're missing that\nsecond person who says \"let's try it,\" the startup never happens.\nAnd that is another area where undergrads have an edge. They're\nsurrounded by people willing to say that. At a good college you're\nconcentrated together with a lot of other ambitious and technically\nminded people—probably more concentrated than you'll ever be\nagain. If your nucleus spits out a neutron, there's a good chance\nit will hit another nucleus.The number one question people ask us at Y Combinator is: Where can\nI find a co-founder? That's the biggest problem for someone starting\na startup at 30. When they were in school they knew a lot of good\nco-founders, but by 30 they've either lost touch with them or these\npeople are tied down by jobs they don't want to leave.Viaweb was an anomaly in this respect too. Though we were comparatively\nold, we weren't tied down by impressive jobs. I was trying to be\nan artist, which is not very constraining, and Robert, though 29,\nwas still in grad school due to a little interruption in his academic\ncareer back in 1988. So arguably the Worm made Viaweb possible.\nOtherwise Robert would have been a junior professor at that age,\nand he wouldn't have had time to work on crazy speculative projects\nwith me.Most of the questions people ask Y Combinator we have some kind of\nanswer for, but not the co-founder question. There is no good\nanswer. Co-founders really should be people you already know. And\nby far the best place to meet them is school. You have a large\nsample of smart people; you get to compare how they all perform on\nidentical tasks; and everyone's life is pretty fluid. A lot of\nstartups grow out of schools for this reason. Google, Yahoo, and\nMicrosoft, among others, were all founded by people who met in\nschool. (In Microsoft's case, it was high school.)Many students feel they should wait and get a little more experience\nbefore they start a company. All other things being equal, they\nshould. But all other things are not quite as equal as they look.\nMost students don't realize how rich they are in the scarcest\ningredient in startups, co-founders. If you wait too long, you may\nfind that your friends are now involved in some project they don't\nwant to abandon. The better they are, the more likely this is to\nhappen.One way to mitigate this problem might be to actively plan your\nstartup while you're getting those n years of experience. Sure,\ngo off and get jobs or go to grad school or whatever, but get\ntogether regularly to scheme, so the idea of starting a startup\nstays alive in everyone's brain. I don't know if this works, but\nit can't hurt to try.It would be helpful just to realize what an advantage you have as\nstudents. Some of your classmates are probably going to be successful\nstartup founders; at a great technical university, that is a near\ncertainty. So which ones? If I were you I'd look for the people\nwho are not just smart, but incurable \nbuilders. \nLook\nfor the people who keep starting projects, and finish at least some\nof them. That's what we look for. Above all else, above academic\ncredentials and even the idea you apply with, we look for people\nwho build things.The other place co-founders meet is at work. Fewer do than at\nschool, but there are things you can do to improve the odds. The\nmost important, obviously, is to work somewhere that has a lot of\nsmart, young people. Another is to work for a company located in\na startup hub. It will be easier to talk a co-worker into quitting\nwith you in a place where startups are happening all around you.You might also want to look at the employment agreement you sign\nwhen you get hired. Most will say that any ideas you think of while\nyou're employed by the company belong to them. In practice it's\nhard for anyone to prove what ideas you had when, so the line gets\ndrawn at code. If you're going to start a startup, don't write any\nof the code while you're still employed. Or at least discard any\ncode you wrote while still employed and start over. It's not so\nmuch that your employer will find out and sue you. It won't come\nto that; investors or acquirers or (if you're so lucky) underwriters\nwill nail you first. Between t = 0 and when you buy that yacht,\nsomeone is going to ask if any of your code legally belongs\nto anyone else, and you need to be able to say no.\n[3]The most overreaching employee agreement I've seen so far is Amazon's.\nIn addition to the usual clauses about owning your ideas, you also\ncan't be a founder of a startup that has another founder who worked\nat Amazon—even if you didn't know them or even work there at the\nsame time. I suspect they'd have a hard time enforcing this, but\nit's a bad sign they even try. There are plenty of other places\nto work; you may as well choose one that keeps more of your options\nopen.Speaking of cool places to work, there is of course Google. But I\nnotice something slightly frightening about Google: zero startups\ncome out of there. In that respect it's a black hole. People seem\nto like working at Google too much to leave. So if you hope to start\na startup one day, the evidence so far suggests you shouldn't work\nthere.I realize this seems odd advice. If they make your life so good\nthat you don't want to leave, why not work there? Because, in\neffect, you're probably getting a local maximum. You need a certain\nactivation energy to start a startup. So an employer who's fairly\npleasant to work for can lull you into staying indefinitely, even\nif it would be a net win for you to leave.\n[4]The best place to work, if you want to start a startup, is probably\na startup. In addition to being the right sort of experience, one\nway or another it will be over quickly. You'll either end up rich,\nin which case problem solved, or the startup will get bought, in\nwhich case it it will start to suck to work there and it will be\neasy to leave, or most likely, the thing will blow up and you'll\nbe free again.Your final advantage, ignorance, may not sound very useful. I\ndeliberately used a controversial word for it; you might equally\ncall it innocence. But it seems to be a powerful force. My Y\nCombinator co-founder Jessica Livingston is just about to publish\na book of interviews\nwith startup founders, and I noticed a remarkable pattern in them.\nOne after another said that if they'd known how hard it would be,\nthey would have been too intimidated to start.Ignorance can be useful when it's a counterweight to other forms\nof stupidity. It's useful in starting startups because you're\ncapable of more than you realize. Starting startups is harder than\nyou expect, but you're also capable of more than you expect, so\nthey balance out.Most people look at a company like Apple and think, how could I\never make such a thing? Apple is an institution, and I'm just a\nperson. But every institution was at one point just a handful of\npeople in a room deciding to start something. Institutions are\nmade up, and made up by people no different from you.I'm not saying everyone could start a startup. I'm sure most people\ncouldn't; I don't know much about the population at large. When\nyou get to groups I know well, like hackers, I can say more precisely.\nAt the top schools, I'd guess as many as a quarter of the CS majors\ncould make it as startup founders if they wanted.That \"if they wanted\" is an important qualification—so important\nthat it's almost cheating to append it like that—because once you\nget over a certain threshold of intelligence, which most CS majors\nat top schools are past, the deciding factor in whether you succeed\nas a founder is how much you want to. You don't have to be that\nsmart. If you're not a genius, just start a startup in some unsexy\nfield where you'll have less competition, like software for human\nresources departments. I picked that example at random, but I feel\nsafe in predicting that whatever they have now, it wouldn't take\ngenius to do better. There are a lot of people out there working\non boring stuff who are desperately in need of better software, so\nhowever short you think you fall of Larry and Sergey, you can ratchet\ndown the coolness of the idea far enough to compensate.As well as preventing you from being intimidated, ignorance can\nsometimes help you discover new ideas. Steve Wozniak\nput this very strongly:\n\n All the best things that I did at Apple came from (a) not having\n money and (b) not having done it before, ever. Every single thing\n that we came out with that was really great, I'd never once done\n that thing in my life.\n\nWhen you know nothing, you have to reinvent stuff for yourself, and\nif you're smart your reinventions may be better than what preceded\nthem. This is especially true in fields where the rules change.\nAll our ideas about software were developed in a time when processors\nwere slow, and memories and disks were tiny. Who knows what obsolete\nassumptions are embedded in the conventional wisdom? And the way\nthese assumptions are going to get fixed is not by explicitly\ndeallocating them, but by something more akin to garbage collection.\nSomeone ignorant but smart will come along and reinvent everything,\nand in the process simply fail to reproduce certain existing ideas.MinusSo much for the advantages of young founders. What about the\ndisadvantages? I'm going to start with what goes wrong and try to\ntrace it back to the root causes.What goes wrong with young founders is that they build stuff that\nlooks like class projects. It was only recently that we figured\nthis out ourselves. We noticed a lot of similarities between the\nstartups that seemed to be falling behind, but we couldn't figure\nout how to put it into words. Then finally we realized what it\nwas: they were building class projects.But what does that really mean? What's wrong with class projects?\nWhat's the difference between a class project and a real startup?\nIf we could answer that question it would be useful not just to\nwould-be startup founders but to students in general, because we'd\nbe a long way toward explaining the mystery of the so-called real\nworld.There seem to be two big things missing in class projects: (1) an\niterative definition of a real problem and (2) intensity.The first is probably unavoidable. Class projects will inevitably\nsolve fake problems. For one thing, real problems are rare and\nvaluable. If a professor wanted to have students solve real problems,\nhe'd face the same paradox as someone trying to give an example of\nwhatever \"paradigm\" might succeed the Standard Model of physics.\nThere may well be something that does, but if you could think of\nan example you'd be entitled to the Nobel Prize. Similarly, good\nnew problems are not to be had for the asking.In technology the difficulty is compounded by the fact that real\nstartups tend to discover the problem they're solving by a process\nof evolution. Someone has an idea for something; they build it;\nand in doing so (and probably only by doing so) they realize\nthe problem they should be solving is another one. Even if the\nprofessor let you change your project description on the fly, there\nisn't time enough to do that in a college class, or a market to\nsupply evolutionary pressures. So class\nprojects are mostly about implementation, which is the least\nof your problems in a startup.It's not just that in a startup you work on the idea as well as\nimplementation. The very implementation is different. Its main\npurpose is to refine the idea. Often the only value of most of the\nstuff you build in the first six months is that it proves your\ninitial idea was mistaken. And that's extremely valuable. If\nyou're free of a misconception that everyone else still shares,\nyou're in a powerful position. But you're not thinking that way\nabout a class project. Proving your initial plan was mistaken would\njust get you a bad grade. Instead of building stuff to throw away,\nyou tend to want every line of code to go toward that final goal\nof showing you did a lot of work.That leads to our second difference: the way class projects are\nmeasured. Professors will tend to judge you by the distance between\nthe starting point and where you are now. If someone has achieved\na lot, they should get a good grade. But customers will judge you\nfrom the other direction: the distance remaining between where you\nare now and the features they need. The market doesn't give a shit\nhow hard you worked. Users just want your software to do what they\nneed, and you get a zero otherwise. That is one of the most\ndistinctive differences between school and the real world: there\nis no reward for putting in a good effort. In fact, the whole\nconcept of a \"good effort\" is a fake idea adults invented to encourage\nkids. It is not found in nature.Such lies seem to be helpful to kids. But unfortunately when you\ngraduate they don't give you a list of all the lies they told you\nduring your education. You have to get them beaten out of you by\ncontact with the real world. And this is why so many jobs want\nwork experience. I couldn't understand that when I was in college.\nI knew how to program. In fact, I could tell I knew how to program\nbetter than most people doing it for a living. So what was this\nmysterious \"work experience\" and why did I need it?Now I know what it is, and part of the confusion is grammatical.\nDescribing it as \"work experience\" implies it's like experience\noperating a certain kind of machine, or using a certain programming\nlanguage. But really what work experience refers to is not some\nspecific expertise, but the elimination of certain habits left over\nfrom childhood.One of the defining qualities of kids is that they flake. When\nyou're a kid and you face some hard test, you can cry and say \"I\ncan't\" and they won't make you do it. Of course, no one can make\nyou do anything in the grownup world either. What they do instead\nis fire you. And when motivated by that\nyou find you can do a lot more than you realized. So one of the\nthings employers expect from someone with \"work experience\" is the\nelimination of the flake reflex—the ability to get things done,\nwith no excuses.The other thing you get from work experience is an understanding\nof what work is, and in particular, how intrinsically horrible it\nis. Fundamentally the equation is a brutal one: you have to spend\nmost of your waking hours doing stuff someone else wants, or starve.\nThere are a few places where the work is so interesting that this\nis concealed, because what other people want done happens to coincide\nwith what you want to work on. But you only have to imagine what\nwould happen if they diverged to see the underlying reality.It's not so much that adults lie to kids about this as never explain\nit. They never explain what the deal is with money. You know from\nan early age that you'll have some sort of job, because everyone\nasks what you're going to \"be\" when you grow up. What they\ndon't tell you is that as a kid you're sitting on the shoulders of\nsomeone else who's treading water, and that starting working means\nyou get thrown into the water on your own, and have to start treading\nwater yourself or sink. \"Being\" something is incidental; the\nimmediate problem is not to drown.The relationship between work and money tends to dawn on you only\ngradually. At least it did for me. One's first thought tends to\nbe simply \"This sucks. I'm in debt. Plus I have to get up on monday\nand go to work.\" Gradually you realize that these two things are\nas tightly connected as only a market can make them.So the most important advantage 24 year old founders have over 20\nyear old founders is that they know what they're trying to avoid.\nTo the average undergrad the idea of getting rich translates into\nbuying Ferraris, or being admired. To someone who has learned from\nexperience about the relationship between money and work, it\ntranslates to something way more important: it means you get to opt\nout of the brutal equation that governs the lives of 99.9% of people.\nGetting rich means you can stop treading water.Someone who gets this will work much harder at making a startup\nsucceed—with the proverbial energy of a drowning man, in fact.\nBut understanding the relationship between money and work also\nchanges the way you work. You don't get money just for working,\nbut for doing things other people want. Someone who's figured that\nout will automatically focus more on the user. And that cures the\nother half of the class-project syndrome. After you've been working\nfor a while, you yourself tend to measure what you've done the same\nway the market does.Of course, you don't have to spend years working to learn this\nstuff. If you're sufficiently perceptive you can grasp these things\nwhile you're still in school. Sam Altman did. He must have, because\nLoopt is no class project. And as his example suggests, this can\nbe valuable knowledge. At a minimum, if you get this stuff, you\nalready have most of what you gain from the \"work experience\"\nemployers consider so desirable. But of course if you really get\nit, you can use this information in a way that's more valuable to\nyou than that.NowSo suppose you think you might start a startup at some point, either\nwhen you graduate or a few years after. What should you do now?\nFor both jobs and grad school, there are ways to prepare while\nyou're in college. If you want to get a job when you graduate, you\nshould get summer jobs at places you'd like to work. If you want\nto go to grad school, it will help to work on research projects as\nan undergrad. What's the equivalent for startups? How do you keep\nyour options maximally open?One thing you can do while you're still in school is to learn how\nstartups work. Unfortunately that's not easy. Few if any colleges\nhave classes about startups. There may be business school classes\non entrepreneurship, as they call it over there, but these are\nlikely to be a waste of time. Business schools like to talk about\nstartups, but philosophically they're at the opposite end of the\nspectrum. Most books on startups also seem to be useless. I've\nlooked at a few and none get it right. Books in most fields are\nwritten by people who know the subject from experience, but for\nstartups there's a unique problem: by definition the founders of\nsuccessful startups don't need to write books to make money. As a\nresult most books on the subject end up being written by people who\ndon't understand it.So I'd be skeptical of classes and books. The way to learn about\nstartups is by watching them in action, preferably by working at\none. How do you do that as an undergrad? Probably by sneaking in\nthrough the back door. Just hang around a lot and gradually start\ndoing things for them. Most startups are (or should be) very\ncautious about hiring. Every hire increases the burn rate, and bad\nhires early on are hard to recover from. However, startups usually\nhave a fairly informal atmosphere, and there's always a lot that\nneeds to be done. If you just start doing stuff for them, many\nwill be too busy to shoo you away. You can thus gradually work\nyour way into their confidence, and maybe turn it into an official\njob later, or not, whichever you prefer. This won't work for all\nstartups, but it would work for most I've known.Number two, make the most of the great advantage of school: the\nwealth of co-founders. Look at the people around you and ask\nyourself which you'd like to work with. When you apply that test,\nyou may find you get surprising results. You may find you'd prefer\nthe quiet guy you've mostly ignored to someone who seems impressive\nbut has an attitude to match. I'm not suggesting you suck up to\npeople you don't really like because you think one day they'll be\nsuccessful. Exactly the opposite, in fact: you should only start\na startup with someone you like, because a startup will put your\nfriendship through a stress test. I'm just saying you should think\nabout who you really admire and hang out with them, instead of\nwhoever circumstances throw you together with.Another thing you can do is learn skills that will be useful to you\nin a startup. These may be different from the skills you'd learn\nto get a job. For example, thinking about getting a job will make\nyou want to learn programming languages you think employers want,\nlike Java and C++. Whereas if you start a startup, you get to pick\nthe language, so you have to think about which will actually let\nyou get the most done. If you use that test you might end up\nlearning Ruby or Python instead.\nBut the most important skill for a startup founder isn't a programming\ntechnique. It's a knack for understanding users and figuring out\nhow to give them what they want. I know I repeat this, but that's\nbecause it's so important. And it's a skill you can learn, though\nperhaps habit might be a better word. Get into the habit of thinking\nof software as having users. What do those users want? What would\nmake them say wow?This is particularly valuable for undergrads, because the concept\nof users is missing from most college programming classes. The way\nyou get taught programming in college would be like teaching writing\nas grammar, without mentioning that its purpose is to communicate\nsomething to an audience. Fortunately an audience for software is\nnow only an http request away. So in addition to the programming\nyou do for your classes, why not build some kind of website people\nwill find useful? At the very least it will teach you how to write\nsoftware with users. In the best case, it might not just be\npreparation for a startup, but the startup itself, like it was for\nYahoo and Google.Notes[1]\nEven the desire to protect one's children seems weaker, judging\nfrom things people have historically done to their kids\nrather than risk their community's disapproval. (I assume we still\ndo things that will be regarded in the future as barbaric, but\nhistorical abuses are easier for us to see.)[2]\nWorrying that Y Combinator makes founders move for 3 months\nalso suggests one underestimates how hard it is to start a startup.\nYou're going to have to put up with much greater inconveniences than\nthat.[3]\nMost employee agreements\nsay that any idea relating to the company's present or potential\nfuture business belongs to them. Often as not the second clause could\ninclude any possible startup, and anyone doing due diligence for an \ninvestor or acquirer will assume the worst.To be safe either (a) don't use code written while you\nwere still employed in your previous job, or (b) get your employer to\nrenounce, in writing, any claim to the code you write for your side \nproject. Many will consent to (b) rather than\nlose a prized employee. The downside is that you'll have to tell them\nexactly what your project does.[4]\nGeshke and Warnock only founded Adobe because Xerox ignored\nthem. If Xerox had used what they built, they would probably \nnever have left PARC.Thanks to Jessica Livingston and Robert Morris for reading\ndrafts of this, and to Jeff Arnold and the SIPB for inviting me to\nspeak.\n\nComment on this essay." }, { "path": "data/PaulGrahamEssayMedium/notnot.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nMarch 2007(This essay is derived from talks at the 2007 \nStartup School and the Berkeley CSUA.)We've now been doing Y Combinator long enough to have some data\nabout success rates. Our first batch, in the summer of 2005, had\neight startups in it. Of those eight, it now looks as if at least\nfour succeeded. Three have been acquired: \nReddit was a merger of\ntwo, Reddit and Infogami, and a third was acquired that we can't\ntalk about yet. Another from that batch was \nLoopt, which is doing\nso well they could probably be acquired in about ten minutes if\nthey wanted to.So about half the founders from that first summer, less than two\nyears ago, are now rich, at least by their standards. (One thing\nyou learn when you get rich is that there are many degrees of it.)I'm not ready to predict our success rate will stay as high as 50%.\nThat first batch could have been an anomaly. But we should be able\nto do better than the oft-quoted (and probably made\nup) standard figure of 10%. I'd feel safe aiming at 25%.Even the founders who fail don't seem to have such a bad time. Of\nthose first eight startups, three are now probably dead. In two\ncases the founders just went on to do other things at the end of\nthe summer. I don't think they were traumatized by the experience.\nThe closest to a traumatic failure was Kiko, whose founders kept\nworking on their startup for a whole year before being squashed by\nGoogle Calendar. But they ended up happy. They sold their software\non eBay for a quarter of a million dollars. After they paid back\ntheir angel investors, they had about a year's salary each. \n[1]\nThen they immediately went on to start a new and much more exciting\nstartup, Justin.TV.So here is an even more striking statistic: 0% of that first batch\nhad a terrible experience. They had ups and downs, like every\nstartup, but I don't think any would have traded it for a job in a\ncubicle. And that statistic is probably not an anomaly. Whatever\nour long-term success rate ends up being, I think the rate of people\nwho wish they'd gotten a regular job will stay close to 0%.The big mystery to me is: why don't more people start startups? If\nnearly everyone who does it prefers it to a regular job, and a\nsignificant percentage get rich, why doesn't everyone want to do\nthis? A lot of people think we get thousands of applications for\neach funding cycle. In fact we usually only get several hundred.\nWhy don't more people apply? And while it must seem to anyone\nwatching this world that startups are popping up like crazy, the\nnumber is small compared to the number of people with the necessary\nskills. The great majority of programmers still go straight from\ncollege to cubicle, and stay there.It seems like people are not acting in their own interest. What's\ngoing on? Well, I can answer that. Because of Y Combinator's\nposition at the very start of the venture funding process, we're\nprobably the world's leading experts on the psychology of people\nwho aren't sure if they want to start a company.There's nothing wrong with being unsure. If you're a hacker thinking\nabout starting a startup and hesitating before taking the leap,\nyou're part of a grand tradition. Larry and Sergey seem to have\nfelt the same before they started Google, and so did Jerry and Filo\nbefore they started Yahoo. In fact, I'd guess the most successful\nstartups are the ones started by uncertain hackers rather than\ngung-ho business guys.We have some evidence to support this. Several of the most successful\nstartups we've funded told us later that they only decided to apply\nat the last moment. Some decided only hours before the deadline.The way to deal with uncertainty is to analyze it into components.\nMost people who are reluctant to do something have about eight\ndifferent reasons mixed together in their heads, and don't know\nthemselves which are biggest. Some will be justified and some\nbogus, but unless you know the relative proportion of each, you\ndon't know whether your overall uncertainty is mostly justified or\nmostly bogus.So I'm going to list all the components of people's reluctance to\nstart startups, and explain which are real. Then would-be founders\ncan use this as a checklist to examine their own feelings.I admit my goal is to increase your self-confidence. But there are\ntwo things different here from the usual confidence-building exercise.\nOne is that I'm motivated to be honest. Most people in the\nconfidence-building business have already achieved their goal when\nyou buy the book or pay to attend the seminar where they tell you\nhow great you are. Whereas if I encourage people to start startups\nwho shouldn't, I make my own life worse. If I encourage too many\npeople to apply to Y Combinator, it just means more work for me,\nbecause I have to read all the applications.The other thing that's going to be different is my approach. Instead\nof being positive, I'm going to be negative. Instead of telling\nyou \"come on, you can do it\" I'm going to consider all the reasons\nyou aren't doing it, and show why most (but not all) should be\nignored. We'll start with the one everyone's born with.1. Too youngA lot of people think they're too young to start a startup. Many\nare right. The median age worldwide is about 27, so probably a\nthird of the population can truthfully say they're too young.What's too young? One of our goals with Y Combinator was to discover\nthe lower bound on the age of startup founders. It always seemed\nto us that investors were too conservative here—that they wanted\nto fund professors, when really they should be funding grad students\nor even undergrads.The main thing we've discovered from pushing the edge of this\nenvelope is not where the edge is, but how fuzzy it is. The outer\nlimit may be as low as 16. We don't look beyond 18 because people\nyounger than that can't legally enter into contracts. But the most\nsuccessful founder we've funded so far, Sam Altman, was 19 at the\ntime.Sam Altman, however, is an outlying data point. When he was 19,\nhe seemed like he had a 40 year old inside him. There are other\n19 year olds who are 12 inside.There's a reason we have a distinct word \"adult\" for people over a\ncertain age. There is a threshold you cross. It's conventionally\nfixed at 21, but different people cross it at greatly varying ages.\nYou're old enough to start a startup if you've crossed this threshold,\nwhatever your age.How do you tell? There are a couple tests adults use. I realized\nthese tests existed after meeting Sam Altman, actually. I noticed\nthat I felt like I was talking to someone much older. Afterward I\nwondered, what am I even measuring? What made him seem older?One test adults use is whether you still have the kid flake reflex.\nWhen you're a little kid and you're asked to do something hard, you\ncan cry and say \"I can't do it\" and the adults will probably let\nyou off. As a kid there's a magic button you can press by saying\n\"I'm just a kid\" that will get you out of most difficult situations.\nWhereas adults, by definition, are not allowed to flake. They still\ndo, of course, but when they do they're ruthlessly pruned.The other way to tell an adult is by how they react to a challenge.\nSomeone who's not yet an adult will tend to respond to a challenge\nfrom an adult in a way that acknowledges their dominance. If an\nadult says \"that's a stupid idea,\" a kid will either crawl away\nwith his tail between his legs, or rebel. But rebelling presumes\ninferiority as much as submission. The adult response to\n\"that's a stupid idea,\" is simply to look the other person in the\neye and say \"Really? Why do you think so?\"There are a lot of adults who still react childishly to challenges,\nof course. What you don't often find are kids who react to challenges\nlike adults. When you do, you've found an adult, whatever their\nage.2. Too inexperiencedI once wrote that startup founders should be at least 23, and that\npeople should work for another company for a few years before\nstarting their own. I no longer believe that, and what changed my\nmind is the example of the startups we've funded.I still think 23 is a better age than 21. But the best way to get\nexperience if you're 21 is to start a startup. So, paradoxically,\nif you're too inexperienced to start a startup, what you should do\nis start one. That's a way more efficient cure for inexperience\nthan a normal job. In fact, getting a normal job may actually make\nyou less able to start a startup, by turning you into a tame animal\nwho thinks he needs an office to work in and a product manager to\ntell him what software to write.What really convinced me of this was the Kikos. They started a\nstartup right out of college. Their inexperience caused them to\nmake a lot of mistakes. But by the time we funded their second\nstartup, a year later, they had become extremely formidable. They\nwere certainly not tame animals. And there is no way they'd have\ngrown so much if they'd spent that year working at Microsoft, or\neven Google. They'd still have been diffident junior programmers.So now I'd advise people to go ahead and start startups right out\nof college. There's no better time to take risks than when you're\nyoung. Sure, you'll probably fail. But even failure will get you\nto the ultimate goal faster than getting a job.It worries me a bit to be saying this, because in effect we're\nadvising people to educate themselves by failing at our expense,\nbut it's the truth.3. Not determined enoughYou need a lot of determination to succeed as a startup founder.\nIt's probably the single best predictor of success.Some people may not be determined enough to make it. It's\nhard for me to say for sure, because I'm so determined that I can't\nimagine what's going on in the heads of people who aren't. But I\nknow they exist.Most hackers probably underestimate their determination. I've seen\na lot become visibly more determined as they get used to running a \nstartup. I can think of\nseveral we've funded who would have been delighted at first to be\nbought for $2 million, but are now set on world domination.How can you tell if you're determined enough, when Larry and Sergey\nthemselves were unsure at first about starting a company? I'm\nguessing here, but I'd say the test is whether you're sufficiently\ndriven to work on your own projects. Though they may have been\nunsure whether they wanted to start a company, it doesn't seem as\nif Larry and Sergey were meek little research assistants, obediently\ndoing their advisors' bidding. They started projects of their own.\n4. Not smart enoughYou may need to be moderately smart to succeed as a startup founder.\nBut if you're worried about this, you're probably mistaken. If\nyou're smart enough to worry that you might not be smart enough to\nstart a startup, you probably are.And in any case, starting a startup just doesn't require that much\nintelligence. Some startups do. You have to be good at math to\nwrite Mathematica. But most companies do more mundane stuff where\nthe decisive factor is effort, not brains. Silicon Valley can warp\nyour perspective on this, because there's a cult of smartness here.\nPeople who aren't smart at least try to act that way. But if you\nthink it takes a lot of intelligence to get rich, try spending a\ncouple days in some of the fancier bits of New York or LA.If you don't think you're smart enough to start a startup doing\nsomething technically difficult, just write enterprise software.\nEnterprise software companies aren't technology companies, they're\nsales companies, and sales depends mostly on effort.5. Know nothing about businessThis is another variable whose coefficient should be zero. You\ndon't need to know anything about business to start a startup. The\ninitial focus should be the product. All you need to know in this\nphase is how to build things people want. If you succeed, you'll\nhave to think about how to make money from it. But this is so easy\nyou can pick it up on the fly.I get a fair amount of flak for telling founders just to make\nsomething great and not worry too much about making money. And yet\nall the empirical evidence points that way: pretty much 100% of\nstartups that make something popular manage to make money from it.\nAnd acquirers tell me privately that revenue is not what they buy\nstartups for, but their strategic value. Which means, because they\nmade something people want. Acquirers know the rule holds for them\ntoo: if users love you, you can always make money from that somehow,\nand if they don't, the cleverest business model in the world won't\nsave you.So why do so many people argue with me? I think one reason is that\nthey hate the idea that a bunch of twenty year olds could get rich\nfrom building something cool that doesn't make any money. They\njust don't want that to be possible. But how possible it is doesn't\ndepend on how much they want it to be.For a while it annoyed me to hear myself described as some kind of\nirresponsible pied piper, leading impressionable young hackers down\nthe road to ruin. But now I realize this kind of controversy is a\nsign of a good idea.The most valuable truths are the ones most people don't believe.\nThey're like undervalued stocks. If you start with them, you'll\nhave the whole field to yourself. So when you find an idea you\nknow is good but most people disagree with, you should not\nmerely ignore their objections, but push aggressively in that\ndirection. In this case, that means you should seek out ideas that\nwould be popular but seem hard to make money from.We'll bet a seed round you can't make something popular that we\ncan't figure out how to make money from.6. No cofounderNot having a cofounder is a real problem. A startup is too much\nfor one person to bear. And though we differ from other investors\non a lot of questions, we all agree on this. All investors, without\nexception, are more likely to fund you with a cofounder than without.We've funded two single founders, but in both cases we suggested\ntheir first priority should be to find a cofounder. Both did. But\nwe'd have preferred them to have cofounders before they applied.\nIt's not super hard to get a cofounder for a project that's just\nbeen funded, and we'd rather have cofounders committed enough to\nsign up for something super hard.If you don't have a cofounder, what should you do? Get one. It's\nmore important than anything else. If there's no one where you\nlive who wants to start a startup with you, move where there are\npeople who do. If no one wants to work with you on your current\nidea, switch to an idea people want to work on.If you're still in school, you're surrounded by potential cofounders.\nA few years out it gets harder to find them. Not only do you have\na smaller pool to draw from, but most already have jobs, and perhaps\neven families to support. So if you had friends in college you\nused to scheme about startups with, stay in touch with them as well\nas you can. That may help keep the dream alive.It's possible you could meet a cofounder through something like a\nuser's group or a conference. But I wouldn't be too optimistic.\nYou need to work with someone to know whether you want them as a\ncofounder. \n[2]The real lesson to draw from this is not how to find a cofounder,\nbut that you should start startups when you're young and there are\nlots of them around.7. No ideaIn a sense, it's not a problem if you don't have a good idea, because\nmost startups change their idea anyway. In the average Y Combinator\nstartup, I'd guess 70% of the idea is new at the end of the\nfirst three months. Sometimes it's 100%.In fact, we're so sure the founders are more important than the\ninitial idea that we're going to try something new this funding\ncycle. We're going to let people apply with no idea at all. If you\nwant, you can answer the question on the application form that asks\nwhat you're going to do with \"We have no idea.\" If you seem really\ngood we'll accept you anyway. We're confident we can sit down with\nyou and cook up some promising project.Really this just codifies what we do already. We put little weight\non the idea. We ask mainly out of politeness. The kind of question\non the application form that we really care about is the one where\nwe ask what cool things you've made. If what you've made is version\none of a promising startup, so much the better, but the main thing\nwe care about is whether you're good at making things. Being lead\ndeveloper of a popular open source project counts almost as much.That solves the problem if you get funded by Y Combinator. What\nabout in the general case? Because in another sense, it is a problem\nif you don't have an idea. If you start a startup with no idea,\nwhat do you do next?So here's the brief recipe for getting startup ideas. Find something\nthat's missing in your own life, and supply that need—no matter\nhow specific to you it seems. Steve Wozniak built himself a computer;\nwho knew so many other people would want them? A need that's narrow\nbut genuine is a better starting point than one that's broad but\nhypothetical. So even if the problem is simply that you don't have\na date on Saturday night, if you can think of a way to fix that by\nwriting software, you're onto something, because a lot of other\npeople have the same problem.8. No room for more startupsA lot of people look at the ever-increasing number of startups and\nthink \"this can't continue.\" Implicit in their thinking is a\nfallacy: that there is some limit on the number of startups there\ncould be. But this is false. No one claims there's any limit on\nthe number of people who can work for salary at 1000-person companies.\nWhy should there be any limit on the number who can work for equity\nat 5-person companies? \n[3]Nearly everyone who works is satisfying some kind of need. Breaking\nup companies into smaller units doesn't make those needs go away.\nExisting needs would probably get satisfied more efficiently by a\nnetwork of startups than by a few giant, hierarchical organizations,\nbut I don't think that would mean less opportunity, because satisfying\ncurrent needs would lead to more. Certainly this tends to be the\ncase in individuals. Nor is there anything wrong with that. We\ntake for granted things that medieval kings would have considered\neffeminate luxuries, like whole buildings heated to spring temperatures\nyear round. And if things go well, our descendants will take for\ngranted things we would consider shockingly luxurious. There is\nno absolute standard for material wealth. Health care is a component\nof it, and that alone is a black hole. For the foreseeable future,\npeople will want ever more material wealth, so there is no limit\nto the amount of work available for companies, and for startups in\nparticular.Usually the limited-room fallacy is not expressed directly. Usually\nit's implicit in statements like \"there are only so many startups\nGoogle, Microsoft, and Yahoo can buy.\" Maybe, though the list of\nacquirers is a lot longer than that. And whatever you think of\nother acquirers, Google is not stupid. The reason big companies\nbuy startups is that they've created something valuable. And why\nshould there be any limit to the number of valuable startups companies\ncan acquire, any more than there is a limit to the amount of wealth\nindividual people want? Maybe there would be practical limits on\nthe number of startups any one acquirer could assimilate, but if\nthere is value to be had, in the form of upside that founders are\nwilling to forgo in return for an immediate payment, acquirers will\nevolve to consume it. Markets are pretty smart that way.9. Family to supportThis one is real. I wouldn't advise anyone with a family to start\na startup. I'm not saying it's a bad idea, just that I don't want\nto take responsibility for advising it. I'm willing to take\nresponsibility for telling 22 year olds to start startups. So what\nif they fail? They'll learn a lot, and that job at Microsoft will\nstill be waiting for them if they need it. But I'm not prepared\nto cross moms.What you can do, if you have a family and want to start a startup,\nis start a consulting business you can then gradually turn into a\nproduct business. Empirically the chances of pulling that off seem\nvery small. You're never going to produce Google this way. But at\nleast you'll never be without an income.Another way to decrease the risk is to join an existing startup\ninstead of starting your own. Being one of the first employees of\na startup is a lot like being a founder, in both the good ways and\nthe bad. You'll be roughly 1/n^2 founder, where n is your employee\nnumber.As with the question of cofounders, the real lesson here is to start\nstartups when you're young.10. Independently wealthyThis is my excuse for not starting a startup. Startups are stressful.\nWhy do it if you don't need the money? For every \"serial entrepreneur,\"\nthere are probably twenty sane ones who think \"Start another\ncompany? Are you crazy?\"I've come close to starting new startups a couple times, but I\nalways pull back because I don't want four years of my life to be\nconsumed by random schleps. I know this business well enough to\nknow you can't do it half-heartedly. What makes a good startup\nfounder so dangerous is his willingness to endure infinite schleps.There is a bit of a problem with retirement, though. Like a lot\nof people, I like to work. And one of the many weird little problems\nyou discover when you get rich is that a lot of the interesting\npeople you'd like to work with are not rich. They need to work at\nsomething that pays the bills. Which means if you want to have\nthem as colleagues, you have to work at something that pays the\nbills too, even though you don't need to. I think this is what\ndrives a lot of serial entrepreneurs, actually.That's why I love working on Y Combinator so much. It's an excuse\nto work on something interesting with people I like.11. Not ready for commitmentThis was my reason for not starting a startup for most of my twenties.\nLike a lot of people that age, I valued freedom most of all. I was\nreluctant to do anything that required a commitment of more than a\nfew months. Nor would I have wanted to do anything that completely\ntook over my life the way a startup does. And that's fine. If you\nwant to spend your time travelling around, or playing in a band,\nor whatever, that's a perfectly legitimate reason not to start a\ncompany.If you start a startup that succeeds, it's going to consume at least\nthree or four years. (If it fails, you'll be done a lot quicker.)\nSo you shouldn't do it if you're not ready for commitments on that\nscale. Be aware, though, that if you get a regular job, you'll\nprobably end up working there for as long as a startup would take,\nand you'll find you have much less spare time than you might expect.\nSo if you're ready to clip on that ID badge and go to that orientation\nsession, you may also be ready to start that startup.12. Need for structureI'm told there are people who need structure in their lives. This\nseems to be a nice way of saying they need someone to tell them\nwhat to do. I believe such people exist. There's plenty of empirical\nevidence: armies, religious cults, and so on. They may even be the\nmajority.If you're one of these people, you probably shouldn't start a\nstartup. In fact, you probably shouldn't even go to work for one.\nIn a good startup, you don't get told what to do very much. There\nmay be one person whose job title is CEO, but till the company has\nabout twelve people no one should be telling anyone what to do.\nThat's too inefficient. Each person should just do what they need\nto without anyone telling them.If that sounds like a recipe for chaos, think about a soccer team.\nEleven people manage to work together in quite complicated ways,\nand yet only in occasional emergencies does anyone tell anyone else\nwhat to do. A reporter once asked David Beckham if there were any\nlanguage problems at Real Madrid, since the players were from about\neight different countries. He said it was never an issue, because\neveryone was so good they never had to talk. They all just did the\nright thing.How do you tell if you're independent-minded enough to start a\nstartup? If you'd bristle at the suggestion that you aren't, then\nyou probably are.13. Fear of uncertaintyPerhaps some people are deterred from starting startups because\nthey don't like the uncertainty. If you go to work for Microsoft,\nyou can predict fairly accurately what the next few years will be\nlike—all too accurately, in fact. If you start a startup, anything\nmight happen.Well, if you're troubled by uncertainty, I can solve that problem\nfor you: if you start a startup, it will probably fail. Seriously, \nthough, this is not a bad way to think\nabout the whole experience. Hope for the best, but expect the\nworst. In the worst case, it will at least be interesting. In the\nbest case you might get rich.No one will blame you if the startup tanks, so long as you made a\nserious effort. There may once have been a time when employers\nwould regard that as a mark against you, but they wouldn't now. I\nasked managers at big companies, and they all said they'd prefer\nto hire someone who'd tried to start a startup and failed over\nsomeone who'd spent the same time working at a big company.Nor will investors hold it against you, as long as you didn't fail\nout of laziness or incurable stupidity. I'm told there's a lot\nof stigma attached to failing in other places—in Europe, for\nexample. Not here. In America, companies, like practically\neverything else, are disposable.14. Don't realize what you're avoidingOne reason people who've been out in the world for a year or two\nmake better founders than people straight from college is that they\nknow what they're avoiding. If their startup fails, they'll have\nto get a job, and they know how much jobs suck.If you've had summer jobs in college, you may think you know what\njobs are like, but you probably don't. Summer jobs at technology\ncompanies are not real jobs. If you get a summer job as a waiter,\nthat's a real job. Then you have to carry your weight. But software\ncompanies don't hire students for the summer as a source of cheap\nlabor. They do it in the hope of recruiting them when they graduate.\nSo while they're happy if you produce, they don't expect you to.That will change if you get a real job after you graduate. Then\nyou'll have to earn your keep. And since most of what big companies\ndo is boring, you're going to have to work on boring stuff. Easy,\ncompared to college, but boring. At first it may seem cool to get\npaid for doing easy stuff, after paying to do hard stuff in college.\nBut that wears off after a few months. Eventually it gets demoralizing\nto work on dumb stuff, even if it's easy and you get paid a lot.And that's not the worst of it. The thing that really sucks about\nhaving a regular job is the expectation that you're supposed to be\nthere at certain times. Even Google is afflicted with this,\napparently. And what this means, as everyone who's had a regular\njob can tell you, is that there are going to be times when you have\nabsolutely no desire to work on anything, and you're going to have\nto go to work anyway and sit in front of your screen and pretend\nto. To someone who likes work, as most good hackers do, this is\ntorture.In a startup, you skip all that. There's no concept of office hours\nin most startups. Work and life just get mixed together. But the\ngood thing about that is that no one minds if you have a life at\nwork. In a startup you can do whatever you want most of the time.\nIf you're a founder, what you want to do most of the time is work.\nBut you never have to pretend to.If you took a nap in your office in a big company, it would seem\nunprofessional. But if you're starting a startup and you fall\nasleep in the middle of the day, your cofounders will just assume\nyou were tired.15. Parents want you to be a doctorA significant number of would-be startup founders are probably\ndissuaded from doing it by their parents. I'm not going to say you\nshouldn't listen to them. Families are entitled to their own\ntraditions, and who am I to argue with them? But I will give you\na couple reasons why a safe career might not be what your parents\nreally want for you.One is that parents tend to be more conservative for their kids\nthan they would be for themselves. This is actually a rational\nresponse to their situation. Parents end up sharing more of their\nkids' ill fortune than good fortune. Most parents don't mind this;\nit's part of the job; but it does tend to make them excessively\nconservative. And erring on the side of conservatism is still\nerring. In almost everything, reward is proportionate to risk. So\nby protecting their kids from risk, parents are, without realizing\nit, also protecting them from rewards. If they saw that, they'd\nwant you to take more risks.The other reason parents may be mistaken is that, like generals,\nthey're always fighting the last war. If they want you to be a\ndoctor, odds are it's not just because they want you to help the\nsick, but also because it's a prestigious and lucrative career.\n[4]\nBut not so lucrative or prestigious as it was when their\nopinions were formed. When I was a kid in the seventies, a doctor\nwas the thing to be. There was a sort of golden triangle involving\ndoctors, Mercedes 450SLs, and tennis. All three vertices now seem\npretty dated.The parents who want you to be a doctor may simply not realize how\nmuch things have changed. Would they be that unhappy if you were\nSteve Jobs instead? So I think the way to deal with your parents'\nopinions about what you should do is to treat them like feature\nrequests. Even if your only goal is to please them, the way to do\nthat is not simply to give them what they ask for. Instead think\nabout why they're asking for something, and see if there's a better\nway to give them what they need.16. A job is the defaultThis leads us to the last and probably most powerful reason people\nget regular jobs: it's the default thing to do. Defaults are\nenormously powerful, precisely because they operate without any\nconscious choice.To almost everyone except criminals, it seems an axiom that if you\nneed money, you should get a job. Actually this tradition is not\nmuch more than a hundred years old. Before that, the default way\nto make a living was by farming. It's a bad plan to treat something\nonly a hundred years old as an axiom. By historical standards,\nthat's something that's changing pretty rapidly.We may be seeing another such change right now. I've read a lot\nof economic history, and I understand the startup world pretty well,\nand it now seems to me fairly likely that we're seeing the beginning\nof a change like the one from farming to manufacturing.And you know what? If you'd been around when that change began\n(around 1000 in Europe) it would have seemed to nearly everyone\nthat running off to the city to make your fortune was a crazy thing\nto do. Though serfs were in principle forbidden to leave their\nmanors, it can't have been that hard to run away to a city. There\nwere no guards patrolling the perimeter of the village. What\nprevented most serfs from leaving was that it seemed insanely risky.\nLeave one's plot of land? Leave the people you'd spent your whole\nlife with, to live in a giant city of three or four thousand complete\nstrangers? How would you live? How would you get food, if you\ndidn't grow it?Frightening as it seemed to them, it's now the default with us to\nlive by our wits. So if it seems risky to you to start a startup,\nthink how risky it once seemed to your ancestors to live as we do\nnow. Oddly enough, the people who know this best are the very ones\ntrying to get you to stick to the old model. How can Larry and\nSergey say you should come work as their employee, when they didn't\nget jobs themselves?Now we look back on medieval peasants and wonder how they stood it.\nHow grim it must have been to till the same fields your whole life\nwith no hope of anything better, under the thumb of lords and priests\nyou had to give all your surplus to and acknowledge as your masters.\nI wouldn't be surprised if one day people look back on what we\nconsider a normal job in the same way. How grim it would be to\ncommute every day to a cubicle in some soulless office complex, and\nbe told what to do by someone you had to acknowledge as a boss—someone \nwho could call you into their office and say \"take a seat,\"\nand you'd sit! Imagine having to ask permission to release\nsoftware to users. Imagine being sad on Sunday afternoons because\nthe weekend was almost over, and tomorrow you'd have to get up and\ngo to work. How did they stand it?It's exciting to think we may be on the cusp of another shift like\nthe one from farming to manufacturing. That's why I care about\nstartups. Startups aren't interesting just because they're a way\nto make a lot of money. I couldn't care less about other ways to\ndo that, like speculating in securities. At most those are interesting\nthe way puzzles are. There's more going on with startups. They\nmay represent one of those rare, historic shifts in the way \nwealth is created.That's ultimately what drives us to work on Y Combinator. We want\nto make money, if only so we don't have to stop doing it, but that's\nnot the main goal. There have only been a handful of these great\neconomic shifts in human history. It would be an amazing hack to\nmake one happen faster.\nNotes[1]\nThe only people who lost were us. The angels had convertible\ndebt, so they had first claim on the proceeds of the auction. Y\nCombinator only got 38 cents on the dollar.[2]\nThe best kind of organization for that might be an open source\nproject, but those don't involve a lot of face to face meetings.\nMaybe it would be worth starting one that did.[3]\nThere need to be some number of big companies to acquire the\nstartups, so the number of big companies couldn't decrease to zero.[4]\nThought experiment: If doctors did the same work, but as\nimpoverished outcasts, which parents would still want their kids\nto be doctors?Thanks to Trevor Blackwell, Jessica Livingston, and Robert\nMorris for reading drafts of this, to the founders of Zenter\nfor letting me use their web-based PowerPoint killer even though \nit isn't launched yet, and to Ming-Hay Luk\nof the Berkeley CSUA for inviting me to speak.\nComment on this essay." }, { "path": "data/PaulGrahamEssayMedium/popular.txt", "content": "May 2001(This article was written as a kind of business plan for a\nnew language.\nSo it is missing (because it takes for granted) the most important\nfeature of a good programming language: very powerful abstractions.)A friend of mine once told an eminent operating systems\nexpert that he wanted to design a really good\nprogramming language. The expert told him that it would be a\nwaste of time, that programming languages don't become popular\nor unpopular based on their merits, and so no matter how\ngood his language was, no one would use it. At least, that\nwas what had happened to the language he had designed.What does make a language popular? Do popular\nlanguages deserve their popularity? Is it worth trying to\ndefine a good programming language? How would you do it?I think the answers to these questions can be found by looking \nat hackers, and learning what they want. Programming\nlanguages are for hackers, and a programming language\nis good as a programming language (rather than, say, an\nexercise in denotational semantics or compiler design)\nif and only if hackers like it.1 The Mechanics of PopularityIt's true, certainly, that most people don't choose programming\nlanguages simply based on their merits. Most programmers are told\nwhat language to use by someone else. And yet I think the effect\nof such external factors on the popularity of programming languages\nis not as great as it's sometimes thought to be. I think a bigger\nproblem is that a hacker's idea of a good programming language is\nnot the same as most language designers'.Between the two, the hacker's opinion is the one that matters.\nProgramming languages are not theorems. They're tools, designed\nfor people, and they have to be designed to suit human strengths\nand weaknesses as much as shoes have to be designed for human feet.\nIf a shoe pinches when you put it on, it's a bad shoe, however\nelegant it may be as a piece of sculpture.It may be that the majority of programmers can't tell a good language\nfrom a bad one. But that's no different with any other tool. It\ndoesn't mean that it's a waste of time to try designing a good\nlanguage. Expert hackers \ncan tell a good language when they see\none, and they'll use it. Expert hackers are a tiny minority,\nadmittedly, but that tiny minority write all the good software,\nand their influence is such that the rest of the programmers will\ntend to use whatever language they use. Often, indeed, it is not\nmerely influence but command: often the expert hackers are the very\npeople who, as their bosses or faculty advisors, tell the other\nprogrammers what language to use.The opinion of expert hackers is not the only force that determines\nthe relative popularity of programming languages — legacy software\n(Cobol) and hype (Ada, Java) also play a role — but I think it is\nthe most powerful force over the long term. Given an initial critical\nmass and enough time, a programming language probably becomes about\nas popular as it deserves to be. And popularity further separates\ngood languages from bad ones, because feedback from real live users\nalways leads to improvements. Look at how much any popular language\nhas changed during its life. Perl and Fortran are extreme cases,\nbut even Lisp has changed a lot. Lisp 1.5 didn't have macros, for\nexample; these evolved later, after hackers at MIT had spent a\ncouple years using Lisp to write real programs. [1]So whether or not a language has to be good to be popular, I think\na language has to be popular to be good. And it has to stay popular\nto stay good. The state of the art in programming languages doesn't\nstand still. And yet the Lisps we have today are still pretty much\nwhat they had at MIT in the mid-1980s, because that's the last time\nLisp had a sufficiently large and demanding user base.Of course, hackers have to know about a language before they can\nuse it. How are they to hear? From other hackers. But there has to\nbe some initial group of hackers using the language for others even\nto hear about it. I wonder how large this group has to be; how many\nusers make a critical mass? Off the top of my head, I'd say twenty.\nIf a language had twenty separate users, meaning twenty users who\ndecided on their own to use it, I'd consider it to be real.Getting there can't be easy. I would not be surprised if it is\nharder to get from zero to twenty than from twenty to a thousand.\nThe best way to get those initial twenty users is probably to use\na trojan horse: to give people an application they want, which\nhappens to be written in the new language.2 External FactorsLet's start by acknowledging one external factor that does affect\nthe popularity of a programming language. To become popular, a\nprogramming language has to be the scripting language of a popular\nsystem. Fortran and Cobol were the scripting languages of early\nIBM mainframes. C was the scripting language of Unix, and so, later,\nwas Perl. Tcl is the scripting language of Tk. Java and Javascript\nare intended to be the scripting languages of web browsers.Lisp is not a massively popular language because it is not the\nscripting language of a massively popular system. What popularity\nit retains dates back to the 1960s and 1970s, when it was the\nscripting language of MIT. A lot of the great programmers of the\nday were associated with MIT at some point. And in the early 1970s,\nbefore C, MIT's dialect of Lisp, called MacLisp, was one of the\nonly programming languages a serious hacker would want to use.Today Lisp is the scripting language of two moderately popular\nsystems, Emacs and Autocad, and for that reason I suspect that most\nof the Lisp programming done today is done in Emacs Lisp or AutoLisp.Programming languages don't exist in isolation. To hack is a\ntransitive verb — hackers are usually hacking something — and in\npractice languages are judged relative to whatever they're used to\nhack. So if you want to design a popular language, you either have\nto supply more than a language, or you have to design your language\nto replace the scripting language of some existing system.Common Lisp is unpopular partly because it's an orphan. It did\noriginally come with a system to hack: the Lisp Machine. But Lisp\nMachines (along with parallel computers) were steamrollered by the\nincreasing power of general purpose processors in the 1980s. Common\nLisp might have remained popular if it had been a good scripting\nlanguage for Unix. It is, alas, an atrociously bad one.One way to describe this situation is to say that a language isn't\njudged on its own merits. Another view is that a programming language\nreally isn't a programming language unless it's also the scripting\nlanguage of something. This only seems unfair if it comes as a\nsurprise. I think it's no more unfair than expecting a programming\nlanguage to have, say, an implementation. It's just part of what\na programming language is.A programming language does need a good implementation, of course,\nand this must be free. Companies will pay for software, but individual\nhackers won't, and it's the hackers you need to attract.A language also needs to have a book about it. The book should be\nthin, well-written, and full of good examples. K&R is the ideal\nhere. At the moment I'd almost say that a language has to have a\nbook published by O'Reilly. That's becoming the test of mattering\nto hackers.There should be online documentation as well. In fact, the book\ncan start as online documentation. But I don't think that physical\nbooks are outmoded yet. Their format is convenient, and the de\nfacto censorship imposed by publishers is a useful if imperfect\nfilter. Bookstores are one of the most important places for learning\nabout new languages.3 BrevityGiven that you can supply the three things any language needs — a\nfree implementation, a book, and something to hack — how do you\nmake a language that hackers will like?One thing hackers like is brevity. Hackers are lazy, in the same\nway that mathematicians and modernist architects are lazy: they\nhate anything extraneous. It would not be far from the truth to\nsay that a hacker about to write a program decides what language\nto use, at least subconsciously, based on the total number of\ncharacters he'll have to type. If this isn't precisely how hackers\nthink, a language designer would do well to act as if it were.It is a mistake to try to baby the user with long-winded expressions\nthat are meant to resemble English. Cobol is notorious for this\nflaw. A hacker would consider being asked to writeadd x to y giving zinstead ofz = x+yas something between an insult to his intelligence and a sin against\nGod.It has sometimes been said that Lisp should use first and rest\ninstead of car and cdr, because it would make programs easier to\nread. Maybe for the first couple hours. But a hacker can learn\nquickly enough that car means the first element of a list and cdr\nmeans the rest. Using first and rest means 50% more typing. And\nthey are also different lengths, meaning that the arguments won't\nline up when they're called, as car and cdr often are, in successive\nlines. I've found that it matters a lot how code lines up on the\npage. I can barely read Lisp code when it is set in a variable-width\nfont, and friends say this is true for other languages too.Brevity is one place where strongly typed languages lose. All other\nthings being equal, no one wants to begin a program with a bunch\nof declarations. Anything that can be implicit, should be.The individual tokens should be short as well. Perl and Common Lisp\noccupy opposite poles on this question. Perl programs can be almost\ncryptically dense, while the names of built-in Common Lisp operators\nare comically long. The designers of Common Lisp probably expected\nusers to have text editors that would type these long names for\nthem. But the cost of a long name is not just the cost of typing\nit. There is also the cost of reading it, and the cost of the space\nit takes up on your screen.4 HackabilityThere is one thing more important than brevity to a hacker: being\nable to do what you want. In the history of programming languages\na surprising amount of effort has gone into preventing programmers\nfrom doing things considered to be improper. This is a dangerously\npresumptuous plan. How can the language designer know what the\nprogrammer is going to need to do? I think language designers would\ndo better to consider their target user to be a genius who will\nneed to do things they never anticipated, rather than a bumbler\nwho needs to be protected from himself. The bumbler will shoot\nhimself in the foot anyway. You may save him from referring to\nvariables in another package, but you can't save him from writing\na badly designed program to solve the wrong problem, and taking\nforever to do it.Good programmers often want to do dangerous and unsavory things.\nBy unsavory I mean things that go behind whatever semantic facade\nthe language is trying to present: getting hold of the internal\nrepresentation of some high-level abstraction, for example. Hackers\nlike to hack, and hacking means getting inside things and second\nguessing the original designer.Let yourself be second guessed. When you make any tool, people use\nit in ways you didn't intend, and this is especially true of a\nhighly articulated tool like a programming language. Many a hacker\nwill want to tweak your semantic model in a way that you never\nimagined. I say, let them; give the programmer access to as much\ninternal stuff as you can without endangering runtime systems like\nthe garbage collector.In Common Lisp I have often wanted to iterate through the fields\nof a struct — to comb out references to a deleted object, for example,\nor find fields that are uninitialized. I know the structs are just\nvectors underneath. And yet I can't write a general purpose function\nthat I can call on any struct. I can only access the fields by\nname, because that's what a struct is supposed to mean.A hacker may only want to subvert the intended model of things once\nor twice in a big program. But what a difference it makes to be\nable to. And it may be more than a question of just solving a\nproblem. There is a kind of pleasure here too. Hackers share the\nsurgeon's secret pleasure in poking about in gross innards, the\nteenager's secret pleasure in popping zits. [2] For boys, at least,\ncertain kinds of horrors are fascinating. Maxim magazine publishes\nan annual volume of photographs, containing a mix of pin-ups and\ngrisly accidents. They know their audience.Historically, Lisp has been good at letting hackers have their way.\nThe political correctness of Common Lisp is an aberration. Early\nLisps let you get your hands on everything. A good deal of that\nspirit is, fortunately, preserved in macros. What a wonderful thing,\nto be able to make arbitrary transformations on the source code.Classic macros are a real hacker's tool — simple, powerful, and\ndangerous. It's so easy to understand what they do: you call a\nfunction on the macro's arguments, and whatever it returns gets\ninserted in place of the macro call. Hygienic macros embody the\nopposite principle. They try to protect you from understanding what\nthey're doing. I have never heard hygienic macros explained in one\nsentence. And they are a classic example of the dangers of deciding\nwhat programmers are allowed to want. Hygienic macros are intended\nto protect me from variable capture, among other things, but variable\ncapture is exactly what I want in some macros.A really good language should be both clean and dirty: cleanly\ndesigned, with a small core of well understood and highly orthogonal\noperators, but dirty in the sense that it lets hackers have their\nway with it. C is like this. So were the early Lisps. A real hacker's\nlanguage will always have a slightly raffish character.A good programming language should have features that make the kind\nof people who use the phrase \"software engineering\" shake their\nheads disapprovingly. At the other end of the continuum are languages\nlike Ada and Pascal, models of propriety that are good for teaching\nand not much else.5 Throwaway ProgramsTo be attractive to hackers, a language must be good for writing\nthe kinds of programs they want to write. And that means, perhaps\nsurprisingly, that it has to be good for writing throwaway programs.A throwaway program is a program you write quickly for some limited\ntask: a program to automate some system administration task, or\ngenerate test data for a simulation, or convert data from one format\nto another. The surprising thing about throwaway programs is that,\nlike the \"temporary\" buildings built at so many American universities\nduring World War II, they often don't get thrown away. Many evolve\ninto real programs, with real features and real users.I have a hunch that the best big programs begin life this way,\nrather than being designed big from the start, like the Hoover Dam.\nIt's terrifying to build something big from scratch. When people\ntake on a project that's too big, they become overwhelmed. The\nproject either gets bogged down, or the result is sterile and\nwooden: a shopping mall rather than a real downtown, Brasilia rather\nthan Rome, Ada rather than C.Another way to get a big program is to start with a throwaway\nprogram and keep improving it. This approach is less daunting, and\nthe design of the program benefits from evolution. I think, if one\nlooked, that this would turn out to be the way most big programs\nwere developed. And those that did evolve this way are probably\nstill written in whatever language they were first written in,\nbecause it's rare for a program to be ported, except for political\nreasons. And so, paradoxically, if you want to make a language that\nis used for big systems, you have to make it good for writing\nthrowaway programs, because that's where big systems come from.Perl is a striking example of this idea. It was not only designed\nfor writing throwaway programs, but was pretty much a throwaway\nprogram itself. Perl began life as a collection of utilities for\ngenerating reports, and only evolved into a programming language\nas the throwaway programs people wrote in it grew larger. It was\nnot until Perl 5 (if then) that the language was suitable for\nwriting serious programs, and yet it was already massively popular.What makes a language good for throwaway programs? To start with,\nit must be readily available. A throwaway program is something that\nyou expect to write in an hour. So the language probably must\nalready be installed on the computer you're using. It can't be\nsomething you have to install before you use it. It has to be there.\nC was there because it came with the operating system. Perl was\nthere because it was originally a tool for system administrators,\nand yours had already installed it.Being available means more than being installed, though. An\ninteractive language, with a command-line interface, is more\navailable than one that you have to compile and run separately. A\npopular programming language should be interactive, and start up\nfast.Another thing you want in a throwaway program is brevity. Brevity\nis always attractive to hackers, and never more so than in a program\nthey expect to turn out in an hour.6 LibrariesOf course the ultimate in brevity is to have the program already\nwritten for you, and merely to call it. And this brings us to what\nI think will be an increasingly important feature of programming\nlanguages: library functions. Perl wins because it has large\nlibraries for manipulating strings. This class of library functions\nare especially important for throwaway programs, which are often\noriginally written for converting or extracting data. Many Perl\nprograms probably begin as just a couple library calls stuck\ntogether.I think a lot of the advances that happen in programming languages\nin the next fifty years will have to do with library functions. I\nthink future programming languages will have libraries that are as\ncarefully designed as the core language. Programming language design\nwill not be about whether to make your language strongly or weakly\ntyped, or object oriented, or functional, or whatever, but about\nhow to design great libraries. The kind of language designers who\nlike to think about how to design type systems may shudder at this.\nIt's almost like writing applications! Too bad. Languages are for\nprogrammers, and libraries are what programmers need.It's hard to design good libraries. It's not simply a matter of\nwriting a lot of code. Once the libraries get too big, it can\nsometimes take longer to find the function you need than to write\nthe code yourself. Libraries need to be designed using a small set\nof orthogonal operators, just like the core language. It ought to\nbe possible for the programmer to guess what library call will do\nwhat he needs.Libraries are one place Common Lisp falls short. There are only\nrudimentary libraries for manipulating strings, and almost none\nfor talking to the operating system. For historical reasons, Common\nLisp tries to pretend that the OS doesn't exist. And because you\ncan't talk to the OS, you're unlikely to be able to write a serious\nprogram using only the built-in operators in Common Lisp. You have\nto use some implementation-specific hacks as well, and in practice\nthese tend not to give you everything you want. Hackers would think\na lot more highly of Lisp if Common Lisp had powerful string\nlibraries and good OS support.7 SyntaxCould a language with Lisp's syntax, or more precisely, lack of\nsyntax, ever become popular? I don't know the answer to this\nquestion. I do think that syntax is not the main reason Lisp isn't\ncurrently popular. Common Lisp has worse problems than unfamiliar\nsyntax. I know several programmers who are comfortable with prefix\nsyntax and yet use Perl by default, because it has powerful string\nlibraries and can talk to the os.There are two possible problems with prefix notation: that it is\nunfamiliar to programmers, and that it is not dense enough. The\nconventional wisdom in the Lisp world is that the first problem is\nthe real one. I'm not so sure. Yes, prefix notation makes ordinary\nprogrammers panic. But I don't think ordinary programmers' opinions\nmatter. Languages become popular or unpopular based on what expert\nhackers think of them, and I think expert hackers might be able to\ndeal with prefix notation. Perl syntax can be pretty incomprehensible,\nbut that has not stood in the way of Perl's popularity. If anything\nit may have helped foster a Perl cult.A more serious problem is the diffuseness of prefix notation. For\nexpert hackers, that really is a problem. No one wants to write\n(aref a x y) when they could write a[x,y].In this particular case there is a way to finesse our way out of\nthe problem. If we treat data structures as if they were functions\non indexes, we could write (a x y) instead, which is even shorter\nthan the Perl form. Similar tricks may shorten other types of\nexpressions.We can get rid of (or make optional) a lot of parentheses by making\nindentation significant. That's how programmers read code anyway:\nwhen indentation says one thing and delimiters say another, we go\nby the indentation. Treating indentation as significant would\neliminate this common source of bugs as well as making programs\nshorter.Sometimes infix syntax is easier to read. This is especially true\nfor math expressions. I've used Lisp my whole programming life and\nI still don't find prefix math expressions natural. And yet it is\nconvenient, especially when you're generating code, to have operators\nthat take any number of arguments. So if we do have infix syntax,\nit should probably be implemented as some kind of read-macro.I don't think we should be religiously opposed to introducing syntax\ninto Lisp, as long as it translates in a well-understood way into\nunderlying s-expressions. There is already a good deal of syntax\nin Lisp. It's not necessarily bad to introduce more, as long as no\none is forced to use it. In Common Lisp, some delimiters are reserved\nfor the language, suggesting that at least some of the designers\nintended to have more syntax in the future.One of the most egregiously unlispy pieces of syntax in Common Lisp\noccurs in format strings; format is a language in its own right,\nand that language is not Lisp. If there were a plan for introducing\nmore syntax into Lisp, format specifiers might be able to be included\nin it. It would be a good thing if macros could generate format\nspecifiers the way they generate any other kind of code.An eminent Lisp hacker told me that his copy of CLTL falls open to\nthe section format. Mine too. This probably indicates room for\nimprovement. It may also mean that programs do a lot of I/O.8 EfficiencyA good language, as everyone knows, should generate fast code. But\nin practice I don't think fast code comes primarily from things\nyou do in the design of the language. As Knuth pointed out long\nago, speed only matters in certain critical bottlenecks. And as\nmany programmers have observed since, one is very often mistaken\nabout where these bottlenecks are.So, in practice, the way to get fast code is to have a very good\nprofiler, rather than by, say, making the language strongly typed.\nYou don't need to know the type of every argument in every call in\nthe program. You do need to be able to declare the types of arguments\nin the bottlenecks. And even more, you need to be able to find out\nwhere the bottlenecks are.One complaint people have had with Lisp is that it's hard to tell\nwhat's expensive. This might be true. It might also be inevitable,\nif you want to have a very abstract language. And in any case I\nthink good profiling would go a long way toward fixing the problem:\nyou'd soon learn what was expensive.Part of the problem here is social. Language designers like to\nwrite fast compilers. That's how they measure their skill. They\nthink of the profiler as an add-on, at best. But in practice a good\nprofiler may do more to improve the speed of actual programs written\nin the language than a compiler that generates fast code. Here,\nagain, language designers are somewhat out of touch with their\nusers. They do a really good job of solving slightly the wrong\nproblem.It might be a good idea to have an active profiler — to push\nperformance data to the programmer instead of waiting for him to\ncome asking for it. For example, the editor could display bottlenecks\nin red when the programmer edits the source code. Another approach\nwould be to somehow represent what's happening in running programs.\nThis would be an especially big win in server-based applications,\nwhere you have lots of running programs to look at. An active\nprofiler could show graphically what's happening in memory as a\nprogram's running, or even make sounds that tell what's happening.Sound is a good cue to problems. In one place I worked, we had a\nbig board of dials showing what was happening to our web servers.\nThe hands were moved by little servomotors that made a slight noise\nwhen they turned. I couldn't see the board from my desk, but I\nfound that I could tell immediately, by the sound, when there was\na problem with a server.It might even be possible to write a profiler that would automatically\ndetect inefficient algorithms. I would not be surprised if certain\npatterns of memory access turned out to be sure signs of bad\nalgorithms. If there were a little guy running around inside the\ncomputer executing our programs, he would probably have as long\nand plaintive a tale to tell about his job as a federal government\nemployee. I often have a feeling that I'm sending the processor on\na lot of wild goose chases, but I've never had a good way to look\nat what it's doing.A number of Lisps now compile into byte code, which is then executed\nby an interpreter. This is usually done to make the implementation\neasier to port, but it could be a useful language feature. It might\nbe a good idea to make the byte code an official part of the\nlanguage, and to allow programmers to use inline byte code in\nbottlenecks. Then such optimizations would be portable too.The nature of speed, as perceived by the end-user, may be changing.\nWith the rise of server-based applications, more and more programs\nmay turn out to be i/o-bound. It will be worth making i/o fast.\nThe language can help with straightforward measures like simple,\nfast, formatted output functions, and also with deep structural\nchanges like caching and persistent objects.Users are interested in response time. But another kind of efficiency\nwill be increasingly important: the number of simultaneous users\nyou can support per processor. Many of the interesting applications\nwritten in the near future will be server-based, and the number of\nusers per server is the critical question for anyone hosting such\napplications. In the capital cost of a business offering a server-based\napplication, this is the divisor.For years, efficiency hasn't mattered much in most end-user\napplications. Developers have been able to assume that each user\nwould have an increasingly powerful processor sitting on their\ndesk. And by Parkinson's Law, software has expanded to use the\nresources available. That will change with server-based applications.\nIn that world, the hardware and software will be supplied together.\nFor companies that offer server-based applications, it will make\na very big difference to the bottom line how many users they can\nsupport per server.In some applications, the processor will be the limiting factor,\nand execution speed will be the most important thing to optimize.\nBut often memory will be the limit; the number of simultaneous\nusers will be determined by the amount of memory you need for each\nuser's data. The language can help here too. Good support for\nthreads will enable all the users to share a single heap. It may\nalso help to have persistent objects and/or language level support\nfor lazy loading.9 TimeThe last ingredient a popular language needs is time. No one wants\nto write programs in a language that might go away, as so many\nprogramming languages do. So most hackers will tend to wait until\na language has been around for a couple years before even considering\nusing it.Inventors of wonderful new things are often surprised to discover\nthis, but you need time to get any message through to people. A\nfriend of mine rarely does anything the first time someone asks\nhim. He knows that people sometimes ask for things that they turn\nout not to want. To avoid wasting his time, he waits till the third\nor fourth time he's asked to do something; by then, whoever's asking\nhim may be fairly annoyed, but at least they probably really do\nwant whatever they're asking for.Most people have learned to do a similar sort of filtering on new\nthings they hear about. They don't even start paying attention\nuntil they've heard about something ten times. They're perfectly\njustified: the majority of hot new whatevers do turn out to be a\nwaste of time, and eventually go away. By delaying learning VRML,\nI avoided having to learn it at all.So anyone who invents something new has to expect to keep repeating\ntheir message for years before people will start to get it. We\nwrote what was, as far as I know, the first web-server based\napplication, and it took us years to get it through to people that\nit didn't have to be downloaded. It wasn't that they were stupid.\nThey just had us tuned out.The good news is, simple repetition solves the problem. All you\nhave to do is keep telling your story, and eventually people will\nstart to hear. It's not when people notice you're there that they\npay attention; it's when they notice you're still there.It's just as well that it usually takes a while to gain momentum.\nMost technologies evolve a good deal even after they're first\nlaunched — programming languages especially. Nothing could be better,\nfor a new techology, than a few years of being used only by a small\nnumber of early adopters. Early adopters are sophisticated and\ndemanding, and quickly flush out whatever flaws remain in your\ntechnology. When you only have a few users you can be in close\ncontact with all of them. And early adopters are forgiving when\nyou improve your system, even if this causes some breakage.There are two ways new technology gets introduced: the organic\ngrowth method, and the big bang method. The organic growth method\nis exemplified by the classic seat-of-the-pants underfunded garage\nstartup. A couple guys, working in obscurity, develop some new\ntechnology. They launch it with no marketing and initially have\nonly a few (fanatically devoted) users. They continue to improve\nthe technology, and meanwhile their user base grows by word of\nmouth. Before they know it, they're big.The other approach, the big bang method, is exemplified by the\nVC-backed, heavily marketed startup. They rush to develop a product,\nlaunch it with great publicity, and immediately (they hope) have\na large user base.Generally, the garage guys envy the big bang guys. The big bang\nguys are smooth and confident and respected by the VCs. They can\nafford the best of everything, and the PR campaign surrounding the\nlaunch has the side effect of making them celebrities. The organic\ngrowth guys, sitting in their garage, feel poor and unloved. And\nyet I think they are often mistaken to feel sorry for themselves.\nOrganic growth seems to yield better technology and richer founders\nthan the big bang method. If you look at the dominant technologies\ntoday, you'll find that most of them grew organically.This pattern doesn't only apply to companies. You see it in sponsored\nresearch too. Multics and Common Lisp were big-bang projects, and\nUnix and MacLisp were organic growth projects.10 Redesign\"The best writing is rewriting,\" wrote E. B. White. Every good\nwriter knows this, and it's true for software too. The most important\npart of design is redesign. Programming languages, especially,\ndon't get redesigned enough.To write good software you must simultaneously keep two opposing\nideas in your head. You need the young hacker's naive faith in\nhis abilities, and at the same time the veteran's skepticism. You\nhave to be able to think \nhow hard can it be? with one half of\nyour brain while thinking \nit will never work with the other.The trick is to realize that there's no real contradiction here.\nYou want to be optimistic and skeptical about two different things.\nYou have to be optimistic about the possibility of solving the\nproblem, but skeptical about the value of whatever solution you've\ngot so far.People who do good work often think that whatever they're working\non is no good. Others see what they've done and are full of wonder,\nbut the creator is full of worry. This pattern is no coincidence:\nit is the worry that made the work good.If you can keep hope and worry balanced, they will drive a project\nforward the same way your two legs drive a bicycle forward. In the\nfirst phase of the two-cycle innovation engine, you work furiously\non some problem, inspired by your confidence that you'll be able\nto solve it. In the second phase, you look at what you've done in\nthe cold light of morning, and see all its flaws very clearly. But\nas long as your critical spirit doesn't outweigh your hope, you'll\nbe able to look at your admittedly incomplete system, and think,\nhow hard can it be to get the rest of the way?, thereby continuing\nthe cycle.It's tricky to keep the two forces balanced. In young hackers,\noptimism predominates. They produce something, are convinced it's\ngreat, and never improve it. In old hackers, skepticism predominates,\nand they won't even dare to take on ambitious projects.Anything you can do to keep the redesign cycle going is good. Prose\ncan be rewritten over and over until you're happy with it. But\nsoftware, as a rule, doesn't get redesigned enough. Prose has\nreaders, but software has users. If a writer rewrites an essay,\npeople who read the old version are unlikely to complain that their\nthoughts have been broken by some newly introduced incompatibility.Users are a double-edged sword. They can help you improve your\nlanguage, but they can also deter you from improving it. So choose\nyour users carefully, and be slow to grow their number. Having\nusers is like optimization: the wise course is to delay it. Also,\nas a general rule, you can at any given time get away with changing\nmore than you think. Introducing change is like pulling off a\nbandage: the pain is a memory almost as soon as you feel it.Everyone knows that it's not a good idea to have a language designed\nby a committee. Committees yield bad design. But I think the worst\ndanger of committees is that they interfere with redesign. It is\nso much work to introduce changes that no one wants to bother.\nWhatever a committee decides tends to stay that way, even if most\nof the members don't like it.Even a committee of two gets in the way of redesign. This happens\nparticularly in the interfaces between pieces of software written\nby two different people. To change the interface both have to agree\nto change it at once. And so interfaces tend not to change at all,\nwhich is a problem because they tend to be one of the most ad hoc\nparts of any system.One solution here might be to design systems so that interfaces\nare horizontal instead of vertical — so that modules are always\nvertically stacked strata of abstraction. Then the interface will\ntend to be owned by one of them. The lower of two levels will either\nbe a language in which the upper is written, in which case the\nlower level will own the interface, or it will be a slave, in which\ncase the interface can be dictated by the upper level.11 LispWhat all this implies is that there is hope for a new Lisp. There\nis hope for any language that gives hackers what they want, including\nLisp. I think we may have made a mistake in thinking that hackers\nare turned off by Lisp's strangeness. This comforting illusion may\nhave prevented us from seeing the real problem with Lisp, or at\nleast Common Lisp, which is that it sucks for doing what hackers\nwant to do. A hacker's language needs powerful libraries and\nsomething to hack. Common Lisp has neither. A hacker's language is\nterse and hackable. Common Lisp is not.The good news is, it's not Lisp that sucks, but Common Lisp. If we\ncan develop a new Lisp that is a real hacker's language, I think\nhackers will use it. They will use whatever language does the job.\nAll we have to do is make sure this new Lisp does some important\njob better than other languages.History offers some encouragement. Over time, successive new\nprogramming languages have taken more and more features from Lisp.\nThere is no longer much left to copy before the language you've\nmade is Lisp. The latest hot language, Python, is a watered-down\nLisp with infix syntax and no macros. A new Lisp would be a natural\nstep in this progression.I sometimes think that it would be a good marketing trick to call\nit an improved version of Python. That sounds hipper than Lisp. To\nmany people, Lisp is a slow AI language with a lot of parentheses.\nFritz Kunze's official biography carefully avoids mentioning the\nL-word. But my guess is that we shouldn't be afraid to call the\nnew Lisp Lisp. Lisp still has a lot of latent respect among the\nvery best hackers — the ones who took 6.001 and understood it, for\nexample. And those are the users you need to win.In \"How to Become a Hacker,\" Eric Raymond describes Lisp as something\nlike Latin or Greek — a language you should learn as an intellectual\nexercise, even though you won't actually use it:\n\n Lisp is worth learning for the profound enlightenment experience\n you will have when you finally get it; that experience will make\n you a better programmer for the rest of your days, even if you\n never actually use Lisp itself a lot.\n\nIf I didn't know Lisp, reading this would set me asking questions.\nA language that would make me a better programmer, if it means\nanything at all, means a language that would be better for programming.\nAnd that is in fact the implication of what Eric is saying.As long as that idea is still floating around, I think hackers will\nbe receptive enough to a new Lisp, even if it is called Lisp. But\nthis Lisp must be a hacker's language, like the classic Lisps of\nthe 1970s. It must be terse, simple, and hackable. And it must have\npowerful libraries for doing what hackers want to do now.In the matter of libraries I think there is room to beat languages\nlike Perl and Python at their own game. A lot of the new applications\nthat will need to be written in the coming years will be \nserver-based\napplications. There's no reason a new Lisp shouldn't have string\nlibraries as good as Perl, and if this new Lisp also had powerful\nlibraries for server-based applications, it could be very popular.\nReal hackers won't turn up their noses at a new tool that will let\nthem solve hard problems with a few library calls. Remember, hackers\nare lazy.It could be an even bigger win to have core language support for\nserver-based applications. For example, explicit support for programs\nwith multiple users, or data ownership at the level of type tags.Server-based applications also give us the answer to the question\nof what this new Lisp will be used to hack. It would not hurt to\nmake Lisp better as a scripting language for Unix. (It would be\nhard to make it worse.) But I think there are areas where existing\nlanguages would be easier to beat. I think it might be better to\nfollow the model of Tcl, and supply the Lisp together with a complete\nsystem for supporting server-based applications. Lisp is a natural\nfit for server-based applications. Lexical closures provide a way\nto get the effect of subroutines when the ui is just a series of\nweb pages. S-expressions map nicely onto html, and macros are good\nat generating it. There need to be better tools for writing\nserver-based applications, and there needs to be a new Lisp, and\nthe two would work very well together.12 The Dream LanguageBy way of summary, let's try describing the hacker's dream language.\nThe dream language is \nbeautiful, clean, and terse. It has an\ninteractive toplevel that starts up fast. You can write programs\nto solve common problems with very little code. Nearly all the\ncode in any program you write is code that's specific to your\napplication. Everything else has been done for you.The syntax of the language is brief to a fault. You never have to\ntype an unnecessary character, or even to use the shift key much.Using big abstractions you can write the first version of a program\nvery quickly. Later, when you want to optimize, there's a really\ngood profiler that tells you where to focus your attention. You\ncan make inner loops blindingly fast, even writing inline byte code\nif you need to.There are lots of good examples to learn from, and the language is\nintuitive enough that you can learn how to use it from examples in\na couple minutes. You don't need to look in the manual much. The\nmanual is thin, and has few warnings and qualifications.The language has a small core, and powerful, highly orthogonal\nlibraries that are as carefully designed as the core language. The\nlibraries all work well together; everything in the language fits\ntogether like the parts in a fine camera. Nothing is deprecated,\nor retained for compatibility. The source code of all the libraries\nis readily available. It's easy to talk to the operating system\nand to applications written in other languages.The language is built in layers. The higher-level abstractions are\nbuilt in a very transparent way out of lower-level abstractions,\nwhich you can get hold of if you want.Nothing is hidden from you that doesn't absolutely have to be. The\nlanguage offers abstractions only as a way of saving you work,\nrather than as a way of telling you what to do. In fact, the language\nencourages you to be an equal participant in its design. You can\nchange everything about it, including even its syntax, and anything\nyou write has, as much as possible, the same status as what comes\npredefined.Notes[1] Macros very close to the modern idea were proposed by Timothy\nHart in 1964, two years after Lisp 1.5 was released. What was\nmissing, initially, were ways to avoid variable capture and multiple\nevaluation; Hart's examples are subject to both.[2] In When the Air Hits Your Brain, neurosurgeon Frank Vertosick\nrecounts a conversation in which his chief resident, Gary, talks\nabout the difference between surgeons and internists (\"fleas\"):\n\n Gary and I ordered a large pizza and found an open booth. The\n chief lit a cigarette. \"Look at those goddamn fleas, jabbering\n about some disease they'll see once in their lifetimes. That's\n the trouble with fleas, they only like the bizarre stuff. They\n hate their bread and butter cases. That's the difference between\n us and the fucking fleas. See, we love big juicy lumbar disc\n herniations, but they hate hypertension....\"\n\nIt's hard to think of a lumbar disc herniation as juicy (except\nliterally). And yet I think I know what they mean. I've often had\na juicy bug to track down. Someone who's not a programmer would\nfind it hard to imagine that there could be pleasure in a bug.\nSurely it's better if everything just works. In one way, it is.\nAnd yet there is undeniably a grim satisfaction in hunting down\ncertain sorts of bugs." }, { "path": "data/PaulGrahamEssayMedium/re.txt", "content": "January 2016One advantage of being old is that you can see change happen in\nyour lifetime. A lot of the change I've seen is fragmentation. US\npolitics is much more polarized than it used to be. Culturally we\nhave ever less common ground. The creative class flocks to a handful\nof happy cities, abandoning the rest. And increasing economic\ninequality means the spread between rich and poor is growing too.\nI'd like to propose a hypothesis: that all these trends are instances\nof the same phenomenon. And moreover, that the cause is not some\nforce that's pulling us apart, but rather the erosion of forces\nthat had been pushing us together.Worse still, for those who worry about these trends, the forces\nthat were pushing us together were an anomaly, a one-time combination\nof circumstances that's unlikely to be repeated — and indeed, that\nwe would not want to repeat.The two forces were war (above all World War II), and the rise of\nlarge corporations.The effects of World War II were both economic and social.\nEconomically, it decreased variation in income. Like all modern\narmed forces, America's were socialist economically. From each\naccording to his ability, to each according to his need. More or\nless. Higher ranking members of the military got more (as higher\nranking members of socialist societies always do), but what they\ngot was fixed according to their rank. And the flattening effect\nwasn't limited to those under arms, because the US economy was\nconscripted too. Between 1942 and 1945 all wages were set by the\nNational War Labor Board. Like the military, they defaulted to\nflatness. And this national standardization of wages was so pervasive\nthat its effects could still be seen years after the war ended.\n[1]Business owners weren't supposed to be making money either. FDR\nsaid \"not a single war millionaire\" would be permitted. To ensure\nthat, any increase in a company's profits over prewar levels was\ntaxed at 85%. And when what was left after corporate taxes reached\nindividuals, it was taxed again at a marginal rate of 93%.\n[2]Socially too the war tended to decrease variation. Over 16 million\nmen and women from all sorts of different backgrounds were brought\ntogether in a way of life that was literally uniform. Service rates\nfor men born in the early 1920s approached 80%. And working toward\na common goal, often under stress, brought them still closer together.Though strictly speaking World War II lasted less than 4 years for\nthe US, its effects lasted longer. Wars make central governments\nmore powerful, and World War II was an extreme case of this. In\nthe US, as in all the other Allied countries, the federal government\nwas slow to give up the new powers it had acquired. Indeed, in\nsome respects the war didn't end in 1945; the enemy just switched\nto the Soviet Union. In tax rates, federal power, defense spending,\nconscription, and nationalism, the decades after the war looked more\nlike wartime than prewar peacetime.\n[3]\nAnd the social effects\nlasted too. The kid pulled into the army from behind a mule team\nin West Virginia didn't simply go back to the farm afterward.\nSomething else was waiting for him, something that looked a lot\nlike the army.If total war was the big political story of the 20th century, the\nbig economic story was the rise of a new kind of company. And this\ntoo tended to produce both social and economic cohesion.\n[4]The 20th century was the century of the big, national corporation.\nGeneral Electric, General Foods, General Motors. Developments in\nfinance, communications, transportation, and manufacturing enabled\na new type of company whose goal was above all scale. Version 1\nof this world was low-res: a Duplo world of a few giant companies\ndominating each big market.\n[5]The late 19th and early 20th centuries had been a time of consolidation,\nled especially by J. P. Morgan. Thousands of companies run by their\nfounders were merged into a couple hundred giant ones run by\nprofessional managers. Economies of scale ruled the day. It seemed\nto people at the time that this was the final state of things. John\nD. Rockefeller said in 1880\n\n The day of combination is here to stay. Individualism has gone,\n never to return.\n\nHe turned out to be mistaken, but he seemed right for the next\nhundred years.The consolidation that began in the late 19th century continued for\nmost of the 20th. By the end of World War II, as Michael Lind\nwrites, \"the major sectors of the economy were either organized\nas government-backed cartels or dominated by a few oligopolistic\ncorporations.\"For consumers this new world meant the same choices everywhere, but\nonly a few of them. When I grew up there were only 2 or 3 of most\nthings, and since they were all aiming at the middle of the market\nthere wasn't much to differentiate them.One of the most important instances of this phenomenon was in TV.\nHere there were 3 choices: NBC, CBS, and ABC. Plus public TV for\neggheads and communists. The programs that the 3 networks offered were\nindistinguishable. In fact, here there was a triple pressure toward\nthe center. If one show did try something daring, local affiliates\nin conservative markets would make them stop. Plus since TVs were\nexpensive, whole families watched the same shows together, so they\nhad to be suitable for everyone.And not only did everyone get the same thing, they got it at the\nsame time. It's difficult to imagine now, but every night tens of\nmillions of families would sit down together in front of their TV\nset watching the same show, at the same time, as their next door\nneighbors. What happens now with the Super Bowl used to happen\nevery night. We were literally in sync.\n[6]In a way mid-century TV culture was good. The view it gave of the\nworld was like you'd find in a children's book, and it probably had\nsomething of the effect that (parents hope) children's books have\nin making people behave better. But, like children's books, TV was\nalso misleading. Dangerously misleading, for adults. In his\nautobiography, Robert MacNeil talks of seeing gruesome images that\nhad just come in from Vietnam and thinking, we can't show these to\nfamilies while they're having dinner.I know how pervasive the common culture was, because I tried to opt\nout of it, and it was practically impossible to find alternatives.\nWhen I was 13 I realized, more from internal evidence than any\noutside source, that the ideas we were being fed on TV were crap,\nand I stopped watching it.\n[7]\nBut it wasn't just TV. It seemed\nlike everything around me was crap. The politicians all saying the\nsame things, the consumer brands making almost identical products\nwith different labels stuck on to indicate how prestigious they\nwere meant to be, the balloon-frame houses with fake \"colonial\"\nskins, the cars with several feet of gratuitous metal on each end\nthat started to fall apart after a couple years, the \"red delicious\"\napples that were red but only nominally \napples. And in retrospect, it was crap.\n[8]But when I went looking for alternatives to fill this void, I found\npractically nothing. There was no Internet then. The only place\nto look was in the chain bookstore in our local shopping mall. \n[9]\nThere I found a copy of The Atlantic. I wish I could say it became\na gateway into a wider world, but in fact I found it boring and\nincomprehensible. Like a kid tasting whisky for the first time and\npretending to like it, I preserved that magazine as carefully as\nif it had been a book. I'm sure I still have it somewhere. But\nthough it was evidence that there was, somewhere, a world that\nwasn't red delicious, I didn't find it till college.It wasn't just as consumers that the big companies made us similar.\nThey did as employers too. Within companies there were powerful\nforces pushing people toward a single model of how to look and act.\nIBM was particularly notorious for this, but they were only a little\nmore extreme than other big companies. And the models of how to\nlook and act varied little between companies. Meaning everyone\nwithin this world was expected to seem more or less the same. And\nnot just those in the corporate world, but also everyone who aspired\nto it — which in the middle of the 20th century meant most people\nwho weren't already in it. For most of the 20th century, working-class\npeople tried hard to look middle class. You can see it in old\nphotos. Few adults aspired to look dangerous in 1950.But the rise of national corporations didn't just compress us\nculturally. It compressed us economically too, and on both ends.Along with giant national corporations, we got giant national labor\nunions. And in the mid 20th century the corporations cut deals\nwith the unions where they paid over market price for labor. Partly\nbecause the unions were monopolies. \n[10]\nPartly because, as\ncomponents of oligopolies themselves, the corporations knew they\ncould safely pass the cost on to their customers, because their\ncompetitors would have to as well. And partly because in mid-century\nmost of the giant companies were still focused on finding new ways\nto milk economies of scale. Just as startups rightly pay AWS a\npremium over the cost of running their own servers so they can focus\non growth, many of the big national corporations were willing to\npay a premium for labor. \n[11]As well as pushing incomes up from the bottom, by overpaying unions,\nthe big companies of the 20th century also pushed incomes down at\nthe top, by underpaying their top management. Economist J. K.\nGalbraith wrote in 1967 that \"There are few corporations in which\nit would be suggested that executive salaries are at a maximum.\"\n[12]To some extent this was an illusion. Much of the de facto pay of\nexecutives never showed up on their income tax returns, because it\ntook the form of perks. The higher the rate of income tax, the\nmore pressure there was to pay employees upstream of it. (In the\nUK, where taxes were even higher than in the US, companies would\neven pay their kids' private school tuitions.) One of the most\nvaluable things the big companies of the mid 20th century gave their\nemployees was job security, and this too didn't show up in tax\nreturns or income statistics. So the nature of employment in these\norganizations tended to yield falsely low numbers about economic\ninequality. But even accounting for that, the big companies paid\ntheir best people less than market price. There was no market; the\nexpectation was that you'd work for the same company for decades\nif not your whole career. \n[13]Your work was so illiquid there was little chance of getting market\nprice. But that same illiquidity also encouraged you not to seek\nit. If the company promised to employ you till you retired and\ngive you a pension afterward, you didn't want to extract as much\nfrom it this year as you could. You needed to take care of the\ncompany so it could take care of you. Especially when you'd been\nworking with the same group of people for decades. If you tried\nto squeeze the company for more money, you were squeezing the\norganization that was going to take care of them. Plus if\nyou didn't put the company first you wouldn't be promoted, and if\nyou couldn't switch ladders, promotion on this one was the only way\nup. \n[14]To someone who'd spent several formative years in the armed forces,\nthis situation didn't seem as strange as it does to us now. From\ntheir point of view, as big company executives, they were high-ranking\nofficers. They got paid a lot more than privates. They got to\nhave expense account lunches at the best restaurants and fly around\non the company's Gulfstreams. It probably didn't occur to most of\nthem to ask if they were being paid market price.The ultimate way to get market price is to work for yourself, by\nstarting your own company. That seems obvious to any ambitious\nperson now. But in the mid 20th century it was an alien concept.\nNot because starting one's own company seemed too ambitious, but\nbecause it didn't seem ambitious enough. Even as late as the 1970s,\nwhen I grew up, the ambitious plan was to get lots of education at\nprestigious institutions, and then join some other prestigious\ninstitution and work one's way up the hierarchy. Your prestige was\nthe prestige of the institution you belonged to. People did start\ntheir own businesses of course, but educated people rarely did,\nbecause in those days there was practically zero concept of starting\nwhat we now call a startup: \na business that starts small and grows\nbig. That was much harder to do in the mid 20th century. Starting\none's own business meant starting a business that would start small\nand stay small. Which in those days of big companies often meant\nscurrying around trying to avoid being trampled by elephants. It\nwas more prestigious to be one of the executive class riding the\nelephant.By the 1970s, no one stopped to wonder where the big prestigious\ncompanies had come from in the first place. It seemed like they'd\nalways been there, like the chemical elements. And indeed, there\nwas a double wall between ambitious kids in the 20th century and\nthe origins of the big companies. Many of the big companies were\nroll-ups that didn't have clear founders. And when they did, the\nfounders didn't seem like us. Nearly all of them had been uneducated,\nin the sense of not having been to college. They were what Shakespeare\ncalled rude mechanicals. College trained one to be a member of the\nprofessional classes. Its graduates didn't expect to do the sort\nof grubby menial work that Andrew Carnegie or Henry Ford started\nout doing. \n[15]And in the 20th century there were more and more college graduates.\nThey increased from about 2% of the population in 1900 to about 25%\nin 2000. In the middle of the century our two big forces intersect,\nin the form of the GI Bill, which sent 2.2 million World War II\nveterans to college. Few thought of it in these terms, but the\nresult of making college the canonical path for the ambitious was\na world in which it was socially acceptable to work for Henry Ford,\nbut not to be Henry Ford.\n[16]I remember this world well. I came of age just as it was starting\nto break up. In my childhood it was still dominant. Not quite so\ndominant as it had been. We could see from old TV shows and yearbooks\nand the way adults acted that people in the 1950s and 60s had been\neven more conformist than us. The mid-century model was already\nstarting to get old. But that was not how we saw it at the time.\nWe would at most have said that one could be a bit more daring in\n1975 than 1965. And indeed, things hadn't changed much yet.But change was coming soon. And when the Duplo economy started to\ndisintegrate, it disintegrated in several different ways at once.\nVertically integrated companies literally dis-integrated because\nit was more efficient to. Incumbents faced new competitors as (a)\nmarkets went global and (b) technical innovation started to trump\neconomies of scale, turning size from an asset into a liability.\nSmaller companies were increasingly able to survive as formerly\nnarrow channels to consumers broadened. Markets themselves started\nto change faster, as whole new categories of products appeared. And\nlast but not least, the federal government, which had previously\nsmiled upon J. P. Morgan's world as the natural state of things,\nbegan to realize it wasn't the last word after all.What J. P. Morgan was to the horizontal axis, Henry Ford was to the\nvertical. He wanted to do everything himself. The giant plant he\nbuilt at River Rouge between 1917 and 1928 literally took in iron\nore at one end and sent cars out the other. 100,000 people worked\nthere. At the time it seemed the future. But that is not how car\ncompanies operate today. Now much of the design and manufacturing\nhappens in a long supply chain, whose products the car companies\nultimately assemble and sell. The reason car companies operate\nthis way is that it works better. Each company in the supply chain\nfocuses on what they know best. And they each have to do it well\nor they can be swapped out for another supplier.Why didn't Henry Ford realize that networks of cooperating companies\nwork better than a single big company? One reason is that supplier\nnetworks take a while to evolve. In 1917, doing everything himself\nseemed to Ford the only way to get the scale he needed. And the\nsecond reason is that if you want to solve a problem using a network\nof cooperating companies, you have to be able to coordinate their\nefforts, and you can do that much better with computers. Computers\nreduce the transaction costs that Coase argued are the raison d'etre\nof corporations. That is a fundamental change.In the early 20th century, big companies were synonymous with\nefficiency. In the late 20th century they were synonymous with\ninefficiency. To some extent this was because the companies\nthemselves had become sclerotic. But it was also because our\nstandards were higher.It wasn't just within existing industries that change occurred.\nThe industries themselves changed. It became possible to make lots\nof new things, and sometimes the existing companies weren't the\nones who did it best.Microcomputers are a classic example. The market was pioneered by\nupstarts like Apple. When it got big enough, IBM decided it was\nworth paying attention to. At the time IBM completely dominated\nthe computer industry. They assumed that all they had to do, now\nthat this market was ripe, was to reach out and pick it. Most\npeople at the time would have agreed with them. But what happened\nnext illustrated how much more complicated the world had become.\nIBM did launch a microcomputer. Though quite successful, it did\nnot crush Apple. But even more importantly, IBM itself ended up\nbeing supplanted by a supplier coming in from the side — from\nsoftware, which didn't even seem to be the same business. IBM's\nbig mistake was to accept a non-exclusive license for DOS. It must\nhave seemed a safe move at the time. No other computer manufacturer\nhad ever been able to outsell them. What difference did it make if\nother manufacturers could offer DOS too? The result of that\nmiscalculation was an explosion of inexpensive PC clones. Microsoft\nnow owned the PC standard, and the customer. And the microcomputer\nbusiness ended up being Apple vs Microsoft.Basically, Apple bumped IBM and then Microsoft stole its wallet.\nThat sort of thing did not happen to big companies in mid-century.\nBut it was going to happen increasingly often in the future.Change happened mostly by itself in the computer business. In other\nindustries, legal obstacles had to be removed first. Many of the\nmid-century oligopolies had been anointed by the federal government\nwith policies (and in wartime, large orders) that kept out competitors.\nThis didn't seem as dubious to government officials at the time as\nit sounds to us. They felt a two-party system ensured sufficient\ncompetition in politics. It ought to work for business too.Gradually the government realized that anti-competitive policies\nwere doing more harm than good, and during the Carter administration\nit started to remove them. The word used for this process was\nmisleadingly narrow: deregulation. What was really happening was\nde-oligopolization. It happened to one industry after another.\nTwo of the most visible to consumers were air travel and long-distance\nphone service, which both became dramatically cheaper after\nderegulation.Deregulation also contributed to the wave of hostile takeovers in\nthe 1980s. In the old days the only limit on the inefficiency of\ncompanies, short of actual bankruptcy, was the inefficiency of their\ncompetitors. Now companies had to face absolute rather than relative\nstandards. Any public company that didn't generate sufficient\nreturns on its assets risked having its management replaced with\none that would. Often the new managers did this by breaking companies\nup into components that were more valuable separately.\n[17]Version 1 of the national economy consisted of a few big blocks\nwhose relationships were negotiated in back rooms by a handful of\nexecutives, politicians, regulators, and labor leaders. Version 2\nwas higher resolution: there were more companies, of more different\nsizes, making more different things, and their relationships changed\nfaster. In this world there were still plenty of back room negotiations,\nbut more was left to market forces. Which further accelerated the\nfragmentation.It's a little misleading to talk of versions when describing a\ngradual process, but not as misleading as it might seem. There was\na lot of change in a few decades, and what we ended up with was\nqualitatively different. The companies in the S&P 500 in 1958 had\nbeen there an average of 61 years. By 2012 that number was 18 years.\n[18]The breakup of the Duplo economy happened simultaneously with the\nspread of computing power. To what extent were computers a precondition?\nIt would take a book to answer that. Obviously the spread of computing\npower was a precondition for the rise of startups. I suspect it\nwas for most of what happened in finance too. But was it a\nprecondition for globalization or the LBO wave? I don't know, but\nI wouldn't discount the possibility. It may be that the refragmentation\nwas driven by computers in the way the industrial revolution was\ndriven by steam engines. Whether or not computers were a precondition,\nthey have certainly accelerated it.The new fluidity of companies changed people's relationships with\ntheir employers. Why climb a corporate ladder that might be yanked\nout from under you? Ambitious people started to think of a career\nless as climbing a single ladder than as a series of jobs that might\nbe at different companies. More movement (or even potential movement)\nbetween companies introduced more competition in salaries. Plus\nas companies became smaller it became easier to estimate how much\nan employee contributed to the company's revenue. Both changes\ndrove salaries toward market price. And since people vary dramatically\nin productivity, paying market price meant salaries started to\ndiverge.By no coincidence it was in the early 1980s that the term \"yuppie\"\nwas coined. That word is not much used now, because the phenomenon\nit describes is so taken for granted, but at the time it was a label\nfor something novel. Yuppies were young professionals who made lots\nof money. To someone in their twenties today, this wouldn't seem\nworth naming. Why wouldn't young professionals make lots of money?\nBut until the 1980s, being underpaid early in your career was part\nof what it meant to be a professional. Young professionals were\npaying their dues, working their way up the ladder. The rewards\nwould come later. What was novel about yuppies was that they wanted\nmarket price for the work they were doing now.The first yuppies did not work for startups. That was still in the\nfuture. Nor did they work for big companies. They were professionals\nworking in fields like law, finance, and consulting. But their example \nrapidly inspired their peers. Once they saw that new BMW 325i, they \nwanted one too.Underpaying people at the beginning of their career only works if\neveryone does it. Once some employer breaks ranks, everyone else\nhas to, or they can't get good people. And once started this process\nspreads through the whole economy, because at the beginnings of\npeople's careers they can easily switch not merely employers but\nindustries.But not all young professionals benefitted. You had to produce to\nget paid a lot. It was no coincidence that the first yuppies worked\nin fields where it was easy to measure that.More generally, an idea was returning whose name sounds old-fashioned\nprecisely because it was so rare for so long: that you could make\nyour fortune. As in the past there were multiple ways to do it.\nSome made their fortunes by creating wealth, and others by playing\nzero-sum games. But once it became possible to make one's fortune,\nthe ambitious had to decide whether or not to. A physicist who\nchose physics over Wall Street in 1990 was making a sacrifice that\na physicist in 1960 didn't have to think about.The idea even flowed back into big companies. CEOs of big companies\nmake more now than they used to, and I think much of the reason is\nprestige. In 1960, corporate CEOs had immense prestige. They were\nthe winners of the only economic game in town. But if they made as\nlittle now as they did then, in real dollar terms, they'd seem like\nsmall fry compared to professional athletes and whiz kids making\nmillions from startups and hedge funds. They don't like that idea,\nso now they try to get as much as they can, which is more than they\nhad been getting. \n[19]Meanwhile a similar fragmentation was happening at the other end\nof the economic scale. As big companies' oligopolies became less\nsecure, they were less able to pass costs on to customers and thus\nless willing to overpay for labor. And as the Duplo world of a few\nbig blocks fragmented into many companies of different sizes — some\nof them overseas — it became harder for unions to enforce their\nmonopolies. As a result workers' wages also tended toward market\nprice. Which (inevitably, if unions had been doing their job) tended\nto be lower. Perhaps dramatically so, if automation had decreased\nthe need for some kind of work.And just as the mid-century model induced social as well as economic\ncohesion, its breakup brought social as well as economic fragmentation.\nPeople started to dress and act differently. Those who would later\nbe called the \"creative class\" became more mobile. People who didn't\ncare much for religion felt less pressure to go to church for\nappearances' sake, while those who liked it a lot opted for\nincreasingly colorful forms. Some switched from meat loaf to tofu,\nand others to Hot Pockets. Some switched from driving Ford sedans\nto driving small imported cars, and others to driving SUVs. Kids\nwho went to private schools or wished they did started to dress\n\"preppy,\" and kids who wanted to seem rebellious made a conscious\neffort to look disreputable. In a hundred ways people spread apart.\n[20]Almost four decades later, fragmentation is still increasing. Has\nit been net good or bad? I don't know; the question may be\nunanswerable. Not entirely bad though. We take for granted the\nforms of fragmentation we like, and worry only about the ones we\ndon't. But as someone who caught the tail end of mid-century\nconformism, \nI can tell you it was no utopia.\n[21]My goal here is not to say whether fragmentation has been good or\nbad, just to explain why it's happening. With the centripetal\nforces of total war and 20th century oligopoly mostly gone, what\nwill happen next? And more specifically, is it possible to reverse\nsome of the fragmentation we've seen?If it is, it will have to happen piecemeal. You can't reproduce\nmid-century cohesion the way it was originally produced. It would\nbe insane to go to war just to induce more national unity. And\nonce you understand the degree to which the economic history of the\n20th century was a low-res version 1, it's clear you can't reproduce\nthat either.20th century cohesion was something that happened at least in a\nsense naturally. The war was due mostly to external forces, and\nthe Duplo economy was an evolutionary phase. If you want cohesion\nnow, you'd have to induce it deliberately. And it's not obvious\nhow. I suspect the best we'll be able to do is address the symptoms\nof fragmentation. But that may be enough.The form of fragmentation people worry most about lately is economic inequality, and if you want to eliminate\nthat you're up against a truly formidable headwind that has\nbeen in operation since the stone age. Technology.Technology is\na lever. It magnifies work. And the lever not only grows increasingly\nlong, but the rate at which it grows is itself increasing.Which in turn means the variation in the amount of wealth people\ncan create has not only been increasing, but accelerating. The\nunusual conditions that prevailed in the mid 20th century masked\nthis underlying trend. The ambitious had little choice but to join\nlarge organizations that made them march in step with lots of other\npeople — literally in the case of the armed forces, figuratively\nin the case of big corporations. Even if the big corporations had\nwanted to pay people proportionate to their value, they couldn't\nhave figured out how. But that constraint has gone now. Ever since\nit started to erode in the 1970s, we've seen the underlying forces\nat work again.\n[22]Not everyone who gets rich now does it by creating wealth, certainly.\nBut a significant number do, and the Baumol Effect means all their\npeers get dragged along too.\n[23]\nAnd as long as it's possible to\nget rich by creating wealth, the default tendency will be for\neconomic inequality to increase. Even if you eliminate all the\nother ways to get rich. You can mitigate this with subsidies at\nthe bottom and taxes at the top, but unless taxes are high enough\nto discourage people from creating wealth, you're always going to\nbe fighting a losing battle against increasing variation in\nproductivity.\n[24]That form of fragmentation, like the others, is here to stay. Or\nrather, back to stay. Nothing is forever, but the tendency toward\nfragmentation should be more forever than most things, precisely\nbecause it's not due to any particular cause. It's simply a reversion\nto the mean. When Rockefeller said individualism was gone, he was\nright for a hundred years. It's back now, and that's likely to be\ntrue for longer.I worry that if we don't acknowledge this, we're headed for trouble.\nIf we think 20th century cohesion disappeared because of few policy\ntweaks, we'll be deluded into thinking we can get it back (minus\nthe bad parts, somehow) with a few countertweaks. And then we'll\nwaste our time trying to eliminate fragmentation, when we'd be\nbetter off thinking about how to mitigate its consequences.\nNotes[1]\nLester Thurow, writing in 1975, said the wage differentials\nprevailing at the end of World War II had become so embedded that\nthey \"were regarded as 'just' even after the egalitarian pressures\nof World War II had disappeared. Basically, the same differentials\nexist to this day, thirty years later.\" But Goldin and Margo think\nmarket forces in the postwar period also helped preserve the wartime\ncompression of wages — specifically increased demand for unskilled\nworkers, and oversupply of educated ones.(Oddly enough, the American custom of having employers pay for\nhealth insurance derives from efforts by businesses to circumvent\nNWLB wage controls in order to attract workers.)[2]\nAs always, tax rates don't tell the whole story. There were\nlots of exemptions, especially for individuals. And in World War\nII the tax codes were so new that the government had little acquired\nimmunity to tax avoidance. If the rich paid high taxes during the\nwar it was more because they wanted to than because they had to.After the war, federal tax receipts as a percentage of GDP were\nabout the same as they are now. In fact, for the entire period since\nthe war, tax receipts have stayed close to 18% of GDP, despite\ndramatic changes in tax rates. The lowest point occurred when\nmarginal income tax rates were highest: 14.1% in 1950. Looking at\nthe data, it's hard to avoid the conclusion that tax rates have had\nlittle effect on what people actually paid.[3]\nThough in fact the decade preceding the war had been a time\nof unprecedented federal power, in response to the Depression.\nWhich is not entirely a coincidence, because the Depression was one\nof the causes of the war. In many ways the New Deal was a sort of\ndress rehearsal for the measures the federal government took during\nwartime. The wartime versions were much more drastic and more\npervasive though. As Anthony Badger wrote, \"for many Americans the\ndecisive change in their experiences came not with the New Deal but\nwith World War II.\"[4]\nI don't know enough about the origins of the world wars to\nsay, but it's not inconceivable they were connected to the rise of\nbig corporations. If that were the case, 20th century cohesion would\nhave a single cause.[5]\nMore precisely, there was a bimodal economy consisting, in\nGalbraith's words, of \"the world of the technically dynamic, massively\ncapitalized and highly organized corporations on the one hand and\nthe hundreds of thousands of small and traditional proprietors on\nthe other.\" Money, prestige, and power were concentrated in the\nformer, and there was near zero crossover.[6]\nI wonder how much of the decline in families eating together\nwas due to the decline in families watching TV together afterward.[7]\nI know when this happened because it was the season Dallas\npremiered. Everyone else was talking about what was happening on\nDallas, and I had no idea what they meant.[8]\nI didn't realize it till I started doing research for this\nessay, but the meretriciousness of the products I grew up with is\na well-known byproduct of oligopoly. When companies can't compete\non price, they compete on tailfins.[9]\nMonroeville Mall was at the time of its completion in 1969\nthe largest in the country. In the late 1970s the movie Dawn of\nthe Dead was shot there. Apparently the mall was not just the\nlocation of the movie, but its inspiration; the crowds of shoppers\ndrifting through this huge mall reminded George Romero of zombies.\nMy first job was scooping ice cream in the Baskin-Robbins.[10]\nLabor unions were exempted from antitrust laws by the Clayton\nAntitrust Act in 1914 on the grounds that a person's work is not\n\"a commodity or article of commerce.\" I wonder if that means service\ncompanies are also exempt.[11]\nThe relationships between unions and unionized companies can\neven be symbiotic, because unions will exert political pressure to\nprotect their hosts. According to Michael Lind, when politicians\ntried to attack the A&P supermarket chain because it was putting\nlocal grocery stores out of business, \"A&P successfully defended\nitself by allowing the unionization of its workforce in 1938, thereby\ngaining organized labor as a constituency.\" I've seen this phenomenon\nmyself: hotel unions are responsible for more of the political\npressure against Airbnb than hotel companies.[12]\nGalbraith was clearly puzzled that corporate executives would\nwork so hard to make money for other people (the shareholders)\ninstead of themselves. He devoted much of The New Industrial\nState to trying to figure this out.His theory was that professionalism had replaced money as a motive,\nand that modern corporate executives were, like (good) scientists,\nmotivated less by financial rewards than by the desire to do good\nwork and thereby earn the respect of their peers. There is something\nin this, though I think lack of movement between companies combined\nwith self-interest explains much of observed behavior.[13]\nGalbraith (p. 94) says a 1952 study of the 800 highest paid\nexecutives at 300 big corporations found that three quarters of\nthem had been with their company for more than 20 years.[14]\nIt seems likely that in the first third of the 20th century\nexecutive salaries were low partly because companies then were more\ndependent on banks, who would have disapproved if executives got\ntoo much. This was certainly true in the beginning. The first big\ncompany CEOs were J. P. Morgan's hired hands.Companies didn't start to finance themselves with retained earnings\ntill the 1920s. Till then they had to pay out their earnings in\ndividends, and so depended on banks for capital for expansion.\nBankers continued to sit on corporate boards till the Glass-Steagall\nact in 1933.By mid-century big companies funded 3/4 of their growth from earnings.\nBut the early years of bank dependence, reinforced by the financial\ncontrols of World War II, must have had a big effect on social\nconventions about executive salaries. So it may be that the lack\nof movement between companies was as much the effect of low salaries\nas the cause.Incidentally, the switch in the 1920s to financing growth with\nretained earnings was one cause of the 1929 crash. The banks now\nhad to find someone else to lend to, so they made more margin loans.[15]\nEven now it's hard to get them to. One of the things I find\nhardest to get into the heads of would-be startup founders is how\nimportant it is to do certain kinds of menial work early in the\nlife of a company. Doing things that don't\nscale is to how Henry Ford got started as a high-fiber diet is\nto the traditional peasant's diet: they had no choice but to do the\nright thing, while we have to make a conscious effort.[16]\nFounders weren't celebrated in the press when I was a kid.\n\"Our founder\" meant a photograph of a severe-looking man with a\nwalrus mustache and a wing collar who had died decades ago. The\nthing to be when I was a kid was an executive. If you weren't\naround then it's hard to grasp the cachet that term had. The fancy\nversion of everything was called the \"executive\" model.[17]\nThe wave of hostile takeovers in the 1980s was enabled by a\ncombination of circumstances: court decisions striking down state\nanti-takeover laws, starting with the Supreme Court's 1982 decision\nin Edgar v. MITE Corp.; the Reagan administration's comparatively\nsympathetic attitude toward takeovers; the Depository Institutions\nAct of 1982, which allowed banks and savings and loans to buy\ncorporate bonds; a new SEC rule issued in 1982 (rule 415) that made\nit possible to bring corporate bonds to market faster; the creation\nof the junk bond business by Michael Milken; a vogue for conglomerates\nin the preceding period that caused many companies to be combined\nthat never should have been; a decade of inflation that left many\npublic companies trading below the value of their assets; and not\nleast, the increasing complacency of managements.[18]\nFoster, Richard. \"Creative Destruction Whips through Corporate\nAmerica.\" Innosight, February 2012.[19]\nCEOs of big companies may be overpaid. I don't know enough\nabout big companies to say. But it is certainly not impossible for\na CEO to make 200x as much difference to a company's revenues as\nthe average employee. Look at what Steve Jobs did for Apple when\nhe came back as CEO. It would have been a good deal for the board\nto give him 95% of the company. Apple's market cap the day Steve\ncame back in July 1997 was 1.73 billion. 5% of Apple now (January\n2016) would be worth about 30 billion. And it would not be if Steve\nhadn't come back; Apple probably wouldn't even exist anymore.Merely including Steve in the sample might be enough to answer the\nquestion of whether public company CEOs in the aggregate are overpaid.\nAnd that is not as facile a trick as it might seem, because the\nbroader your holdings, the more the aggregate is what you care\nabout.[20]\nThe late 1960s were famous for social upheaval. But that was\nmore rebellion (which can happen in any era if people are provoked\nsufficiently) than fragmentation. You're not seeing fragmentation\nunless you see people breaking off to both left and right.[21]\nGlobally the trend has been in the other direction. While\nthe US is becoming more fragmented, the world as a whole is becoming\nless fragmented, and mostly in good ways.[22]\nThere were a handful of ways to make a fortune in the mid\n20th century. The main one was drilling for oil, which was open\nto newcomers because it was not something big companies could\ndominate through economies of scale. How did individuals accumulate\nlarge fortunes in an era of such high taxes? Giant tax loopholes\ndefended by two of the most powerful men in Congress, Sam Rayburn\nand Lyndon Johnson.But becoming a Texas oilman was not in 1950 something one could\naspire to the way starting a startup or going to work on Wall Street\nwere in 2000, because (a) there was a strong local component and\n(b) success depended so much on luck.[23]\nThe Baumol Effect induced by startups is very visible in\nSilicon Valley. Google will pay people millions of dollars a year\nto keep them from leaving to start or join startups.[24]\nI'm not claiming variation in productivity is the only cause\nof economic inequality in the US. But it's a significant cause, and\nit will become as big a cause as it needs to, in the sense that if\nyou ban other ways to get rich, people who want to get rich will\nuse this route instead.Thanks to Sam Altman, Trevor Blackwell, Paul Buchheit, Patrick\nCollison, Ron Conway, Chris Dixon, Benedict Evans, Richard Florida,\nBen Horowitz, Jessica Livingston, Robert Morris, Tim O'Reilly, Geoff\nRalston, Max Roser, Alexia Tsotsis, and Qasar Younis for reading\ndrafts of this. Max also told me about several valuable sources.BibliographyAllen, Frederick Lewis. The Big Change. Harper, 1952.Averitt, Robert. The Dual Economy. Norton, 1968.Badger, Anthony. The New Deal. Hill and Wang, 1989.Bainbridge, John. The Super-Americans. Doubleday, 1961.Beatty, Jack. Collossus. Broadway, 2001.Brinkley, Douglas. Wheels for the World. Viking, 2003.Brownleee, W. Elliot. Federal Taxation in America. Cambridge, 1996.Chandler, Alfred. The Visible Hand. Harvard, 1977.Chernow, Ron. The House of Morgan. Simon & Schuster, 1990.Chernow, Ron. Titan: The Life of John D. Rockefeller. Random House,\n1998.Galbraith, John. The New Industrial State. Houghton Mifflin, 1967.Goldin, Claudia and Robert A. Margo. \"The Great Compression: The\nWage Structure in the United States at Mid-Century.\" NBER Working\nPaper 3817, 1991.Gordon, John. An Empire of Wealth. HarperCollins, 2004.Klein, Maury. The Genesis of Industrial America, 1870-1920. Cambridge,\n2007.Lind, Michael. Land of Promise. HarperCollins, 2012.Mickelthwaite, John, and Adrian Wooldridge. The Company. Modern\nLibrary, 2003.Nasaw, David. Andrew Carnegie. Penguin, 2006.Sobel, Robert. The Age of Giant Corporations. Praeger, 1993.Thurow, Lester. Generating Inequality: Mechanisms of Distribution.\nBasic Books, 1975.Witte, John. The Politics and Development of the Federal Income\nTax. Wisconsin, 1985.Related:" }, { "path": "data/PaulGrahamEssayMedium/road.txt", "content": "September 2001\n(This article explains why much of the next generation of software\nmay be server-based, what that will mean for programmers,\nand why this new kind of software is a great opportunity for startups.\nIt's derived from a talk at BBN Labs.)\nIn the summer of 1995, my friend Robert Morris and I decided to\nstart a startup. The PR campaign leading up to Netscape's IPO was\nrunning full blast then, and there was a lot of talk in the press\nabout online commerce. At the time there might have been thirty\nactual stores on the Web, all made by hand. If there were going\nto be a lot of online stores, there would need to be software for making\nthem, so we decided to write some.For the first week or so we intended to make this an ordinary \ndesktop application. Then one day we had the idea of making the\nsoftware run on our Web server, using the browser as an\ninterface. We tried rewriting the software to work over\nthe Web, and it was clear that this was the way to go.\nIf we wrote our software to run on the server, it would be a lot easier\nfor the users and for us as well.This turned out to be a good plan. Now, as \nYahoo Store, this\nsoftware is the most popular online store builder, with\nabout 14,000 users.When we started Viaweb, hardly anyone understood what we meant when\nwe said that the software ran on the server. It was not until\nHotmail was launched a year later that people started to get it.\nNow everyone knows that this is a valid approach. There is\na name now for what we were: an Application Service Provider,\nor ASP.I think that a lot of the next generation of software will be\nwritten on this model. Even Microsoft, who have the most to\nlose, seem to see the inevitablity of moving some things off\nthe desktop. If software moves\noff the desktop and onto servers, it will mean a very different\nworld for developers. This article describes the surprising\nthings we saw, as some of the first visitors to this new world.\nTo the extent software does move onto\nservers, what I'm describing here is the future.The Next Thing?When we look back on the desktop software era, I think we'll marvel\nat the inconveniences people put up with, just as we marvel now at\nwhat early car owners put up with. For the first twenty or thirty\nyears, you had to be a car expert to own a car. But cars were such\na big win that lots of people who weren't car experts wanted to\nhave them as well.Computers are in this phase now. When you own a desktop computer,\nyou end up learning a lot more than you wanted to know about what's\nhappening inside it. But more than half the households in the US\nown one. My mother has a computer that she uses for email and for\nkeeping accounts. About a year ago she was alarmed to receive a\nletter from Apple, offering her a discount on a new version of the\noperating system. There's something wrong when a sixty-five year\nold woman who wants to use a computer for email and accounts has\nto think about installing new operating systems. Ordinary users\nshouldn't even know the words \"operating system,\" much less \"device\ndriver\" or \"patch.\"There is now another way to deliver software that will save users\nfrom becoming system administrators. Web-based applications are\nprograms that run on Web servers and use Web pages as the user\ninterface. For the average user this new kind of software will be\neasier, cheaper, more mobile, more reliable, and often more powerful\nthan desktop software.With Web-based software, most users won't have to think about\nanything except the applications they use. All the messy, changing\nstuff will be sitting on a server somewhere, maintained by the kind\nof people who are good at that kind of thing. And so you won't\nordinarily need a computer, per se, to use software. All you'll\nneed will be something with a keyboard, a screen, and a Web browser.\nMaybe it will have wireless Internet access. Maybe it will also\nbe your cell phone. Whatever it is, it will be consumer electronics:\nsomething that costs about $200, and that people choose mostly\nbased on how the case looks. You'll pay more for Internet services\nthan you do for the hardware, just as you do now with telephones. [1]It will take about a tenth of a second for a click to get to the\nserver and back, so users of heavily interactive software, like\nPhotoshop, will still want to have the computations happening on\nthe desktop. But if you look at the kind of things most people\nuse computers for, a tenth of a second latency would not be a\nproblem. My mother doesn't really need a desktop computer, and\nthere are a lot of people like her.The Win for UsersNear my house there is a car with a bumper sticker that reads \"death\nbefore inconvenience.\" Most people, most of the time, will take\nwhatever choice requires least work. If Web-based software wins,\nit will be because it's more convenient. And it looks as if it\nwill be, for users and developers both.To use a purely Web-based application, all you need is a browser\nconnected to the Internet. So you can use a Web-based application\nanywhere. When you install software on your desktop computer, you\ncan only use it on that computer. Worse still, your files are\ntrapped on that computer. The inconvenience of this model becomes\nmore and more evident as people get used to networks.The thin end of the wedge here was Web-based email. Millions of\npeople now realize that you should have access to email messages\nno matter where you are. And if you can see your email, why not\nyour calendar? \nIf you can discuss a document with your colleagues,\nwhy can't you edit it? Why should any of your data be trapped on\nsome computer sitting on a faraway desk?The whole idea of \"your computer\" is going away, and being replaced\nwith \"your data.\" You should be able to get at your data from any\ncomputer. Or rather, any client, and a client doesn't have to be\na computer.Clients shouldn't store data; they should be like telephones. In\nfact they may become telephones, or vice versa. And as clients\nget smaller, you have another reason not to keep your data on them:\nsomething you carry around with you can be lost or stolen. Leaving\nyour PDA in a taxi is like a disk crash, except that your data is\nhanded to someone else \ninstead of being vaporized.With purely Web-based software, neither your data nor the applications\nare kept on the client. So you don't have to install anything to\nuse it. And when there's no installation, you don't have to worry\nabout installation going wrong. There can't be incompatibilities\nbetween the application and your operating system, because the\nsoftware doesn't run on your operating system.Because it needs no installation, it will be easy, and common, to\ntry Web-based software before you \"buy\" it. You should expect to\nbe able to test-drive any Web-based application for free, just by\ngoing to the site where it's offered. At Viaweb our whole site\nwas like a big arrow pointing users to the test drive.After trying the demo, signing up for the service should require\nnothing more than filling out a brief form (the briefer the better).\nAnd that should be the last work the user has to do. With Web-based\nsoftware, you should get new releases without paying extra, or\ndoing any work, or possibly even knowing about it.Upgrades won't be the big shocks they are now. Over time applications\nwill quietly grow more powerful. This will take some effort on\nthe part of the developers. They will have to design software so\nthat it can be updated without confusing the users. That's a new\nproblem, but there are ways to solve it.With Web-based applications, everyone uses the same version, and\nbugs can be fixed as soon as they're discovered. So Web-based\nsoftware should have far fewer bugs than desktop software. At\nViaweb, I doubt we ever had ten known bugs at any one time. That's\norders of magnitude better than desktop software.Web-based applications can be used by several people at the same\ntime. This is an obvious win for collaborative applications, but\nI bet users will start to want this in most applications once they\nrealize it's possible. It will often be useful to let two people\nedit the same document, for example. Viaweb let multiple users\nedit a site simultaneously, more because that was the right way to\nwrite the software than because we expected users to want to, but\nit turned out that many did.When you use a Web-based application, your data will be safer.\nDisk crashes won't be a thing of the past, but users won't hear\nabout them anymore. They'll happen within server farms. And\ncompanies offering Web-based applications will actually do backups--\nnot only because they'll have real system administrators worrying\nabout such things, but because an ASP that does lose people's data\nwill be in big, big trouble. When people lose their own data in\na disk crash, they can't get that mad, because they only have\nthemselves to be mad at. When a company loses their data for them,\nthey'll get a lot madder.Finally, Web-based software should be less vulnerable to viruses.\nIf the client doesn't run anything except a browser, there's less\nchance of running viruses, and no data locally to damage. And a\nprogram that attacked the servers themselves should find them very\nwell defended. [2]For users, Web-based software will be less stressful. I think if\nyou looked inside the average Windows user you'd find a huge and\npretty much untapped desire for software meeting that description.\nUnleashed, it could be a powerful force.City of CodeTo developers, the most conspicuous difference between Web-based\nand desktop software is that a Web-based application is not a single\npiece of code. It will be a collection of programs of different\ntypes rather than a single big binary. And so designing Web-based\nsoftware is like desiging a city rather than a building: as well\nas buildings you need roads, street signs, utilities, police and\nfire departments, and plans for both growth and various kinds of\ndisasters.At Viaweb, software included fairly big applications that users\ntalked to directly, programs that those programs used, programs\nthat ran constantly in the background looking for problems, programs\nthat tried to restart things if they broke, programs that ran\noccasionally to compile statistics or build indexes for searches,\nprograms we ran explicitly to garbage-collect resources or to move\nor restore data, programs that pretended to be users (to measure\nperformance or expose bugs), programs for diagnosing network\ntroubles, programs for doing backups, interfaces to outside services,\nsoftware that drove an impressive collection of dials displaying\nreal-time server statistics (a hit with visitors, but indispensable\nfor us too), modifications (including bug fixes) to open-source\nsoftware, and a great many configuration files and settings. Trevor\nBlackwell wrote a spectacular program for moving stores to new\nservers across the country, without shutting them down, after we\nwere bought by Yahoo. Programs paged us, sent faxes and email to\nusers, conducted transactions with credit card processors, and\ntalked to one another through sockets, pipes, http requests, ssh,\nudp packets, shared memory, and files. Some of Viaweb even consisted\nof the absence of programs, since one of the keys to Unix security\nis not to run unnecessary utilities that people might use to break\ninto your servers.It did not end with software. We spent a lot of time thinking\nabout server configurations. We built the servers ourselves, from\ncomponents-- partly to save money, and partly to get exactly what\nwe wanted. We had to think about whether our upstream ISP had fast\nenough connections to all the backbones. We serially \ndated\nRAID suppliers.But hardware is not just something to worry about. When you control\nit you can do more for users. With a desktop application, you can\nspecify certain minimum hardware, but you can't add more. If you\nadminister the servers, you can in one step enable all your users\nto page people, or send faxes, or send commands by phone, or process\ncredit cards, etc, just by installing the relevant hardware. We\nalways looked for new ways to add features with hardware, not just\nbecause it pleased users, but also as a way to distinguish ourselves\nfrom competitors who (either because they sold desktop software,\nor resold Web-based applications through ISPs) didn't have direct\ncontrol over the hardware.Because the software in a Web-based application will be a collection\nof programs rather than a single binary, it can be written in any\nnumber of different languages. When you're writing desktop software,\nyou're practically forced to write the application in the same\nlanguage as the underlying operating system-- meaning C and C++.\nAnd so these languages (especially among nontechnical people like\nmanagers and VCs) got to be considered as the languages for \"serious\"\nsoftware development. But that was just an artifact of the way\ndesktop software had to be delivered. For server-based software\nyou can use any language you want. [3] Today a lot of the top\nhackers are using languages far removed from C and C++: Perl,\nPython, and even Lisp.With server-based software, no one can tell you what language to\nuse, because you control the whole system, right down to the\nhardware. Different languages are good for different tasks. You\ncan use whichever is best for each. And when you have competitors,\n\"you can\" means \"you must\" (we'll return to this later), because\nif you don't take advantage of this possibility, your competitors\nwill.Most of our competitors used C and C++, and this made their software\nvisibly inferior because (among other things), they had no way\naround the statelessness of CGI scripts. If you were going to\nchange something, all the changes had to happen on one page, with\nan Update button at the bottom. As I've written elsewhere, by\nusing Lisp, which many people still consider \na research language,\nwe could make the Viaweb editor behave more like desktop software.ReleasesOne of the most important changes in this new world is the way you\ndo releases. In the desktop software business, doing a release is\na huge trauma, in which the whole company sweats and strains to\npush out a single, giant piece of code. Obvious comparisons suggest\nthemselves, both to the process and the resulting product.With server-based software, you can make changes almost as you\nwould in a program you were writing for yourself. You release\nsoftware as a series of incremental changes instead of an occasional\nbig explosion. A typical desktop software company might do one or\ntwo releases a year. At Viaweb we often did three to five releases\na day.When you switch to this new model, you realize how much software\ndevelopment is affected by the way it is released. Many of the\nnastiest problems you see in the desktop software business are due\nto catastrophic nature of releases.When you release only one new version a year, you tend to deal with\nbugs wholesale. Some time before the release date you assemble a\nnew version in which half the code has been torn out and replaced,\nintroducing countless bugs. Then a squad of QA people step in and\nstart counting them, and the programmers work down the list, fixing\nthem. They do not generally get to the end of the list, and indeed,\nno one is sure where the end is. It's like fishing rubble out of\na pond. You never really know what's happening inside the software.\nAt best you end up with a statistical sort of correctness.With server-based software, most of the change is small and\nincremental. That in itself is less likely to introduce bugs. It\nalso means you know what to test most carefully when you're about\nto release software: the last thing you changed. You end up with\na much firmer grip on the code. As a general rule, you do know\nwhat's happening inside it. You don't have the source code memorized,\nof course, but when you read the source you do it like a pilot\nscanning the instrument panel, not like a detective trying to\nunravel some mystery.Desktop software breeds a certain fatalism about bugs. You know\nthat you're shipping something loaded with bugs, and you've even\nset up mechanisms to compensate for it (e.g. patch releases). So\nwhy worry about a few more? Soon you're releasing whole features\nyou know are broken. \nApple \ndid this earlier this year. They felt\nunder pressure to release their new OS, whose release date had\nalready slipped four times, but some of the software (support for\nCDs and DVDs) wasn't ready. The solution? They released the OS\nwithout the unfinished parts, and users will have to install them\nlater.With Web-based software, you never have to release software before\nit works, and you can release it as soon as it does work.The industry veteran may be thinking, it's a fine-sounding idea to\nsay that you never have to release software before it works, but\nwhat happens when you've promised to deliver a new version of your\nsoftware by a certain date? With Web-based software, you wouldn't\nmake such a promise, because there are no versions. Your software\nchanges gradually and continuously. Some changes might be bigger\nthan others, but the idea of versions just doesn't naturally fit\nonto Web-based software.If anyone remembers Viaweb this might sound odd, because we were\nalways announcing new versions. This was done entirely for PR\npurposes. The trade press, we learned, thinks in version numbers.\nThey will give you major coverage for a major release, meaning a\nnew first digit on the version number, and generally a paragraph\nat most for a point release, meaning a new digit after the decimal\npoint.Some of our competitors were offering desktop software and actually\nhad version numbers. And for these releases, the mere fact of\nwhich seemed to us evidence of their backwardness, they would get\nall kinds of publicity. We didn't want to miss out, so we started\ngiving version numbers to our software too. When we wanted some\npublicity, we'd make a list of all the features we'd added since\nthe last \"release,\" stick a new version number on the software,\nand issue a press release saying that the new version was available\nimmediately. Amazingly, no one ever called us on it.By the time we were bought, we had done this three times, so we\nwere on Version 4. Version 4.1 if I remember correctly. After\nViaweb became Yahoo Store, there was no longer such a desperate\nneed for publicity, so although the software continued to evolve,\nthe whole idea of version numbers was quietly dropped.BugsThe other major technical advantage of Web-based software is that\nyou can reproduce most bugs. You have the users' data right there\non your disk. If someone breaks your software, you don't have to\ntry to guess what's going on, as you would with desktop software:\nyou should be able to reproduce the error while they're on the\nphone with you. You might even know about it already, if you have\ncode for noticing errors built into your application.Web-based software gets used round the clock, so everything you do\nis immediately put through the wringer. Bugs turn up quickly.Software companies are sometimes accused of letting the users debug\ntheir software. And that is just what I'm advocating. For Web-based\nsoftware it's actually a good plan, because the bugs are fewer and\ntransient. When you release software gradually you get far fewer\nbugs to start with. And when you can reproduce errors and release\nchanges instantly, you can find and fix most bugs as soon as they\nappear. We never had enough bugs at any one time to bother with\na formal bug-tracking system.You should test changes before you release them, of course, so no\nmajor bugs should get released. Those few that inevitably slip\nthrough will involve borderline cases and will only affect the few\nusers that encounter them before someone calls in to complain. As\nlong as you fix bugs right away, the net effect, for the average\nuser, is far fewer bugs. I doubt the average Viaweb user ever saw\na bug.Fixing fresh bugs is easier than fixing old ones. It's usually\nfairly quick to find a bug in code you just wrote. When it turns\nup you often know what's wrong before you even look at the source,\nbecause you were already worrying about it subconsciously. Fixing\na bug in something you wrote six months ago (the average case if\nyou release once a year) is a lot more work. And since you don't\nunderstand the code as well, you're more likely to fix it in an\nugly way, or even introduce more bugs. [4]When you catch bugs early, you also get fewer compound bugs.\nCompound bugs are two separate bugs that interact: you trip going\ndownstairs, and when you reach for the handrail it comes off in\nyour hand. In software this kind of bug is the hardest to find,\nand also tends to have the worst consequences. [5] The traditional\n\"break everything and then filter out the bugs\" approach inherently\nyields a lot of compound bugs. And software that's released in a\nseries of small changes inherently tends not to. The floors are\nconstantly being swept clean of any loose objects that might later\nget stuck in something.It helps if you use a technique called functional programming.\nFunctional programming means avoiding side-effects. It's something\nyou're more likely to see in research papers than commercial\nsoftware, but for Web-based applications it turns out to be really\nuseful. It's hard to write entire programs as purely functional\ncode, but you can write substantial chunks this way. It makes\nthose parts of your software easier to test, because they have no\nstate, and that is very convenient in a situation where you are\nconstantly making and testing small modifications. I wrote much\nof Viaweb's editor in this style, and we made our scripting language,\nRTML, \na purely functional language.People from the desktop software business will find this hard to\ncredit, but at Viaweb bugs became almost a game. Since most released\nbugs involved borderline cases, the users who encountered them were\nlikely to be advanced users, pushing the envelope. Advanced users\nare more forgiving about bugs, especially since you probably\nintroduced them in the course of adding some feature they were\nasking for. In fact, because bugs were rare and you had to be\ndoing sophisticated things to see them, advanced users were often\nproud to catch one. They would call support in a spirit more of\ntriumph than anger, as if they had scored points off us.SupportWhen you can reproduce errors, it changes your approach to customer\nsupport. At most software companies, support is offered as a way\nto make customers feel better. They're either calling you about\na known bug, or they're just doing something wrong and you have to\nfigure out what. In either case there's not much you can learn\nfrom them. And so you tend to view support calls as a pain in the\nass that you want to isolate from your developers as much as\npossible.This was not how things worked at Viaweb. At Viaweb, support was\nfree, because we wanted to hear from customers. If someone had a\nproblem, we wanted to know about it right away so that we could\nreproduce the error and release a fix.So at Viaweb the developers were always in close contact with\nsupport. The customer support people were about thirty feet away\nfrom the programmers, and knew that they could always interrupt\nanything with a report of a genuine bug. We would leave a board\nmeeting to fix a serious bug.Our approach to support made everyone happier. The customers were\ndelighted. Just imagine how it would feel to call a support line\nand be treated as someone bringing important news. The customer\nsupport people liked it because it meant they could help the users,\ninstead of reading scripts to them. And the programmers liked it\nbecause they could reproduce bugs instead of just hearing vague\nsecond-hand reports about them.Our policy of fixing bugs on the fly changed the relationship\nbetween customer support people and hackers. At most software\ncompanies, support people are underpaid human shields, and hackers\nare little copies of God the Father, creators of the world. Whatever\nthe procedure for reporting bugs, it is likely to be one-directional:\nsupport people who hear about bugs fill out some form that eventually\ngets passed on (possibly via QA) to programmers, who put it on\ntheir list of things to do. It was very different at Viaweb.\nWithin a minute of hearing about a bug from a customer, the support\npeople could be standing next to a programmer hearing him say \"Shit,\nyou're right, it's a bug.\" It delighted the support people to hear\nthat \"you're right\" from the hackers. They used to bring us bugs\nwith the same expectant air as a cat bringing you a mouse it has\njust killed. It also made them more careful in judging the\nseriousness of a bug, because now their honor was on the line.After we were bought by Yahoo, the customer support people were\nmoved far away from the programmers. It was only then that we\nrealized that they were effectively QA and to some extent marketing\nas well. In addition to catching bugs, they were the keepers of\nthe knowledge of vaguer, buglike things, like features that confused\nusers. [6] They were also a kind of proxy focus group; we could\nask them which of two new features users wanted more, and they were\nalways right.MoraleBeing able to release software immediately is a big motivator.\nOften as I was walking to work I would think of some change I wanted\nto make to the software, and do it that day. This worked for bigger\nfeatures as well. Even if something was going to take two weeks\nto write (few projects took longer), I knew I could see the effect\nin the software as soon as it was done.If I'd had to wait a year for the next release, I would have shelved\nmost of these ideas, for a while at least. The thing about ideas,\nthough, is that they lead to more ideas. Have you ever noticed\nthat when you sit down to write something, half the ideas that end\nup in it are ones you thought of while writing it? The same thing\nhappens with software. Working to implement one idea gives you\nmore ideas. So shelving an idea costs you not only that delay in\nimplementing it, but also all the ideas that implementing it would\nhave led to. In fact, shelving an idea probably even inhibits new\nideas: as you start to think of some new feature, you catch sight\nof the shelf and think \"but I already have a lot of new things I\nwant to do for the next release.\"What big companies do instead of implementing features is plan\nthem. At Viaweb we sometimes ran into trouble on this account.\nInvestors and analysts would ask us what we had planned for the\nfuture. The truthful answer would have been, we didn't have any\nplans. We had general ideas about things we wanted to improve,\nbut if we knew how we would have done it already. What were we\ngoing to do in the next six months? Whatever looked like the biggest\nwin. I don't know if I ever dared give this answer, but that was\nthe truth. Plans are just another word for ideas on the shelf.\nWhen we thought of good ideas, we implemented them.At Viaweb, as at many software companies, most code had one definite\nowner. But when you owned something you really owned it: no one\nexcept the owner of a piece of software had to approve (or even\nknow about) a release. There was no protection against breakage\nexcept the fear of looking like an idiot to one's peers, and that\nwas more than enough. I may have given the impression that we just\nblithely plowed forward writing code. We did go fast, but we\nthought very carefully before we released software onto those\nservers. And paying attention is more important to reliability\nthan moving slowly. Because he pays close attention, a Navy pilot\ncan land a 40,000 lb. aircraft at 140 miles per hour on a pitching\ncarrier deck, at night, more safely than the average teenager can\ncut a bagel.This way of writing software is a double-edged sword of course.\nIt works a lot better for a small team of good, trusted programmers\nthan it would for a big company of mediocre ones, where bad ideas\nare caught by committees instead of the people that had them.Brooks in ReverseFortunately, Web-based software does require fewer programmers.\nI once worked for a medium-sized desktop software company that had\nover 100 people working in engineering as a whole. Only 13 of\nthese were in product development. All the rest were working on\nreleases, ports, and so on. With Web-based software, all you need\n(at most) are the 13 people, because there are no releases, ports,\nand so on.Viaweb was written by just three people. [7] I was always under\npressure to hire more, because we wanted to get bought, and we knew\nthat buyers would have a hard time paying a high price for a company\nwith only three programmers. (Solution: we hired more, but created\nnew projects for them.)When you can write software with fewer programmers, it saves you\nmore than money. As Fred Brooks pointed out in The Mythical\nMan-Month, adding people to a project tends to slow it down. The\nnumber of possible connections between developers grows exponentially\nwith the size of the group. The larger the group, the more time\nthey'll spend in meetings negotiating how their software will work\ntogether, and the more bugs they'll get from unforeseen interactions.\nFortunately, this process also works in reverse: as groups get\nsmaller, software development gets exponentially more efficient.\nI can't remember the programmers at Viaweb ever having an actual\nmeeting. We never had more to say at any one time than we could\nsay as we were walking to lunch.If there is a downside here, it is that all the programmers have\nto be to some degree system administrators as well. When you're\nhosting software, someone has to be watching the servers, and in\npractice the only people who can do this properly are the ones who\nwrote the software. At Viaweb our system had so many components\nand changed so frequently that there was no definite border between\nsoftware and infrastructure. Arbitrarily declaring such a border\nwould have constrained our design choices. And so although we were\nconstantly hoping that one day (\"in a couple months\") everything\nwould be stable enough that we could hire someone whose job was\njust to worry about the servers, it never happened.I don't think it could be any other way, as long as you're still\nactively developing the product. Web-based software is never going\nto be something you write, check in, and go home. It's a live\nthing, running on your servers right now. A bad bug might not just\ncrash one user's process; it could crash them all. If a bug in\nyour code corrupts some data on disk, you have to fix it. And so\non. We found that you don't have to watch the servers every minute\n(after the first year or so), but you definitely want to keep an\neye on things you've changed recently. You don't release code late\nat night and then go home.Watching UsersWith server-based software, you're in closer touch with your code.\nYou can also be in closer touch with your users. Intuit is famous\nfor introducing themselves to customers at retail stores and asking\nto follow them home. If you've ever watched someone use your\nsoftware for the first time, you know what surprises must have\nawaited them.Software should do what users think it will. But you can't have\nany idea what users will be thinking, believe me, until you watch\nthem. And server-based software gives you unprecedented information\nabout their behavior. You're not limited to small, artificial\nfocus groups. You can see every click made by every user. You\nhave to consider carefully what you're going to look at, because\nyou don't want to violate users' privacy, but even the most general\nstatistical sampling can be very useful.When you have the users on your server, you don't have to rely on\nbenchmarks, for example. Benchmarks are simulated users. With\nserver-based software, you can watch actual users. To decide what\nto optimize, just log into a server and see what's consuming all\nthe CPU. And you know when to stop optimizing too: we eventually\ngot the Viaweb editor to the point where it was memory-bound rather\nthan CPU-bound, and since there was nothing we could do to decrease\nthe size of users' data (well, nothing easy), we knew we might as\nwell stop there.Efficiency matters for server-based software, because you're paying\nfor the hardware. The number of users you can support per server\nis the divisor of your capital cost, so if you can make your software\nvery efficient you can undersell competitors and still make a\nprofit. At Viaweb we got the capital cost per user down to about\n$5. It would be less now, probably less than the cost of sending\nthem the first month's bill. Hardware is free now, if your software\nis reasonably efficient.Watching users can guide you in design as well as optimization.\nViaweb had a scripting language called RTML that let advanced users\ndefine their own page styles. We found that RTML became a kind of\nsuggestion box, because users only used it when the predefined page\nstyles couldn't do what they wanted. Originally the editor put\nbutton bars across the page, for example, but after a number of\nusers used RTML to put buttons down the left \nside, \nwe made that an\noption (in fact the default) in the predefined page styles.Finally, by watching users you can often tell when they're in\ntrouble. And since the customer is always right, that's a sign of\nsomething you need to fix. At Viaweb the key to getting users was\nthe online test drive. It was not just a series of slides built\nby marketing people. In our test drive, users actually used the\nsoftware. It took about five minutes, and at the end of it they\nhad built a real, working store.\nThe test drive was the way we got nearly all our new users. I\nthink it will be the same for most Web-based applications. If\nusers can get through a test drive successfully, they'll like the\nproduct. If they get confused or bored, they won't. So anything\nwe could do to get more people through the test drive would increase\nour growth rate.I studied click trails of people taking the test drive and found\nthat at a certain step they would get confused and click on the\nbrowser's Back button. (If you try writing Web-based applications,\nyou'll find that the Back button becomes one of your most interesting\nphilosophical problems.) So I added a message at that point, telling\nusers that they were nearly finished, and reminding them not to\nclick on the Back button. Another great thing about Web-based\nsoftware is that you get instant feedback from changes: the number\nof people completing the test drive rose immediately from 60% to\n90%. And since the number of new users was a function of the number\nof completed test drives, our revenue growth increased by 50%, just\nfrom that change.MoneyIn the early 1990s I read an article in which someone said that\nsoftware was a subscription business. At first this seemed a very\ncynical statement. But later I realized that it reflects reality:\nsoftware development is an ongoing process. I think it's cleaner\nif you openly charge subscription fees, instead of forcing people\nto keep buying and installing new versions so that they'll keep\npaying you. And fortunately, subscriptions are the natural way to\nbill for Web-based applications.Hosting applications is an area where companies will play a role\nthat is not likely to be filled by freeware. Hosting applications\nis a lot of stress, and has real expenses. No one is going to want\nto do it for free.For companies, Web-based applications are an ideal source of revenue.\nInstead of starting each quarter with a blank slate, you have a\nrecurring revenue stream. Because your software evolves gradually,\nyou don't have to worry that a new model will flop; there never\nneed be a new model, per se, and if you do something to the software\nthat users hate, you'll know right away. You have no trouble with\nuncollectable bills; if someone won't pay you can just turn off\nthe service. And there is no possibility of piracy.That last \"advantage\" may turn out to be a problem. Some amount\nof piracy is to the advantage of software companies. If some user\nreally would not have bought your software at any price, you haven't\nlost anything if he uses a pirated copy. In fact you gain, because\nhe is one more user helping to make your software the standard--\nor who might buy a copy later, when he graduates from high school.When they can, companies like to do something called price\ndiscrimination, which means charging each customer as much as they\ncan afford. [8] Software is particularly suitable for price\ndiscrimination, because the marginal cost is close to zero. This\nis why some software costs more to run on Suns than on Intel boxes:\na company that uses Suns is not interested in saving money and can\nsafely be charged more. Piracy is effectively the lowest tier of\nprice discrimination. I think that software companies understand\nthis and deliberately turn a blind eye to some kinds of piracy. [9] \nWith server-based software they are going to have to come up with \nsome other solution.Web-based software sells well, especially in comparison to desktop\nsoftware, because it's easy to buy. You might think that people\ndecide to buy something, and then buy it, as two separate steps.\nThat's what I thought before Viaweb, to the extent I thought about\nthe question at all. In fact the second step can propagate back\ninto the first: if something is hard to buy, people will change\ntheir mind about whether they wanted it. And vice versa: you'll\nsell more of something when it's easy to buy. I buy more books\nbecause Amazon exists. Web-based software is just about the easiest\nthing in the world to buy, especially if you have just done an\nonline demo. Users should not have to do much more than enter a\ncredit card number. (Make them do more at your peril.)\nSometimes Web-based software is offered through ISPs acting as\nresellers. This is a bad idea. You have to be administering the\nservers, because you need to be constantly improving both hardware\nand software. If you give up direct control of the servers, you\ngive up most of the advantages of developing Web-based applications.Several of our competitors shot themselves in the foot this way--\nusually, I think, because they were overrun by suits who were\nexcited about this huge potential channel, and didn't realize that\nit would ruin the product they hoped to sell through it. Selling\nWeb-based software through ISPs is like selling sushi through\nvending machines.CustomersWho will the customers be? At Viaweb they were initially individuals\nand smaller companies, and I think this will be the rule with\nWeb-based applications. These are the users who are ready to try\nnew things, partly because they're more flexible, and partly because\nthey want the lower costs of new technology.Web-based applications will often be the best thing for big companies\ntoo (though they'll be slow to realize it). The best intranet is\nthe Internet. If a company uses true Web-based applications, the\nsoftware will work better, the servers will be better administered,\nand employees will have access to the system from anywhere.The argument against this approach usually hinges on security: if\naccess is easier for employees, it will be for bad guys too. Some\nlarger merchants were reluctant to use Viaweb because they thought\ncustomers' credit card information would be safer on their own\nservers. It was not easy to make this point diplomatically, but\nin fact the data was almost certainly safer in our hands than\ntheirs. Who can hire better people to manage security, a technology\nstartup whose whole business is running servers, or a clothing\nretailer? Not only did we have better people worrying about\nsecurity, we worried more about it. If someone broke into the\nclothing retailer's servers, it would affect at most one merchant,\ncould probably be hushed up, and in the worst case might get one\nperson fired. If someone broke into ours, it could affect thousands\nof merchants, would probably end up as news on CNet, and could put\nus out of business.If you want to keep your money safe, do you keep it under your\nmattress at home, or put it in a bank? This argument applies to\nevery aspect of server administration: not just security, but\nuptime, bandwidth, load management, backups, etc. Our existence\ndepended on doing these things right. Server problems were the\nbig no-no for us, like a dangerous toy would be for a toy maker,\nor a salmonella outbreak for a food processor.A big company that uses Web-based applications is to that extent\noutsourcing IT. Drastic as it sounds, I think this is generally\na good idea. Companies are likely to get better service this way\nthan they would from in-house system administrators. System\nadministrators can become cranky and unresponsive because they're\nnot directly exposed to competitive pressure: a salesman has to\ndeal with customers, and a developer has to deal with competitors'\nsoftware, but a system administrator, like an old bachelor, has\nfew external forces to keep him in line. [10] At Viaweb we had\nexternal forces in plenty to keep us in line. The people calling\nus were customers, not just co-workers. If a server got wedged,\nwe jumped; just thinking about it gives me a jolt of adrenaline,\nyears later.So Web-based applications will ordinarily be the right answer for\nbig companies too. They will be the last to realize it, however,\njust as they were with desktop computers. And partly for the same\nreason: it will be worth a lot of money to convince big companies\nthat they need something more expensive.There is always a tendency for rich customers to buy expensive\nsolutions, even when cheap solutions are better, because the people\noffering expensive solutions can spend more to sell them. At Viaweb\nwe were always up against this. We lost several high-end merchants\nto Web consulting firms who convinced them they'd be better off if\nthey paid half a million dollars for a custom-made online store on\ntheir own server. They were, as a rule, not better off, as more\nthan one discovered when Christmas shopping season came around and\nloads rose on their server. Viaweb was a lot more sophisticated\nthan what most of these merchants got, but we couldn't afford to\ntell them. At $300 a month, we couldn't afford to send a team of\nwell-dressed and authoritative-sounding people to make presentations\nto customers.A large part of what big companies pay extra for is the cost of\nselling expensive things to them. (If the Defense Department pays\na thousand dollars for toilet seats, it's partly because it costs\na lot to sell toilet seats for a thousand dollars.) And this is\none reason intranet software will continue to thrive, even though\nit is probably a bad idea. It's simply more expensive. There is\nnothing you can do about this conundrum, so the best plan is to go\nfor the smaller customers first. The rest will come in time.Son of ServerRunning software on the server is nothing new. In fact it's the\nold model: mainframe applications are all server-based. If\nserver-based software is such a good idea, why did it lose last\ntime? Why did desktop computers eclipse mainframes?At first desktop computers didn't look like much of a threat. The\nfirst users were all hackers-- or hobbyists, as they were called\nthen. They liked microcomputers because they were cheap. For the\nfirst time, you could have your own computer. The phrase \"personal\ncomputer\" is part of the language now, but when it was first used\nit had a deliberately audacious sound, like the phrase \"personal\nsatellite\" would today.Why did desktop computers take over? I think it was because they\nhad better software. And I think the reason microcomputer software\nwas better was that it could be written by small companies.I don't think many people realize how fragile and tentative startups\nare in the earliest stage. Many startups begin almost by accident--\nas a couple guys, either with day jobs or in school, writing a\nprototype of something that might, if it looks promising, turn into\na company. At this larval stage, any significant obstacle will stop\nthe startup dead in its tracks. Writing mainframe software required\ntoo much commitment up front. Development machines were expensive,\nand because the customers would be big companies, you'd need an\nimpressive-looking sales force to sell it to them. Starting a\nstartup to write mainframe software would be a much more serious\nundertaking than just hacking something together on your Apple II\nin the evenings. And so you didn't get a lot of startups writing\nmainframe applications.The arrival of desktop computers inspired a lot of new software,\nbecause writing applications for them seemed an attainable goal to\nlarval startups. Development was cheap, and the customers would\nbe individual people that you could reach through computer stores\nor even by mail-order.The application that pushed desktop computers out into the mainstream\nwas VisiCalc, the \nfirst spreadsheet. It was written by two guys\nworking in an attic, and yet did things no mainframe software could\ndo. [11] VisiCalc was such an advance, in its time, that people\nbought Apple IIs just to run it. And this was the beginning of a\ntrend: desktop computers won because startups wrote software for\nthem.It looks as if server-based software will be good this time around,\nbecause startups will write it. Computers are so cheap now that\nyou can get started, as we did, using a desktop computer as a\nserver. Inexpensive processors have eaten the workstation market\n(you rarely even hear the word now) and are most of the way through\nthe server market; Yahoo's servers, which deal with loads as high\nas any on the Internet, all have the same inexpensive Intel processors\nthat you have in your desktop machine. And once you've written\nthe software, all you need to sell it is a Web site. Nearly all\nour users came direct to our site through word of mouth and references\nin the press. [12]Viaweb was a typical larval startup. We were terrified of starting\na company, and for the first few months comforted ourselves by\ntreating the whole thing as an experiment that we might call off\nat any moment. Fortunately, there were few obstacles except\ntechnical ones. While we were writing the software, our Web server\nwas the same desktop machine we used for development, connected to\nthe outside world by a dialup line. Our only expenses in that\nphase were food and rent.There is all the more reason for startups to write Web-based software\nnow, because writing desktop software has become a lot less fun.\nIf you want to write desktop software now you do it on Microsoft's\nterms, calling their APIs and working around their buggy OS. And\nif you manage to write something that takes off, you may find that\nyou were merely doing market research for Microsoft.If a company wants to make a platform that startups will build on,\nthey have to make it something that hackers themselves will want\nto use. That means it has to be inexpensive and well-designed.\nThe Mac was popular with hackers when it first came out, and a lot\nof them wrote software for it. [13] You see this less with Windows,\nbecause hackers don't use it. The kind of people who are good at\nwriting software tend to be running Linux or FreeBSD now.I don't think we would have started a startup to write desktop\nsoftware, because desktop software has to run on Windows, and before\nwe could write software for Windows we'd have to use it. The Web \nlet us do an end-run around Windows, and deliver software running \non Unix direct to users through the browser. That is a liberating \nprospect, a lot like the arrival of PCs twenty-five years ago.MicrosoftBack when desktop computers arrived, IBM was the giant that everyone\nwas afraid of. It's hard to imagine now, but I remember the feeling\nvery well. Now the frightening giant is Microsoft, and I don't\nthink they are as blind to the threat facing them as IBM was.\nAfter all, Microsoft deliberately built their business in IBM's\nblind spot.I mentioned earlier that my mother doesn't really need a desktop\ncomputer. Most users probably don't. That's a problem for Microsoft,\nand they know it. If applications run on remote servers, no one\nneeds Windows. What will Microsoft do? Will they be able to use\ntheir control of the desktop to prevent, or constrain, this new\ngeneration of software?My guess is that Microsoft will develop some kind of server/desktop\nhybrid, where the operating system works together with servers they\ncontrol. At a minimum, files will be centrally available for users\nwho want that. I don't expect Microsoft to go all the way to the\nextreme of doing the computations on the server, with only a browser\nfor a client, if they can avoid it. If you only need a browser for\na client, you don't need Microsoft on the client, and if Microsoft\ndoesn't control the client, they can't push users towards their\nserver-based applications.I think Microsoft will have a hard time keeping the genie in the\nbottle. There will be too many different types of clients for them\nto control them all. And if Microsoft's applications only work\nwith some clients, competitors will be able to trump them by offering\napplications that work from any client. [14]In a world of Web-based applications, there is no automatic place\nfor Microsoft. They may succeed in making themselves a place, but\nI don't think they'll dominate this new world as they did the world\nof desktop applications.It's not so much that a competitor will trip them up as that they\nwill trip over themselves. With the rise of Web-based software,\nthey will be facing not just technical problems but their own\nwishful thinking. What they need to do is cannibalize their existing\nbusiness, and I can't see them facing that. The same single-mindedness\nthat has brought them this far will now be working against them.\nIBM was in exactly the same situation, and they could not master\nit. IBM made a late and half-hearted entry into the microcomputer\nbusiness because they were ambivalent about threatening their cash\ncow, mainframe computing. Microsoft will likewise be hampered by\nwanting to save the desktop. A cash cow can be a damned heavy\nmonkey on your back.I'm not saying that no one will dominate server-based applications.\nSomeone probably will eventually. But I think that there will be\na good long period of cheerful chaos, just as there was in the\nearly days of microcomputers. That was a good time for startups.\nLots of small companies flourished, and did it by making cool\nthings.Startups but More SoThe classic startup is fast and informal, with few people and little\nmoney. Those few people work very hard, and technology magnifies\nthe effect of the decisions they make. If they win, they win big.In a startup writing Web-based applications, everything you associate\nwith startups is taken to an extreme. You can write and launch a\nproduct with even fewer people and even less money. You have to\nbe even faster, and you can get away with being more informal.\nYou can literally launch your product as three guys sitting in the\nliving room of an apartment, and a server collocated at an ISP.\nWe did.Over time the teams have gotten smaller, faster, and more informal.\nIn 1960, software development meant a roomful of men with horn\nrimmed glasses and narrow black neckties, industriously writing\nten lines of code a day on IBM coding forms. In 1980, it was a\nteam of eight to ten people wearing jeans to the office and typing\ninto vt100s. Now it's a couple of guys sitting in a living room\nwith laptops. (And jeans turn out not to be the last word in\ninformality.)Startups are stressful, and this, unfortunately, is also taken to\nan extreme with Web-based applications. \nMany software companies, especially at the beginning, have periods\nwhere the developers slept under their desks and so on. The alarming\nthing about Web-based software is that there is nothing to prevent\nthis becoming the default. The stories about sleeping under desks\nusually end: then at last we shipped it and we all went home and\nslept for a week. Web-based software never ships. You can work\n16-hour days for as long as you want to. And because you can, and\nyour competitors can, you tend to be forced to. You can, so you\nmust. It's Parkinson's Law running in reverse.The worst thing is not the hours but the responsibility. Programmers\nand system administrators traditionally each have their own separate\nworries. Programmers have to worry about bugs, and system\nadministrators have to worry about infrastructure. Programmers\nmay spend a long day up to their elbows in source code, but at some\npoint they get to go home and forget about it. System administrators\nnever quite leave the job behind, but when they do get paged at\n4:00 AM, they don't usually have to do anything very complicated.\nWith Web-based applications, these two kinds of stress get combined.\nThe programmers become system administrators, but without the\nsharply defined limits that ordinarily make the job bearable.At Viaweb we spent the first six months just writing software. We\nworked the usual long hours of an early startup. In a desktop\nsoftware company, this would have been the part where we were\nworking hard, but it felt like a vacation compared to the next\nphase, when we took users onto our server. The second biggest\nbenefit of selling Viaweb to Yahoo (after the money) was to be able\nto dump ultimate responsibility for the whole thing onto the\nshoulders of a big company.Desktop software forces users to become system administrators.\nWeb-based software forces programmers to. There is less stress in\ntotal, but more for the programmers. That's not necessarily bad\nnews. If you're a startup competing with a big company, it's good\nnews. [15] Web-based applications offer a straightforward way to\noutwork your competitors. No startup asks for more.Just Good EnoughOne thing that might deter you from writing Web-based applications\nis the lameness of Web pages as a UI. That is a problem, I admit.\nThere were a few things we would have really liked to add to\nHTML and HTTP. What matters, though, is that Web pages are just\ngood enough.There is a parallel here with the first microcomputers. The\nprocessors in those machines weren't actually intended to be the\nCPUs of computers. They were designed to be used in things like\ntraffic lights. But guys like Ed Roberts, who designed the \nAltair,\nrealized that they were just good enough. You could combine one\nof these chips with some memory (256 bytes in the first Altair),\nand front panel switches, and you'd have a working computer. Being\nable to have your own computer was so exciting that there were\nplenty of people who wanted to buy them, however limited.Web pages weren't designed to be a UI for applications, but they're\njust good enough. And for a significant number of users, software\nthat you can use from any browser will be enough of a win in itself\nto outweigh any awkwardness in the UI. Maybe you can't write the\nbest-looking spreadsheet using HTML, but you can write a spreadsheet\nthat several people can use simultaneously from different locations\nwithout special client software, or that can incorporate live data\nfeeds, or that can page you when certain conditions are triggered.\nMore importantly, you can write new kinds of applications that\ndon't even have names yet. VisiCalc was not merely a microcomputer\nversion of a mainframe application, after all-- it was a new type\nof application.Of course, server-based applications don't have to be Web-based.\nYou could have some other kind of client. But I'm pretty sure\nthat's a bad idea. It would be very convenient if you could assume\nthat everyone would install your client-- so convenient that you\ncould easily convince yourself that they all would-- but if they\ndon't, you're hosed. Because Web-based software assumes nothing\nabout the client, it will work anywhere the Web works. That's a\nbig advantage already, and the advantage will grow as new Web\ndevices proliferate. Users will like you because your software\njust works, and your life will be easier because you won't have to\ntweak it for every new client. [16]I feel like I've watched the evolution of the Web as closely as\nanyone, and I can't predict what's going to happen with clients.\nConvergence is probably coming, but where? I can't pick a winner.\nOne thing I can predict is conflict between AOL and Microsoft.\nWhatever Microsoft's .NET turns out to be, it will probably involve\nconnecting the desktop to servers. Unless AOL fights back, they\nwill either be pushed aside or turned into a pipe between Microsoft\nclient and server software. If Microsoft and AOL get into a client\nwar, the only thing sure to work on both will be browsing the Web,\nmeaning Web-based applications will be the only kind that work\neverywhere.How will it all play out? I don't know. And you don't have to\nknow if you bet on Web-based applications. No one can break that\nwithout breaking browsing. The Web may not be the only way to\ndeliver software, but it's one that works now and will continue to\nwork for a long time. Web-based applications are cheap to develop,\nand easy for even the smallest startup to deliver. They're a lot\nof work, and of a particularly stressful kind, but that only makes\nthe odds better for startups.Why Not?E. B. White was amused to learn from a farmer friend that many\nelectrified fences don't have any current running through them.\nThe cows apparently learn to stay away from them, and after that\nyou don't need the current. \"Rise up, cows!\" he wrote, \"Take your\nliberty while despots snore!\"If you're a hacker who has thought of one day starting a startup,\nthere are probably two things keeping you from doing it. One is\nthat you don't know anything about business. The other is that\nyou're afraid of competition. Neither of these fences have any\ncurrent in them.There are only two things you have to know about business: build\nsomething users love, and make more than you spend. If you get\nthese two right, you'll be ahead of most startups. You can figure\nout the rest as you go.You may not at first make more than you spend, but as long as the\ngap is closing fast enough you'll be ok. If you start out underfunded,\nit will at least encourage a habit of frugality. The less you\nspend, the easier it is to make more than you spend. Fortunately,\nit can be very cheap to launch a Web-based application. We launched\non under $10,000, and it would be even cheaper today. We had to\nspend thousands on a server, and thousands more to get SSL. (The\nonly company selling SSL software at the time was Netscape.) Now\nyou can rent a much more powerful server, with SSL included, for\nless than we paid for bandwidth alone. You could launch a Web-based\napplication now for less than the cost of a fancy office chair.As for building something users love, here are some general tips.\nStart by making something clean and simple that you would want to\nuse yourself. Get a version 1.0 out fast, then continue to improve\nthe software, listening closely to the users as you do. The customer\nis always right, but different customers are right about different\nthings; the least sophisticated users show you what you need to\nsimplify and clarify, and the most sophisticated tell you what\nfeatures you need to add. The best thing software can be is easy,\nbut the way to do this is to get the defaults right, not to limit\nusers' choices. Don't get complacent if your competitors' software\nis lame; the standard to compare your software to is what it could\nbe, not what your current competitors happen to have. Use your\nsoftware yourself, all the time. Viaweb was supposed to be an\nonline store builder, but we used it to make our own site too.\nDon't listen to marketing people or designers or product managers\njust because of their job titles. If they have good ideas, use\nthem, but it's up to you to decide; software has to be designed by\nhackers who understand design, not designers who know a little\nabout software. If you can't design software as well as implement\nit, don't start a startup.Now let's talk about competition. What you're afraid of is not\npresumably groups of hackers like you, but actual companies, with\noffices and business plans and salesmen and so on, right? Well,\nthey are more afraid of you than you are of them, and they're right.\nIt's a lot easier for a couple of hackers to figure out how to rent\noffice space or hire sales people than it is for a company of any\nsize to get software written. I've been on both sides, and I know.\nWhen Viaweb was bought by Yahoo, I suddenly found myself working\nfor a big company, and it was like trying to run through waist-deep\nwater.I don't mean to disparage Yahoo. They had some good hackers, and\nthe top management were real butt-kickers. For a big company, they\nwere exceptional. But they were still only about a tenth as\nproductive as a small startup. No big company can do much better\nthan that. What's scary about Microsoft is that a company so\nbig can develop software at all. They're like a mountain that\ncan walk.Don't be intimidated. You can do as much that Microsoft can't as\nthey can do that you can't. And no one can stop you. You don't\nhave to ask anyone's permission to develop Web-based applications.\nYou don't have to do licensing deals, or get shelf space in retail\nstores, or grovel to have your application bundled with the OS.\nYou can deliver software right to the browser, and no one can get\nbetween you and potential users without preventing them from browsing\nthe Web.You may not believe it, but I promise you, Microsoft is scared of\nyou. The complacent middle managers may not be, but Bill is,\nbecause he was you once, back in 1975, the last time a new way of\ndelivering software appeared.Notes[1] Realizing that much of the money is in the services, companies\nbuilding lightweight clients have usually tried to combine the\nhardware with an \nonline service. \n This approach has not worked\nwell, partly because you need two different kinds of companies to\nbuild consumer electronics and to run an online service, and partly\nbecause users hate the idea. Giving away the razor and making\nmoney on the blades may work for Gillette, but a razor is much\nsmaller commitment than a Web terminal. Cell phone handset makers\nare satisfied to sell hardware without trying to capture the service\nrevenue as well. That should probably be the model for Internet\nclients too. If someone just sold a nice-looking little box with\na Web browser that you could use to connect through any ISP, every\ntechnophobe in the country would buy one.[2] Security always depends more on not screwing up than any design\ndecision, but the nature of server-based software will make developers\npay more attention to not screwing up. Compromising a server could\ncause such damage that ASPs (that want to stay in business) are\nlikely to be careful about security.[3] In 1995, when we started Viaweb, Java applets were supposed to\nbe the technology everyone was going to use to develop server-based\napplications. Applets seemed to us an old-fashioned idea. Download\nprograms to run on the client? Simpler just to go all the way and\nrun the programs on the server. We wasted little time\non applets, but countless other startups must have been lured into\nthis tar pit. Few can have escaped alive, or Microsoft could not\nhave gotten away with dropping Java in the most recent version of\nExplorer.[4] This point is due to Trevor Blackwell, who adds \"the cost of\nwriting software goes up more than linearly with its size. Perhaps\nthis is mainly due to fixing old bugs, and the cost can be more\nlinear if all bugs are found quickly.\"[5] The hardest kind of bug to find may be a variant of compound\nbug where one bug happens to compensate for another. When you fix\none bug, the other becomes visible. But it will seem as if the\nfix is at fault, since that was the last thing you changed.[6] Within Viaweb we once had a contest to describe the worst thing\nabout our software. Two customer support people tied for first\nprize with entries I still shiver to recall. We fixed both problems\nimmediately.[7] Robert Morris wrote the ordering system, which shoppers used\nto place orders. Trevor Blackwell wrote the image generator and\nthe manager, which merchants used to retrieve orders, view statistics,\nand configure domain names etc. I wrote the editor, which merchants\nused to build their sites. The ordering system and image generator\nwere written in C and C++, the manager mostly in Perl, and the editor\nin Lisp.[8] Price discrimination is so pervasive (how often have you heard\na retailer claim that their buying power meant lower prices for\nyou?) that I was surprised to find it was outlawed in the U.S. by\nthe Robinson-Patman Act of 1936. This law does not appear to be\nvigorously enforced.[9] In No Logo, Naomi Klein says that clothing brands favored by\n\"urban youth\" do not try too hard to prevent shoplifting because\nin their target market the shoplifters are also the fashion leaders.[10] Companies often wonder what to outsource and what not to.\nOne possible answer: outsource any job that's not directly exposed\nto competitive pressure, because outsourcing it will thereby expose\nit to competitive pressure.[11] The two guys were Dan Bricklin and Bob Frankston. Dan wrote\na prototype in Basic in a couple days, then over the course of the\nnext year they worked together (mostly at night) to make a more\npowerful version written in 6502 machine language. Dan was at\nHarvard Business School at the time and Bob nominally had a day\njob writing software. \"There was no great risk in doing a business,\"\nBob wrote, \"If it failed it failed. No big deal.\"[12] It's not quite as easy as I make it sound. It took a painfully\nlong time for word of mouth to get going, and we did not start to\nget a lot of press coverage until we hired a \nPR firm \n(admittedly\nthe best in the business) for $16,000 per month. However, it was\ntrue that the only significant channel was our own Web site.[13] If the Mac was so great, why did it lose? Cost, again.\nMicrosoft concentrated on the software business, and unleashed a\nswarm of cheap component suppliers on Apple hardware. It did not\nhelp, either, that suits took over during a critical period.[14] One thing that would help Web-based applications, and help\nkeep the next generation of software from being overshadowed by\nMicrosoft, would be a good open-source browser. Mozilla is\nopen-source but seems to have suffered from having been corporate\nsoftware for so long. A small, fast browser that was actively\nmaintained would be a great thing in itself, and would probably\nalso encourage companies to build little Web appliances.Among other things, a proper open-source browser would cause HTTP\nand HTML to continue to evolve (as e.g. Perl has). It would help\nWeb-based applications greatly to be able to distinguish between\nselecting a link and following it; all you'd need to do this would\nbe a trivial enhancement of HTTP, to allow multiple urls in a\nrequest. Cascading menus would also be good.If you want to change the world, write a new Mosaic. Think it's\ntoo late? In 1998 a lot of people thought it was too late to launch\na new search engine, but Google proved them wrong. There is always\nroom for something new if the current options suck enough. Make\nsure it works on all the free OSes first-- new things start with\ntheir users.[15] Trevor Blackwell, who probably knows more about this from\npersonal experience than anyone, writes:\"I would go farther in saying that because server-based software\nis so hard on the programmers, it causes a fundamental economic\nshift away from large companies. It requires the kind of intensity\nand dedication from programmers that they will only be willing to\nprovide when it's their own company. Software companies can hire\nskilled people to work in a not-too-demanding environment, and can\nhire unskilled people to endure hardships, but they can't hire\nhighly skilled people to bust their asses. Since capital is no\nlonger needed, big companies have little to bring to the table.\"[16] In the original version of this essay, I advised avoiding\nJavascript. That was a good plan in 2001, but Javascript now works.\nThanks to Sarah Harlin, Trevor Blackwell, Robert Morris, Eric Raymond, Ken Anderson,\nand Dan Giffin for reading drafts of this paper; to Dan Bricklin and\nBob Frankston for information about VisiCalc; and again to Ken Anderson\nfor inviting me to speak at BBN.\n\nYou'll find this essay and 14 others in\nHackers & Painters.\n" }, { "path": "data/PaulGrahamEssayMedium/start.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nMarch 2005(This essay is derived from a talk at the Harvard Computer\nSociety.)You need three things to create a successful startup: to start with\ngood people, to make something customers actually want, and to spend\nas little money as possible. Most startups that fail do it because\nthey fail at one of these. A startup that does all three will\nprobably succeed.And that's kind of exciting, when you think about it, because all\nthree are doable. Hard, but doable. And since a startup that\nsucceeds ordinarily makes its founders rich, that implies getting\nrich is doable too. Hard, but doable.If there is one message I'd like to get across about startups,\nthat's it. There is no magically difficult step that requires\nbrilliance to solve.The IdeaIn particular, you don't need a brilliant \nidea to start a startup\naround. The way a startup makes money is to offer people better\ntechnology than they have now. But what people have now is often\nso bad that it doesn't take brilliance to do better.Google's plan, for example, was simply to create a search site that\ndidn't suck. They had three new ideas: index more of the Web, use\nlinks to rank search results, and have clean, simple web pages with\nunintrusive keyword-based ads. Above all, they were determined to\nmake a site that was good to use. No doubt there are great technical\ntricks within Google, but the overall plan was straightforward.\nAnd while they probably have bigger ambitions now, this alone brings\nthem a billion dollars a year. [1]There are plenty of other areas that are just as backward as search\nwas before Google. I can think of several heuristics for generating\nideas for startups, but most reduce to this: look at something\npeople are trying to do, and figure out how to do it in a way that\ndoesn't suck.For example, dating sites currently suck far worse than search did\nbefore Google. They all use the same simple-minded model.\nThey seem to have approached the problem by thinking about how to\ndo database matches instead of how dating works in the real world.\nAn undergrad could build something better as a class project. And\nyet there's a lot of money at stake. Online dating is a valuable\nbusiness now, and it might be worth a hundred times as much if it\nworked.An idea for a startup, however, is only a beginning. A lot of\nwould-be startup founders think the key to the whole process is the\ninitial idea, and from that point all you have to do is execute.\nVenture capitalists know better. If you go to VC firms with a\nbrilliant idea that you'll tell them about if they sign a nondisclosure\nagreement, most will tell you to get lost. That shows how much a \nmere idea is worth. The market price is less than the inconvenience \nof signing an NDA.Another sign of how little the initial idea is worth is the number\nof startups that change their plan en route. Microsoft's original\nplan was to make money selling programming languages, of all things.\nTheir current business model didn't occur to them until IBM dropped\nit in their lap five years later.Ideas for startups are worth something, certainly, but the trouble\nis, they're not transferrable. They're not something you could\nhand to someone else to execute. Their value is mainly as starting\npoints: as questions for the people who had them to continue thinking\nabout.What matters is not ideas, but the people who have them. Good\npeople can fix bad ideas, but good ideas can't save bad people. \nPeopleWhat do I mean by good people? One of the best tricks I learned \nduring our startup was a rule for deciding \nwho to hire. Could you\ndescribe the person as an animal? It might be hard to translate \nthat into another language, but I think everyone in the US knows \nwhat it means. It means someone who takes their work a little too \nseriously; someone who does what they do so well that they pass\nright through professional and cross over into obsessive.What it means specifically depends on the job: a salesperson who\njust won't take no for an answer; a hacker who will stay up till \n4:00 AM rather than go to bed leaving code with a bug in it; a PR \nperson who will cold-call New York Times reporters on their cell\nphones; a graphic designer who feels physical pain when something \nis two millimeters out of place.Almost everyone who worked for us was an animal at what they did. \nThe woman in charge of sales was so tenacious that I used to feel\nsorry for potential customers on the phone with her. You could \nsense them squirming on the hook, but you knew there would be no \nrest for them till they'd signed up.If you think about people you know, you'll find the animal test is\neasy to apply. Call the person's image to mind and imagine the\nsentence \"so-and-so is an animal.\" If you laugh, they're not. You\ndon't need or perhaps even want this quality in big companies, but\nyou need it in a startup.For programmers we had three additional tests. Was the person\ngenuinely smart? If so, could they actually get things done? And\nfinally, since a few good hackers have unbearable personalities, \ncould we stand to have them around?That last test filters out surprisingly few people. We could bear\nany amount of nerdiness if someone was truly smart. What we couldn't\nstand were people with a lot of attitude. But most of those weren't\ntruly smart, so our third test was largely a restatement of the\nfirst.When nerds are unbearable it's usually because they're trying too\nhard to seem smart. But the smarter they are, the less pressure\nthey feel to act smart. So as a rule you can recognize genuinely\nsmart people by their ability to say things like \"I don't know,\" \n\"Maybe you're right,\" and \"I don't understand x well enough.\"This technique doesn't always work, because people can be influenced\nby their environment. In the MIT CS department, there seems to be\na tradition of acting like a brusque know-it-all. I'm told it derives\nultimately from Marvin Minsky, in the same way the classic airline\npilot manner is said to derive from Chuck Yeager. Even genuinely\nsmart people start to act this way there, so you have to make\nallowances.It helped us to have Robert Morris, who is one of the readiest to\nsay \"I don't know\" of anyone I've met. (At least, he was before he \nbecame a professor at MIT.) No one dared put on attitude around \nRobert, because he was obviously smarter than they were and yet had\nzero attitude himself.Like most startups, ours began with a group of friends, and it was\nthrough personal contacts that we got most of the people we hired.\nThis is a crucial difference between startups and big companies.\nBeing friends with someone for even a couple days will tell you \nmore than companies could ever learn in interviews. [2]It's no coincidence that startups start around universities, because\nthat's where smart people meet. It's not what people learn in \nclasses at MIT and Stanford that has made technology companies\nspring up around them. They could sing campfire songs in the classes\nso long as admissions worked the same.If you start a startup, there's a good chance it will be with people\nyou know from college or grad school. So in theory you ought to \ntry to make friends with as many smart people as you can in school,\nright? Well, no. Don't make a conscious effort to schmooze; that\ndoesn't work well with hackers.What you should do in college is work on your own projects. Hackers\nshould do this even if they don't plan to start startups, because \nit's the only real way to learn how to program. In some cases you\nmay collaborate with other students, and this is the best way to\nget to know good hackers. The project may even grow into a startup.\nBut once again, I wouldn't aim too directly at either target. Don't\nforce things; just work on stuff you like with people you like.Ideally you want between two and four founders. It would be hard\nto start with just one. One person would find the moral weight of\nstarting a company hard to bear. Even Bill Gates, who seems to be \nable to bear a good deal of moral weight, had to have a co-founder. \nBut you don't want so many founders that the company starts to look\nlike a group photo. Partly because you don't need a lot of people\nat first, but mainly because the more founders you have, the worse\ndisagreements you'll have. When there are just two or three founders,\nyou know you have to resolve disputes immediately or perish. If\nthere are seven or eight, disagreements can linger and harden into\nfactions. You don't want mere voting; you need unanimity.In a technology startup, which most startups are, the founders\nshould include technical people. During the Internet Bubble there \nwere a number of startups founded by business people who then went\nlooking for hackers to create their product for them. This doesn't \nwork well. Business people are bad at deciding what to do with \ntechnology, because they don't know what the options are, or which\nkinds of problems are hard and which are easy. And when business\npeople try to hire hackers, they can't tell which ones are \ngood.\nEven other hackers have a hard time doing that. \nFor business people it's roulette.Do the founders of a startup have to include business people? That\ndepends. We thought so when we started ours, and we asked several \npeople who were said to know about this mysterious thing called\n\"business\" if they would be the president. But they all said no,\nso I had to do it myself. And what I discovered was that business\nwas no great mystery. It's not something like physics or medicine\nthat requires extensive study. You just try to get people to pay\nyou for stuff.I think the reason I made such a mystery of business was that I was\ndisgusted by the idea of doing it. I wanted to work in the pure, \nintellectual world of software, not deal with customers' mundane \nproblems. People who don't want to get dragged into some kind of\nwork often develop a protective incompetence at it. Paul Erdos was\nparticularly good at this. By seeming unable even to cut a grapefruit\nin half (let alone go to the store and buy one), he forced other\npeople to do such things for him, leaving all his time free for\nmath. Erdos was an extreme case, but most husbands use the same \ntrick to some degree.Once I was forced to discard my protective incompetence, I found\nthat business was neither so hard nor so boring as I feared. There\nare esoteric areas of business that are quite hard, like tax law\nor the pricing of derivatives, but you don't need to know about \nthose in a startup. All you need to know about business to run a \nstartup are commonsense things people knew before there were business\nschools, or even universities.If you work your way down the Forbes 400 making an x next to the \nname of each person with an MBA, you'll learn something important\nabout business school. After Warren Buffett, you don't hit another \nMBA till number 22,\nPhil Knight, the CEO of Nike. There are only 5 MBAs in the top\n50. What you notice in the Forbes 400 are a lot of people with \ntechnical backgrounds. Bill Gates, Steve Jobs, Larry Ellison,\nMichael Dell, Jeff Bezos, Gordon Moore. The rulers of the technology\nbusiness tend to come from technology, not business. So if you \nwant to invest two years in something that will help you succeed \nin business, the evidence suggests you'd do better to learn how to \nhack than get an MBA. [3]There is one reason you might want to include business people in a\nstartup, though: because you have to have at least one person willing\nand able to focus on what customers want. Some believe only business\npeople can do this-- that hackers can implement software, but not \ndesign it. That's nonsense. There's nothing about knowing how to\nprogram that prevents hackers from understanding users, or about\nnot knowing how to program that magically enables business people \nto understand them.If you can't understand users, however, you should either learn how\nor find a co-founder who can. That is the single most important\nissue for technology startups, and the rock that sinks more of them\nthan anything else.What Customers WantIt's not just startups that have to worry about this. I think most\nbusinesses that fail do it because they don't give customers what\nthey want. Look at restaurants. A large percentage fail, about a\nquarter in the first year. But can you think of one restaurant\nthat had really good food and went out of business?Restaurants with great food seem to prosper no matter what. A \nrestaurant with great food can be expensive, crowded, noisy, dingy,\nout of the way, and even have bad service, and people will keep\ncoming. It's true that a restaurant with mediocre food can sometimes \nattract customers through gimmicks. But that approach is very \nrisky. It's more straightforward just to make the food good.It's the same with technology. You hear all kinds of reasons why\nstartups fail. But can you think of one that had a massively popular\nproduct and still failed?In nearly every failed startup, the real problem was that customers\ndidn't want the product. For most, the cause of death is listed \nas \"ran out of funding,\" but that's only the immediate cause. Why \ncouldn't they get more funding? Probably because the product was\na dog, or never seemed likely to be done, or both.When I was trying to think of the things every startup needed to \ndo, I almost included a fourth: get a version 1 out as soon as you\ncan. But I decided not to, because that's implicit in making\nsomething customers want. The only way to make something customers\nwant is to get a prototype in front of them and refine it based on \ntheir reactions.The other approach is what I call the \"Hail Mary\" strategy. You \nmake elaborate plans for a product, hire a team of engineers to \ndevelop it (people who do this tend to use the term \"engineer\" for \nhackers), and then find after a year that you've spent two million\ndollars to develop something no one wants. This was not uncommon\nduring the Bubble, especially in companies run by business types, \nwho thought of software development as something terrifying that\ntherefore had to be carefully planned.We never even considered that approach. As a Lisp hacker, I come \nfrom the tradition of rapid prototyping. I would not claim (at\nleast, not here) that this is the right way to write every program,\nbut it's certainly the right way to write software for a startup.\nIn a startup, your initial plans are almost certain to be wrong in\nsome way, and your first priority should be to figure out where. \nThe only way to do that is to try implementing them.Like most startups, we changed our plan on the fly. At first we\nexpected our customers to be Web consultants. But it turned out\nthey didn't like us, because our software was easy to use and we hosted\nthe site. It would be too easy for clients to fire them. We also\nthought we'd be able to sign up a lot of catalog companies, because\nselling online was a natural extension of their existing business.\nBut in 1996 that was a hard sell. The middle managers we talked \nto at catalog companies saw the Web not as an opportunity, but as\nsomething that meant more work for them.We did get a few of the more adventurous catalog companies. Among\nthem was Frederick's of Hollywood, which gave us valuable experience\ndealing with heavy loads on our servers. But most of our users \nwere small, individual merchants who saw the Web as an opportunity \nto build a business. Some had retail stores, but many only existed\nonline. And so we changed direction to focus on these users.\nInstead of concentrating on the features Web consultants and catalog\ncompanies would want, we worked to make the software easy to use.I learned something valuable from that. It's worth trying very, \nvery hard to make technology easy to use. Hackers are so used to\ncomputers that they have no idea how horrifying software seems to\nnormal people. Stephen Hawking's editor told him that every equation\nhe included in his book would cut sales in half. When you work on\nmaking technology easier to use, you're riding that curve up instead \nof down. A 10% improvement in ease of use doesn't just increase \nyour sales 10%. It's more likely to double your sales.How do you figure out what customers want? Watch them. One of the\nbest places to do this was at trade shows. Trade shows didn't pay \nas a way of getting new customers, but they were worth it as market\nresearch. We didn't just give canned presentations at trade shows.\nWe used to show people how to build real, working stores. Which \nmeant we got to watch as they used our software, and talk to them \nabout what they needed.No matter what kind of startup you start, it will probably be a \nstretch for you, the founders, to understand what users want. The\nonly kind of software you can build without studying users is the \nsort for which you are the typical user. But this is just the kind\nthat tends to be open source: operating systems, programming\nlanguages, editors, and so on. So if you're developing technology\nfor money, you're probably not going to be developing it for people\nlike you. Indeed, you can use this as a way to generate ideas for\nstartups: what do people who are not like you want from technology?When most people think of startups, they think of companies like\nApple or Google. Everyone knows these, because they're big consumer\nbrands. But for every startup like that, there are twenty more \nthat operate in niche markets or live quietly down in the infrastructure.\nSo if you start a successful startup, odds are you'll start one of \nthose.Another way to say that is, if you try to start the kind of startup\nthat has to be a big consumer brand, the odds against succeeding\nare steeper. The best odds are in niche markets. Since startups \nmake money by offering people something better than they had before,\nthe best opportunities are where things suck most. And it would \nbe hard to find a place where things suck more than in corporate \nIT departments. You would not believe the amount of money companies\nspend on software, and the crap they get in return. This imbalance\nequals opportunity.If you want ideas for startups, one of the most valuable things you\ncould do is find a middle-sized non-technology company and spend a \ncouple weeks just watching what they do with computers. Most good\nhackers have no more idea of the horrors perpetrated in these places\nthan rich Americans do of what goes on in Brazilian slums.Start by writing software for smaller companies, because it's easier\nto sell to them. It's worth so much to sell stuff to big companies\nthat the people selling them the crap they currently use spend a\nlot of time and money to do it. And while you can outhack Oracle\nwith one frontal lobe tied behind your back, you can't outsell an\nOracle salesman. So if you want to win through better technology,\naim at smaller customers. [4]They're the more strategically valuable part of the market anyway. \nIn technology, the low end always eats the high end. It's easier \nto make an inexpensive product more powerful than to make a powerful\nproduct cheaper. So the products that start as cheap, simple options\ntend to gradually grow more powerful till, like water rising in a \nroom, they squash the \"high-end\" products against the ceiling. Sun\ndid this to mainframes, and Intel is doing it to Sun. Microsoft\nWord did it to desktop publishing software like Interleaf and\nFramemaker. Mass-market digital cameras are doing it to the expensive\nmodels made for professionals. Avid did it to the manufacturers \nof specialized video editing systems, and now Apple is doing it to\nAvid. Henry Ford did it to the car makers that preceded\nhim. If you build the simple, inexpensive option, you'll not only\nfind it easier to sell at first, but you'll also be in the best \nposition to conquer the rest of the market.It's very dangerous to let anyone fly under you. If you have the\ncheapest, easiest product, you'll own the low end. And if you\ndon't, you're in the crosshairs of whoever does.Raising MoneyTo make all this happen, you're going to need money. Some startups\nhave been self-funding-- Microsoft for example-- but most aren't.\nI think it's wise to take money from investors. To be self-funding,\nyou have to start as a consulting company, and it's hard to switch\nfrom that to a product company.Financially, a startup is like a pass/fail course. The way to get\nrich from a startup is to maximize the company's chances of succeeding,\nnot to maximize the amount of stock you retain. So if you can trade\nstock for something that improves your odds, it's probably a smart \nmove.To most hackers, getting investors seems like a terrifying and\nmysterious process. Actually it's merely tedious. I'll try to\ngive an outline of how it works.The first thing you'll need is a few tens of thousands of dollars \nto pay your expenses while you develop a prototype. This is called\nseed capital. Because so little money is involved, raising seed\ncapital is comparatively easy-- at least in the sense of getting a\nquick yes or no.Usually you get seed money from individual rich people called\n\"angels.\" Often they're people who themselves got rich from technology.\nAt the seed stage, investors don't expect you to have an elaborate\nbusiness plan. Most know that they're supposed to decide quickly.\nIt's not unusual to get a check within a week based on a half-page\nagreement.We started Viaweb with $10,000 of seed money from our friend Julian.\nBut he gave us a lot more than money. He's a former CEO and also\na corporate lawyer, so he gave us a lot of valuable advice about\nbusiness, and also did all the legal work of getting us set up as\na company. Plus he introduced us to one of the two \nangel investors who supplied our next round of funding.Some angels, especially those with technology backgrounds, may be \nsatisfied with a demo and a verbal description of what you plan to \ndo. But many will want a copy of your business plan, if only to\nremind themselves what they invested in.Our angels asked for one, and looking back, I'm amazed how much\nworry it caused me. \"Business plan\" has that word \"business\" in\nit, so I figured it had to be something I'd have to read a book\nabout business plans to write. Well, it doesn't. At this stage,\nall most investors expect is a brief description of what you plan \nto do and how you're going to make money from it, and the resumes \nof the founders. If you just sit down and write out what you've\nbeen saying to one another, that should be fine. It shouldn't take\nmore than a couple hours, and you'll probably find that writing it\nall down gives you more ideas about what to do.For the angel to have someone to make the check out to, you're going\nto have to have some kind of company. Merely incorporating yourselves\nisn't hard. The problem is, for the company to exist, you have to\ndecide who the founders are, and how much stock they each have. If\nthere are two founders with the same qualifications who are both\nequally committed to the business, that's easy. But if you have a\nnumber of people who are expected to contribute in varying degrees,\narranging the proportions of stock can be hard. And once you've\ndone it, it tends to be set in stone.I have no tricks for dealing with this problem. All I can say is,\ntry hard to do it right. I do have a rule of thumb for recognizing\nwhen you have, though. When everyone feels they're getting a\nslightly bad deal, that they're doing more than they should for the\namount of stock they have, the stock is optimally apportioned.There is more to setting up a company than incorporating it, of\ncourse: insurance, business license, unemployment compensation, \nvarious things with the IRS. I'm not even sure what the list is,\nbecause we, ah, skipped all that. When we got real funding near\nthe end of 1996, we hired a great CFO, who fixed everything \nretroactively. It turns out that no one comes and arrests you if\nyou don't do everything you're supposed to when starting a company.\nAnd a good thing too, or a lot of startups would never get started.\n[5]It can be dangerous to delay turning yourself into a company, because\none or more of the founders might decide to split off and start \nanother company doing the same thing. This does happen. So when\nyou set up the company, as well as as apportioning the stock, you\nshould get all the founders to sign something agreeing that everyone's\nideas belong to this company, and that this company is going to be\neveryone's only job.[If this were a movie, ominous music would begin here.]While you're at it, you should ask what else they've signed. One\nof the worst things that can happen to a startup is to run into \nintellectual property problems. We did, and it came closer to \nkilling us than any competitor ever did.As we were in the middle of getting bought, we discovered that one\nof our people had, early on, been bound by an agreement that said\nall his ideas belonged to the giant company that was paying for him\nto go to grad school. In theory, that could have meant someone\nelse owned big chunks of our software. So the acquisition came to\na screeching halt while we tried to sort this out. The problem \nwas, since we'd been about to be acquired, we'd allowed ourselves \nto run low on cash. Now we needed to raise more to keep going. \nBut it's hard to raise money with an IP cloud over your head, because\ninvestors can't judge how serious it is.Our existing investors, knowing that we needed money and had nowhere\nelse to get it, at this point attempted certain gambits which I\nwill not describe in detail, except to remind readers that the word \n\"angel\" is a metaphor. The founders thereupon proposed to walk \naway from the company, after giving the investors a brief tutorial \non how to administer the servers themselves. And while this was\nhappening, the acquirers used the delay as an excuse to welch on \nthe deal.Miraculously it all turned out ok. The investors backed down; we\ndid another round of funding at a reasonable valuation; the giant\ncompany finally gave us a piece of paper saying they didn't own our\nsoftware; and six months later we were bought by Yahoo for much\nmore than the earlier acquirer had agreed to pay. So we were happy\nin the end, though the experience probably took several years off \nmy life.Don't do what we did. Before you consummate a startup, ask \neveryone about their previous IP history.Once you've got a company set up, it may seem presumptuous to go\nknocking on the doors of rich people and asking them to invest tens\nof thousands of dollars in something that is really just a bunch \nof guys with some ideas. But when you look at it from the rich\npeople's point of view, the picture is more encouraging. Most rich \npeople are looking for good investments. If you really think you\nhave a chance of succeeding, you're doing them a favor by letting\nthem invest. Mixed with any annoyance they might feel about being \napproached will be the thought: are these guys the next Google?Usually angels are financially equivalent to founders. They get \nthe same kind of stock and get diluted the same amount in future\nrounds. How much stock should they get? That depends on how\nambitious you feel. When you offer x percent of your company for\ny dollars, you're implicitly claiming a certain value for the whole\ncompany. Venture investments are usually described in terms of\nthat number. If you give an investor new shares equal to 5% of\nthose already outstanding in return for $100,000, then you've done\nthe deal at a pre-money valuation of $2 million.How do you decide what the value of the company should be? There\nis no rational way. At this stage the company is just a bet. I\ndidn't realize that when we were raising money. Julian\nthought we ought to value the company at several million \ndollars. I thought it was preposterous to claim that a couple\nthousand lines of code, which was all we had at the time, were worth\nseveral million dollars. Eventually we settled on one million,\nbecause Julian said no one would invest in a company with a valuation\nany lower. [6]What I didn't grasp at the time was that the valuation wasn't just \nthe value of the code we'd written so far. It was also the value\nof our ideas, which turned out to be right, and of all the future\nwork we'd do, which turned out to be a lot.The next round of funding is the one in which you might deal with \nactual \nventure capital firms. \nBut don't wait till you've burned \nthrough your last round of funding to start approaching them. VCs are slow to\nmake up their minds. They can take months. You don't want to be \nrunning out of money while you're trying to negotiate with them.Getting money from an actual VC firm is a bigger deal than getting\nmoney from angels. The amounts of money involved are larger, millions\nusually. So the deals take longer, dilute you more, and impose\nmore onerous conditions.Sometimes the VCs want to install a new CEO of their own choosing. \nUsually the claim is that you need someone mature and experienced,\nwith a business background. Maybe in some cases this is true. And\nyet Bill Gates was young and inexperienced and had no business \nbackground, and he seems to have done ok. Steve Jobs got booted\nout of his own company by someone mature and experienced, with a\nbusiness background, who then proceeded to ruin the company. So I\nthink people who are mature and experienced, with a business\nbackground, may be overrated. We used to call these guys \"newscasters,\"\nbecause they had neat hair and spoke in deep, confident voices, and\ngenerally didn't know much more than they read on the teleprompter.We talked to a number of VCs, but eventually we ended up financing\nour startup entirely with angel money. The main reason was that \nwe feared a brand-name VC firm would stick us with a newscaster as\npart of the deal. That might have been ok if he was content to\nlimit himself to talking to the press, but what if he wanted to \nhave a say in running the company? That would have led to disaster,\nbecause our software was so complex. We were a company whose whole\nm.o. was to win through better technology. The strategic decisions\nwere mostly decisions about technology, and we didn't need any help\nwith those.This was also one reason we didn't go public. Back in 1998 our CFO\ntried to talk me into it. In those days you could go public as a\ndogfood portal, so as a company with a real product and real revenues,\nwe might have done well. But I feared it would have meant taking\non a newscaster-- someone who, as they say, \"can talk Wall Street's\nlanguage.\"I'm happy to see Google is bucking that trend. They didn't talk\nWall Street's language when they did their IPO, and Wall Street\ndidn't buy. And now Wall Street is collectively kicking itself.\nThey'll pay attention next time. Wall Street learns new languages \nfast when money is involved.You have more leverage negotiating with VCs than you realize. The \nreason is other VCs. I know a number of VCs now, and when you talk\nto them you realize that it's a seller's market. Even now there\nis too much money chasing too few good deals.VCs form a pyramid. At the top are famous ones like Sequoia and\nKleiner Perkins, but beneath those are a huge number you've never \nheard of. What they all have in common is that a dollar from them \nis worth one dollar. Most VCs will tell you that they don't just \nprovide money, but connections and advice. If you're talking to \nVinod Khosla or John Doerr or Mike Moritz, this is true. But such\nadvice and connections can come very expensive. And as you go down\nthe food chain the VCs get rapidly \n\ndumber. A few steps down from \nthe top you're basically talking to bankers who've picked up a few\nnew vocabulary words from reading Wired. (Does your product\nuse XML?) So I'd advise you to be skeptical about claims\nof experience and connections. Basically, a VC is a source of\nmoney. I'd be inclined to go with whoever offered the most money \nthe soonest with the least strings attached.You may wonder how much to tell VCs. And you should, because some\nof them may one day be funding your competitors. I think the best\nplan is not to be overtly secretive, but not to tell them everything\neither. After all, as most VCs say, they're more interested in the\npeople than the ideas. The main reason they want to talk about\nyour idea is to judge you, not the idea. So as long as you seem\nlike you know what you're doing, you can probably keep a few things\nback from them. [7]Talk to as many VCs as you can, even if you don't want their money,\nbecause a) they may be on the board of someone who will buy you, \nand b) if you seem impressive, they'll be discouraged from investing\nin your competitors. The most efficient way to reach VCs, especially\nif you only want them to know about you and don't want their money,\nis at the conferences that are occasionally organized for startups \nto present to them.Not Spending ItWhen and if you get an infusion of real money from investors, what\nshould you do with it? Not spend it, that's what. In nearly every \nstartup that fails, the proximate cause is running out of money. \nUsually there is something deeper wrong. But even a proximate cause\nof death is worth trying hard to avoid.During the Bubble many startups tried to \"get big fast.\" Ideally\nthis meant getting a lot of customers fast. But it was easy for\nthe meaning to slide over into hiring a lot of people fast.Of the two versions, the one where you get a lot of customers fast\nis of course preferable. But even that may be overrated. The idea\nis to get there first and get all the users, leaving none for\ncompetitors. But I think in most businesses the advantages of being\nfirst to market are not so overwhelmingly great. Google is again\na case in point. When they appeared it seemed as if search was a\nmature market, dominated by big players who'd spent millions to\nbuild their brands: Yahoo, Lycos, Excite, Infoseek, Altavista, \nInktomi. Surely 1998 was a little late to arrive at the party.But as the founders of Google knew, brand is worth next to nothing\nin the search business. You can come along at any point and make \nsomething better, and users will gradually seep over to you. As \nif to emphasize the point, Google never did any advertising. They're\nlike dealers; they sell the stuff, but they know better than to use\nit themselves.The competitors Google buried would have done better to spend those\nmillions improving their software. Future startups should learn\nfrom that mistake. Unless you're in a market where products are \nas undifferentiated as cigarettes or vodka or laundry detergent,\nspending a lot on brand advertising is a sign of breakage. And few\nif any Web businesses are so undifferentiated. The dating sites \nare running big ad campaigns right now, which is all the \nmore evidence they're ripe for the picking. (Fee, fie, fo, fum, I \nsmell a company run by marketing guys.)We were compelled by circumstances to grow slowly, and in retrospect\nit was a good thing. The founders all learned to do every job in \nthe company. As well as writing software, I had to do sales and\ncustomer support. At sales I was not very good. I was persistent,\nbut I didn't have the smoothness of a good salesman. My message \nto potential customers was: you'd be stupid not to sell online, and \nif you sell online you'd be stupid to use anyone else's software. \nBoth statements were true, but that's not the way to convince people.I was great at customer support though. Imagine talking to a\ncustomer support person who not only knew everything about the\nproduct, but would apologize abjectly if there was a bug, and then\nfix it immediately, while you were on the phone with them. Customers\nloved us. And we loved them, because when you're growing slow by\nword of mouth, your first batch of users are the ones who were smart\nenough to find you by themselves. There is nothing more valuable,\nin the early stages of a startup, than smart users. If you listen\nto them, they'll tell you exactly how to make a winning product. \nAnd not only will they give you this advice for free, they'll pay\nyou.We officially launched in early 1996. By the end of that year we\nhad about 70 users. Since this was the era of \"get big fast,\" I\nworried about how small and obscure we were. But in fact we were\ndoing exactly the right thing. Once you get big (in users or\nemployees) it gets hard to change your product. That year was\neffectively a laboratory for improving our software. By the end \nof it, we were so far ahead of our competitors that they never had \na hope of catching up. And since all the hackers had spent many\nhours talking to users, we understood online commerce way better\nthan anyone else.That's the key to success as a startup. There is nothing more \nimportant than understanding your business. You might think that\nanyone in a business must, ex officio, understand it. Far from it. \nGoogle's secret\nweapon was simply that they understood search. I was working for \nYahoo when Google appeared, and Yahoo didn't understand search. I\nknow because I once tried to convince the powers that be that we\nhad to make search better, and I got in reply what was then the\nparty line about it: that Yahoo was no longer a mere \"search engine.\"\nSearch was now only a small percentage of our page views, less than\none month's growth, and now that we were established as a \"media \ncompany,\" or \"portal,\" or whatever we were, search could safely be\nallowed to wither and drop off, like an umbilical cord.Well, a small fraction of page views they may be, but they are an \nimportant fraction, because they are the page views that Web sessions \nstart with. I think Yahoo gets that now.Google understands a few other things most Web companies still\ndon't. The most important is that you should put users before\nadvertisers, even though the advertisers are paying and users aren't.\nOne of my favorite bumper stickers reads \"if the people lead, the \nleaders will follow.\" Paraphrased for the Web, this becomes \"get\nall the users, and the advertisers will follow.\" More generally,\ndesign your product to please users first, and then think about how\nto make money from it. If you don't put users first, you leave a \ngap for competitors who do.To make something users love, you have to understand them. And the\nbigger you are, the harder that is. So I say \"get big slow.\" The\nslower you burn through your funding, the more time you have to\nlearn.The other reason to spend money slowly is to encourage a culture \nof cheapness. That's something Yahoo did understand. David Filo's \ntitle was \"Chief Yahoo,\" but he was proud that his unofficial title\nwas \"Cheap Yahoo.\" Soon after we arrived at Yahoo, we got an email\nfrom Filo, who had been crawling around our directory hierarchy, \nasking if it was really necessary to store so much of our data on\nexpensive RAID drives. I was impressed by that. Yahoo's market\ncap then was already in the billions, and they were still worrying\nabout wasting a few gigs of disk space.When you get a couple million dollars from a VC firm, you tend to\nfeel rich. It's important to realize you're not. A rich company\nis one with large revenues. This money isn't revenue. It's money\ninvestors have given you in the hope you'll be able to generate \nrevenues. So despite those millions in the bank, you're still poor.For most startups the model should be grad student, not law firm.\nAim for cool and cheap, not expensive and impressive. For us the\ntest of whether a startup understood this was whether they had Aeron\nchairs. The Aeron came out during the Bubble and was very popular\nwith startups. Especially the type, all too common then, that was\nlike a bunch of kids playing house with money supplied by VCs. We \nhad office chairs so cheap that the arms all fell off. This was \nslightly embarrassing at the time, but in retrospect the grad-studenty\natmosphere of our office was another of those things we did right \nwithout knowing it.Our offices were in a wooden triple-decker in Harvard Square. It\nhad been an apartment until about the 1970s, and there was still a \nclaw-footed bathtub in the bathroom. It must once have been inhabited\nby someone fairly eccentric, because a lot of the chinks in the \nwalls were stuffed with aluminum foil, as if to protect against \ncosmic rays. When eminent visitors came to see us, we were a bit\nsheepish about the low production values. But in fact that place\nwas the perfect space for a startup. We felt like our role was to \nbe impudent underdogs instead of corporate stuffed shirts, and that \nis exactly the spirit you want.An apartment is also the right kind of place for developing software.\nCube farms suck for that, as you've probably discovered if you've\ntried it. Ever notice how much easier it is to hack at home than\nat work? So why not make work more like home?When you're looking for space for a startup, don't feel that it has\nto look professional. Professional means doing good work, not\nelevators and glass walls. I'd advise most startups to avoid\ncorporate space at first and just rent an apartment. You want to\nlive at the office in a startup, so why not have a place designed\nto be lived in as your office?Besides being cheaper and better to work in, apartments tend to be\nin better locations than office buildings. And for a startup\nlocation is very important. The key to productivity is for people\nto come back to work after dinner. Those hours after the phone\nstops ringing are by far the best for getting work done. Great\nthings happen when a group of employees go out to dinner together, \ntalk over ideas, and then come back to their offices to implement \nthem. So you want to be in a place where there are a lot of\nrestaurants around, not some dreary office park that's a wasteland\nafter 6:00 PM. Once a company shifts over into the model where \neveryone drives home to the suburbs for dinner, however late, you've\nlost something extraordinarily valuable. God help you if you\nactually start in that mode.If I were going to start a startup today, there are only three \nplaces I'd consider doing it: on the Red Line near Central, Harvard,\nor Davis Squares (Kendall is too sterile); in Palo Alto on University\nor California Aves; and in Berkeley immediately north or south of \ncampus. These are the only places I know that have the right kind\nof vibe.The most important way to not spend money is by not hiring people. \nI may be an extremist, but I think hiring people is the worst thing\na company can do. To start with, people are a recurring expense, \nwhich is the worst kind. They also tend to cause you to grow out \nof your space, and perhaps even move to the sort of uncool office\nbuilding that will make your software worse. But worst of all,\nthey slow you down: instead of sticking your head in someone's \noffice and checking out an idea with them, eight people have to\nhave a meeting about it. So the fewer people you can hire, the\nbetter.During the Bubble a lot of startups had the opposite policy. They\nwanted to get \"staffed up\" as soon as possible, as if you couldn't \nget anything done unless there was someone with the corresponding \njob title. That's big company thinking. Don't hire people to fill\nthe gaps in some a priori org chart. The only reason to hire someone\nis to do something you'd like to do but can't.If hiring unnecessary people is expensive and slows you down, why\ndo nearly all companies do it? I think the main reason is that\npeople like the idea of having a lot of people working for them.\nThis weakness often extends right up to the CEO. If you ever end\nup running a company, you'll find the most common question people\nask is how many employees you have. This is their way of weighing\nyou. It's not just random people who ask this; even reporters do.\nAnd they're going to be a lot more impressed if the answer is a\nthousand than if it's ten.This is ridiculous, really. If two companies have the same revenues,\nit's the one with fewer employees that's more impressive. When \npeople used to ask me how many people our startup had, and I answered\n\"twenty,\" I could see them thinking that we didn't count for much.\nI used to want to add \"but our main competitor, whose ass we regularly\nkick, has a hundred and forty, so can we have credit for the larger\nof the two numbers?\"As with office space, the number of your employees is a choice \nbetween seeming impressive, and being impressive. Any of you who \nwere nerds in high school know about this \nchoice. Keep doing it when you start a company.Should You?But should you start a company? Are you the right sort of person\nto do it? If you are, is it worth it?More people are the right sort of person to start a startup than\nrealize it. That's the main reason I wrote this. There could be \nten times more startups than there are, and that would probably be\na good thing.I was, I now realize, exactly the right sort of person to start a \nstartup. But the idea terrified me at first. I was forced into \nit because I was a Lisp hacker. The company\nI'd been consulting for seemed to be running into trouble, and there \nwere not a lot of other companies using Lisp. Since I couldn't \nbear the thought of programming in another language (this was 1995,\nremember, when \"another language\" meant C++) the only option seemed\nto be to start a new company using Lisp.I realize this sounds far-fetched, but if you're a Lisp hacker\nyou'll know what I mean. And if the idea of starting a startup\nfrightened me so much that I only did it out of necessity, there \nmust be a lot of people who would be good at it but who are too \nintimidated to try.So who should start a startup? Someone who is a good hacker, between\nabout 23 and 38, and who wants to solve the money problem in one\nshot instead of getting paid gradually over a conventional working\nlife.I can't say precisely what a good hacker is. At a first rate \nuniversity this might include the top half of computer science \nmajors. Though of course you don't have to be a CS major to be a\nhacker; I was a philosophy major in college.It's hard to tell whether you're a good hacker, especially when\nyou're young. Fortunately the process of starting startups tends\nto select them automatically. What drives people to start startups\nis (or should be) looking at existing technology and thinking, don't \nthese guys realize they should be doing x, y, and z? And that's \nalso a sign that one is a good hacker.I put the lower bound at 23 not because there's something that\ndoesn't happen to your brain till then, but because you need to see\nwhat it's like in an existing business before you try running your\nown. The business doesn't have to be a startup. I spent a year\nworking for a software company to pay off my college loans. It was\nthe worst year of my adult life, but I learned, without realizing \nit at the time, a lot of valuable lessons about the software business.\nIn this case they were mostly negative lessons: don't have a lot\nof meetings; don't have chunks of code that multiple people own;\ndon't have a sales guy running the company; don't make a high-end\nproduct; don't let your code get too big; don't leave finding bugs\nto QA people; don't go too long between releases; don't isolate\ndevelopers from users; don't move from Cambridge to Route 128; and\nso on. [8] But negative lessons are just as valuable as positive \nones. Perhaps even more valuable: it's hard to repeat a brilliant\nperformance, but it's straightforward to avoid errors. [9]The other reason it's hard to start a company before 23 is that \npeople won't take you seriously. VCs won't trust you, and will try\nto reduce you to a mascot as a condition of funding. Customers\nwill worry you're going to flake out and leave them stranded. Even\nyou yourself, unless you're very unusual, will feel your age to \nsome degree; you'll find it awkward to be the boss of someone much \nolder than you, and if you're 21, hiring only people younger rather \nlimits your options.Some people could probably start a company at 18 if they wanted to.\nBill Gates was 19 when he and Paul Allen started Microsoft. (Paul \nAllen was 22, though, and that probably made a difference.) So if\nyou're thinking, I don't care what he says, I'm going to start a\ncompany now, you may be the sort of person who could get away with\nit.The other cutoff, 38, has a lot more play in it. One reason I put \nit there is that I don't think many people have the physical stamina\nmuch past that age. I used to work till 2:00 or 3:00 AM every\nnight, seven days a week. I don't know if I could do that now.Also,\nstartups are a big risk financially. If you try something that\nblows up and leaves you broke at 26, big deal; a lot of 26 year\nolds are broke. By 38 you can't take so many risks-- especially\nif you have kids.My final test may be the most restrictive. Do you actually want\nto start a startup? What it amounts to, economically, is compressing\nyour working life into the smallest possible space. Instead of\nworking at an ordinary rate for 40 years, you work like hell for \nfour. And maybe end up with nothing-- though in that case it\nprobably won't take four years.During this time you'll do little but work, because when you're not\nworking, your competitors will be. My only leisure activities were\nrunning, which I needed to do to keep working anyway, and about\nfifteen minutes of reading a night. I had a girlfriend for a total\nof two months during that three year period. Every couple weeks I\nwould take a few hours off to visit a used bookshop or go to a \nfriend's house for dinner. I went to visit my family twice.\nOtherwise I just worked.Working was often fun, because the people I worked with were some\nof my best friends. Sometimes it was even technically interesting.\nBut only about 10% of the time. The best I can say for the other\n90% is that some of it is funnier in hindsight than it seemed then.\nLike the time the power went off in Cambridge for about six hours,\nand we made the mistake of trying to start a gasoline powered\ngenerator inside our offices. I won't try that again.I don't think the amount of bullshit you have to deal with in a\nstartup is more than you'd endure in an ordinary working life. It's\nprobably less, in fact; it just seems like a lot because it's \ncompressed into a short period. So mainly what a startup buys you \nis time. That's the way to think about it if you're trying to \ndecide whether to start one. If you're the sort of person who would\nlike to solve the money problem once and for all instead of working \nfor a salary for 40 years, then a startup makes sense.For a lot of people the conflict is between startups and graduate\nschool. Grad students are just the age, and just the sort of people,\nto start software startups. You may worry that if you do you'll \nblow your chances of an academic career. But it's possible to be \npart of a startup and stay in grad school, especially at first. \nTwo of our three original hackers were in grad school the whole \ntime, and both got their degrees. \nThere are few sources of energy\nso powerful as a procrastinating grad student.If you do have to\nleave grad school, in the worst case it won't be for too long. If\na startup fails, it will probably fail quickly enough that you can \nreturn to academic life. And if it succeeds, you may find you no \nlonger have such a burning desire to be an assistant professor.If you want to do it, do it. Starting a startup is not the great\nmystery it seems from outside. It's not something you have to know\nabout \"business\" to do. Build something users love, and spend less\nthan you make. How hard is that?Notes[1] Google's revenues are about two billion a year, but half comes\nfrom ads on other sites.[2] One advantage startups have over established companies is that\nthere are no discrimination laws about starting businesses. For \nexample, I would be reluctant to start a startup with a woman\nwho had small children, or was likely to have them soon. But you're\nnot allowed to ask prospective employees if they plan to have kids \nsoon. Believe it or not, under current US law, you're not even \nallowed to discriminate on the basis of intelligence. Whereas when\nyou're starting a company, you can discriminate on any basis you\nwant about who you start it with.[3] Learning to hack is a lot cheaper than business school, because\nyou can do it mostly on your own. For the price of a Linux box, a\ncopy of K&R, and a few hours of advice from your neighbor's fifteen\nyear old son, you'll be well on your way.[4] Corollary: Avoid starting a startup to sell things to the biggest\ncompany of all, the government. Yes, there are lots of opportunities\nto sell them technology. But let someone else start those startups.[5] A friend who started a company in Germany told me they do care \nabout the paperwork there, and that there's more of it. Which helps\nexplain why there are not more startups in Germany.[6] At the seed stage our valuation was in principle $100,000, because\nJulian got 10% of the company. But this is a very misleading number,\nbecause the money was the least important of the things Julian gave us.[7] The same goes for companies that seem to want to acquire you.\nThere will be a few that are only pretending to in order to pick\nyour brains. But you can never tell for sure which these are, so\nthe best approach is to seem entirely open, but to fail to mention\na few critical technical secrets.[8] I was as bad an employee as this place was a company. I\napologize to anyone who had to work with me there.[9] You could probably write a book about how to succeed in business\nby doing everything in exactly the opposite way from the DMV.Thanks to Trevor Blackwell, Sarah Harlin, Jessica Livingston,\nand Robert Morris for reading drafts of this essay, and to Steve\nMelendez and Gregory Price for inviting me to speak." }, { "path": "data/PaulGrahamEssayMedium/startupfunding.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nNovember 2005\nVenture funding works like gears. A typical startup goes through\nseveral rounds of funding, and at each round you want to take just\nenough money to reach the speed where you can shift into the next\ngear.Few startups get it quite right. Many are underfunded. A few are\noverfunded, which is like trying to start driving in third gear.I think it would help founders to understand funding better—not\njust the mechanics of it, but what investors are thinking. I was\nsurprised recently when I realized that all the worst problems we\nfaced in our startup were due not to competitors, but investors.\nDealing with competitors was easy by comparison.I don't mean to suggest that our investors were nothing but a drag\non us. They were helpful in negotiating deals, for example. I\nmean more that conflicts with investors are particularly nasty.\nCompetitors punch you in the jaw, but investors have you by the\nballs.Apparently our situation was not unusual. And if trouble with\ninvestors is one of the biggest threats to a startup, managing them\nis one of the most important skills founders need to learn.Let's start by talking about the five sources of startup funding.\nThen we'll trace the life of a hypothetical (very fortunate) startup\nas it shifts gears through successive rounds.Friends and FamilyA lot of startups get their first funding from friends and family.\nExcite did, for example: after the founders graduated from college,\nthey borrowed $15,000 from their parents to start a company. With\nthe help of some part-time jobs they made it last 18 months.If your friends or family happen to be rich, the line blurs between\nthem and angel investors. At Viaweb we got our first $10,000 of\nseed money from our friend Julian, but he was sufficiently rich\nthat it's hard to say whether he should be classified as a friend\nor angel. He was also a lawyer, which was great, because it meant\nwe didn't have to pay legal bills out of that initial small sum.The advantage of raising money from friends and family is that\nthey're easy to find. You already know them. There are three main\ndisadvantages: you mix together your business and personal life;\nthey will probably not be as well connected as angels or venture\nfirms; and they may not be accredited investors, which could\ncomplicate your life later.The SEC defines an \"accredited investor\" as someone with over a\nmillion dollars in liquid assets or an income of over $200,000 a\nyear. The regulatory burden is much lower if a company's shareholders\nare all accredited investors. Once you take money from the general\npublic you're more restricted in what you can do. \n[1]A startup's life will be more complicated, legally, if any of the\ninvestors aren't accredited. In an IPO, it might not merely add\nexpense, but change the outcome. A lawyer I asked about it said:\n\n When the company goes public, the SEC will carefully study all\n prior issuances of stock by the company and demand that it take\n immediate action to cure any past violations of securities laws.\n Those remedial actions can delay, stall or even kill the IPO.\n\nOf course the odds of any given startup doing an IPO are small.\nBut not as small as they might seem. A lot of startups that end up\ngoing public didn't seem likely to at first. (Who could have guessed\nthat the company Wozniak and Jobs started in their spare time selling\nplans for microcomputers would yield one of the biggest IPOs of the\ndecade?) Much of the value of a startup consists of that tiny\nprobability multiplied by the huge outcome.It wasn't because they weren't accredited investors that I didn't\nask my parents for seed money, though. When we were starting Viaweb,\nI didn't know about the concept of an accredited investor, and\ndidn't stop to think about the value of investors' connections.\nThe reason I didn't take money from my parents was that I didn't\nwant them to lose it.ConsultingAnother way to fund a startup is to get a job. The best sort of\njob is a consulting project in which you can build whatever software\nyou wanted to sell as a startup. Then you can gradually transform\nyourself from a consulting company into a product company, and have\nyour clients pay your development expenses.This is a good plan for someone with kids, because it takes most\nof the risk out of starting a startup. There never has to be a\ntime when you have no revenues. Risk and reward are usually\nproportionate, however: you should expect a plan that cuts the risk\nof starting a startup also to cut the average return. In this case,\nyou trade decreased financial risk for increased risk that your\ncompany won't succeed as a startup.But isn't the consulting company itself a startup? No, not generally.\nA company has to be more than small and newly founded to be a\nstartup. There are millions of small businesses in America, but\nonly a few thousand are startups. To be a startup, a company has\nto be a product business, not a service business. By which I mean\nnot that it has to make something physical, but that it has to have\none thing it sells to many people, rather than doing custom work\nfor individual clients. Custom work doesn't scale. To be a startup\nyou need to be the band that sells a million copies of a song, not\nthe band that makes money by playing at individual weddings and bar\nmitzvahs.The trouble with consulting is that clients have an awkward habit\nof calling you on the phone. Most startups operate close to the\nmargin of failure, and the distraction of having to deal with clients\ncould be enough to put you over the edge. Especially if you have\ncompetitors who get to work full time on just being a startup.So you have to be very disciplined if you take the consulting route.\nYou have to work actively to prevent your company growing into a\n\"weed tree,\" dependent on this source of easy but low-margin money.\n[2]Indeed, the biggest danger of consulting may be that it gives you\nan excuse for failure. In a startup, as in grad school, a lot of\nwhat ends up driving you are the expectations of your family and\nfriends. Once you start a startup and tell everyone that's what\nyou're doing, you're now on a path labelled \"get rich or bust.\" You\nnow have to get rich, or you've failed.Fear of failure is an extraordinarily powerful force. Usually it\nprevents people from starting things, but once you publish some\ndefinite ambition, it switches directions and starts working in\nyour favor. I think it's a pretty clever piece of jiujitsu to set\nthis irresistible force against the slightly less immovable object\nof becoming rich. You won't have it driving you if your stated\nambition is merely to start a consulting company that you will one\nday morph into a startup.An advantage of consulting, as a way to develop a product, is that\nyou know you're making something at least one customer wants. But\nif you have what it takes to start a startup you should have\nsufficient vision not to need this crutch.Angel InvestorsAngels are individual rich people. The word was first used\nfor backers of Broadway plays, but now applies to individual investors\ngenerally. Angels who've made money in technology are preferable,\nfor two reasons: they understand your situation, and they're a\nsource of contacts and advice.The contacts and advice can be more important than the money. When\ndel.icio.us took money from investors, they took money from, among\nothers, Tim O'Reilly. The amount he put in was small compared to\nthe VCs who led the round, but Tim is a smart and influential guy\nand it's good to have him on your side.You can do whatever you want with money from consulting or friends\nand family. With angels we're now talking about venture funding\nproper, so it's time to introduce the concept of exit strategy.\nYounger would-be founders are often surprised that investors expect\nthem either to sell the company or go public. The reason is that\ninvestors need to get their capital back. They'll only consider\ncompanies that have an exit strategy—meaning companies that could\nget bought or go public.This is not as selfish as it sounds. There are few large, private\ntechnology companies. Those that don't fail all seem to get bought\nor go public. The reason is that employees are investors too—of\ntheir time—and they want just as much to be able to cash out. If\nyour competitors offer employees stock options that might make them\nrich, while you make it clear you plan to stay private, your\ncompetitors will get the best people. So the principle of an \"exit\"\nis not just something forced on startups by investors, but part of\nwhat it means to be a startup.Another concept we need to introduce now is valuation. When someone\nbuys shares in a company, that implicitly establishes a value for\nit. If someone pays $20,000 for 10% of a company, the company is\nin theory worth $200,000. I say \"in theory\" because in early stage\ninvesting, valuations are voodoo. As a company gets more established,\nits valuation gets closer to an actual market value. But in a newly\nfounded startup, the valuation number is just an artifact of the\nrespective contributions of everyone involved.Startups often \"pay\" investors who will help the company in some\nway by letting them invest at low valuations. If I had a startup\nand Steve Jobs wanted to invest in it, I'd give him the stock for\n$10, just to be able to brag that he was an investor. Unfortunately,\nit's impractical (if not illegal) to adjust the valuation of the\ncompany up and down for each investor. Startups' valuations are\nsupposed to rise over time. So if you're going to sell cheap stock\nto eminent angels, do it early, when it's natural for the company\nto have a low valuation.Some angel investors join together in syndicates. Any city where\npeople start startups will have one or more of them. In Boston the\nbiggest is the Common\nAngels. In the Bay Area it's the Band\nof Angels. You can find groups near you through the Angel Capital Association.\n[3]\nHowever, most angel investors don't belong to these groups. In\nfact, the more prominent the angel, the less likely they are to\nbelong to a group.Some angel groups charge you money to pitch your idea to them.\nNeedless to say, you should never do this.One of the dangers of taking investment from individual angels,\nrather than through an angel group or investment firm, is that they\nhave less reputation to protect. A big-name VC firm will not screw\nyou too outrageously, because other founders would avoid them if\nword got out. With individual angels you don't have this protection,\nas we found to our dismay in our own startup. In many startups'\nlives there comes a point when you're at the investors' \nmercy—when you're out of money and the only place to get more is your\nexisting investors. When we got into such a scrape, our investors\ntook advantage of it in a way that a name-brand VC probably wouldn't\nhave.Angels have a corresponding advantage, however: they're also not\nbound by all the rules that VC firms are. And so they can, for\nexample, allow founders to cash out partially in a funding round,\nby selling some of their stock directly to the investors. I think\nthis will become more common; the average founder is eager to do\nit, and selling, say, half a million dollars worth of stock will\nnot, as VCs fear, cause most founders to be any less committed to\nthe business.The same angels who tried to screw us also let us do this, and so\non balance I'm grateful rather than angry. (As in families, relations\nbetween founders and investors can be complicated.)The best way to find angel investors is through personal introductions.\nYou could try to cold-call angel groups near you, but angels, like\nVCs, will pay more attention to deals recommended by someone they\nrespect.Deal terms with angels vary a lot. There are no generally accepted\nstandards. Sometimes angels' deal terms are as fearsome as VCs'.\nOther angels, particularly in the earliest stages, will invest based\non a two-page agreement.Angels who only invest occasionally may not themselves know what\nterms they want. They just want to invest in this startup. What\nkind of anti-dilution protection do they want? Hell if they know.\nIn these situations, the deal terms tend to be random: the angel\nasks his lawyer to create a vanilla agreement, and the terms end\nup being whatever the lawyer considers vanilla. Which in practice\nusually means, whatever existing agreement he finds lying around\nhis firm. (Few legal documents are created from scratch.)These heaps o' boilerplate are a problem for small startups, because\nthey tend to grow into the union of all preceding documents. I\nknow of one startup that got from an angel investor what amounted\nto a five hundred pound handshake: after deciding to invest, the\nangel presented them with a 70-page agreement. The startup didn't\nhave enough money to pay a lawyer even to read it, let alone negotiate\nthe terms, so the deal fell through.One solution to this problem would be to have the startup's lawyer\nproduce the agreement, instead of the angel's. Some angels might\nbalk at this, but others would probably welcome it.Inexperienced angels often get cold feet when the time comes to\nwrite that big check. In our startup, one of the two angels in the\ninitial round took months to pay us, and only did after repeated\nnagging from our lawyer, who was also, fortunately, his lawyer.It's obvious why investors delay. Investing in startups is risky!\nWhen a company is only two months old, every day you wait\ngives you 1.7% more data about their trajectory. But the investor\nis already being compensated for that risk in the low price of the\nstock, so it is unfair to delay.Fair or not, investors do it if you let them. Even VCs do it. And\nfunding delays are a big distraction for founders, who ought to be\nworking on their company, not worrying about investors. What's a\nstartup to do? With both investors and acquirers, the only leverage\nyou have is competition. If an investor knows you have other\ninvestors lined up, he'll be a lot more eager to close-- and not\njust because he'll worry about losing the deal, but because if other\ninvestors are interested, you must be worth investing in. It's the\nsame with acquisitions. No one wants to buy you till someone else\nwants to buy you, and then everyone wants to buy you.The key to closing deals is never to stop pursuing alternatives.\nWhen an investor says he wants to invest in you, or an acquirer\nsays they want to buy you, don't believe it till you get the\ncheck. Your natural tendency when an investor says yes will\nbe to relax and go back to writing code. Alas, you can't; you have\nto keep looking for more investors, if only to get this one to act.\n[4]Seed Funding FirmsSeed firms are like angels in that they invest relatively small\namounts at early stages, but like VCs in that they're companies\nthat do it as a business, rather than individuals making occasional\ninvestments on the side.Till now, nearly all seed firms have been so-called \"incubators,\"\nso Y Combinator gets called\none too, though the only thing we have in common is that we invest\nin the earliest phase.According to the National Association of Business Incubators, there\nare about 800 incubators in the US. This is an astounding number,\nbecause I know the founders of a lot of startups, and I can't think\nof one that began in an incubator.What is an incubator? I'm not sure myself. The defining quality\nseems to be that you work in their space. That's where the name\n\"incubator\" comes from. They seem to vary a great deal in other\nrespects. At one extreme is the sort of pork-barrel project where\na town gets money from the state government to renovate a vacant\nbuilding as a \"high-tech incubator,\" as if it were merely lack of\nthe right sort of office space that had till now prevented the town\nfrom becoming a \nstartup hub. \nAt the other extreme are places like\nIdealab, which generates ideas for new startups internally and hires\npeople to work for them.The classic Bubble incubators, most of which now seem to be dead,\nwere like VC firms except that they took a much bigger role in the\nstartups they funded. In addition to working in their space, you\nwere supposed to use their office staff, lawyers, accountants, and\nso on.Whereas incubators tend (or tended) to exert more control than VCs,\nY Combinator exerts less. \nAnd we think it's better if startups operate out of their own\npremises, however crappy, than the offices of their investors. So\nit's annoying that we keep getting called an \"incubator,\" but perhaps\ninevitable, because there's only one of us so far and no word yet\nfor what we are. If we have to be called something, the obvious\nname would be \"excubator.\" (The name is more excusable if one\nconsiders it as meaning that we enable people to escape cubicles.)Because seed firms are companies rather than individual people,\nreaching them is easier than reaching angels. Just go to their web\nsite and send them an email. The importance of personal introductions\nvaries, but is less than with angels or VCs.The fact that seed firms are companies also means the investment\nprocess is more standardized. (This is generally true with angel\ngroups too.) Seed firms will probably have set deal terms they use\nfor every startup they fund. The fact that the deal terms are\nstandard doesn't mean they're favorable to you, but if other startups\nhave signed the same agreements and things went well for them, it's\na sign the terms are reasonable.Seed firms differ from angels and VCs in that they invest exclusively\nin the earliest phases—often when the company is still just an\nidea. Angels and even VC firms occasionally do this, but they also\ninvest at later stages.The problems are different in the early stages. For example, in\nthe first couple months a startup may completely redefine their idea. So seed investors usually care less\nabout the idea than the people. This is true of all venture funding,\nbut especially so in the seed stage.Like VCs, one of the advantages of seed firms is the advice they\noffer. But because seed firms operate in an earlier phase, they\nneed to offer different kinds of advice. For example, a seed firm\nshould be able to give advice about how to approach VCs, which VCs\nobviously don't need to do; whereas VCs should be able to give\nadvice about how to hire an \"executive team,\" which is not an issue\nin the seed stage.In the earliest phases, a lot of the problems are technical, so\nseed firms should be able to help with technical as well as business\nproblems.Seed firms and angel investors generally want to invest in the\ninitial phases of a startup, then hand them off to VC firms for the\nnext round. Occasionally startups go from seed funding direct to\nacquisition, however, and I expect this to become increasingly\ncommon.Google has been aggressively pursuing this route, and now Yahoo is too. Both\nnow compete directly with VCs. And this is a smart move. Why wait\nfor further funding rounds to jack up a startup's price? When a\nstartup reaches the point where VCs have enough information to\ninvest in it, the acquirer should have enough information to buy\nit. More information, in fact; with their technical depth, the\nacquirers should be better at picking winners than VCs.Venture Capital FundsVC firms are like seed firms in that they're actual companies, but\nthey invest other people's money, and much larger amounts of it.\nVC investments average several million dollars. So they tend to\ncome later in the life of a startup, are harder to get, and come\nwith tougher terms.The word \"venture capitalist\" is sometimes used loosely for any\nventure investor, but there is a sharp difference between VCs and\nother investors: VC firms are organized as funds, much like\nhedge funds or mutual funds. The fund managers, who are called\n\"general partners,\" get about 2% of the fund annually as a management\nfee, plus about 20% of the fund's gains.There is a very sharp dropoff in performance among VC firms, because\nin the VC business both success and failure are self-perpetuating.\nWhen an investment scores spectacularly, as Google did for Kleiner\nand Sequoia, it generates a lot of good publicity for the VCs. And\nmany founders prefer to take money from successful VC firms, because\nof the legitimacy it confers. Hence a vicious (for the losers)\ncycle: VC firms that have been doing badly will only get the deals\nthe bigger fish have rejected, causing them to continue to do badly.As a result, of the thousand or so VC funds in the US now, only\nabout 50 are likely to make money, and it is very hard for a new\nfund to break into this group.In a sense, the lower-tier VC firms are a bargain for founders.\nThey may not be quite as smart or as well connected as the big-name\nfirms, but they are much hungrier for deals. This means you should\nbe able to get better terms from them.Better how? The most obvious is valuation: they'll take less of\nyour company. But as well as money, there's power. I think founders\nwill increasingly be able to stay on as CEO, and on terms that will\nmake it fairly hard to fire them later.The most dramatic change, I predict,\nis that VCs will allow founders to \ncash out partially by selling\nsome of their stock direct to the VC firm. VCs have traditionally\nresisted letting founders get anything before the ultimate \"liquidity\nevent.\" But they're also desperate for deals. And since I know\nfrom my own experience that the rule against buying stock from\nfounders is a stupid one, this is a natural place for things to\ngive as venture funding becomes more and more a seller's market.The disadvantage of taking money from less known firms is that\npeople will assume, correctly or not, that you were turned down by\nthe more exalted ones. But, like where you went to college, the\nname of your VC stops mattering once you have some performance to\nmeasure. So the more confident you are, the less you need a\nbrand-name VC. We funded Viaweb entirely with angel money; it never\noccurred to us that the backing of a well known VC firm would make\nus seem more impressive.\n[5]Another danger of less known firms is that, like angels, they have\nless reputation to protect. I suspect it's the lower-tier firms\nthat are responsible for most of the tricks that have given VCs\nsuch a bad reputation among hackers. They are doubly hosed: the\ngeneral partners themselves are less able, and yet they have harder\nproblems to solve, because the top VCs skim off all the best deals,\nleaving the lower-tier firms exactly the startups that are likely\nto blow up.For example, lower-tier firms are much more likely to pretend to\nwant to do a deal with you just to lock you up while they decide\nif they really want to. One experienced CFO said:\n\n The better ones usually will not give a term sheet unless they\n really want to do a deal. The second or third tier firms have a\n much higher break rate—it could be as high as 50%.\n\nIt's obvious why: the lower-tier firms' biggest fear, when chance\nthrows them a bone, is that one of the big dogs will notice and\ntake it away. The big dogs don't have to worry about that.Falling victim to this trick could really hurt you. As one\nVC told me:\n\n If you were talking to four VCs, told three of them that you\n accepted a term sheet, and then have to call them back to tell\n them you were just kidding, you are absolutely damaged goods.\n\nHere's a partial solution: when a VC offers you a term sheet, ask\nhow many of their last 10 term sheets turned into deals. This will\nat least force them to lie outright if they want to mislead you.Not all the people who work at VC firms are partners. Most firms\nalso have a handful of junior employees called something like\nassociates or analysts. If you get a call from a VC\nfirm, go to their web site and check whether the person you talked\nto is a partner. Odds are it will be a junior person; they scour\nthe web looking for startups their bosses could invest in. The\njunior people will tend to seem very positive about your company.\nThey're not pretending; they want to believe you're a hot\nprospect, because it would be a huge coup for them if their firm\ninvested in a company they discovered. Don't be misled by this\noptimism. It's the partners who decide, and they view things with\na colder eye.Because VCs invest large amounts, the money comes with more\nrestrictions. Most only come into effect if the company gets into\ntrouble. For example, VCs generally write it into the deal that\nin any sale, they get their investment back first. So if the company\ngets sold at a low price, the founders could get nothing. Some VCs\nnow require that in any sale they get 4x their investment back\nbefore the common stock holders (that is, you) get anything, but\nthis is an abuse that should be resisted.Another difference with large investments is that the founders are\nusually required to accept \"vesting\"—to surrender their stock and\nearn it back over the next 4-5 years. VCs don't want to invest\nmillions in a company the founders could just walk away from.\nFinancially, vesting has little effect, but in some situations it\ncould mean founders will have less power. If VCs got de facto\ncontrol of the company and fired one of the founders, he'd lose any\nunvested stock unless there was specific protection against this.\nSo vesting would in that situation force founders to toe the line.The most noticeable change when a startup takes serious funding is\nthat the founders will no longer have complete control. Ten years\nago VCs used to insist that founders step down as CEO and hand the\njob over to a business guy they supplied. This is less the rule\nnow, partly because the disasters of the Bubble showed that generic\nbusiness guys don't make such great CEOs.But while founders will increasingly be able to stay on as CEO,\nthey'll have to cede some power, because the board of directors\nwill become more powerful. In the seed stage, the board is generally\na formality; if you want to talk to the other board members, you\njust yell into the next room. This stops with VC-scale money. In\na typical VC funding deal, the board of directors might be composed\nof two VCs, two founders, and one outside person acceptable to both.\nThe board will have ultimate power, which means the founders now\nhave to convince instead of commanding.This is not as bad as it sounds, however. Bill Gates is in the\nsame position; he doesn't have majority control of Microsoft; in\nprinciple he also has to convince instead of commanding. And yet\nhe seems pretty commanding, doesn't he? As long as things are going\nsmoothly, boards don't interfere much. The danger comes when there's\na bump in the road, as happened to Steve Jobs at Apple.Like angels, VCs prefer to invest in deals that come to them through\npeople they know. So while nearly all VC funds have some address\nyou can send your business plan to, VCs privately admit the chance\nof getting funding by this route is near zero. One recently told\nme that he did not know a single startup that got funded this way.I suspect VCs accept business plans \"over the transom\" more as a\nway to keep tabs on industry trends than as a source of deals. In\nfact, I would strongly advise against mailing your business plan\nrandomly to VCs, because they treat this as evidence of laziness.\nDo the extra work of getting personal introductions. As one VC put\nit:\n\n I'm not hard to find. I know a lot of people. If you can't find\n some way to reach me, how are you going to create a successful\n company?\n\nOne of the most difficult problems for startup founders is deciding\nwhen to approach VCs. You really only get one chance, because they\nrely heavily on first impressions. And you can't approach some and\nsave others for later, because (a) they ask who else you've talked\nto and when and (b) they talk among themselves. If you're talking\nto one VC and he finds out that you were rejected by another several\nmonths ago, you'll definitely seem shopworn.So when do you approach VCs? When you can convince them. If the\nfounders have impressive resumes and the idea isn't hard to understand,\nyou could approach VCs quite early. Whereas if the founders are\nunknown and the idea is very novel, you might have to launch the\nthing and show that users loved it before VCs would be convinced.If several VCs are interested in you, they will sometimes be willing\nto split the deal between them. They're more likely to do this if\nthey're close in the VC pecking order. Such deals may be a net win\nfor founders, because you get multiple VCs interested in your\nsuccess, and you can ask each for advice about the other. One\nfounder I know wrote:\n\n Two-firm deals are great. It costs you a little more equity, but\n being able to play the two firms off each other (as well as ask\n one if the other is being out of line) is invaluable.\n\nWhen you do negotiate with VCs, remember that they've done this a\nlot more than you have. They've invested in dozens of startups,\nwhereas this is probably the first you've founded. But don't let\nthem or the situation intimidate you. The average founder is smarter\nthan the average VC. So just do what you'd do in any complex,\nunfamiliar situation: proceed deliberately, and question anything\nthat seems odd.It is, unfortunately, common for VCs to put terms in an agreement\nwhose consequences surprise founders later, and also common for VCs\nto defend things they do by saying that they're standard in the\nindustry. Standard, schmandard; the whole industry is only a few\ndecades old, and rapidly evolving. The concept of \"standard\" is a\nuseful one when you're operating on a small scale (Y Combinator\nuses identical terms for every deal because for tiny seed-stage\ninvestments it's not worth the overhead of negotiating individual\ndeals), but it doesn't apply at the VC level. On that scale, every\nnegotiation is unique.Most successful startups get money from more than one of the preceding\nfive sources. \n[6]\nAnd, confusingly, the names of funding sources\nalso tend to be used as the names of different rounds. The best\nway to explain how it all works is to follow the case of a hypothetical\nstartup.Stage 1: Seed RoundOur startup begins when a group of three friends have an idea--\neither an idea for something they might build, or simply the idea\n\"let's start a company.\" Presumably they already have some source\nof food and shelter. But if you have food and shelter, you probably\nalso have something you're supposed to be working on: either\nclasswork, or a job. So if you want to work full-time on a startup,\nyour money situation will probably change too.A lot of startup founders say they started the company without any\nidea of what they planned to do. This is actually less common than\nit seems: many have to claim they thought of the idea after quitting\nbecause otherwise their former employer would own it.The three friends decide to take the leap. Since most startups are\nin competitive businesses, you not only want to work full-time on\nthem, but more than full-time. So some or all of the friends quit\ntheir jobs or leave school. (Some of the founders in a startup can\nstay in grad school, but at least one has to make the company his\nfull-time job.)They're going to run the company out of one of their apartments at\nfirst, and since they don't have any users they don't have to pay\nmuch for infrastructure. Their main expenses are setting up the\ncompany, which costs a couple thousand dollars in legal work and\nregistration fees, and the living expenses of the founders.The phrase \"seed investment\" covers a broad range. To some VC firms\nit means $500,000, but to most startups it means several months'\nliving expenses. We'll suppose our group of friends start with\n$15,000 from their friend's rich uncle, who they give 5% of the\ncompany in return. There's only common stock at this stage. They\nleave 20% as an options pool for later employees (but they set\nthings up so that they can issue this stock to themselves if they\nget bought early and most is still unissued), and the three founders\neach get 25%.By living really cheaply they think they can make the remaining\nmoney last five months. When you have five months' runway left,\nhow soon do you need to start looking for your next round? Answer:\nimmediately. It takes time to find investors, and time (always\nmore than you expect) for the deal to close even after they say\nyes. So if our group of founders know what they're doing they'll\nstart sniffing around for angel investors right away. But of course\ntheir main job is to build version 1 of their software.The friends might have liked to have more money in this first phase,\nbut being slightly underfunded teaches them an important lesson.\nFor a startup, cheapness is power. The lower your costs, the more\noptions you have—not just at this stage, but at every point till\nyou're profitable. When you have a high \"burn rate,\" you're always\nunder time pressure, which means (a) you don't have time for your\nideas to evolve, and (b) you're often forced to take deals you don't\nlike.Every startup's rule should be: spend little, and work fast.After ten weeks' work the three friends have built a prototype that\ngives one a taste of what their product will do. It's not what\nthey originally set out to do—in the process of writing it, they\nhad some new ideas. And it only does a fraction of what the finished\nproduct will do, but that fraction includes stuff that no one else\nhas done before.They've also written at least a skeleton business plan, addressing\nthe five fundamental questions: what they're going to do, why users\nneed it, how large the market is, how they'll make money, and who\nthe competitors are and why this company is going to beat them.\n(That last has to be more specific than \"they suck\" or \"we'll work\nreally hard.\")If you have to choose between spending time on the demo or the\nbusiness plan, spend most on the demo. Software is not only more\nconvincing, but a better way to explore ideas.Stage 2: Angel RoundWhile writing the prototype, the group has been traversing their\nnetwork of friends in search of angel investors. They find some\njust as the prototype is demoable. When they demo it, one of the\nangels is willing to invest. Now the group is looking for more\nmoney: they want enough to last for a year, and maybe to hire a\ncouple friends. So they're going to raise $200,000.The angel agrees to invest at a pre-money valuation of $1 million.\nThe company issues $200,000 worth of new shares to the angel; if\nthere were 1000 shares before the deal, this means 200 additional\nshares. The angel now owns 200/1200 shares, or a sixth of the\ncompany, and all the previous shareholders' percentage ownership\nis diluted by a sixth. After the deal, the capitalization table\nlooks like this:\n\nshareholder shares percent\n-------------------------------\nangel 200 16.7\nuncle 50 4.2\neach founder 250 20.8\noption pool 200 16.7\n ---- -----\ntotal 1200 100\n\nTo keep things simple, I had the angel do a straight cash for stock\ndeal. In reality the angel might be more likely to make the\ninvestment in the form of a convertible loan. A convertible loan\nis a loan that can be converted into stock later; it works out the\nsame as a stock purchase in the end, but gives the angel more\nprotection against being squashed by VCs in future rounds.Who pays the legal bills for this deal? The startup, remember,\nonly has a couple thousand left. In practice this turns out to be\na sticky problem that usually gets solved in some improvised way.\nMaybe the startup can find lawyers who will do it cheaply in the\nhope of future work if the startup succeeds. Maybe someone has a\nlawyer friend. Maybe the angel pays for his lawyer to represent\nboth sides. (Make sure if you take the latter route that the lawyer\nis representing you rather than merely advising you, or his\nonly duty is to the investor.)An angel investing $200k would probably expect a seat on the board\nof directors. He might also want preferred stock, meaning a special\nclass of stock that has some additional rights over the common stock\neveryone else has. Typically these rights include vetoes over major\nstrategic decisions, protection against being diluted in future\nrounds, and the right to get one's investment back first if the\ncompany is sold.Some investors might expect the founders to accept vesting for a\nsum this size, and others wouldn't. VCs are more likely to require\nvesting than angels. At Viaweb we managed to raise $2.5 million\nfrom angels without ever accepting vesting, largely because we were\nso inexperienced that we were appalled at the idea. In practice\nthis turned out to be good, because it made us harder to push around.Our experience was unusual; vesting is the norm for amounts that\nsize. Y Combinator doesn't require vesting, because (a) we invest\nsuch small amounts, and (b) we think it's unnecessary, and that the\nhope of getting rich is enough motivation to keep founders at work.\nBut maybe if we were investing millions we would think differently.I should add that vesting is also a way for founders to protect\nthemselves against one another. It solves the problem of what to\ndo if one of the founders quits. So some founders impose it on\nthemselves when they start the company.The angel deal takes two weeks to close, so we are now three months\ninto the life of the company.The point after you get the first big chunk of angel money will\nusually be the happiest phase in a startup's life. It's a lot like\nbeing a postdoc: you have no immediate financial worries, and few\nresponsibilities. You get to work on juicy kinds of work, like\ndesigning software. You don't have to spend time on bureaucratic\nstuff, because you haven't hired any bureaucrats yet. Enjoy it\nwhile it lasts, and get as much done as you can, because you will\nnever again be so productive.With an apparently inexhaustible sum of money sitting safely in the\nbank, the founders happily set to work turning their prototype into\nsomething they can release. They hire one of their friends—at\nfirst just as a consultant, so they can try him out—and then a\nmonth later as employee #1. They pay him the smallest salary he can\nlive on, plus 3% of the company in restricted stock, vesting over\nfour years. (So after this the option pool is down to 13.7%). \n[7]\nThey also spend a little money on a freelance graphic designer.How much stock do you give early employees? That varies so much\nthat there's no conventional number. If you get someone really\ngood, really early, it might be wise to give him as much stock as\nthe founders. The one universal rule is that the amount of stock\nan employee gets decreases polynomially with the age of the company.\nIn other words, you get rich as a power of how early you were. So\nif some friends want you to come work for their startup, don't wait\nseveral months before deciding.A month later, at the end of month four, our group of founders have\nsomething they can launch. Gradually through word of mouth they\nstart to get users. Seeing the system in use by real users—people\nthey don't know—gives them lots of new ideas. Also they find\nthey now worry obsessively about the status of their server. (How\nrelaxing founders' lives must have been when startups wrote VisiCalc.)By the end of month six, the system is starting to have a solid\ncore of features, and a small but devoted following. People start\nto write about it, and the founders are starting to feel like experts\nin their field.We'll assume that their startup is one that could put millions more\nto use. Perhaps they need to spend a lot on marketing, or build\nsome kind of expensive infrastructure, or hire highly paid salesmen.\nSo they decide to start talking to VCs. They get introductions to\nVCs from various sources: their angel investor connects them with\na couple; they meet a few at conferences; a couple VCs call them\nafter reading about them.Step 3: Series A RoundArmed with their now somewhat fleshed-out business plan and able\nto demo a real, working system, the founders visit the VCs they\nhave introductions to. They find the VCs intimidating and inscrutable.\nThey all ask the same question: who else have you pitched to? (VCs\nare like high school girls: they're acutely aware of their position\nin the VC pecking order, and their interest in a company is a\nfunction of the interest other VCs show in it.)One of the VC firms says they want to invest and offers the founders\na term sheet. A term sheet is a summary of what the deal terms\nwill be when and if they do a deal; lawyers will fill in the details\nlater. By accepting the term sheet, the startup agrees to turn\naway other VCs for some set amount of time while this firm does the\n\"due diligence\" required for the deal. Due diligence is the corporate\nequivalent of a background check: the purpose is to uncover any\nhidden bombs that might sink the company later, like serious design\nflaws in the product, pending lawsuits against the company,\nintellectual property issues, and so on. VCs' legal and financial\ndue diligence is pretty thorough, but the technical due diligence\nis generally a joke. \n[8]The due diligence discloses no ticking bombs, and six weeks later\nthey go ahead with the deal. Here are the terms: a $2 million\ninvestment at a pre-money valuation of $4 million, meaning that\nafter the deal closes the VCs will own a third of the company (2 /\n(4 + 2)). The VCs also insist that prior to the deal the option\npool be enlarged by an additional hundred shares. So the total\nnumber of new shares issued is 750, and the cap table becomes:\n\nshareholder shares percent\n-------------------------------\nVCs 650 33.3\nangel 200 10.3\nuncle 50 2.6\neach founder 250 12.8\nemployee 36* 1.8 *unvested\noption pool 264 13.5\n ---- -----\ntotal 1950 100\n\nThis picture is unrealistic in several respects. For example, while\nthe percentages might end up looking like this, it's unlikely that\nthe VCs would keep the existing numbers of shares. In fact, every\nbit of the startup's paperwork would probably be replaced, as if\nthe company were being founded anew. Also, the money might come\nin several tranches, the later ones subject to various \nconditions—though this is apparently more common in deals with lower-tier VCs\n(whose lot in life is to fund more dubious startups) than with the\ntop firms.And of course any VCs reading this are probably rolling on the floor\nlaughing at how my hypothetical VCs let the angel keep his 10.3 of\nthe company. I admit, this is the Bambi version; in simplifying\nthe picture, I've also made everyone nicer. In the real world, VCs\nregard angels the way a jealous husband feels about his wife's\nprevious boyfriends. To them the company didn't exist before they\ninvested in it. \n[9]I don't want to give the impression you have to do an angel round\nbefore going to VCs. In this example I stretched things out to\nshow multiple sources of funding in action. Some startups could go\ndirectly from seed funding to a VC round; several of the companies\nwe've funded have.The founders are required to vest their shares over four years, and\nthe board is now reconstituted to consist of two VCs, two founders,\nand a fifth person acceptable to both. The angel investor cheerfully\nsurrenders his board seat.At this point there is nothing new our startup can teach us about\nfunding—or at least, nothing good. \n[10]\nThe startup will almost\ncertainly hire more people at this point; those millions must be\nput to work, after all. The company may do additional funding\nrounds, presumably at higher valuations. They may if they are\nextraordinarily fortunate do an IPO, which we should remember is\nalso in principle a round of funding, regardless of its de facto\npurpose. But that, if not beyond the bounds of possibility, is\nbeyond the scope of this article.Deals Fall ThroughAnyone who's been through a startup will find the preceding portrait\nto be missing something: disasters. If there's one thing all\nstartups have in common, it's that something is always going wrong.\nAnd nowhere more than in matters of funding.For example, our hypothetical startup never spent more than half\nof one round before securing the next. That's more ideal than\ntypical. Many startups—even successful ones—come close to\nrunning out of money at some point. Terrible things happen to\nstartups when they run out of money, because they're designed for\ngrowth, not adversity.But the most unrealistic thing about the series of deals I've\ndescribed is that they all closed. In the startup world, closing\nis not what deals do. What deals do is fall through. If you're\nstarting a startup you would do well to remember that. Birds fly;\nfish swim; deals fall through.Why? Partly the reason deals seem to fall through so often is that\nyou lie to yourself. You want the deal to close, so you start to\nbelieve it will. But even correcting for this, startup deals fall\nthrough alarmingly often—far more often than, say, deals to buy\nreal estate. The reason is that it's such a risky environment.\nPeople about to fund or acquire a startup are prone to wicked cases\nof buyer's remorse. They don't really grasp the risk they're taking\ntill the deal's about to close. And then they panic. And not just\ninexperienced angel investors, but big companies too.So if you're a startup founder wondering why some angel investor\nisn't returning your phone calls, you can at least take comfort in\nthe thought that the same thing is happening to other deals a hundred\ntimes the size.The example of a startup's history that I've presented is like a\nskeleton—accurate so far as it goes, but needing to be fleshed\nout to be a complete picture. To get a complete picture, just add\nin every possible disaster.A frightening prospect? In a way. And yet also in a way encouraging.\nThe very uncertainty of startups frightens away almost everyone.\nPeople overvalue stability—especially young\npeople, who ironically need it least. And so in starting a startup,\nas in any really bold undertaking, merely deciding to do it gets\nyou halfway there. On the day of the race, most of the other runners\nwon't show up.\nNotes[1]\nThe aim of such regulations is to protect widows and orphans\nfrom crooked investment schemes; people with a million dollars in\nliquid assets are assumed to be able to protect themselves.\nThe unintended consequence is that the investments that generate\nthe highest returns, like hedge funds, are available only to the\nrich.[2]\nConsulting is where product companies go to die. IBM is the\nmost famous example. So starting as a consulting company is like\nstarting out in the grave and trying to work your way up into the\nworld of the living.[3]\nIf \"near you\" doesn't mean the Bay Area, Boston, or Seattle,\nconsider moving. It's not a coincidence you haven't heard of many\nstartups from Philadelphia.[4]\nInvestors are often compared to sheep. And they are like sheep,\nbut that's a rational response to their situation. Sheep act the\nway they do for a reason. If all the other sheep head for a certain\nfield, it's probably good grazing. And when a wolf appears, is he\ngoing to eat a sheep in the middle of the flock, or one near the\nedge?[5]\nThis was partly confidence, and partly simple ignorance. We\ndidn't know ourselves which VC firms were the impressive ones. We\nthought software was all that mattered. But that turned out to be\nthe right direction to be naive in: it's much better to overestimate\nthan underestimate the importance of making a good product.[6]\nI've omitted one source: government grants. I don't think\nthese are even worth thinking about for the average startup.\nGovernments may mean well when they set up grant programs to encourage\nstartups, but what they give with one hand they take away with the\nother: the process of applying is inevitably so arduous, and the\nrestrictions on what you can do with the money so burdensome, that\nit would be easier to take a job to get the money.\nYou should be especially suspicious of grants whose purpose is some\nkind of social engineering-- e.g. to encourage more startups to be\nstarted in Mississippi. Free money to start a startup in a place\nwhere few succeed is hardly free.Some government agencies run venture funding groups, which make\ninvestments rather than giving grants. For example, the CIA runs\na venture fund called In-Q-Tel that is modelled on private sector\nfunds and apparently generates good returns. They would probably\nbe worth approaching—if you don't mind taking money from the CIA.[7]\nOptions have largely been replaced with restricted stock, which\namounts to the same thing. Instead of earning the right to buy\nstock, the employee gets the stock up front, and earns the right\nnot to have to give it back. The shares set aside for this purpose\nare still called the \"option pool.\"[8]\nFirst-rate technical people do not generally hire themselves\nout to do due diligence for VCs. So the most difficult\npart for startup founders is often responding politely to the inane\nquestions of the \"expert\" they send to look you over.[9]\nVCs regularly wipe out angels by issuing arbitrary amounts of\nnew stock. They seem to have a standard piece of casuistry for\nthis situation: that the angels are no longer working to help the\ncompany, and so don't deserve to keep their stock. This of course\nreflects a willful misunderstanding of what investment means; like\nany investor, the angel is being compensated for risks he took\nearlier. By a similar logic, one could argue that the VCs should\nbe deprived of their shares when the company goes public.[10]\nOne new thing the company might encounter is a down\nround, or a funding round at valuation lower than the previous\nround. Down rounds are bad news; it is generally the common stock\nholders who take the hit. Some of the most fearsome provisions in\nVC deal terms have to do with down rounds—like \"full ratchet\nanti-dilution,\" which is as frightening as it sounds.Founders are tempted to ignore these clauses, because they think\nthe company will either be a big success or a complete bust. VCs\nknow otherwise: it's not uncommon for startups to have moments of\nadversity before they ultimately succeed. So it's worth negotiating\nanti-dilution provisions, even though you don't think you need to,\nand VCs will try to make you feel that you're being gratuitously\ntroublesome.Thanks to Sam Altman, Hutch Fishman, Steve Huffman, Jessica\nLivingston, Sesha Pratap, Stan Reiss, Andy Singleton, Zak Stone,\nand Aaron Swartz for reading drafts of this." }, { "path": "data/PaulGrahamEssayMedium/startupideas.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nNovember 2012The way to get startup ideas is not to try to think of startup\nideas. It's to look for problems, preferably problems you have\nyourself.The very best startup ideas tend to have three things in common:\nthey're something the founders themselves want, that they themselves\ncan build, and that few others realize are worth doing. Microsoft,\nApple, Yahoo, Google, and Facebook all began this way.\nProblemsWhy is it so important to work on a problem you have? Among other\nthings, it ensures the problem really exists. It sounds obvious\nto say you should only work on problems that exist. And yet by far\nthe most common mistake startups make is to solve problems no one\nhas.I made it myself. In 1995 I started a company to put art galleries\nonline. But galleries didn't want to be online. It's not how the\nart business works. So why did I spend 6 months working on this\nstupid idea? Because I didn't pay attention to users. I invented\na model of the world that didn't correspond to reality, and worked\nfrom that. I didn't notice my model was wrong until I tried\nto convince users to pay for what we'd built. Even then I took\nembarrassingly long to catch on. I was attached to my model of the\nworld, and I'd spent a lot of time on the software. They had to\nwant it!Why do so many founders build things no one wants? Because they\nbegin by trying to think of startup ideas. That m.o. is doubly\ndangerous: it doesn't merely yield few good ideas; it yields bad\nideas that sound plausible enough to fool you into working on them.At YC we call these \"made-up\" or \"sitcom\" startup ideas. Imagine\none of the characters on a TV show was starting a startup. The\nwriters would have to invent something for it to do. But coming\nup with good startup ideas is hard. It's not something you can do\nfor the asking. So (unless they got amazingly lucky) the writers\nwould come up with an idea that sounded plausible, but was actually\nbad.For example, a social network for pet owners. It doesn't sound\nobviously mistaken. Millions of people have pets. Often they care\na lot about their pets and spend a lot of money on them. Surely\nmany of these people would like a site where they could talk to\nother pet owners. Not all of them perhaps, but if just 2 or 3\npercent were regular visitors, you could have millions of users.\nYou could serve them targeted offers, and maybe charge for premium\nfeatures. \n[1]The danger of an idea like this is that when you run it by your\nfriends with pets, they don't say \"I would never use this.\" They\nsay \"Yeah, maybe I could see using something like that.\" Even when\nthe startup launches, it will sound plausible to a lot of people.\nThey don't want to use it themselves, at least not right now, but\nthey could imagine other people wanting it. Sum that reaction\nacross the entire population, and you have zero users. \n[2]\nWellWhen a startup launches, there have to be at least some users who\nreally need what they're making — not just people who could see\nthemselves using it one day, but who want it urgently. Usually\nthis initial group of users is small, for the simple reason that\nif there were something that large numbers of people urgently needed\nand that could be built with the amount of effort a startup usually\nputs into a version one, it would probably already exist. Which\nmeans you have to compromise on one dimension: you can either build\nsomething a large number of people want a small amount, or something\na small number of people want a large amount. Choose the latter.\nNot all ideas of that type are good startup ideas, but nearly all\ngood startup ideas are of that type.Imagine a graph whose x axis represents all the people who might\nwant what you're making and whose y axis represents how much they\nwant it. If you invert the scale on the y axis, you can envision\ncompanies as holes. Google is an immense crater: hundreds of\nmillions of people use it, and they need it a lot. A startup just\nstarting out can't expect to excavate that much volume. So you\nhave two choices about the shape of hole you start with. You can\neither dig a hole that's broad but shallow, or one that's narrow\nand deep, like a well.Made-up startup ideas are usually of the first type. Lots of people\nare mildly interested in a social network for pet owners.Nearly all good startup ideas are of the second type. Microsoft\nwas a well when they made Altair Basic. There were only a couple\nthousand Altair owners, but without this software they were programming\nin machine language. Thirty years later Facebook had the same\nshape. Their first site was exclusively for Harvard students, of\nwhich there are only a few thousand, but those few thousand users\nwanted it a lot.When you have an idea for a startup, ask yourself: who wants this\nright now? Who wants this so much that they'll use it even when\nit's a crappy version one made by a two-person startup they've never\nheard of? If you can't answer that, the idea is probably bad. \n[3]You don't need the narrowness of the well per se. It's depth you\nneed; you get narrowness as a byproduct of optimizing for depth\n(and speed). But you almost always do get it. In practice the\nlink between depth and narrowness is so strong that it's a good\nsign when you know that an idea will appeal strongly to a specific\ngroup or type of user.But while demand shaped like a well is almost a necessary condition\nfor a good startup idea, it's not a sufficient one. If Mark\nZuckerberg had built something that could only ever have appealed\nto Harvard students, it would not have been a good startup idea.\nFacebook was a good idea because it started with a small market\nthere was a fast path out of. Colleges are similar enough that if\nyou build a facebook that works at Harvard, it will work at any\ncollege. So you spread rapidly through all the colleges. Once you\nhave all the college students, you get everyone else simply by\nletting them in.Similarly for Microsoft: Basic for the Altair; Basic for other\nmachines; other languages besides Basic; operating systems;\napplications; IPO.\nSelfHow do you tell whether there's a path out of an idea? How do you\ntell whether something is the germ of a giant company, or just a\nniche product? Often you can't. The founders of Airbnb didn't\nrealize at first how big a market they were tapping. Initially\nthey had a much narrower idea. They were going to let hosts rent\nout space on their floors during conventions. They didn't foresee\nthe expansion of this idea; it forced itself upon them gradually.\nAll they knew at first is that they were onto something. That's\nprobably as much as Bill Gates or Mark Zuckerberg knew at first.Occasionally it's obvious from the beginning when there's a path\nout of the initial niche. And sometimes I can see a path that's\nnot immediately obvious; that's one of our specialties at YC. But\nthere are limits to how well this can be done, no matter how much\nexperience you have. The most important thing to understand about\npaths out of the initial idea is the meta-fact that these are hard\nto see.So if you can't predict whether there's a path out of an idea, how\ndo you choose between ideas? The truth is disappointing but\ninteresting: if you're the right sort of person, you have the right\nsort of hunches. If you're at the leading edge of a field that's\nchanging fast, when you have a hunch that something is worth doing,\nyou're more likely to be right.In Zen and the Art of Motorcycle Maintenance, Robert Pirsig says:\n\n You want to know how to paint a perfect painting? It's easy. Make\n yourself perfect and then just paint naturally.\n\nI've wondered about that passage since I read it in high school.\nI'm not sure how useful his advice is for painting specifically,\nbut it fits this situation well. Empirically, the way to have good\nstartup ideas is to become the sort of person who has them.Being at the leading edge of a field doesn't mean you have to be\none of the people pushing it forward. You can also be at the leading\nedge as a user. It was not so much because he was a programmer\nthat Facebook seemed a good idea to Mark Zuckerberg as because he\nused computers so much. If you'd asked most 40 year olds in 2004\nwhether they'd like to publish their lives semi-publicly on the\nInternet, they'd have been horrified at the idea. But Mark already\nlived online; to him it seemed natural.Paul Buchheit says that people at the leading edge of a rapidly\nchanging field \"live in the future.\" Combine that with Pirsig and\nyou get:\n\n Live in the future, then build what's missing.\n\nThat describes the way many if not most of the biggest startups got\nstarted. Neither Apple nor Yahoo nor Google nor Facebook were even\nsupposed to be companies at first. They grew out of things their\nfounders built because there seemed a gap in the world.If you look at the way successful founders have had their ideas,\nit's generally the result of some external stimulus hitting a\nprepared mind. Bill Gates and Paul Allen hear about the Altair and\nthink \"I bet we could write a Basic interpreter for it.\" Drew Houston\nrealizes he's forgotten his USB stick and thinks \"I really need to\nmake my files live online.\" Lots of people heard about the Altair.\nLots forgot USB sticks. The reason those stimuli caused those\nfounders to start companies was that their experiences had prepared\nthem to notice the opportunities they represented.The verb you want to be using with respect to startup ideas is not\n\"think up\" but \"notice.\" At YC we call ideas that grow naturally\nout of the founders' own experiences \"organic\" startup ideas. The\nmost successful startups almost all begin this way.That may not have been what you wanted to hear. You may have\nexpected recipes for coming up with startup ideas, and instead I'm\ntelling you that the key is to have a mind that's prepared in the\nright way. But disappointing though it may be, this is the truth.\nAnd it is a recipe of a sort, just one that in the worst case takes\na year rather than a weekend.If you're not at the leading edge of some rapidly changing field,\nyou can get to one. For example, anyone reasonably smart can\nprobably get to an edge of programming (e.g. building mobile apps)\nin a year. Since a successful startup will consume at least 3-5\nyears of your life, a year's preparation would be a reasonable\ninvestment. Especially if you're also looking for a cofounder.\n[4]You don't have to learn programming to be at the leading edge of a\ndomain that's changing fast. Other domains change fast. But while\nlearning to hack is not necessary, it is for the forseeable future\nsufficient. As Marc Andreessen put it, software is eating the world,\nand this trend has decades left to run.Knowing how to hack also means that when you have ideas, you'll be\nable to implement them. That's not absolutely necessary (Jeff Bezos\ncouldn't) but it's an advantage. It's a big advantage, when you're\nconsidering an idea like putting a college facebook online, if\ninstead of merely thinking \"That's an interesting idea,\" you can\nthink instead \"That's an interesting idea. I'll try building an\ninitial version tonight.\" It's even better when you're both a\nprogrammer and the target user, because then the cycle of generating\nnew versions and testing them on users can happen inside one head.\nNoticingOnce you're living in the future in some respect, the way to notice\nstartup ideas is to look for things that seem to be missing. If\nyou're really at the leading edge of a rapidly changing field, there\nwill be things that are obviously missing. What won't be obvious\nis that they're startup ideas. So if you want to find startup\nideas, don't merely turn on the filter \"What's missing?\" Also turn\noff every other filter, particularly \"Could this be a big company?\"\nThere's plenty of time to apply that test later. But if you're\nthinking about that initially, it may not only filter out lots\nof good ideas, but also cause you to focus on bad ones.Most things that are missing will take some time to see. You almost\nhave to trick yourself into seeing the ideas around you.But you know the ideas are out there. This is not one of those\nproblems where there might not be an answer. It's impossibly\nunlikely that this is the exact moment when technological progress\nstops. You can be sure people are going to build things in the\nnext few years that will make you think \"What did I do before x?\"And when these problems get solved, they will probably seem flamingly\nobvious in retrospect. What you need to do is turn off the filters\nthat usually prevent you from seeing them. The most powerful is\nsimply taking the current state of the world for granted. Even the\nmost radically open-minded of us mostly do that. You couldn't get\nfrom your bed to the front door if you stopped to question everything.But if you're looking for startup ideas you can sacrifice some of\nthe efficiency of taking the status quo for granted and start to\nquestion things. Why is your inbox overflowing? Because you get\na lot of email, or because it's hard to get email out of your inbox?\nWhy do you get so much email? What problems are people trying to\nsolve by sending you email? Are there better ways to solve them?\nAnd why is it hard to get emails out of your inbox? Why do you\nkeep emails around after you've read them? Is an inbox the optimal\ntool for that?Pay particular attention to things that chafe you. The advantage\nof taking the status quo for granted is not just that it makes life\n(locally) more efficient, but also that it makes life more tolerable.\nIf you knew about all the things we'll get in the next 50 years but\ndon't have yet, you'd find present day life pretty constraining,\njust as someone from the present would if they were sent back 50\nyears in a time machine. When something annoys you, it could be\nbecause you're living in the future.When you find the right sort of problem, you should probably be\nable to describe it as obvious, at least to you. When we started\nViaweb, all the online stores were built by hand, by web designers\nmaking individual HTML pages. It was obvious to us as programmers\nthat these sites would have to be generated by software.\n[5]Which means, strangely enough, that coming up with startup ideas\nis a question of seeing the obvious. That suggests how weird this\nprocess is: you're trying to see things that are obvious, and yet\nthat you hadn't seen.Since what you need to do here is loosen up your own mind, it may\nbe best not to make too much of a direct frontal attack on the\nproblem — i.e. to sit down and try to think of ideas. The best\nplan may be just to keep a background process running, looking for\nthings that seem to be missing. Work on hard problems, driven\nmainly by curiosity, but have a second self watching over your\nshoulder, taking note of gaps and anomalies. \n[6]Give yourself some time. You have a lot of control over the rate\nat which you turn yours into a prepared mind, but you have less\ncontrol over the stimuli that spark ideas when they hit it. If\nBill Gates and Paul Allen had constrained themselves to come up\nwith a startup idea in one month, what if they'd chosen a month\nbefore the Altair appeared? They probably would have worked on a\nless promising idea. Drew Houston did work on a less promising\nidea before Dropbox: an SAT prep startup. But Dropbox was a much\nbetter idea, both in the absolute sense and also as a match for his\nskills.\n[7]A good way to trick yourself into noticing ideas is to work on\nprojects that seem like they'd be cool. If you do that, you'll\nnaturally tend to build things that are missing. It wouldn't seem\nas interesting to build something that already existed.Just as trying to think up startup ideas tends to produce bad ones,\nworking on things that could be dismissed as \"toys\" often produces\ngood ones. When something is described as a toy, that means it has\neverything an idea needs except being important. It's cool; users\nlove it; it just doesn't matter. But if you're living in the future\nand you build something cool that users love, it may matter more\nthan outsiders think. Microcomputers seemed like toys when Apple\nand Microsoft started working on them. I'm old enough to remember\nthat era; the usual term for people with their own microcomputers\nwas \"hobbyists.\" BackRub seemed like an inconsequential science\nproject. The Facebook was just a way for undergrads to stalk one\nanother.At YC we're excited when we meet startups working on things that\nwe could imagine know-it-alls on forums dismissing as toys. To us\nthat's positive evidence an idea is good.If you can afford to take a long view (and arguably you can't afford\nnot to), you can turn \"Live in the future and build what's missing\"\ninto something even better:\n\n Live in the future and build what seems interesting.\n\nSchoolThat's what I'd advise college students to do, rather than trying\nto learn about \"entrepreneurship.\" \"Entrepreneurship\" is something\nyou learn best by doing it. The examples of the most successful\nfounders make that clear. What you should be spending your time\non in college is ratcheting yourself into the future. College is\nan incomparable opportunity to do that. What a waste to sacrifice\nan opportunity to solve the hard part of starting a startup — becoming \nthe sort of person who can have organic startup ideas — by \nspending time learning about the easy part. Especially since\nyou won't even really learn about it, any more than you'd learn\nabout sex in a class. All you'll learn is the words for things.The clash of domains is a particularly fruitful source of ideas.\nIf you know a lot about programming and you start learning about\nsome other field, you'll probably see problems that software could\nsolve. In fact, you're doubly likely to find good problems in\nanother domain: (a) the inhabitants of that domain are not as likely\nas software people to have already solved their problems with\nsoftware, and (b) since you come into the new domain totally ignorant,\nyou don't even know what the status quo is to take it for granted.So if you're a CS major and you want to start a startup, instead\nof taking a class on entrepreneurship you're better off taking a\nclass on, say, genetics. Or better still, go work for a biotech\ncompany. CS majors normally get summer jobs at computer hardware\nor software companies. But if you want to find startup ideas, you\nmight do better to get a summer job in some unrelated field. \n[8]Or don't take any extra classes, and just build things. It's no\ncoincidence that Microsoft and Facebook both got started in January.\nAt Harvard that is (or was) Reading Period, when students have no\nclasses to attend because they're supposed to be studying for finals.\n[9]But don't feel like you have to build things that will become startups. That's\npremature optimization. Just build things. Preferably with other\nstudents. It's not just the classes that make a university such a\ngood place to crank oneself into the future. You're also surrounded\nby other people trying to do the same thing. If you work together\nwith them on projects, you'll end up producing not just organic\nideas, but organic ideas with organic founding teams — and that,\nempirically, is the best combination.Beware of research. If an undergrad writes something all his friends\nstart using, it's quite likely to represent a good startup idea.\nWhereas a PhD dissertation is extremely unlikely to. For some\nreason, the more a project has to count as research, the less likely\nit is to be something that could be turned into a startup.\n[10]\nI think the reason is that the subset of ideas that count as research\nis so narrow that it's unlikely that a project that satisfied that\nconstraint would also satisfy the orthogonal constraint of solving\nusers' problems. Whereas when students (or professors) build\nsomething as a side-project, they automatically gravitate toward\nsolving users' problems — perhaps even with an additional energy\nthat comes from being freed from the constraints of research.\nCompetitionBecause a good idea should seem obvious, when you have one you'll\ntend to feel that you're late. Don't let that deter you. Worrying\nthat you're late is one of the signs of a good idea. Ten minutes\nof searching the web will usually settle the question. Even if you\nfind someone else working on the same thing, you're probably not\ntoo late. It's exceptionally rare for startups to be killed by\ncompetitors — so rare that you can almost discount the possibility.\nSo unless you discover a competitor with the sort of lock-in that\nwould prevent users from choosing you, don't discard the idea.If you're uncertain, ask users. The question of whether you're too\nlate is subsumed by the question of whether anyone urgently needs\nwhat you plan to make. If you have something that no competitor\ndoes and that some subset of users urgently need, you have a\nbeachhead. \n[11]The question then is whether that beachhead is big enough. Or more\nimportantly, who's in it: if the beachhead consists of people doing\nsomething lots more people will be doing in the future, then it's\nprobably big enough no matter how small it is. For example, if\nyou're building something differentiated from competitors by the\nfact that it works on phones, but it only works on the newest phones,\nthat's probably a big enough beachhead.Err on the side of doing things where you'll face competitors.\nInexperienced founders usually give competitors more credit than\nthey deserve. Whether you succeed depends far more on you than on\nyour competitors. So better a good idea with competitors than a\nbad one without.You don't need to worry about entering a \"crowded market\" so long\nas you have a thesis about what everyone else in it is overlooking.\nIn fact that's a very promising starting point. Google was that\ntype of idea. Your thesis has to be more precise than \"we're going\nto make an x that doesn't suck\" though. You have to be able to\nphrase it in terms of something the incumbents are overlooking.\nBest of all is when you can say that they didn't have the courage\nof their convictions, and that your plan is what they'd have done\nif they'd followed through on their own insights. Google was that\ntype of idea too. The search engines that preceded them shied away\nfrom the most radical implications of what they were doing — particularly \nthat the better a job they did, the faster users would\nleave.A crowded market is actually a good sign, because it means both\nthat there's demand and that none of the existing solutions are\ngood enough. A startup can't hope to enter a market that's obviously\nbig and yet in which they have no competitors. So any startup that\nsucceeds is either going to be entering a market with existing\ncompetitors, but armed with some secret weapon that will get them\nall the users (like Google), or entering a market that looks small\nbut which will turn out to be big (like Microsoft). \n[12]\nFiltersThere are two more filters you'll need to turn off if you want to\nnotice startup ideas: the unsexy filter and the schlep filter.Most programmers wish they could start a startup by just writing\nsome brilliant code, pushing it to a server, and having users pay\nthem lots of money. They'd prefer not to deal with tedious problems\nor get involved in messy ways with the real world. Which is a\nreasonable preference, because such things slow you down. But this\npreference is so widespread that the space of convenient startup\nideas has been stripped pretty clean. If you let your mind wander\na few blocks down the street to the messy, tedious ideas, you'll\nfind valuable ones just sitting there waiting to be implemented.The schlep filter is so dangerous that I wrote a separate essay\nabout the condition it induces, which I called \nschlep blindness.\nI gave Stripe as an example of a startup that benefited from turning\noff this filter, and a pretty striking example it is. Thousands\nof programmers were in a position to see this idea; thousands of\nprogrammers knew how painful it was to process payments before\nStripe. But when they looked for startup ideas they didn't see\nthis one, because unconsciously they shrank from having to deal\nwith payments. And dealing with payments is a schlep for Stripe,\nbut not an intolerable one. In fact they might have had net less\npain; because the fear of dealing with payments kept most people\naway from this idea, Stripe has had comparatively smooth sailing\nin other areas that are sometimes painful, like user acquisition.\nThey didn't have to try very hard to make themselves heard by users,\nbecause users were desperately waiting for what they were building.The unsexy filter is similar to the schlep filter, except it keeps\nyou from working on problems you despise rather than ones you fear.\nWe overcame this one to work on Viaweb. There were interesting\nthings about the architecture of our software, but we weren't\ninterested in ecommerce per se. We could see the problem was one\nthat needed to be solved though.Turning off the schlep filter is more important than turning off\nthe unsexy filter, because the schlep filter is more likely to be\nan illusion. And even to the degree it isn't, it's a worse form\nof self-indulgence. Starting a successful startup is going to be\nfairly laborious no matter what. Even if the product doesn't entail\na lot of schleps, you'll still have plenty dealing with investors,\nhiring and firing people, and so on. So if there's some idea you\nthink would be cool but you're kept away from by fear of the schleps\ninvolved, don't worry: any sufficiently good idea will have as many.The unsexy filter, while still a source of error, is not as entirely\nuseless as the schlep filter. If you're at the leading edge of a\nfield that's changing rapidly, your ideas about what's sexy will\nbe somewhat correlated with what's valuable in practice. Particularly\nas you get older and more experienced. Plus if you find an idea\nsexy, you'll work on it more enthusiastically. \n[13]\nRecipesWhile the best way to discover startup ideas is to become the sort\nof person who has them and then build whatever interests you,\nsometimes you don't have that luxury. Sometimes you need an idea\nnow. For example, if you're working on a startup and your initial\nidea turns out to be bad.For the rest of this essay I'll talk about tricks for coming up\nwith startup ideas on demand. Although empirically you're better\noff using the organic strategy, you could succeed this way. You\njust have to be more disciplined. When you use the organic method,\nyou don't even notice an idea unless it's evidence that something\nis truly missing. But when you make a conscious effort to think\nof startup ideas, you have to replace this natural constraint with\nself-discipline. You'll see a lot more ideas, most of them bad,\nso you need to be able to filter them.One of the biggest dangers of not using the organic method is the\nexample of the organic method. Organic ideas feel like inspirations.\nThere are a lot of stories about successful startups that began\nwhen the founders had what seemed a crazy idea but \"just knew\" it\nwas promising. When you feel that about an idea you've had while\ntrying to come up with startup ideas, you're probably mistaken.When searching for ideas, look in areas where you have some expertise.\nIf you're a database expert, don't build a chat app for teenagers\n(unless you're also a teenager). Maybe it's a good idea, but you\ncan't trust your judgment about that, so ignore it. There have to\nbe other ideas that involve databases, and whose quality you can\njudge. Do you find it hard to come up with good ideas involving\ndatabases? That's because your expertise raises your standards.\nYour ideas about chat apps are just as bad, but you're giving\nyourself a Dunning-Kruger pass in that domain.The place to start looking for ideas is things you need. There\nmust be things you need.\n[14]One good trick is to ask yourself whether in your previous job you\never found yourself saying \"Why doesn't someone make x? If someone\nmade x we'd buy it in a second.\" If you can think of any x people\nsaid that about, you probably have an idea. You know there's demand,\nand people don't say that about things that are impossible to build.More generally, try asking yourself whether there's something unusual\nabout you that makes your needs different from most other people's.\nYou're probably not the only one. It's especially good if you're\ndifferent in a way people will increasingly be.If you're changing ideas, one unusual thing about you is the idea\nyou'd previously been working on. Did you discover any needs while\nworking on it? Several well-known startups began this way. Hotmail\nbegan as something its founders wrote to talk about their previous\nstartup idea while they were working at their day jobs. \n[15]A particularly promising way to be unusual is to be young. Some\nof the most valuable new ideas take root first among people in their\nteens and early twenties. And while young founders are at a\ndisadvantage in some respects, they're the only ones who really\nunderstand their peers. It would have been very hard for someone\nwho wasn't a college student to start Facebook. So if you're a\nyoung founder (under 23 say), are there things you and your friends\nwould like to do that current technology won't let you?The next best thing to an unmet need of your own is an unmet need\nof someone else. Try talking to everyone you can about the gaps\nthey find in the world. What's missing? What would they like to\ndo that they can't? What's tedious or annoying, particularly in\ntheir work? Let the conversation get general; don't be trying too\nhard to find startup ideas. You're just looking for something to\nspark a thought. Maybe you'll notice a problem they didn't consciously\nrealize they had, because you know how to solve it.When you find an unmet need that isn't your own, it may be somewhat\nblurry at first. The person who needs something may not know exactly\nwhat they need. In that case I often recommend that founders act\nlike consultants — that they do what they'd do if they'd been\nretained to solve the problems of this one user. People's problems\nare similar enough that nearly all the code you write this way will\nbe reusable, and whatever isn't will be a small price to start out\ncertain that you've reached the bottom of the well.\n[16]One way to ensure you do a good job solving other people's problems\nis to make them your own. When Rajat Suri of E la Carte decided\nto write software for restaurants, he got a job as a waiter to learn\nhow restaurants worked. That may seem like taking things to extremes,\nbut startups are extreme. We love it when founders do such things.In fact, one strategy I recommend to people who need a new idea is\nnot merely to turn off their schlep and unsexy filters, but to seek\nout ideas that are unsexy or involve schleps. Don't try to start\nTwitter. Those ideas are so rare that you can't find them by looking\nfor them. Make something unsexy that people will pay you for.A good trick for bypassing the schlep and to some extent the unsexy\nfilter is to ask what you wish someone else would build, so that\nyou could use it. What would you pay for right now?Since startups often garbage-collect broken companies and industries,\nit can be a good trick to look for those that are dying, or deserve\nto, and try to imagine what kind of company would profit from their\ndemise. For example, journalism is in free fall at the moment.\nBut there may still be money to be made from something like journalism.\nWhat sort of company might cause people in the future to say \"this\nreplaced journalism\" on some axis?But imagine asking that in the future, not now. When one company\nor industry replaces another, it usually comes in from the side.\nSo don't look for a replacement for x; look for something that\npeople will later say turned out to be a replacement for x. And\nbe imaginative about the axis along which the replacement occurs.\nTraditional journalism, for example, is a way for readers to get\ninformation and to kill time, a way for writers to make money and\nto get attention, and a vehicle for several different types of\nadvertising. It could be replaced on any of these axes (it has\nalready started to be on most).When startups consume incumbents, they usually start by serving\nsome small but important market that the big players ignore. It's\nparticularly good if there's an admixture of disdain in the big\nplayers' attitude, because that often misleads them. For example,\nafter Steve Wozniak built the computer that became the Apple I, he\nfelt obliged to give his then-employer Hewlett-Packard the option\nto produce it. Fortunately for him, they turned it down, and one\nof the reasons they did was that it used a TV for a monitor, which\nseemed intolerably déclassé to a high-end hardware company like HP\nwas at the time. \n[17]Are there groups of \nscruffy \nbut sophisticated users like the early\nmicrocomputer \"hobbyists\" that are currently being ignored by the\nbig players? A startup with its sights set on bigger things can\noften capture a small market easily by expending an effort that\nwouldn't be justified by that market alone.Similarly, since the most successful startups generally ride some\nwave bigger than themselves, it could be a good trick to look for\nwaves and ask how one could benefit from them. The prices of gene\nsequencing and 3D printing are both experiencing Moore's Law-like\ndeclines. What new things will we be able to do in the new world\nwe'll have in a few years? What are we unconsciously ruling out\nas impossible that will soon be possible?\nOrganicBut talking about looking explicitly for waves makes it clear that\nsuch recipes are plan B for getting startup ideas. Looking for\nwaves is essentially a way to simulate the organic method. If\nyou're at the leading edge of some rapidly changing field, you don't\nhave to look for waves; you are the wave.Finding startup ideas is a subtle business, and that's why most\npeople who try fail so miserably. It doesn't work well simply to\ntry to think of startup ideas. If you do that, you get bad ones\nthat sound dangerously plausible. The best approach is more indirect:\nif you have the right sort of background, good startup ideas will\nseem obvious to you. But even then, not immediately. It takes\ntime to come across situations where you notice something missing.\nAnd often these gaps won't seem to be ideas for companies, just\nthings that would be interesting to build. Which is why it's good\nto have the time and the inclination to build things just because\nthey're interesting.Live in the future and build what seems interesting. Strange as\nit sounds, that's the real recipe.\nNotes[1]\nThis form of bad idea has been around as long as the web. It\nwas common in the 1990s, except then people who had it used to say\nthey were going to create a portal for x instead of a social network\nfor x. Structurally the idea is stone soup: you post a sign saying\n\"this is the place for people interested in x,\" and all those people\nshow up and you make money from them. What lures founders into\nthis sort of idea are statistics about the millions of people who\nmight be interested in each type of x. What they forget is that\nany given person might have 20 affinities by this standard, and no\none is going to visit 20 different communities regularly.[2]\nI'm not saying, incidentally, that I know for sure a social\nnetwork for pet owners is a bad idea. I know it's a bad idea the\nway I know randomly generated DNA would not produce a viable organism.\nThe set of plausible sounding startup ideas is many times larger\nthan the set of good ones, and many of the good ones don't even\nsound that plausible. So if all you know about a startup idea is\nthat it sounds plausible, you have to assume it's bad.[3]\nMore precisely, the users' need has to give them sufficient\nactivation energy to start using whatever you make, which can vary\na lot. For example, the activation energy for enterprise software\nsold through traditional channels is very high, so you'd have to\nbe a lot better to get users to switch. Whereas the activation\nenergy required to switch to a new search engine is low. Which in\nturn is why search engines are so much better than enterprise\nsoftware.[4]\nThis gets harder as you get older. While the space of ideas\ndoesn't have dangerous local maxima, the space of careers does.\nThere are fairly high walls between most of the paths people take\nthrough life, and the older you get, the higher the walls become.[5]\nIt was also obvious to us that the web was going to be a big\ndeal. Few non-programmers grasped that in 1995, but the programmers\nhad seen what GUIs had done for desktop computers.[6]\nMaybe it would work to have this second self keep a journal,\nand each night to make a brief entry listing the gaps and anomalies\nyou'd noticed that day. Not startup ideas, just the raw gaps and\nanomalies.[7]\nSam Altman points out that taking time to come up with an\nidea is not merely a better strategy in an absolute sense, but also\nlike an undervalued stock in that so few founders do it.There's comparatively little competition for the best ideas, because\nfew founders are willing to put in the time required to notice them.\nWhereas there is a great deal of competition for mediocre ideas,\nbecause when people make up startup ideas, they tend to make up the\nsame ones.[8]\nFor the computer hardware and software companies, summer jobs\nare the first phase of the recruiting funnel. But if you're good\nyou can skip the first phase. If you're good you'll have no trouble\ngetting hired by these companies when you graduate, regardless of\nhow you spent your summers.[9]\nThe empirical evidence suggests that if colleges want to help\ntheir students start startups, the best thing they can do is leave\nthem alone in the right way.[10]\nI'm speaking here of IT startups; in biotech things are different.[11]\nThis is an instance of a more general rule: focus on users,\nnot competitors. The most important information about competitors\nis what you learn via users anyway.[12]\nIn practice most successful startups have elements of both.\nAnd you can describe each strategy in terms of the other by adjusting\nthe boundaries of what you call the market. But it's useful to\nconsider these two ideas separately.[13]\nI almost hesitate to raise that point though. Startups are\nbusinesses; the point of a business is to make money; and with that\nadditional constraint, you can't expect you'll be able to spend all\nyour time working on what interests you most.[14]\nThe need has to be a strong one. You can retroactively\ndescribe any made-up idea as something you need. But do you really\nneed that recipe site or local event aggregator as much as Drew\nHouston needed Dropbox, or Brian Chesky and Joe Gebbia needed Airbnb?Quite often at YC I find myself asking founders \"Would you use this\nthing yourself, if you hadn't written it?\" and you'd be surprised\nhow often the answer is no.[15]\nPaul Buchheit points out that trying to sell something bad\ncan be a source of better ideas:\"The best technique I've found for dealing with YC companies that\nhave bad ideas is to tell them to go sell the product ASAP (before\nwasting time building it). Not only do they learn that nobody\nwants what they are building, they very often come back with a\nreal idea that they discovered in the process of trying to sell\nthe bad idea.\"[16]\nHere's a recipe that might produce the next Facebook, if\nyou're college students. If you have a connection to one of the\nmore powerful sororities at your school, approach the queen bees\nthereof and offer to be their personal IT consultants, building\nanything they could imagine needing in their social lives that\ndidn't already exist. Anything that got built this way would be\nvery promising, because such users are not just the most demanding\nbut also the perfect point to spread from.I have no idea whether this would work.[17]\nAnd the reason it used a TV for a monitor is that Steve Wozniak\nstarted out by solving his own problems. He, like most of his\npeers, couldn't afford a monitor.Thanks to Sam Altman, Mike Arrington, Paul Buchheit, John Collison,\nPatrick Collison, Garry Tan, and Harj Taggar for reading drafts of\nthis, and Marc Andreessen, Joe Gebbia, Reid Hoffman, Shel Kaphan,\nMike Moritz and Kevin Systrom for answering my questions about\nstartup history." }, { "path": "data/PaulGrahamEssayMedium/wealth.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nMay 2004\n(This essay was originally published in Hackers \n& Painters.)\nIf you wanted to get rich, how would you do it? I think your best\nbet would be to start or join a startup. That's been a \nreliable way to get rich for hundreds of years. The word \"startup\" \ndates from the 1960s, but what happens in one is \nvery similar to the venture-backed trading voyages of the\nMiddle Ages.Startups usually involve technology, so much so that the phrase\n\"high-tech startup\" is almost redundant. A startup is a small\ncompany that takes on a hard technical problem.Lots of people get rich knowing nothing more than that.\nYou don't have to know physics to be a good pitcher. But\nI think it could give you an edge to understand the underlying principles.\nWhy do startups have to be small? \nWill a startup inevitably stop being a startup as it\ngrows larger? \nAnd why do they so often work on\ndeveloping new technology? Why are there so many startups\nselling new drugs or computer software, and none selling corn oil\nor laundry detergent?The PropositionEconomically, you can think of a startup as a way to \ncompress your whole working life into a few years. Instead\nof working at a low intensity for forty years, you work as\nhard as you possibly can for four. This pays especially well\nin technology, where you earn a premium for working fast.Here is a brief sketch of the economic proposition. If you're\na good hacker in your mid twenties, you can\nget a job paying about $80,000 per year. So on average \nsuch a hacker must be\nable to do at least $80,000 worth of work per year for the \ncompany just to break even. You could probably\nwork twice as many hours as a corporate employee, and if\nyou focus you can probably get three times as much done in\nan hour. \n[1]\nYou should get another multiple of two, at\nleast, by eliminating the drag \nof the pointy-haired middle\nmanager who would be your boss in a big company.\nThen there is one more multiple: how much smarter are you\nthan your job description expects you to be?\nSuppose another multiple of three. Combine all these multipliers, and I'm\nclaiming you could be 36 times more \nproductive than you're expected to be in a random corporate\njob. \n[2]\n If a fairly good hacker is worth $80,000 a year at a \nbig company, then a smart\nhacker working very hard without any corporate\nbullshit to slow him down should be able to do work worth about\n$3 million a year.Like all back-of-the-envelope calculations, this one\nhas a lot of wiggle room. I wouldn't try to\ndefend the actual numbers. But I stand by the \nstructure of the calculation. I'm not claiming\nthe multiplier is precisely 36, but it is certainly more\nthan 10, and probably rarely as high as 100.If $3 million a year seems\nhigh, remember that we're talking about the limit case:\nthe case where you not only have zero leisure time\nbut indeed work so hard that you endanger your health.Startups are not magic. They don't change the laws of\nwealth creation. They just represent a point at the far end of the curve.\nThere is a conservation law at work here: if\nyou want to make a million dollars, you have to endure a \nmillion dollars' worth of pain. \nFor example, one way to\nmake a million dollars would be to work for the \nPost Office your whole life, and save every penny of your \nsalary. Imagine the stress of working for the Post \nOffice for fifty years. In a startup you compress all\nthis stress into three or four years. You do tend to get a \ncertain \nbulk discount if you buy the economy-size pain,\nbut you can't evade the fundamental conservation law.\nIf starting a startup were easy, everyone would do it.Millions, not BillionsIf $3 million a year seems high to some people, it will seem\nlow to others. Three million? \nHow do I get to be a billionaire, like Bill Gates?So let's get Bill Gates out of the way right now. It's not\na good idea to use famous rich people \nas examples, because the press only \nwrite about the very richest, and these tend to be outliers.\nBill Gates is a smart, determined, and hardworking man,\nbut you need more than\nthat to make as much money as he has. You also need to be\nvery lucky.There is a large random\nfactor in the success of any company. So the guys you end \nup reading about in the papers are the ones who are very \nsmart, totally dedicated, and win the lottery.\nCertainly Bill is smart and dedicated, but Microsoft also \nhappens to have been the beneficiary of one of the most spectacular\nblunders in the history of business: the licensing deal for\nDOS. No doubt Bill did \neverything he could to steer IBM into making that blunder, \nand he has done an excellent job of exploiting it, but if\nthere had been one person with a brain on IBM's side,\nMicrosoft's future would have been very different.\nMicrosoft at that stage had little leverage over IBM.\nThey were effectively a component supplier. If IBM had \nrequired an exclusive license, as they should have, Microsoft\nwould still have signed the deal. It would still have\nmeant a lot of money for them, and IBM\ncould easily have gotten an operating system elsewhere.Instead IBM ended up using all its power in the market\nto give Microsoft control of the PC standard. From \nthat point, all Microsoft had to do was execute. They\nnever had to bet the company on a bold decision. All they\nhad to do was play hardball with licensees and copy more\ninnovative products reasonably promptly.If IBM hadn't made this mistake, Microsoft would\nstill have been a successful company, but it\ncould not have grown so big so fast. \nBill Gates would be rich, but he'd be somewhere\nnear the bottom of the Forbes 400 with the other guys his age.There are a lot of ways to get\nrich, and this essay is about only one of them. This\nessay is about how to make money by creating wealth and\ngetting paid for it. There are plenty of other ways to \nget money, including chance, speculation, marriage, inheritance, \ntheft, extortion, fraud, monopoly,\ngraft, lobbying,\ncounterfeiting, and prospecting. Most of the greatest fortunes\nhave probably involved several of these.The advantage of creating wealth, as a way to get rich,\nis not just that it's more legitimate \n(many of the other methods are now illegal) \nbut that it's more\nstraightforward. You just have to do something people want.Money Is Not WealthIf you want to create wealth, it will help to understand what it is. \nWealth is not the same thing as money. \n[3]\n Wealth is as old as\nhuman history. Far older, in fact; ants have wealth. \nMoney is a comparatively recent invention.Wealth is the fundamental thing. Wealth is stuff we want: food, \nclothes, houses, cars, gadgets, travel to interesting places,\nand so on. You can have wealth without\nhaving money. If you had a magic machine that\ncould on command make you a car or cook you dinner or do your\nlaundry, or do anything else you wanted, you wouldn't need money.\nWhereas if you were in the middle of Antarctica, where there is\nnothing to buy, it wouldn't matter how much money you had.Wealth is what you want, not money. But if wealth is the important\nthing, why does everyone talk about making money? It is\na kind of shorthand: money is a way of moving wealth, and in practice\nthey are usually interchangeable. But they are not the same thing,\nand unless you plan to get rich by counterfeiting, talking about\nmaking money can make it harder to understand how to \nmake money.Money is a side effect of specialization.\nIn a specialized society, most of the\nthings you need, you can't make for yourself. If you want a potato\nor a pencil or a place to live, you have to get it from someone\nelse.How do you get the person who grows the potatoes to give you some?\nBy giving him something he wants in return. But you can't get\nvery far by trading things directly with the people who\nneed them. If you make violins, and none of the local\nfarmers wants one, how will you eat?The solution societies find, as they get more specialized, is to\nmake the trade into a two-step process. Instead of trading violins\ndirectly for potatoes, you trade violins for, say, silver, \nwhich you can then trade again for anything else you need. The\nintermediate stuff-- the medium of exchange-- can be anything that's\nrare and portable. Historically metals have been the most common,\nbut recently we've been using a medium of exchange, called the dollar,\nthat doesn't physically exist. It works as a medium of exchange,\nhowever, because its rarity \nis guaranteed by the U.S. Government.The advantage of a medium of exchange is that it makes trade work.\nThe disadvantage is that it tends to obscure what trade really\nmeans. People think that what a business does is make money.\nBut money is just the intermediate stage-- just\na shorthand-- for whatever people want.\nWhat most businesses really do is make \nwealth. They do something people want. \n[4]The Pie FallacyA surprising number of people retain from childhood the idea\nthat there is a fixed amount of wealth in the world. \nThere is, in any normal family, a fixed amount of money at \nany moment. But that's not the same thing.When wealth is talked about in this context, it is often\ndescribed as a pie. \"You can't make the pie larger,\"\nsay politicians.\nWhen you're\ntalking about the amount of money in one family's bank\naccount, or the amount available to a government from one\nyear's tax revenue, this is true. \nIf one person gets more, someone else has to get less.I can remember believing, as a child, that if a few\nrich people had all the money, it left less for everyone else.\nMany people seem to continue to believe something like this\nwell into adulthood. This fallacy is usually there in the \nbackground when you hear someone talking about how x percent\nof the population have y percent of the wealth. If you plan\nto start a startup, then whether you realize it or not, you're\nplanning to disprove the Pie Fallacy.What leads people astray here is the abstraction of\nmoney. Money is not wealth. It's\njust something we use to move wealth around.\nSo although there may be, in certain specific moments (like\nyour family, this month) a fixed amount of money available to\ntrade with other people for things you want,\nthere is not a fixed amount of wealth in the world. \nYou can make more wealth. Wealth has been getting created and\ndestroyed (but on balance, created) for all of human history.Suppose you own a beat-up old car. \nInstead of sitting on your butt next\nsummer, you could spend the time restoring your car to pristine condition.\nIn doing so you create wealth. The world is-- and\nyou specifically are-- one pristine old car the richer. And not\njust in some metaphorical way. If you sell your car,\nyou'll get more for it.In restoring your old car you have made yourself\nricher. You haven't made anyone else poorer. So there is\nobviously not a fixed pie. And in fact, when you look at \nit this way, you wonder why anyone would think there was. \n[5]Kids know, without knowing they know, that they can create\nwealth. If you need to give someone a present and don't\nhave any money, you make one. But kids are so bad at making\nthings that they consider home-made presents to be a distinct,\ninferior, sort of thing to store-bought ones-- a mere expression\nof the proverbial thought that counts. \nAnd indeed, the lumpy ashtrays\nwe made for our parents did not have much of a resale market.CraftsmenThe people most likely to grasp that wealth can be\ncreated are the ones who are good at making things, the craftsmen.\nTheir hand-made objects become store-bought ones. \nBut with the rise of industrialization there are fewer and\nfewer craftsmen. One of the biggest remaining groups is\ncomputer programmers.A programmer can sit down in front of a computer and\ncreate wealth. A good piece of software is, in itself, \na valuable thing.\nThere is no manufacturing to confuse the issue. Those\ncharacters you type \nare a complete, finished product.\nIf someone sat down and wrote a web\nbrowser that didn't suck (a fine idea, by the way), the world\nwould be that much richer.\n[5b]Everyone in a company works together to create\nwealth, in the sense of making more things people want.\nMany of the employees (e.g. the people in the mailroom or\nthe personnel department) work at one remove from the \nactual making of stuff. Not the programmers. They\nliterally think the product, one line at a time.\nAnd so it's clearer to programmers that wealth is something\nthat's made, rather than being distributed, like slices of a\npie, by some imaginary Daddy.It's also obvious to programmers that there are huge variations\nin the rate at which wealth is created. At Viaweb we had one\nprogrammer who was a sort of monster of productivity. \nI remember watching what he did one long day and estimating that\nhe had added several hundred thousand dollars\nto the market value of the company. \nA great programmer, on a roll, could \ncreate a million dollars worth of wealth in a couple weeks.\nA mediocre programmer over the same period will generate zero or\neven negative wealth (e.g. by introducing bugs).This is\nwhy so many of the best programmers are libertarians.\nIn our world, you sink or swim, and there are no excuses.\nWhen those far removed from the creation of wealth-- undergraduates,\nreporters, politicians-- hear\nthat the richest 5% of the people have \nhalf the total wealth, they tend to think injustice!\nAn experienced programmer would be more likely to think\nis that all? The top 5% of programmers\nprobably write 99% of the good software.Wealth can be created without being sold. Scientists, till\nrecently at least, effectively donated the wealth they \ncreated. We are all richer for knowing about penicillin,\nbecause we're less likely to die from infections. Wealth\nis whatever people want, and not dying is certainly something\nwe want. Hackers often donate their work by \nwriting open source software that anyone can use for free.\nI am much the richer for the operating system\nFreeBSD, which I'm running on the computer I'm using now,\nand so is Yahoo, which runs it on all their servers.What a Job IsIn industrialized countries, people belong to one institution or\nanother at least until their twenties. After all those years you get\nused to the idea of belonging to a group of people who all get up\nin the morning, go to some set of buildings, and do things that they\ndo not, ordinarily, enjoy doing. Belonging to such a group becomes\npart of your identity: name, age, role, institution.\nIf you have to introduce yourself, or\nsomeone else describes you, it will be as something like, John\nSmith, age 10, a student at such and such elementary school, or\nJohn Smith, age 20, a student at such and such college.When John Smith finishes school he is expected to get a job. And\nwhat getting a job seems to mean is joining another institution.\nSuperficially it's a lot like college. You pick the companies you\nwant to work for and apply to join them. If one likes you, you\nbecome a member of this new group. You get up in the morning and\ngo to a new set of buildings, and do things that you do not, ordinarily,\nenjoy doing. There are a few differences: life is not as much fun,\nand you get paid, instead of paying, as you did in college. But\nthe similarities feel greater than the differences. John Smith is\nnow John Smith, 22, a software developer at such and such corporation.In fact John Smith's\nlife has changed more than he realizes. Socially, a company\nlooks much like college, but the deeper you go into the\nunderlying reality, the more different it gets.What a company does, and has to do if it wants to continue to\nexist, is earn money. And the way most companies make money\nis by creating wealth. Companies can be so specialized that this\nsimilarity is concealed, but it is not only manufacturing \ncompanies that create wealth. A big component of wealth is\nlocation. \nRemember that magic machine that could\nmake you cars and cook you dinner and so on? It would not be\nso useful if it delivered your dinner to a random location\nin central Asia. \nIf wealth means what people want, companies that move\nthings also create wealth. Ditto for\nmany other kinds of companies that don't make anything\nphysical. Nearly all companies exist to do something people\nwant.And that's what you do, as well, when you go to work for a company.\nBut here there is another layer that tends to obscure the underlying\nreality. In a company, the work you do is averaged together with\na lot of other people's. \nYou may not even be aware you're doing something people\nwant. Your contribution may be indirect. But the company as a\nwhole must be giving people something they want, or they won't make\nany money. And if they are paying you x dollars a year, then on\naverage you must be contributing at least x dollars a year worth\nof work, or the company will be spending more than it makes,\nand will go out of business.Someone graduating from college thinks, and is told, that he needs\nto get a job, as if the important thing were becoming a member of \nan institution. A more direct way to put it would be: you need to\nstart doing something people want. You don't\nneed to\njoin a company to do that. All a company is is a group of people\nworking together to do something people want. It's doing something people\nwant that matters, not joining the group. \n[6]For most people the \nbest plan probably is to go to work for some existing\ncompany. But it is a good idea to understand what's happening \nwhen you do this. A job means doing something people want,\naveraged together with everyone else in that company.Working HarderThat averaging gets to be a problem.\nI think the single biggest problem afflicting large companies is the \ndifficulty of assigning a value to each person's work. \nFor the most part they punt. In a\nbig company you get paid a fairly predictable salary for working \nfairly hard. You're expected not to be obviously incompetent or\nlazy, but you're not expected to devote your whole life to your\nwork.It turns out, though, that there are economies of scale in how much of your\nlife you devote to your work. In the right kind of business, \nsomeone who really devoted himself to work could generate ten or\neven a hundred times as much wealth as an average\nemployee. A programmer, for example, instead of chugging along\nmaintaining and updating an existing piece of software, could write\na whole new piece of software, and with it create a new source of\nrevenue.Companies are not set up to reward people who want to do this. \nYou can't go to your boss and say, I'd like to start working ten\ntimes as hard, so will you please pay me ten times as much? For\none thing, the official fiction is that you are already working as\nhard as you can. But a more serious problem is that the company\nhas no way of measuring the value of your work.Salesmen are an exception. It's easy \nto measure how much revenue they generate, and they're\nusually paid a percentage of it. If a salesman wants to work harder,\nhe can just start doing it, and he will automatically\nget paid proportionally more.There is one other job besides sales where big companies can\nhire first-rate people: in the top management jobs. \nAnd for the same reason: their performance can\nbe measured. The top managers are\nheld responsible for the performance of the entire company.\nBecause an ordinary employee's performance can't usually\nbe measured, he is not expected to do\nmore than put in a solid effort. Whereas top management, like\nsalespeople, have to actually come up with the numbers.\nThe CEO of a company that tanks cannot plead that he put in \na solid effort. If the company does badly, he's done badly.A company that could pay all its employees so straightforwardly \nwould be enormously successful. Many employees would work harder\nif they could get paid for it. More importantly,\nsuch a company would attract people who wanted to work\nespecially hard. \nIt would crush its competitors.Unfortunately, companies can't pay everyone like salesmen. Salesmen\nwork alone. Most employees' work is tangled together. Suppose\na company makes some kind of consumer gadget. The \nengineers build a reliable gadget with all kinds of new features;\nthe industrial designers design a beautiful case for it; and then\nthe marketing people convince everyone that\nit's something they've got to have. How do you know how much of the\ngadget's sales are due to each group's efforts? Or, for that\nmatter, how much is due to the creators of past gadgets that gave\nthe company a reputation for quality? There's no way to \nuntangle all their contributions. Even if you could read the minds\nof the consumers, you'd find these factors were all blurred together.If you want to go faster, it's a problem to have your work\ntangled together with a large number of other people's. In a \nlarge group, your performance is not separately measurable-- and \nthe rest of the group slows you down.Measurement and LeverageTo get rich you need to get yourself in a situation with two\nthings, measurement and leverage. You need to be in a\nposition where your performance can be measured, or there is\nno way to get paid more by doing more. And you have to\nhave leverage, in the sense that the decisions you make have \na big effect.Measurement alone is not enough. An example of a job with\nmeasurement but not leverage is doing piecework in a\nsweatshop. Your performance is measured and you get paid \naccordingly, but you have no scope for decisions. The only\ndecision you get to make is how fast you work, and that\ncan probably only increase your earnings by a factor\nof two or three.An example of a job with both measurement and leverage would\nbe lead actor in a movie. Your performance can be measured in the\ngross of the movie. And you have leverage in the sense that your\nperformance can make or break it.CEOs also have both measurement and leverage. They're measured,\nin that the performance of the company is their performance.\nAnd they have leverage in that their decisions\nset the whole company moving in one direction or another.I think everyone who gets rich by their own efforts will be\nfound to be in a situation with measurement and leverage. \nEveryone I can think of does: CEOs, movie stars, \nhedge fund managers, professional athletes. A good hint to the\npresence of leverage is the possibility of failure.\nUpside must be balanced by downside, so if there is \nbig potential for gain there must also be a terrifying\npossibility of loss. CEOs, stars, fund managers, and athletes\nall live with the sword hanging over their heads;\nthe moment they start to suck, they're out. If you're in\na job that feels safe, you are not going to get rich,\nbecause if there is no danger there is almost certainly no leverage.But you don't have to become a CEO or a movie star to\nbe in a situation with measurement and leverage. All you \nneed to do is be part of a small group working on a\nhard problem.Smallness = MeasurementIf you can't measure the value of the work done by individual \nemployees, you can get close. You can measure the value\nof the work done by small groups.One level at which you can accurately measure the revenue\ngenerated by employees is at the level of the whole company. \nWhen the company is small, you are thereby fairly close to \nmeasuring the contributions of individual employees. A viable\nstartup might only have ten employees, which puts you within a\nfactor of ten of measuring individual effort.Starting or joining a startup is thus as close as most\npeople can get to saying to one's boss, I want to work ten times\nas hard, so please pay me ten times as much. There are two\ndifferences: you're not saying it to your boss, but directly to the\ncustomers (for whom your boss is only a proxy after all), and\nyou're not doing it individually, but along with a small group\nof other ambitious people.It will, ordinarily, be a group. Except in a few unusual kinds\nof work, like acting or writing books, you can't be a company \nof one person. \nAnd the people you work with had better be good, because it's their work that\nyours is going to be averaged with.A big company is like a giant galley driven by a thousand rowers.\nTwo things keep the speed of the\ngalley down. One is that individual rowers don't see any\nresult from working harder. \nThe other is that, in a group of a\nthousand people, the average rower is likely to be\npretty average.If you took ten people at random out of the big galley and\nput them in a boat by themselves, they could probably go \nfaster. They would have both carrot and stick to motivate \nthem. An energetic rower would be encouraged by the thought\nthat he could have a visible effect on the speed of\nthe boat. And if someone was lazy, the others would be more likely\nto notice and complain.But the real advantage of the ten-man boat shows when \nyou take the ten best rowers out of the big galley\nand put them in a boat together. They will have all\nthe extra motivation that comes from being in a small group.\nBut more importantly, by selecting that small a group\nyou can get the best rowers. Each one will be in\nthe top 1%. It's a much better deal for them to average \ntheir work together with a small group of their peers than to \naverage it with everyone.That's the real point of startups. Ideally, you are getting\ntogether with a group of other people who also want to work\na lot harder, and get paid a lot more, than they would in\na big company. And because startups tend to get founded \nby self-selecting groups of ambitious people who already \nknow one another (at least by reputation), the level of \nmeasurement is more precise than you get from smallness alone.\nA startup is not merely ten people, but ten people like you.Steve Jobs once said that the success or failure of a startup\ndepends on the first ten employees. I agree. If \nanything, it's more like the first five.\nBeing small is not, in itself, what makes startups kick butt, \nbut rather that small groups can be select.\nYou don't want small in the sense of a\nvillage, but small in the sense of an all-star team.The larger a group, the closer its average member will be to the average\nfor the population as a whole. So all other things being\nequal, a very able person in a big company is probably\ngetting a bad deal, because his performance is dragged down by\nthe overall lower performance of the others. Of course,\nall other things often are not equal: the able person may \nnot care about money, or may prefer the stability of a large\ncompany. But a very able person who does care about money\nwill ordinarily do better to go off and work with a small\ngroup of peers.Technology = LeverageStartups offer anyone a way to be in a situation with\nmeasurement and leverage.\nThey allow measurement because they're small,\nand they offer leverage because they\nmake money by inventing new technology.What is technology? It's technique. It's the way \nwe all do things. And when\nyou discover a new way to do things, its value is multiplied\nby all the people who use it. It is the proverbial fishing\nrod, rather than the fish. That's the difference between a\nstartup and a restaurant or a barber shop. You fry eggs or cut \nhair one customer at a time. Whereas if \nyou solve a technical problem that a lot of people care about,\nyou help everyone who uses your solution. \nThat's leverage.If you look at history, it seems that most people\nwho got rich by creating wealth did it by developing\nnew technology. You just can't fry eggs or cut hair fast enough.\nWhat made the Florentines rich in 1200 \nwas the discovery of new techniques for making the high-tech \nproduct of the time, fine woven cloth. What made the\nDutch rich in 1600 was the discovery of shipbuilding and\nnavigation techniques that enabled them to dominate the seas\nof the Far East.Fortunately there is a natural fit between smallness and\nsolving hard problems. The leading edge of technology moves\nfast. Technology that's valuable today could be worthless\nin a couple years. Small companies are more at home in this\nworld, because they don't have layers of bureaucracy to\nslow them down.\nAlso, technical advances tend to come from unorthodox approaches,\nand small companies are less constrained by convention.Big companies can develop technology. They just can't do it\nquickly. Their size makes them slow and prevents\nthem from rewarding employees for the extraordinary\neffort required. So in practice big companies only get to develop \ntechnology in fields where large capital requirements prevent startups from\ncompeting with them, like microprocessors, power plants, \nor passenger aircraft. And even in those fields they depend heavily\non startups for components and ideas.It's obvious that biotech or software startups exist to solve\nhard technical problems, but \nI think it will also be found to be true \nin businesses that don't seem to be about technology. McDonald's,\nfor example, grew big by designing a system, the McDonald's \nfranchise, that could then be reproduced at will all over the \nface of the earth. A McDonald's franchise is controlled by rules\nso precise that it is practically\na piece of software. Write once, run everywhere.\nDitto for Wal-Mart. Sam Walton got rich not by being a \nretailer, but by designing a new kind of store.Use difficulty as a guide not just in selecting the overall\naim of your company, but also at decision points along the way.\nAt Viaweb one of our rules of thumb was run upstairs.\nSuppose you are a little, nimble guy being chased by a big,\nfat, bully. You open a door and find yourself in a \nstaircase. Do you go up or down? I say up. The\nbully can probably run downstairs as fast as you can.\nGoing upstairs his bulk will be more of a disadvantage.\nRunning upstairs is hard for you but even harder for him.What this meant in practice was that we deliberately sought \nhard problems. If there were two features we could add to our\nsoftware, both equally valuable in proportion to their difficulty,\nwe'd always take the harder one. Not just because it was \nmore valuable, but because it was harder.\nWe delighted in forcing bigger, slower competitors\nto follow us over difficult ground.\nLike guerillas, startups prefer the difficult terrain of the\nmountains, where the troops of the central government\ncan't follow. I can remember times when we were just\nexhausted after wrestling all day with some horrible technical\nproblem. And I'd be delighted, because something that was \nhard for us would be impossible for our competitors.This is not just a good way to run a startup. It's what\na startup is.\nVenture capitalists know about this and have a phrase for it:\nbarriers to entry. If you go to a VC with a new \nidea and ask him to invest in it, one of the first things\nhe'll ask is, how hard would this be for someone else to \ndevelop? That is, how much difficult ground\nhave you put between yourself and potential pursuers? \n[7]\nAnd you had better have a convincing explanation of why \nyour technology would be hard to duplicate. Otherwise as\nsoon as some big company becomes aware of it, they'll make\ntheir own, and with their brand name, capital, and\ndistribution clout, they'll take away your market overnight.\nYou'd be like guerillas caught in the open field by regular\narmy forces.One way to put up barriers to entry is through patents. \nBut patents may not provide much protection. \nCompetitors commonly find ways to work around a patent.\nAnd if they can't, they \nmay simply violate it and invite you to sue them.\nA big company is not afraid to be sued; it's an everyday thing\nfor them. They'll make sure that suing them is expensive and\ntakes a long time.\nEver heard of Philo Farnsworth? He invented\ntelevision. The reason you've never\nheard of him is that his company was not the one to make\nmoney from it. \n[8]\nThe company that did was RCA, and\nFarnsworth's reward for his efforts was a decade of\npatent litigation.Here, as so often, the best defense is a good offense. If\nyou can develop technology that's simply too hard for\ncompetitors to duplicate, you don't need to rely on other\ndefenses. Start by picking a hard problem, and\nthen at every decision point, take the harder choice. \n[9]The Catch(es)If it were simply a matter of working harder than \nan ordinary employee and getting paid proportionately, it would\nobviously be a good deal to start a startup. Up to a point it\nwould be more fun. I don't think many people \nlike the slow pace of big companies, the interminable meetings,\nthe water-cooler conversations, the clueless middle managers,\nand so on.Unfortunately there are a couple catches. One is that you\ncan't choose the point on the curve that you want to inhabit.\nYou can't decide, for example, that you'd like to work just\ntwo or three times as hard, and get paid that much more. When\nyou're running a startup, your competitors decide how\nhard you work. And they pretty much all make the same decision:\nas hard as you possibly can.The other catch is that the payoff is only on average proportionate\nto your productivity. There is, as I said before, a large\nrandom multiplier in the success of any company. So in\npractice the deal is not that you're 30 times as productive and get \npaid 30 times as much. It is that you're 30 times as productive,\nand get paid between zero and a thousand times as much.\nIf the mean is 30x, the median is probably zero.\nMost startups tank, and not just the dogfood \nportals we all heard about during\nthe Internet Bubble. It's common for a startup\nto be developing a genuinely good product, take slightly\ntoo long to do it, run out of money, and have to shut down.A startup is like a mosquito. A bear can absorb a hit and a crab\nis armored against one, but a mosquito is designed for one thing:\nto score. No energy is wasted on defense. The defense of mosquitos, \nas a species, is that there are a lot of them, but this is little \nconsolation to the individual mosquito.Startups, like mosquitos, tend to be an all-or-nothing proposition.\nAnd you don't generally know which of the two you're going to\nget till the last minute. \nViaweb came close to tanking several times. Our trajectory\nwas like a sine wave. Fortunately we got bought at\nthe top of the cycle, but it was damned close. While we were\nvisiting Yahoo in California to talk about selling the company\nto them, we had to borrow a conference room to reassure\nan investor who was about to back out of a new round of funding \nthat we needed to stay alive.The all-or-nothing aspect of startups was not something we wanted.\nViaweb's hackers were all extremely risk-averse.\nIf there had been some way just to work super hard and get\npaid for it, without having a lottery mixed in, we would have\nbeen delighted. We would have much preferred a 100% chance of\n$1 million to a 20% chance of $10 million, even though \ntheoretically the second is worth twice as much. Unfortunately,\nthere is not currently any space in the business world where\nyou can get the first deal.The closest you can get is by\nselling your startup in the early stages, giving up upside \n(and risk) for a smaller but guaranteed payoff. We had a \nchance to do this, and stupidly, as we then thought, let it slip by.\nAfter that we became comically eager to sell.\nFor the next year or so,\nif anyone expressed the slightest curiosity about Viaweb\nwe would try to sell them the company. But there were no takers,\nso we had to keep going.It would have been a bargain to \nbuy us at an early stage, but companies doing acquisitions are not\nlooking for bargains. A company big enough to acquire \nstartups will be big enough to be fairly conservative, and \nwithin the company the people in charge of acquisitions will\nbe among the more conservative, because they are likely to be\nbusiness school types who joined the company late. \nThey would rather overpay for a safe choice. So\nit is easier to sell an established startup, even at a large\npremium, than an early-stage one.Get UsersI think it's a good idea to get bought, if you can. Running a\nbusiness is different from growing one.\nIt is just as well to let a big company take over once you reach \ncruising altitude. It's\nalso financially wiser, because selling allows you to diversify.\nWhat would you think of a financial advisor who put all his\nclient's assets into one volatile stock?How do you get bought? Mostly by doing the same things \nyou'd do if you didn't intend to sell the company. Being \nprofitable, for example. But getting bought is also an art\nin its own right, and one that we spent a lot of time trying\nto master.Potential buyers will\nalways delay if they can. The hard part about getting\nbought is getting them to act. For most people, the most powerful motivator\nis not the hope of gain, but the fear of loss. For potential\nacquirers, the most powerful motivator is the prospect that \none of their competitors will buy you. This, as we found, \ncauses CEOs to take red-eyes. \nThe second biggest is the worry that, if they don't buy you \nnow, you'll continue to grow rapidly and will cost more to\nacquire later, or even become a competitor.In both cases, what it all comes down to is users. \nYou'd think that a company about to buy you would do a lot of\nresearch and decide for themselves how valuable your technology\nwas. Not at all. What they go by is the number of users you\nhave.In effect, acquirers assume the customers know who has the\nbest technology. And this is not as stupid as it sounds. Users \nare the only real proof that you've created wealth. Wealth is \nwhat people want, and if people aren't using your software,\nmaybe it's not just because you're bad at marketing. Maybe it's\nbecause you haven't made what they want.Venture capitalists have a list of danger signs to watch out for.\nNear the top is the company run by techno-weenies who are \nobsessed with solving interesting technical problems, instead\nof making users happy. In a startup, you're not just trying to\nsolve problems. You're trying to solve problems that \nusers care about.So I think you should make users the test, just as \nacquirers do. Treat a startup as an optimization problem \nin which performance is measured by number of users. As anyone\nwho has tried to optimize software knows, the key is measurement.\nWhen you try to guess where your program is slow, and what would\nmake it faster, you almost always guess wrong.Number of users may not be the perfect test, but it will \nbe very close. It's what acquirers care about. It's what \nrevenues depend on. \nIt's what makes competitors unhappy.\nIt's what impresses reporters, and potential\nnew users. Certainly it's a better test than your a priori\nnotions of what problems are important to solve, no matter how\ntechnically adept you are.Among other things, treating a startup as an optimization\nproblem will help you avoid another\npitfall that VCs worry about, and rightly-- taking a long time\nto develop a product. Now we can recognize this as something\nhackers already know to avoid: premature optimization. Get a version \n1.0 out there as soon as you can. Until you have some users to\nmeasure, you're optimizing based on guesses.The ball you need to keep your eye on here is the underlying\nprinciple that wealth is what people want. If you plan to get \nrich by creating wealth, you have to know what people want. \nSo few businesses really pay attention to making customers happy.\nHow often do you walk into a store, or call a company on the\nphone, with a feeling of dread in the back of your mind?\nWhen you hear \"your call is important to us, please stay on\nthe line,\" do you think, oh good, now everything will be all right?A restaurant can afford to serve the occasional burnt dinner.\nBut in technology, you cook one thing and that's what everyone\neats. So any difference between what people want and what\nyou deliver is multiplied. \nYou please or annoy\ncustomers wholesale. The closer you can get to what they want,\nthe more wealth you generate.Wealth and PowerMaking wealth is not the only way to get rich. For most of\nhuman history it has not even been the most common. Until\na few centuries ago,\nthe main sources of wealth were mines, slaves and serfs,\nland, and cattle,\nand the only ways to acquire these rapidly were by inheritance,\nmarriage, conquest, or confiscation. \nNaturally wealth had a bad reputation.Two things changed. The first was the rule of law. For most of the world's\nhistory, if you did somehow accumulate a fortune, the ruler or his \nhenchmen \nwould find a way to steal it.\nBut in medieval Europe something new happened.\nA new class of merchants and manufacturers\nbegan to collect in towns. \n[10]\nTogether they were able to withstand the local feudal\nlord. So \nfor the first time in our history, the bullies stopped stealing the\nnerds' lunch money.\nThis was naturally a great incentive,\nand possibly indeed the main cause of the second big change,\nindustrialization.A great deal has been written about the causes of the Industrial \nRevolution. But surely a necessary, if not sufficient, condition\nwas that people who made fortunes be able to enjoy them in peace.\n[11]\nOne piece of evidence is what happened to countries\nthat tried to return to the old model, like the Soviet\nUnion, and to a lesser extent Britain under the labor\ngovernments of the 1960s and early 1970s. Take away the incentive\nof wealth, and technical innovation grinds to a halt.Remember what a startup is, economically: \na way of saying, I want to work faster. Instead of accumulating\nmoney slowly by being paid a regular wage for fifty years, I \nwant to get it over with as soon as possible. So governments\nthat forbid you to accumulate wealth are in effect decreeing\nthat you work slowly. They're willing to let you earn $3 million over\nfifty years, but they're not willing to let you work so hard that\nyou can do it in two. They are like\nthe corporate boss that you can't go to and say, I want to work\nten times as hard, so please pay me ten times a much.\nExcept this is not a boss you can escape by starting your own\ncompany.The problem with working slowly is not just that technical\ninnovation happens slowly. It's that it tends not to happen at all.\nIt's only when you're deliberately looking for hard problems,\nas a way to use speed to the greatest advantage, that you take\non this kind of project. Developing new technology is a \npain in the ass. It is, as Edison said, one percent \ninspiration and ninety-nine percent perspiration. \nWithout the incentive of wealth, no one wants to do it.\nEngineers will work on sexy projects like fighter planes and moon\nrockets for ordinary salaries, but more mundane technologies\nlike light bulbs or semiconductors have to be developed by entrepreneurs.Startups\nare not just something that happened in Silicon Valley in \nthe last couple decades. Since it became possible to\nget rich by creating wealth, everyone who has done it has\nused essentially the same recipe: measurement and leverage,\nwhere measurement comes from working with a small\ngroup, and leverage from developing new techniques.\nThe recipe was the same in Florence in 1200 as it is \nin Santa Clara today.Understanding this may help to answer an important question:\nwhy Europe grew so powerful.\nWas it something about the geography of \nEurope? Was it that Europeans are somehow racially superior?\nWas it their religion? The answer (or at least\nthe proximate cause) may be that the\nEuropeans \nrode on the crest of a powerful new idea: allowing those who\nmade a lot of money to keep it.Once you're allowed to do that, \npeople who want to get rich can do it by generating\nwealth instead of stealing it.\nThe resulting technological growth translates not only \ninto wealth but into military power. The theory that led to\nthe stealth plane was developed by a Soviet mathematician.\nBut because the Soviet Union didn't have a computer industry,\nit remained for them a theory;\nthey didn't have hardware capable of executing the calculations\nfast enough to design an actual airplane.In that respect the Cold War teaches the same lesson as\nWorld War II and, for that matter, most wars in recent history.\nDon't let a ruling\nclass of warriors and politicians squash the entrepreneurs.\nThe same recipe that makes individuals rich\nmakes countries powerful. Let the nerds keep their lunch\nmoney, and you rule the world.Notes[1]\nOne valuable thing you tend to get only in startups is\nuninterruptability. Different kinds of\nwork have different time quanta. Someone proofreading a\nmanuscript\ncould probably be interrupted every fifteen minutes\nwith little loss of productivity. But the time quantum for\nhacking is very long: it might take an hour just to load\na problem into your head. So the\ncost of having someone from personnel\ncall you about a form you forgot to fill out can be huge.This is why hackers give you such a baleful stare as they\nturn from their screen to answer your question. Inside\ntheir heads a giant house of cards is tottering.The mere possibility of being interrupted deters hackers\nfrom starting hard projects. This is why they\ntend to work late at night, and why it's next to impossible\nto write great software in a cubicle (except late at night).One great advantage of startups is that they don't yet have\nany of the people who interrupt you. There is no personnel\ndepartment, and thus no form nor anyone to call you about it.[2]\nFaced with the idea that people working for startups might be\n20 or 30 times as productive as those working for large companies,\nexecutives at large companies will naturally wonder, how could\nI get the people working for me to do that? The answer is\nsimple: pay them to.Internally most companies are run like Communist states.\nIf you believe in free markets, why not turn your company into one?Hypothesis: A company will be maximally profitable when each\nemployee is paid in proportion to the wealth they generate.[3]\nUntil recently even governments sometimes didn't grasp the\ndistinction between money and wealth. Adam\nSmith (Wealth of Nations, v:i) mentions several\nthat tried to preserve their\n\"wealth\" by forbidding the export of gold or silver.\nBut having more of the medium of exchange would not make\na country richer; if you have more money chasing the same\namount of material wealth, the only result is higher prices.[4]\nThere are many senses of the word \"wealth,\" not all of\nthem material. I'm not trying to make a deep philosophical\npoint here about which\nis the true kind. I'm writing about one specific,\nrather technical sense of the word \"wealth.\" What\npeople will give you money for.\nThis is an interesting sort of wealth to study, because\nit is the kind that prevents you from starving.\nAnd what people will give you money for depends on them,\nnot you.When you're starting a business,\nit's easy to slide into thinking that customers\nwant what you do. During the Internet Bubble I talked\nto a woman who, because she liked the outdoors, was\nstarting an \"outdoor portal.\" You know what\nkind of business you should start if you like\nthe outdoors? One to recover data from crashed hard disks.What's the connection? None at all. Which is precisely my point.\nIf you want\nto create wealth (in the narrow technical sense of not\nstarving) then you should be especially skeptical about any\nplan that centers on things you like doing.\nThat is where your idea of what's valuable is least\nlikely to coincide with other people's.[5]\nIn the average car restoration you probably do make everyone\nelse microscopically poorer, by doing a small amount of damage to\nthe environment. While environmental costs should be taken\ninto account, they don't\nmake wealth a zero-sum game. For example, if you repair\na machine that's broken because a part has come unscrewed,\nyou create wealth with no environmental cost.[5b]\nThis essay was written before Firefox.[6]\nMany people feel confused and depressed in\ntheir early twenties. Life seemed so much more fun in college.\nWell, of course it was. Don't be fooled by the surface similarities.\nYou've gone from guest to servant.\nIt's possible to have fun in this new world. \nAmong other things, you now get to go behind the doors that say\n\"authorized personnel only.\"\nBut the change is a shock at first, and all the worse\nif you're not consciously aware of it.[7]\nWhen VCs asked us how long it would take another startup\nto duplicate our software, we used to reply that they probably\nwouldn't be able to at all. I think this made us seem naive,\nor liars.[8]\nFew technologies have one clear inventor. So as\na rule, if you know the \"inventor\" of something\n(the telephone, the assembly line, the airplane, \nthe light bulb, the transistor) it is because their\ncompany made money from it, and the company's PR people worked\nhard to spread the story. If you don't know who invented\nsomething (the automobile, the television, the computer,\nthe jet engine, the laser), it's because other companies\nmade all the money.[9]\nThis is a good plan for life in general.\nIf you have two choices, choose the harder.\nIf you're trying to decide whether to go out running or\nsit home and watch TV, go running.\nProbably the reason this trick works so well is that\nwhen you have two choices and one is harder, the\nonly reason you're even considering the other is laziness.\nYou know in the back of your mind what's the right thing\nto do, and this trick merely forces you to acknowledge it.[10]\nIt is probably no accident that the middle class\nfirst appeared in northern Italy and the low countries,\nwhere there were no strong central governments. These two\nregions were the richest of their time and became the twin\ncenters from which Renaissance civilization radiated.\nIf they no longer play that role, it is because\nother places, like the United States, have been truer to the\nprinciples they discovered.[11]\nIt may indeed be a sufficient condition. But if so, why didn't\nthe Industrial Revolution happen earlier? Two possible (and\nnot incompatible) answers: (a) It did. \nThe Industrial Revolution was one in a series.\n(b) Because in medieval towns, monopolies\nand guild regulations initially slowed the development of new means\nof production.\n\nComment on this essay." }, { "path": "data/PaulGrahamEssayMedium/worked.txt", "content": "February 2021Before college the two main things I worked on, outside of school,\r\nwere writing and programming. I didn't write essays. I wrote what\r\nbeginning writers were supposed to write then, and probably still\r\nare: short stories. My stories were awful. They had hardly any plot,\r\njust characters with strong feelings, which I imagined made them\r\ndeep.The first programs I tried writing were on the IBM 1401 that our\r\nschool district used for what was then called \"data processing.\"\r\nThis was in 9th grade, so I was 13 or 14. The school district's\r\n1401 happened to be in the basement of our junior high school, and\r\nmy friend Rich Draves and I got permission to use it. It was like\r\na mini Bond villain's lair down there, with all these alien-looking\r\nmachines — CPU, disk drives, printer, card reader — sitting up\r\non a raised floor under bright fluorescent lights.The language we used was an early version of Fortran. You had to\r\ntype programs on punch cards, then stack them in the card reader\r\nand press a button to load the program into memory and run it. The\r\nresult would ordinarily be to print something on the spectacularly\r\nloud printer.I was puzzled by the 1401. I couldn't figure out what to do with\r\nit. And in retrospect there's not much I could have done with it.\r\nThe only form of input to programs was data stored on punched cards,\r\nand I didn't have any data stored on punched cards. The only other\r\noption was to do things that didn't rely on any input, like calculate\r\napproximations of pi, but I didn't know enough math to do anything\r\ninteresting of that type. So I'm not surprised I can't remember any\r\nprograms I wrote, because they can't have done much. My clearest\r\nmemory is of the moment I learned it was possible for programs not\r\nto terminate, when one of mine didn't. On a machine without\r\ntime-sharing, this was a social as well as a technical error, as\r\nthe data center manager's expression made clear.With microcomputers, everything changed. Now you could have a\r\ncomputer sitting right in front of you, on a desk, that could respond\r\nto your keystrokes as it was running instead of just churning through\r\na stack of punch cards and then stopping. \r\n[1]The first of my friends to get a microcomputer built it himself.\r\nIt was sold as a kit by Heathkit. I remember vividly how impressed\r\nand envious I felt watching him sitting in front of it, typing\r\nprograms right into the computer.Computers were expensive in those days and it took me years of\r\nnagging before I convinced my father to buy one, a TRS-80, in about\r\n1980. The gold standard then was the Apple II, but a TRS-80 was\r\ngood enough. This was when I really started programming. I wrote\r\nsimple games, a program to predict how high my model rockets would\r\nfly, and a word processor that my father used to write at least one\r\nbook. There was only room in memory for about 2 pages of text, so\r\nhe'd write 2 pages at a time and then print them out, but it was a\r\nlot better than a typewriter.Though I liked programming, I didn't plan to study it in college.\r\nIn college I was going to study philosophy, which sounded much more\r\npowerful. It seemed, to my naive high school self, to be the study\r\nof the ultimate truths, compared to which the things studied in\r\nother fields would be mere domain knowledge. What I discovered when\r\nI got to college was that the other fields took up so much of the\r\nspace of ideas that there wasn't much left for these supposed\r\nultimate truths. All that seemed left for philosophy were edge cases\r\nthat people in other fields felt could safely be ignored.I couldn't have put this into words when I was 18. All I knew at\r\nthe time was that I kept taking philosophy courses and they kept\r\nbeing boring. So I decided to switch to AI.AI was in the air in the mid 1980s, but there were two things\r\nespecially that made me want to work on it: a novel by Heinlein\r\ncalled The Moon is a Harsh Mistress, which featured an intelligent\r\ncomputer called Mike, and a PBS documentary that showed Terry\r\nWinograd using SHRDLU. I haven't tried rereading The Moon is a Harsh\r\nMistress, so I don't know how well it has aged, but when I read it\r\nI was drawn entirely into its world. It seemed only a matter of\r\ntime before we'd have Mike, and when I saw Winograd using SHRDLU,\r\nit seemed like that time would be a few years at most. All you had\r\nto do was teach SHRDLU more words.There weren't any classes in AI at Cornell then, not even graduate\r\nclasses, so I started trying to teach myself. Which meant learning\r\nLisp, since in those days Lisp was regarded as the language of AI.\r\nThe commonly used programming languages then were pretty primitive,\r\nand programmers' ideas correspondingly so. The default language at\r\nCornell was a Pascal-like language called PL/I, and the situation\r\nwas similar elsewhere. Learning Lisp expanded my concept of a program\r\nso fast that it was years before I started to have a sense of where\r\nthe new limits were. This was more like it; this was what I had\r\nexpected college to do. It wasn't happening in a class, like it was\r\nsupposed to, but that was ok. For the next couple years I was on a\r\nroll. I knew what I was going to do.For my undergraduate thesis, I reverse-engineered SHRDLU. My God\r\ndid I love working on that program. It was a pleasing bit of code,\r\nbut what made it even more exciting was my belief — hard to imagine\r\nnow, but not unique in 1985 — that it was already climbing the\r\nlower slopes of intelligence.I had gotten into a program at Cornell that didn't make you choose\r\na major. You could take whatever classes you liked, and choose\r\nwhatever you liked to put on your degree. I of course chose \"Artificial\r\nIntelligence.\" When I got the actual physical diploma, I was dismayed\r\nto find that the quotes had been included, which made them read as\r\nscare-quotes. At the time this bothered me, but now it seems amusingly\r\naccurate, for reasons I was about to discover.I applied to 3 grad schools: MIT and Yale, which were renowned for\r\nAI at the time, and Harvard, which I'd visited because Rich Draves\r\nwent there, and was also home to Bill Woods, who'd invented the\r\ntype of parser I used in my SHRDLU clone. Only Harvard accepted me,\r\nso that was where I went.I don't remember the moment it happened, or if there even was a\r\nspecific moment, but during the first year of grad school I realized\r\nthat AI, as practiced at the time, was a hoax. By which I mean the\r\nsort of AI in which a program that's told \"the dog is sitting on\r\nthe chair\" translates this into some formal representation and adds\r\nit to the list of things it knows.What these programs really showed was that there's a subset of\r\nnatural language that's a formal language. But a very proper subset.\r\nIt was clear that there was an unbridgeable gap between what they\r\ncould do and actually understanding natural language. It was not,\r\nin fact, simply a matter of teaching SHRDLU more words. That whole\r\nway of doing AI, with explicit data structures representing concepts,\r\nwas not going to work. Its brokenness did, as so often happens,\r\ngenerate a lot of opportunities to write papers about various\r\nband-aids that could be applied to it, but it was never going to\r\nget us Mike.So I looked around to see what I could salvage from the wreckage\r\nof my plans, and there was Lisp. I knew from experience that Lisp\r\nwas interesting for its own sake and not just for its association\r\nwith AI, even though that was the main reason people cared about\r\nit at the time. So I decided to focus on Lisp. In fact, I decided\r\nto write a book about Lisp hacking. It's scary to think how little\r\nI knew about Lisp hacking when I started writing that book. But\r\nthere's nothing like writing a book about something to help you\r\nlearn it. The book, On Lisp, wasn't published till 1993, but I wrote\r\nmuch of it in grad school.Computer Science is an uneasy alliance between two halves, theory\r\nand systems. The theory people prove things, and the systems people\r\nbuild things. I wanted to build things. I had plenty of respect for\r\ntheory — indeed, a sneaking suspicion that it was the more admirable\r\nof the two halves — but building things seemed so much more exciting.The problem with systems work, though, was that it didn't last.\r\nAny program you wrote today, no matter how good, would be obsolete\r\nin a couple decades at best. People might mention your software in\r\nfootnotes, but no one would actually use it. And indeed, it would\r\nseem very feeble work. Only people with a sense of the history of\r\nthe field would even realize that, in its time, it had been good.There were some surplus Xerox Dandelions floating around the computer\r\nlab at one point. Anyone who wanted one to play around with could\r\nhave one. I was briefly tempted, but they were so slow by present\r\nstandards; what was the point? No one else wanted one either, so\r\noff they went. That was what happened to systems work.I wanted not just to build things, but to build things that would\r\nlast.In this dissatisfied state I went in 1988 to visit Rich Draves at\r\nCMU, where he was in grad school. One day I went to visit the\r\nCarnegie Institute, where I'd spent a lot of time as a kid. While\r\nlooking at a painting there I realized something that might seem\r\nobvious, but was a big surprise to me. There, right on the wall,\r\nwas something you could make that would last. Paintings didn't\r\nbecome obsolete. Some of the best ones were hundreds of years old.And moreover this was something you could make a living doing. Not\r\nas easily as you could by writing software, of course, but I thought\r\nif you were really industrious and lived really cheaply, it had to\r\nbe possible to make enough to survive. And as an artist you could\r\nbe truly independent. You wouldn't have a boss, or even need to get\r\nresearch funding.I had always liked looking at paintings. Could I make them? I had\r\nno idea. I'd never imagined it was even possible. I knew intellectually\r\nthat people made art — that it didn't just appear spontaneously\r\n— but it was as if the people who made it were a different species.\r\nThey either lived long ago or were mysterious geniuses doing strange\r\nthings in profiles in Life magazine. The idea of actually being\r\nable to make art, to put that verb before that noun, seemed almost\r\nmiraculous.That fall I started taking art classes at Harvard. Grad students\r\ncould take classes in any department, and my advisor, Tom Cheatham,\r\nwas very easy going. If he even knew about the strange classes I\r\nwas taking, he never said anything.So now I was in a PhD program in computer science, yet planning to\r\nbe an artist, yet also genuinely in love with Lisp hacking and\r\nworking away at On Lisp. In other words, like many a grad student,\r\nI was working energetically on multiple projects that were not my\r\nthesis.I didn't see a way out of this situation. I didn't want to drop out\r\nof grad school, but how else was I going to get out? I remember\r\nwhen my friend Robert Morris got kicked out of Cornell for writing\r\nthe internet worm of 1988, I was envious that he'd found such a\r\nspectacular way to get out of grad school.Then one day in April 1990 a crack appeared in the wall. I ran into\r\nprofessor Cheatham and he asked if I was far enough along to graduate\r\nthat June. I didn't have a word of my dissertation written, but in\r\nwhat must have been the quickest bit of thinking in my life, I\r\ndecided to take a shot at writing one in the 5 weeks or so that\r\nremained before the deadline, reusing parts of On Lisp where I\r\ncould, and I was able to respond, with no perceptible delay \"Yes,\r\nI think so. I'll give you something to read in a few days.\"I picked applications of continuations as the topic. In retrospect\r\nI should have written about macros and embedded languages. There's\r\na whole world there that's barely been explored. But all I wanted\r\nwas to get out of grad school, and my rapidly written dissertation\r\nsufficed, just barely.Meanwhile I was applying to art schools. I applied to two: RISD in\r\nthe US, and the Accademia di Belli Arti in Florence, which, because\r\nit was the oldest art school, I imagined would be good. RISD accepted\r\nme, and I never heard back from the Accademia, so off to Providence\r\nI went.I'd applied for the BFA program at RISD, which meant in effect that\r\nI had to go to college again. This was not as strange as it sounds,\r\nbecause I was only 25, and art schools are full of people of different\r\nages. RISD counted me as a transfer sophomore and said I had to do\r\nthe foundation that summer. The foundation means the classes that\r\neveryone has to take in fundamental subjects like drawing, color,\r\nand design.Toward the end of the summer I got a big surprise: a letter from\r\nthe Accademia, which had been delayed because they'd sent it to\r\nCambridge England instead of Cambridge Massachusetts, inviting me\r\nto take the entrance exam in Florence that fall. This was now only\r\nweeks away. My nice landlady let me leave my stuff in her attic. I\r\nhad some money saved from consulting work I'd done in grad school;\r\nthere was probably enough to last a year if I lived cheaply. Now\r\nall I had to do was learn Italian.Only stranieri (foreigners) had to take this entrance exam. In\r\nretrospect it may well have been a way of excluding them, because\r\nthere were so many stranieri attracted by the idea of studying\r\nart in Florence that the Italian students would otherwise have been\r\noutnumbered. I was in decent shape at painting and drawing from the\r\nRISD foundation that summer, but I still don't know how I managed\r\nto pass the written exam. I remember that I answered the essay\r\nquestion by writing about Cezanne, and that I cranked up the\r\nintellectual level as high as I could to make the most of my limited\r\nvocabulary. \r\n[2]I'm only up to age 25 and already there are such conspicuous patterns.\r\nHere I was, yet again about to attend some august institution in\r\nthe hopes of learning about some prestigious subject, and yet again\r\nabout to be disappointed. The students and faculty in the painting\r\ndepartment at the Accademia were the nicest people you could imagine,\r\nbut they had long since arrived at an arrangement whereby the\r\nstudents wouldn't require the faculty to teach anything, and in\r\nreturn the faculty wouldn't require the students to learn anything.\r\nAnd at the same time all involved would adhere outwardly to the\r\nconventions of a 19th century atelier. We actually had one of those\r\nlittle stoves, fed with kindling, that you see in 19th century\r\nstudio paintings, and a nude model sitting as close to it as possible\r\nwithout getting burned. Except hardly anyone else painted her besides\r\nme. The rest of the students spent their time chatting or occasionally\r\ntrying to imitate things they'd seen in American art magazines.Our model turned out to live just down the street from me. She made\r\na living from a combination of modelling and making fakes for a\r\nlocal antique dealer. She'd copy an obscure old painting out of a\r\nbook, and then he'd take the copy and maltreat it to make it look\r\nold. \r\n[3]While I was a student at the Accademia I started painting still\r\nlives in my bedroom at night. These paintings were tiny, because\r\nthe room was, and because I painted them on leftover scraps of\r\ncanvas, which was all I could afford at the time. Painting still\r\nlives is different from painting people, because the subject, as\r\nits name suggests, can't move. People can't sit for more than about\r\n15 minutes at a time, and when they do they don't sit very still.\r\nSo the traditional m.o. for painting people is to know how to paint\r\na generic person, which you then modify to match the specific person\r\nyou're painting. Whereas a still life you can, if you want, copy\r\npixel by pixel from what you're seeing. You don't want to stop\r\nthere, of course, or you get merely photographic accuracy, and what\r\nmakes a still life interesting is that it's been through a head.\r\nYou want to emphasize the visual cues that tell you, for example,\r\nthat the reason the color changes suddenly at a certain point is\r\nthat it's the edge of an object. By subtly emphasizing such things\r\nyou can make paintings that are more realistic than photographs not\r\njust in some metaphorical sense, but in the strict information-theoretic\r\nsense. \r\n[4]I liked painting still lives because I was curious about what I was\r\nseeing. In everyday life, we aren't consciously aware of much we're\r\nseeing. Most visual perception is handled by low-level processes\r\nthat merely tell your brain \"that's a water droplet\" without telling\r\nyou details like where the lightest and darkest points are, or\r\n\"that's a bush\" without telling you the shape and position of every\r\nleaf. This is a feature of brains, not a bug. In everyday life it\r\nwould be distracting to notice every leaf on every bush. But when\r\nyou have to paint something, you have to look more closely, and\r\nwhen you do there's a lot to see. You can still be noticing new\r\nthings after days of trying to paint something people usually take\r\nfor granted, just as you can after\r\ndays of trying to write an essay about something people usually\r\ntake for granted.This is not the only way to paint. I'm not 100% sure it's even a\r\ngood way to paint. But it seemed a good enough bet to be worth\r\ntrying.Our teacher, professor Ulivi, was a nice guy. He could see I worked\r\nhard, and gave me a good grade, which he wrote down in a sort of\r\npassport each student had. But the Accademia wasn't teaching me\r\nanything except Italian, and my money was running out, so at the\r\nend of the first year I went back to the US.I wanted to go back to RISD, but I was now broke and RISD was very\r\nexpensive, so I decided to get a job for a year and then return to\r\nRISD the next fall. I got one at a company called Interleaf, which\r\nmade software for creating documents. You mean like Microsoft Word?\r\nExactly. That was how I learned that low end software tends to eat\r\nhigh end software. But Interleaf still had a few years to live yet.\r\n[5]Interleaf had done something pretty bold. Inspired by Emacs, they'd\r\nadded a scripting language, and even made the scripting language a\r\ndialect of Lisp. Now they wanted a Lisp hacker to write things in\r\nit. This was the closest thing I've had to a normal job, and I\r\nhereby apologize to my boss and coworkers, because I was a bad\r\nemployee. Their Lisp was the thinnest icing on a giant C cake, and\r\nsince I didn't know C and didn't want to learn it, I never understood\r\nmost of the software. Plus I was terribly irresponsible. This was\r\nback when a programming job meant showing up every day during certain\r\nworking hours. That seemed unnatural to me, and on this point the\r\nrest of the world is coming around to my way of thinking, but at\r\nthe time it caused a lot of friction. Toward the end of the year I\r\nspent much of my time surreptitiously working on On Lisp, which I\r\nhad by this time gotten a contract to publish.The good part was that I got paid huge amounts of money, especially\r\nby art student standards. In Florence, after paying my part of the\r\nrent, my budget for everything else had been $7 a day. Now I was\r\ngetting paid more than 4 times that every hour, even when I was\r\njust sitting in a meeting. By living cheaply I not only managed to\r\nsave enough to go back to RISD, but also paid off my college loans.I learned some useful things at Interleaf, though they were mostly\r\nabout what not to do. I learned that it's better for technology\r\ncompanies to be run by product people than sales people (though\r\nsales is a real skill and people who are good at it are really good\r\nat it), that it leads to bugs when code is edited by too many people,\r\nthat cheap office space is no bargain if it's depressing, that\r\nplanned meetings are inferior to corridor conversations, that big,\r\nbureaucratic customers are a dangerous source of money, and that\r\nthere's not much overlap between conventional office hours and the\r\noptimal time for hacking, or conventional offices and the optimal\r\nplace for it.But the most important thing I learned, and which I used in both\r\nViaweb and Y Combinator, is that the low end eats the high end:\r\nthat it's good to be the \"entry level\" option, even though that\r\nwill be less prestigious, because if you're not, someone else will\r\nbe, and will squash you against the ceiling. Which in turn means\r\nthat prestige is a danger sign.When I left to go back to RISD the next fall, I arranged to do\r\nfreelance work for the group that did projects for customers, and\r\nthis was how I survived for the next several years. When I came\r\nback to visit for a project later on, someone told me about a new\r\nthing called HTML, which was, as he described it, a derivative of\r\nSGML. Markup language enthusiasts were an occupational hazard at\r\nInterleaf and I ignored him, but this HTML thing later became a big\r\npart of my life.In the fall of 1992 I moved back to Providence to continue at RISD.\r\nThe foundation had merely been intro stuff, and the Accademia had\r\nbeen a (very civilized) joke. Now I was going to see what real art\r\nschool was like. But alas it was more like the Accademia than not.\r\nBetter organized, certainly, and a lot more expensive, but it was\r\nnow becoming clear that art school did not bear the same relationship\r\nto art that medical school bore to medicine. At least not the\r\npainting department. The textile department, which my next door\r\nneighbor belonged to, seemed to be pretty rigorous. No doubt\r\nillustration and architecture were too. But painting was post-rigorous.\r\nPainting students were supposed to express themselves, which to the\r\nmore worldly ones meant to try to cook up some sort of distinctive\r\nsignature style.A signature style is the visual equivalent of what in show business\r\nis known as a \"schtick\": something that immediately identifies the\r\nwork as yours and no one else's. For example, when you see a painting\r\nthat looks like a certain kind of cartoon, you know it's by Roy\r\nLichtenstein. So if you see a big painting of this type hanging in\r\nthe apartment of a hedge fund manager, you know he paid millions\r\nof dollars for it. That's not always why artists have a signature\r\nstyle, but it's usually why buyers pay a lot for such work.\r\n[6]There were plenty of earnest students too: kids who \"could draw\"\r\nin high school, and now had come to what was supposed to be the\r\nbest art school in the country, to learn to draw even better. They\r\ntended to be confused and demoralized by what they found at RISD,\r\nbut they kept going, because painting was what they did. I was not\r\none of the kids who could draw in high school, but at RISD I was\r\ndefinitely closer to their tribe than the tribe of signature style\r\nseekers.I learned a lot in the color class I took at RISD, but otherwise I\r\nwas basically teaching myself to paint, and I could do that for\r\nfree. So in 1993 I dropped out. I hung around Providence for a bit,\r\nand then my college friend Nancy Parmet did me a big favor. A\r\nrent-controlled apartment in a building her mother owned in New\r\nYork was becoming vacant. Did I want it? It wasn't much more than\r\nmy current place, and New York was supposed to be where the artists\r\nwere. So yes, I wanted it!\r\n[7]Asterix comics begin by zooming in on a tiny corner of Roman Gaul\r\nthat turns out not to be controlled by the Romans. You can do\r\nsomething similar on a map of New York City: if you zoom in on the\r\nUpper East Side, there's a tiny corner that's not rich, or at least\r\nwasn't in 1993. It's called Yorkville, and that was my new home.\r\nNow I was a New York artist — in the strictly technical sense of\r\nmaking paintings and living in New York.I was nervous about money, because I could sense that Interleaf was\r\non the way down. Freelance Lisp hacking work was very rare, and I\r\ndidn't want to have to program in another language, which in those\r\ndays would have meant C++ if I was lucky. So with my unerring nose\r\nfor financial opportunity, I decided to write another book on Lisp.\r\nThis would be a popular book, the sort of book that could be used\r\nas a textbook. I imagined myself living frugally off the royalties\r\nand spending all my time painting. (The painting on the cover of\r\nthis book, ANSI Common Lisp, is one that I painted around this\r\ntime.)The best thing about New York for me was the presence of Idelle and\r\nJulian Weber. Idelle Weber was a painter, one of the early\r\nphotorealists, and I'd taken her painting class at Harvard. I've\r\nnever known a teacher more beloved by her students. Large numbers\r\nof former students kept in touch with her, including me. After I\r\nmoved to New York I became her de facto studio assistant.She liked to paint on big, square canvases, 4 to 5 feet on a side.\r\nOne day in late 1994 as I was stretching one of these monsters there\r\nwas something on the radio about a famous fund manager. He wasn't\r\nthat much older than me, and was super rich. The thought suddenly\r\noccurred to me: why don't I become rich? Then I'll be able to work\r\non whatever I want.Meanwhile I'd been hearing more and more about this new thing called\r\nthe World Wide Web. Robert Morris showed it to me when I visited\r\nhim in Cambridge, where he was now in grad school at Harvard. It\r\nseemed to me that the web would be a big deal. I'd seen what graphical\r\nuser interfaces had done for the popularity of microcomputers. It\r\nseemed like the web would do the same for the internet.If I wanted to get rich, here was the next train leaving the station.\r\nI was right about that part. What I got wrong was the idea. I decided\r\nwe should start a company to put art galleries online. I can't\r\nhonestly say, after reading so many Y Combinator applications, that\r\nthis was the worst startup idea ever, but it was up there. Art\r\ngalleries didn't want to be online, and still don't, not the fancy\r\nones. That's not how they sell. I wrote some software to generate\r\nweb sites for galleries, and Robert wrote some to resize images and\r\nset up an http server to serve the pages. Then we tried to sign up\r\ngalleries. To call this a difficult sale would be an understatement.\r\nIt was difficult to give away. A few galleries let us make sites\r\nfor them for free, but none paid us.Then some online stores started to appear, and I realized that\r\nexcept for the order buttons they were identical to the sites we'd\r\nbeen generating for galleries. This impressive-sounding thing called\r\nan \"internet storefront\" was something we already knew how to build.So in the summer of 1995, after I submitted the camera-ready copy\r\nof ANSI Common Lisp to the publishers, we started trying to write\r\nsoftware to build online stores. At first this was going to be\r\nnormal desktop software, which in those days meant Windows software.\r\nThat was an alarming prospect, because neither of us knew how to\r\nwrite Windows software or wanted to learn. We lived in the Unix\r\nworld. But we decided we'd at least try writing a prototype store\r\nbuilder on Unix. Robert wrote a shopping cart, and I wrote a new\r\nsite generator for stores — in Lisp, of course.We were working out of Robert's apartment in Cambridge. His roommate\r\nwas away for big chunks of time, during which I got to sleep in his\r\nroom. For some reason there was no bed frame or sheets, just a\r\nmattress on the floor. One morning as I was lying on this mattress\r\nI had an idea that made me sit up like a capital L. What if we ran\r\nthe software on the server, and let users control it by clicking\r\non links? Then we'd never have to write anything to run on users'\r\ncomputers. We could generate the sites on the same server we'd serve\r\nthem from. Users wouldn't need anything more than a browser.This kind of software, known as a web app, is common now, but at\r\nthe time it wasn't clear that it was even possible. To find out,\r\nwe decided to try making a version of our store builder that you\r\ncould control through the browser. A couple days later, on August\r\n12, we had one that worked. The UI was horrible, but it proved you\r\ncould build a whole store through the browser, without any client\r\nsoftware or typing anything into the command line on the server.Now we felt like we were really onto something. I had visions of a\r\nwhole new generation of software working this way. You wouldn't\r\nneed versions, or ports, or any of that crap. At Interleaf there\r\nhad been a whole group called Release Engineering that seemed to\r\nbe at least as big as the group that actually wrote the software.\r\nNow you could just update the software right on the server.We started a new company we called Viaweb, after the fact that our\r\nsoftware worked via the web, and we got $10,000 in seed funding\r\nfrom Idelle's husband Julian. In return for that and doing the\r\ninitial legal work and giving us business advice, we gave him 10%\r\nof the company. Ten years later this deal became the model for Y\r\nCombinator's. We knew founders needed something like this, because\r\nwe'd needed it ourselves.At this stage I had a negative net worth, because the thousand\r\ndollars or so I had in the bank was more than counterbalanced by\r\nwhat I owed the government in taxes. (Had I diligently set aside\r\nthe proper proportion of the money I'd made consulting for Interleaf?\r\nNo, I had not.) So although Robert had his graduate student stipend,\r\nI needed that seed funding to live on.We originally hoped to launch in September, but we got more ambitious\r\nabout the software as we worked on it. Eventually we managed to\r\nbuild a WYSIWYG site builder, in the sense that as you were creating\r\npages, they looked exactly like the static ones that would be\r\ngenerated later, except that instead of leading to static pages,\r\nthe links all referred to closures stored in a hash table on the\r\nserver.It helped to have studied art, because the main goal of an online\r\nstore builder is to make users look legit, and the key to looking\r\nlegit is high production values. If you get page layouts and fonts\r\nand colors right, you can make a guy running a store out of his\r\nbedroom look more legit than a big company.(If you're curious why my site looks so old-fashioned, it's because\r\nit's still made with this software. It may look clunky today, but\r\nin 1996 it was the last word in slick.)In September, Robert rebelled. \"We've been working on this for a\r\nmonth,\" he said, \"and it's still not done.\" This is funny in\r\nretrospect, because he would still be working on it almost 3 years\r\nlater. But I decided it might be prudent to recruit more programmers,\r\nand I asked Robert who else in grad school with him was really good.\r\nHe recommended Trevor Blackwell, which surprised me at first, because\r\nat that point I knew Trevor mainly for his plan to reduce everything\r\nin his life to a stack of notecards, which he carried around with\r\nhim. But Rtm was right, as usual. Trevor turned out to be a\r\nfrighteningly effective hacker.It was a lot of fun working with Robert and Trevor. They're the two\r\nmost independent-minded people \r\nI know, and in completely different\r\nways. If you could see inside Rtm's brain it would look like a\r\ncolonial New England church, and if you could see inside Trevor's\r\nit would look like the worst excesses of Austrian Rococo.We opened for business, with 6 stores, in January 1996. It was just\r\nas well we waited a few months, because although we worried we were\r\nlate, we were actually almost fatally early. There was a lot of\r\ntalk in the press then about ecommerce, but not many people actually\r\nwanted online stores.\r\n[8]There were three main parts to the software: the editor, which\r\npeople used to build sites and which I wrote, the shopping cart,\r\nwhich Robert wrote, and the manager, which kept track of orders and\r\nstatistics, and which Trevor wrote. In its time, the editor was one\r\nof the best general-purpose site builders. I kept the code tight\r\nand didn't have to integrate with any other software except Robert's\r\nand Trevor's, so it was quite fun to work on. If all I'd had to do\r\nwas work on this software, the next 3 years would have been the\r\neasiest of my life. Unfortunately I had to do a lot more, all of\r\nit stuff I was worse at than programming, and the next 3 years were\r\ninstead the most stressful.There were a lot of startups making ecommerce software in the second\r\nhalf of the 90s. We were determined to be the Microsoft Word, not\r\nthe Interleaf. Which meant being easy to use and inexpensive. It\r\nwas lucky for us that we were poor, because that caused us to make\r\nViaweb even more inexpensive than we realized. We charged $100 a\r\nmonth for a small store and $300 a month for a big one. This low\r\nprice was a big attraction, and a constant thorn in the sides of\r\ncompetitors, but it wasn't because of some clever insight that we\r\nset the price low. We had no idea what businesses paid for things.\r\n$300 a month seemed like a lot of money to us.We did a lot of things right by accident like that. For example,\r\nwe did what's now called \"doing things that \r\ndon't scale,\" although\r\nat the time we would have described it as \"being so lame that we're\r\ndriven to the most desperate measures to get users.\" The most common\r\nof which was building stores for them. This seemed particularly\r\nhumiliating, since the whole raison d'etre of our software was that\r\npeople could use it to make their own stores. But anything to get\r\nusers.We learned a lot more about retail than we wanted to know. For\r\nexample, that if you could only have a small image of a man's shirt\r\n(and all images were small then by present standards), it was better\r\nto have a closeup of the collar than a picture of the whole shirt.\r\nThe reason I remember learning this was that it meant I had to\r\nrescan about 30 images of men's shirts. My first set of scans were\r\nso beautiful too.Though this felt wrong, it was exactly the right thing to be doing.\r\nBuilding stores for users taught us about retail, and about how it\r\nfelt to use our software. I was initially both mystified and repelled\r\nby \"business\" and thought we needed a \"business person\" to be in\r\ncharge of it, but once we started to get users, I was converted,\r\nin much the same way I was converted to \r\nfatherhood once I had kids.\r\nWhatever users wanted, I was all theirs. Maybe one day we'd have\r\nso many users that I couldn't scan their images for them, but in\r\nthe meantime there was nothing more important to do.Another thing I didn't get at the time is that \r\ngrowth rate is the\r\nultimate test of a startup. Our growth rate was fine. We had about\r\n70 stores at the end of 1996 and about 500 at the end of 1997. I\r\nmistakenly thought the thing that mattered was the absolute number\r\nof users. And that is the thing that matters in the sense that\r\nthat's how much money you're making, and if you're not making enough,\r\nyou might go out of business. But in the long term the growth rate\r\ntakes care of the absolute number. If we'd been a startup I was\r\nadvising at Y Combinator, I would have said: Stop being so stressed\r\nout, because you're doing fine. You're growing 7x a year. Just don't\r\nhire too many more people and you'll soon be profitable, and then\r\nyou'll control your own destiny.Alas I hired lots more people, partly because our investors wanted\r\nme to, and partly because that's what startups did during the\r\nInternet Bubble. A company with just a handful of employees would\r\nhave seemed amateurish. So we didn't reach breakeven until about\r\nwhen Yahoo bought us in the summer of 1998. Which in turn meant we\r\nwere at the mercy of investors for the entire life of the company.\r\nAnd since both we and our investors were noobs at startups, the\r\nresult was a mess even by startup standards.It was a huge relief when Yahoo bought us. In principle our Viaweb\r\nstock was valuable. It was a share in a business that was profitable\r\nand growing rapidly. But it didn't feel very valuable to me; I had\r\nno idea how to value a business, but I was all too keenly aware of\r\nthe near-death experiences we seemed to have every few months. Nor\r\nhad I changed my grad student lifestyle significantly since we\r\nstarted. So when Yahoo bought us it felt like going from rags to\r\nriches. Since we were going to California, I bought a car, a yellow\r\n1998 VW GTI. I remember thinking that its leather seats alone were\r\nby far the most luxurious thing I owned.The next year, from the summer of 1998 to the summer of 1999, must\r\nhave been the least productive of my life. I didn't realize it at\r\nthe time, but I was worn out from the effort and stress of running\r\nViaweb. For a while after I got to California I tried to continue\r\nmy usual m.o. of programming till 3 in the morning, but fatigue\r\ncombined with Yahoo's prematurely aged\r\nculture and grim cube farm\r\nin Santa Clara gradually dragged me down. After a few months it\r\nfelt disconcertingly like working at Interleaf.Yahoo had given us a lot of options when they bought us. At the\r\ntime I thought Yahoo was so overvalued that they'd never be worth\r\nanything, but to my astonishment the stock went up 5x in the next\r\nyear. I hung on till the first chunk of options vested, then in the\r\nsummer of 1999 I left. It had been so long since I'd painted anything\r\nthat I'd half forgotten why I was doing this. My brain had been\r\nentirely full of software and men's shirts for 4 years. But I had\r\ndone this to get rich so I could paint, I reminded myself, and now\r\nI was rich, so I should go paint.When I said I was leaving, my boss at Yahoo had a long conversation\r\nwith me about my plans. I told him all about the kinds of pictures\r\nI wanted to paint. At the time I was touched that he took such an\r\ninterest in me. Now I realize it was because he thought I was lying.\r\nMy options at that point were worth about $2 million a month. If I\r\nwas leaving that kind of money on the table, it could only be to\r\ngo and start some new startup, and if I did, I might take people\r\nwith me. This was the height of the Internet Bubble, and Yahoo was\r\nground zero of it. My boss was at that moment a billionaire. Leaving\r\nthen to start a new startup must have seemed to him an insanely,\r\nand yet also plausibly, ambitious plan.But I really was quitting to paint, and I started immediately.\r\nThere was no time to lose. I'd already burned 4 years getting rich.\r\nNow when I talk to founders who are leaving after selling their\r\ncompanies, my advice is always the same: take a vacation. That's\r\nwhat I should have done, just gone off somewhere and done nothing\r\nfor a month or two, but the idea never occurred to me.So I tried to paint, but I just didn't seem to have any energy or\r\nambition. Part of the problem was that I didn't know many people\r\nin California. I'd compounded this problem by buying a house up in\r\nthe Santa Cruz Mountains, with a beautiful view but miles from\r\nanywhere. I stuck it out for a few more months, then in desperation\r\nI went back to New York, where unless you understand about rent\r\ncontrol you'll be surprised to hear I still had my apartment, sealed\r\nup like a tomb of my old life. Idelle was in New York at least, and\r\nthere were other people trying to paint there, even though I didn't\r\nknow any of them.When I got back to New York I resumed my old life, except now I was\r\nrich. It was as weird as it sounds. I resumed all my old patterns,\r\nexcept now there were doors where there hadn't been. Now when I was\r\ntired of walking, all I had to do was raise my hand, and (unless\r\nit was raining) a taxi would stop to pick me up. Now when I walked\r\npast charming little restaurants I could go in and order lunch. It\r\nwas exciting for a while. Painting started to go better. I experimented\r\nwith a new kind of still life where I'd paint one painting in the\r\nold way, then photograph it and print it, blown up, on canvas, and\r\nthen use that as the underpainting for a second still life, painted\r\nfrom the same objects (which hopefully hadn't rotted yet).Meanwhile I looked for an apartment to buy. Now I could actually\r\nchoose what neighborhood to live in. Where, I asked myself and\r\nvarious real estate agents, is the Cambridge of New York? Aided by\r\noccasional visits to actual Cambridge, I gradually realized there\r\nwasn't one. Huh.Around this time, in the spring of 2000, I had an idea. It was clear\r\nfrom our experience with Viaweb that web apps were the future. Why\r\nnot build a web app for making web apps? Why not let people edit\r\ncode on our server through the browser, and then host the resulting\r\napplications for them?\r\n[9]\r\nYou could run all sorts of services\r\non the servers that these applications could use just by making an\r\nAPI call: making and receiving phone calls, manipulating images,\r\ntaking credit card payments, etc.I got so excited about this idea that I couldn't think about anything\r\nelse. It seemed obvious that this was the future. I didn't particularly\r\nwant to start another company, but it was clear that this idea would\r\nhave to be embodied as one, so I decided to move to Cambridge and\r\nstart it. I hoped to lure Robert into working on it with me, but\r\nthere I ran into a hitch. Robert was now a postdoc at MIT, and\r\nthough he'd made a lot of money the last time I'd lured him into\r\nworking on one of my schemes, it had also been a huge time sink.\r\nSo while he agreed that it sounded like a plausible idea, he firmly\r\nrefused to work on it.Hmph. Well, I'd do it myself then. I recruited Dan Giffin, who had\r\nworked for Viaweb, and two undergrads who wanted summer jobs, and\r\nwe got to work trying to build what it's now clear is about twenty\r\ncompanies and several open source projects worth of software. The\r\nlanguage for defining applications would of course be a dialect of\r\nLisp. But I wasn't so naive as to assume I could spring an overt\r\nLisp on a general audience; we'd hide the parentheses, like Dylan\r\ndid.By then there was a name for the kind of company Viaweb was, an\r\n\"application service provider,\" or ASP. This name didn't last long\r\nbefore it was replaced by \"software as a service,\" but it was current\r\nfor long enough that I named this new company after it: it was going\r\nto be called Aspra.I started working on the application builder, Dan worked on network\r\ninfrastructure, and the two undergrads worked on the first two\r\nservices (images and phone calls). But about halfway through the\r\nsummer I realized I really didn't want to run a company — especially\r\nnot a big one, which it was looking like this would have to be. I'd\r\nonly started Viaweb because I needed the money. Now that I didn't\r\nneed money anymore, why was I doing this? If this vision had to be\r\nrealized as a company, then screw the vision. I'd build a subset\r\nthat could be done as an open source project.Much to my surprise, the time I spent working on this stuff was not\r\nwasted after all. After we started Y Combinator, I would often\r\nencounter startups working on parts of this new architecture, and\r\nit was very useful to have spent so much time thinking about it and\r\neven trying to write some of it.The subset I would build as an open source project was the new Lisp,\r\nwhose parentheses I now wouldn't even have to hide. A lot of Lisp\r\nhackers dream of building a new Lisp, partly because one of the\r\ndistinctive features of the language is that it has dialects, and\r\npartly, I think, because we have in our minds a Platonic form of\r\nLisp that all existing dialects fall short of. I certainly did. So\r\nat the end of the summer Dan and I switched to working on this new\r\ndialect of Lisp, which I called Arc, in a house I bought in Cambridge.The following spring, lightning struck. I was invited to give a\r\ntalk at a Lisp conference, so I gave one about how we'd used Lisp\r\nat Viaweb. Afterward I put a postscript file of this talk online,\r\non paulgraham.com, which I'd created years before using Viaweb but\r\nhad never used for anything. In one day it got 30,000 page views.\r\nWhat on earth had happened? The referring urls showed that someone\r\nhad posted it on Slashdot.\r\n[10]Wow, I thought, there's an audience. If I write something and put\r\nit on the web, anyone can read it. That may seem obvious now, but\r\nit was surprising then. In the print era there was a narrow channel\r\nto readers, guarded by fierce monsters known as editors. The only\r\nway to get an audience for anything you wrote was to get it published\r\nas a book, or in a newspaper or magazine. Now anyone could publish\r\nanything.This had been possible in principle since 1993, but not many people\r\nhad realized it yet. I had been intimately involved with building\r\nthe infrastructure of the web for most of that time, and a writer\r\nas well, and it had taken me 8 years to realize it. Even then it\r\ntook me several years to understand the implications. It meant there\r\nwould be a whole new generation of \r\nessays.\r\n[11]In the print era, the channel for publishing essays had been\r\nvanishingly small. Except for a few officially anointed thinkers\r\nwho went to the right parties in New York, the only people allowed\r\nto publish essays were specialists writing about their specialties.\r\nThere were so many essays that had never been written, because there\r\nhad been no way to publish them. Now they could be, and I was going\r\nto write them.\r\n[12]I've worked on several different things, but to the extent there\r\nwas a turning point where I figured out what to work on, it was\r\nwhen I started publishing essays online. From then on I knew that\r\nwhatever else I did, I'd always write essays too.I knew that online essays would be a \r\nmarginal medium at first.\r\nSocially they'd seem more like rants posted by nutjobs on their\r\nGeoCities sites than the genteel and beautifully typeset compositions\r\npublished in The New Yorker. But by this point I knew enough to\r\nfind that encouraging instead of discouraging.One of the most conspicuous patterns I've noticed in my life is how\r\nwell it has worked, for me at least, to work on things that weren't\r\nprestigious. Still life has always been the least prestigious form\r\nof painting. Viaweb and Y Combinator both seemed lame when we started\r\nthem. I still get the glassy eye from strangers when they ask what\r\nI'm writing, and I explain that it's an essay I'm going to publish\r\non my web site. Even Lisp, though prestigious intellectually in\r\nsomething like the way Latin is, also seems about as hip.It's not that unprestigious types of work are good per se. But when\r\nyou find yourself drawn to some kind of work despite its current\r\nlack of prestige, it's a sign both that there's something real to\r\nbe discovered there, and that you have the right kind of motives.\r\nImpure motives are a big danger for the ambitious. If anything is\r\ngoing to lead you astray, it will be the desire to impress people.\r\nSo while working on things that aren't prestigious doesn't guarantee\r\nyou're on the right track, it at least guarantees you're not on the\r\nmost common type of wrong one.Over the next several years I wrote lots of essays about all kinds\r\nof different topics. O'Reilly reprinted a collection of them as a\r\nbook, called Hackers & Painters after one of the essays in it. I\r\nalso worked on spam filters, and did some more painting. I used to\r\nhave dinners for a group of friends every thursday night, which\r\ntaught me how to cook for groups. And I bought another building in\r\nCambridge, a former candy factory (and later, twas said, porn\r\nstudio), to use as an office.One night in October 2003 there was a big party at my house. It was\r\na clever idea of my friend Maria Daniels, who was one of the thursday\r\ndiners. Three separate hosts would all invite their friends to one\r\nparty. So for every guest, two thirds of the other guests would be\r\npeople they didn't know but would probably like. One of the guests\r\nwas someone I didn't know but would turn out to like a lot: a woman\r\ncalled Jessica Livingston. A couple days later I asked her out.Jessica was in charge of marketing at a Boston investment bank.\r\nThis bank thought it understood startups, but over the next year,\r\nas she met friends of mine from the startup world, she was surprised\r\nhow different reality was. And how colorful their stories were. So\r\nshe decided to compile a book of \r\ninterviews with startup founders.When the bank had financial problems and she had to fire half her\r\nstaff, she started looking for a new job. In early 2005 she interviewed\r\nfor a marketing job at a Boston VC firm. It took them weeks to make\r\nup their minds, and during this time I started telling her about\r\nall the things that needed to be fixed about venture capital. They\r\nshould make a larger number of smaller investments instead of a\r\nhandful of giant ones, they should be funding younger, more technical\r\nfounders instead of MBAs, they should let the founders remain as\r\nCEO, and so on.One of my tricks for writing essays had always been to give talks.\r\nThe prospect of having to stand up in front of a group of people\r\nand tell them something that won't waste their time is a great\r\nspur to the imagination. When the Harvard Computer Society, the\r\nundergrad computer club, asked me to give a talk, I decided I would\r\ntell them how to start a startup. Maybe they'd be able to avoid the\r\nworst of the mistakes we'd made.So I gave this talk, in the course of which I told them that the\r\nbest sources of seed funding were successful startup founders,\r\nbecause then they'd be sources of advice too. Whereupon it seemed\r\nthey were all looking expectantly at me. Horrified at the prospect\r\nof having my inbox flooded by business plans (if I'd only known),\r\nI blurted out \"But not me!\" and went on with the talk. But afterward\r\nit occurred to me that I should really stop procrastinating about\r\nangel investing. I'd been meaning to since Yahoo bought us, and now\r\nit was 7 years later and I still hadn't done one angel investment.Meanwhile I had been scheming with Robert and Trevor about projects\r\nwe could work on together. I missed working with them, and it seemed\r\nlike there had to be something we could collaborate on.As Jessica and I were walking home from dinner on March 11, at the\r\ncorner of Garden and Walker streets, these three threads converged.\r\nScrew the VCs who were taking so long to make up their minds. We'd\r\nstart our own investment firm and actually implement the ideas we'd\r\nbeen talking about. I'd fund it, and Jessica could quit her job and\r\nwork for it, and we'd get Robert and Trevor as partners too.\r\n[13]Once again, ignorance worked in our favor. We had no idea how to\r\nbe angel investors, and in Boston in 2005 there were no Ron Conways\r\nto learn from. So we just made what seemed like the obvious choices,\r\nand some of the things we did turned out to be novel.There are multiple components to Y Combinator, and we didn't figure\r\nthem all out at once. The part we got first was to be an angel firm.\r\nIn those days, those two words didn't go together. There were VC\r\nfirms, which were organized companies with people whose job it was\r\nto make investments, but they only did big, million dollar investments.\r\nAnd there were angels, who did smaller investments, but these were\r\nindividuals who were usually focused on other things and made\r\ninvestments on the side. And neither of them helped founders enough\r\nin the beginning. We knew how helpless founders were in some respects,\r\nbecause we remembered how helpless we'd been. For example, one thing\r\nJulian had done for us that seemed to us like magic was to get us\r\nset up as a company. We were fine writing fairly difficult software,\r\nbut actually getting incorporated, with bylaws and stock and all\r\nthat stuff, how on earth did you do that? Our plan was not only to\r\nmake seed investments, but to do for startups everything Julian had\r\ndone for us.YC was not organized as a fund. It was cheap enough to run that we\r\nfunded it with our own money. That went right by 99% of readers,\r\nbut professional investors are thinking \"Wow, that means they got\r\nall the returns.\" But once again, this was not due to any particular\r\ninsight on our part. We didn't know how VC firms were organized.\r\nIt never occurred to us to try to raise a fund, and if it had, we\r\nwouldn't have known where to start.\r\n[14]The most distinctive thing about YC is the batch model: to fund a\r\nbunch of startups all at once, twice a year, and then to spend three\r\nmonths focusing intensively on trying to help them. That part we\r\ndiscovered by accident, not merely implicitly but explicitly due\r\nto our ignorance about investing. We needed to get experience as\r\ninvestors. What better way, we thought, than to fund a whole bunch\r\nof startups at once? We knew undergrads got temporary jobs at tech\r\ncompanies during the summer. Why not organize a summer program where\r\nthey'd start startups instead? We wouldn't feel guilty for being\r\nin a sense fake investors, because they would in a similar sense\r\nbe fake founders. So while we probably wouldn't make much money out\r\nof it, we'd at least get to practice being investors on them, and\r\nthey for their part would probably have a more interesting summer\r\nthan they would working at Microsoft.We'd use the building I owned in Cambridge as our headquarters.\r\nWe'd all have dinner there once a week — on tuesdays, since I was\r\nalready cooking for the thursday diners on thursdays — and after\r\ndinner we'd bring in experts on startups to give talks.We knew undergrads were deciding then about summer jobs, so in a\r\nmatter of days we cooked up something we called the Summer Founders\r\nProgram, and I posted an \r\nannouncement \r\non my site, inviting undergrads\r\nto apply. I had never imagined that writing essays would be a way\r\nto get \"deal flow,\" as investors call it, but it turned out to be\r\nthe perfect source.\r\n[15]\r\nWe got 225 applications for the Summer\r\nFounders Program, and we were surprised to find that a lot of them\r\nwere from people who'd already graduated, or were about to that\r\nspring. Already this SFP thing was starting to feel more serious\r\nthan we'd intended.We invited about 20 of the 225 groups to interview in person, and\r\nfrom those we picked 8 to fund. They were an impressive group. That\r\nfirst batch included reddit, Justin Kan and Emmett Shear, who went\r\non to found Twitch, Aaron Swartz, who had already helped write the\r\nRSS spec and would a few years later become a martyr for open access,\r\nand Sam Altman, who would later become the second president of YC.\r\nI don't think it was entirely luck that the first batch was so good.\r\nYou had to be pretty bold to sign up for a weird thing like the\r\nSummer Founders Program instead of a summer job at a legit place\r\nlike Microsoft or Goldman Sachs.The deal for startups was based on a combination of the deal we did\r\nwith Julian ($10k for 10%) and what Robert said MIT grad students\r\ngot for the summer ($6k). We invested $6k per founder, which in the\r\ntypical two-founder case was $12k, in return for 6%. That had to\r\nbe fair, because it was twice as good as the deal we ourselves had\r\ntaken. Plus that first summer, which was really hot, Jessica brought\r\nthe founders free air conditioners.\r\n[16]Fairly quickly I realized that we had stumbled upon the way to scale\r\nstartup funding. Funding startups in batches was more convenient\r\nfor us, because it meant we could do things for a lot of startups\r\nat once, but being part of a batch was better for the startups too.\r\nIt solved one of the biggest problems faced by founders: the\r\nisolation. Now you not only had colleagues, but colleagues who\r\nunderstood the problems you were facing and could tell you how they\r\nwere solving them.As YC grew, we started to notice other advantages of scale. The\r\nalumni became a tight community, dedicated to helping one another,\r\nand especially the current batch, whose shoes they remembered being\r\nin. We also noticed that the startups were becoming one another's\r\ncustomers. We used to refer jokingly to the \"YC GDP,\" but as YC\r\ngrows this becomes less and less of a joke. Now lots of startups\r\nget their initial set of customers almost entirely from among their\r\nbatchmates.I had not originally intended YC to be a full-time job. I was going\r\nto do three things: hack, write essays, and work on YC. As YC grew,\r\nand I grew more excited about it, it started to take up a lot more\r\nthan a third of my attention. But for the first few years I was\r\nstill able to work on other things.In the summer of 2006, Robert and I started working on a new version\r\nof Arc. This one was reasonably fast, because it was compiled into\r\nScheme. To test this new Arc, I wrote Hacker News in it. It was\r\noriginally meant to be a news aggregator for startup founders and\r\nwas called Startup News, but after a few months I got tired of\r\nreading about nothing but startups. Plus it wasn't startup founders\r\nwe wanted to reach. It was future startup founders. So I changed\r\nthe name to Hacker News and the topic to whatever engaged one's\r\nintellectual curiosity.HN was no doubt good for YC, but it was also by far the biggest\r\nsource of stress for me. If all I'd had to do was select and help\r\nfounders, life would have been so easy. And that implies that HN\r\nwas a mistake. Surely the biggest source of stress in one's work\r\nshould at least be something close to the core of the work. Whereas\r\nI was like someone who was in pain while running a marathon not\r\nfrom the exertion of running, but because I had a blister from an\r\nill-fitting shoe. When I was dealing with some urgent problem during\r\nYC, there was about a 60% chance it had to do with HN, and a 40%\r\nchance it had do with everything else combined.\r\n[17]As well as HN, I wrote all of YC's internal software in Arc. But\r\nwhile I continued to work a good deal in Arc, I gradually stopped\r\nworking on Arc, partly because I didn't have time to, and partly\r\nbecause it was a lot less attractive to mess around with the language\r\nnow that we had all this infrastructure depending on it. So now my\r\nthree projects were reduced to two: writing essays and working on\r\nYC.YC was different from other kinds of work I've done. Instead of\r\ndeciding for myself what to work on, the problems came to me. Every\r\n6 months there was a new batch of startups, and their problems,\r\nwhatever they were, became our problems. It was very engaging work,\r\nbecause their problems were quite varied, and the good founders\r\nwere very effective. If you were trying to learn the most you could\r\nabout startups in the shortest possible time, you couldn't have\r\npicked a better way to do it.There were parts of the job I didn't like. Disputes between cofounders,\r\nfiguring out when people were lying to us, fighting with people who\r\nmaltreated the startups, and so on. But I worked hard even at the\r\nparts I didn't like. I was haunted by something Kevin Hale once\r\nsaid about companies: \"No one works harder than the boss.\" He meant\r\nit both descriptively and prescriptively, and it was the second\r\npart that scared me. I wanted YC to be good, so if how hard I worked\r\nset the upper bound on how hard everyone else worked, I'd better\r\nwork very hard.One day in 2010, when he was visiting California for interviews,\r\nRobert Morris did something astonishing: he offered me unsolicited\r\nadvice. I can only remember him doing that once before. One day at\r\nViaweb, when I was bent over double from a kidney stone, he suggested\r\nthat it would be a good idea for him to take me to the hospital.\r\nThat was what it took for Rtm to offer unsolicited advice. So I\r\nremember his exact words very clearly. \"You know,\" he said, \"you\r\nshould make sure Y Combinator isn't the last cool thing you do.\"At the time I didn't understand what he meant, but gradually it\r\ndawned on me that he was saying I should quit. This seemed strange\r\nadvice, because YC was doing great. But if there was one thing rarer\r\nthan Rtm offering advice, it was Rtm being wrong. So this set me\r\nthinking. It was true that on my current trajectory, YC would be\r\nthe last thing I did, because it was only taking up more of my\r\nattention. It had already eaten Arc, and was in the process of\r\neating essays too. Either YC was my life's work or I'd have to leave\r\neventually. And it wasn't, so I would.In the summer of 2012 my mother had a stroke, and the cause turned\r\nout to be a blood clot caused by colon cancer. The stroke destroyed\r\nher balance, and she was put in a nursing home, but she really\r\nwanted to get out of it and back to her house, and my sister and I\r\nwere determined to help her do it. I used to fly up to Oregon to\r\nvisit her regularly, and I had a lot of time to think on those\r\nflights. On one of them I realized I was ready to hand YC over to\r\nsomeone else.I asked Jessica if she wanted to be president, but she didn't, so\r\nwe decided we'd try to recruit Sam Altman. We talked to Robert and\r\nTrevor and we agreed to make it a complete changing of the guard.\r\nUp till that point YC had been controlled by the original LLC we\r\nfour had started. But we wanted YC to last for a long time, and to\r\ndo that it couldn't be controlled by the founders. So if Sam said\r\nyes, we'd let him reorganize YC. Robert and I would retire, and\r\nJessica and Trevor would become ordinary partners.When we asked Sam if he wanted to be president of YC, initially he\r\nsaid no. He wanted to start a startup to make nuclear reactors.\r\nBut I kept at it, and in October 2013 he finally agreed. We decided\r\nhe'd take over starting with the winter 2014 batch. For the rest\r\nof 2013 I left running YC more and more to Sam, partly so he could\r\nlearn the job, and partly because I was focused on my mother, whose\r\ncancer had returned.She died on January 15, 2014. We knew this was coming, but it was\r\nstill hard when it did.I kept working on YC till March, to help get that batch of startups\r\nthrough Demo Day, then I checked out pretty completely. (I still\r\ntalk to alumni and to new startups working on things I'm interested\r\nin, but that only takes a few hours a week.)What should I do next? Rtm's advice hadn't included anything about\r\nthat. I wanted to do something completely different, so I decided\r\nI'd paint. I wanted to see how good I could get if I really focused\r\non it. So the day after I stopped working on YC, I started painting.\r\nI was rusty and it took a while to get back into shape, but it was\r\nat least completely engaging.\r\n[18]I spent most of the rest of 2014 painting. I'd never been able to\r\nwork so uninterruptedly before, and I got to be better than I had\r\nbeen. Not good enough, but better. Then in November, right in the\r\nmiddle of a painting, I ran out of steam. Up till that point I'd\r\nalways been curious to see how the painting I was working on would\r\nturn out, but suddenly finishing this one seemed like a chore. So\r\nI stopped working on it and cleaned my brushes and haven't painted\r\nsince. So far anyway.I realize that sounds rather wimpy. But attention is a zero sum\r\ngame. If you can choose what to work on, and you choose a project\r\nthat's not the best one (or at least a good one) for you, then it's\r\ngetting in the way of another project that is. And at 50 there was\r\nsome opportunity cost to screwing around.I started writing essays again, and wrote a bunch of new ones over\r\nthe next few months. I even wrote a couple that \r\nweren't about\r\nstartups. Then in March 2015 I started working on Lisp again.The distinctive thing about Lisp is that its core is a language\r\ndefined by writing an interpreter in itself. It wasn't originally\r\nintended as a programming language in the ordinary sense. It was\r\nmeant to be a formal model of computation, an alternative to the\r\nTuring machine. If you want to write an interpreter for a language\r\nin itself, what's the minimum set of predefined operators you need?\r\nThe Lisp that John McCarthy invented, or more accurately discovered,\r\nis an answer to that question.\r\n[19]McCarthy didn't realize this Lisp could even be used to program\r\ncomputers till his grad student Steve Russell suggested it. Russell\r\ntranslated McCarthy's interpreter into IBM 704 machine language,\r\nand from that point Lisp started also to be a programming language\r\nin the ordinary sense. But its origins as a model of computation\r\ngave it a power and elegance that other languages couldn't match.\r\nIt was this that attracted me in college, though I didn't understand\r\nwhy at the time.McCarthy's 1960 Lisp did nothing more than interpret Lisp expressions.\r\nIt was missing a lot of things you'd want in a programming language.\r\nSo these had to be added, and when they were, they weren't defined\r\nusing McCarthy's original axiomatic approach. That wouldn't have\r\nbeen feasible at the time. McCarthy tested his interpreter by\r\nhand-simulating the execution of programs. But it was already getting\r\nclose to the limit of interpreters you could test that way — indeed,\r\nthere was a bug in it that McCarthy had overlooked. To test a more\r\ncomplicated interpreter, you'd have had to run it, and computers\r\nthen weren't powerful enough.Now they are, though. Now you could continue using McCarthy's\r\naxiomatic approach till you'd defined a complete programming language.\r\nAnd as long as every change you made to McCarthy's Lisp was a\r\ndiscoveredness-preserving transformation, you could, in principle,\r\nend up with a complete language that had this quality. Harder to\r\ndo than to talk about, of course, but if it was possible in principle,\r\nwhy not try? So I decided to take a shot at it. It took 4 years,\r\nfrom March 26, 2015 to October 12, 2019. It was fortunate that I\r\nhad a precisely defined goal, or it would have been hard to keep\r\nat it for so long.I wrote this new Lisp, called Bel, \r\nin itself in Arc. That may sound\r\nlike a contradiction, but it's an indication of the sort of trickery\r\nI had to engage in to make this work. By means of an egregious\r\ncollection of hacks I managed to make something close enough to an\r\ninterpreter written in itself that could actually run. Not fast,\r\nbut fast enough to test.I had to ban myself from writing essays during most of this time,\r\nor I'd never have finished. In late 2015 I spent 3 months writing\r\nessays, and when I went back to working on Bel I could barely\r\nunderstand the code. Not so much because it was badly written as\r\nbecause the problem is so convoluted. When you're working on an\r\ninterpreter written in itself, it's hard to keep track of what's\r\nhappening at what level, and errors can be practically encrypted\r\nby the time you get them.So I said no more essays till Bel was done. But I told few people\r\nabout Bel while I was working on it. So for years it must have\r\nseemed that I was doing nothing, when in fact I was working harder\r\nthan I'd ever worked on anything. Occasionally after wrestling for\r\nhours with some gruesome bug I'd check Twitter or HN and see someone\r\nasking \"Does Paul Graham still code?\"Working on Bel was hard but satisfying. I worked on it so intensively\r\nthat at any given time I had a decent chunk of the code in my head\r\nand could write more there. I remember taking the boys to the\r\ncoast on a sunny day in 2015 and figuring out how to deal with some\r\nproblem involving continuations while I watched them play in the\r\ntide pools. It felt like I was doing life right. I remember that\r\nbecause I was slightly dismayed at how novel it felt. The good news\r\nis that I had more moments like this over the next few years.In the summer of 2016 we moved to England. We wanted our kids to\r\nsee what it was like living in another country, and since I was a\r\nBritish citizen by birth, that seemed the obvious choice. We only\r\nmeant to stay for a year, but we liked it so much that we still\r\nlive there. So most of Bel was written in England.In the fall of 2019, Bel was finally finished. Like McCarthy's\r\noriginal Lisp, it's a spec rather than an implementation, although\r\nlike McCarthy's Lisp it's a spec expressed as code.Now that I could write essays again, I wrote a bunch about topics\r\nI'd had stacked up. I kept writing essays through 2020, but I also\r\nstarted to think about other things I could work on. How should I\r\nchoose what to do? Well, how had I chosen what to work on in the\r\npast? I wrote an essay for myself to answer that question, and I\r\nwas surprised how long and messy the answer turned out to be. If\r\nthis surprised me, who'd lived it, then I thought perhaps it would\r\nbe interesting to other people, and encouraging to those with\r\nsimilarly messy lives. So I wrote a more detailed version for others\r\nto read, and this is the last sentence of it.\nNotes[1]\r\nMy experience skipped a step in the evolution of computers:\r\ntime-sharing machines with interactive OSes. I went straight from\r\nbatch processing to microcomputers, which made microcomputers seem\r\nall the more exciting.[2]\r\nItalian words for abstract concepts can nearly always be\r\npredicted from their English cognates (except for occasional traps\r\nlike polluzione). It's the everyday words that differ. So if you\r\nstring together a lot of abstract concepts with a few simple verbs,\r\nyou can make a little Italian go a long way.[3]\r\nI lived at Piazza San Felice 4, so my walk to the Accademia\r\nwent straight down the spine of old Florence: past the Pitti, across\r\nthe bridge, past Orsanmichele, between the Duomo and the Baptistery,\r\nand then up Via Ricasoli to Piazza San Marco. I saw Florence at\r\nstreet level in every possible condition, from empty dark winter\r\nevenings to sweltering summer days when the streets were packed with\r\ntourists.[4]\r\nYou can of course paint people like still lives if you want\r\nto, and they're willing. That sort of portrait is arguably the apex\r\nof still life painting, though the long sitting does tend to produce\r\npained expressions in the sitters.[5]\r\nInterleaf was one of many companies that had smart people and\r\nbuilt impressive technology, and yet got crushed by Moore's Law.\r\nIn the 1990s the exponential growth in the power of commodity (i.e.\r\nIntel) processors rolled up high-end, special-purpose hardware and\r\nsoftware companies like a bulldozer.[6]\r\nThe signature style seekers at RISD weren't specifically\r\nmercenary. In the art world, money and coolness are tightly coupled.\r\nAnything expensive comes to be seen as cool, and anything seen as\r\ncool will soon become equally expensive.[7]\r\nTechnically the apartment wasn't rent-controlled but\r\nrent-stabilized, but this is a refinement only New Yorkers would\r\nknow or care about. The point is that it was really cheap, less\r\nthan half market price.[8]\r\nMost software you can launch as soon as it's done. But when\r\nthe software is an online store builder and you're hosting the\r\nstores, if you don't have any users yet, that fact will be painfully\r\nobvious. So before we could launch publicly we had to launch\r\nprivately, in the sense of recruiting an initial set of users and\r\nmaking sure they had decent-looking stores.[9]\r\nWe'd had a code editor in Viaweb for users to define their\r\nown page styles. They didn't know it, but they were editing Lisp\r\nexpressions underneath. But this wasn't an app editor, because the\r\ncode ran when the merchants' sites were generated, not when shoppers\r\nvisited them.[10]\r\nThis was the first instance of what is now a familiar experience,\r\nand so was what happened next, when I read the comments and found\r\nthey were full of angry people. How could I claim that Lisp was\r\nbetter than other languages? Weren't they all Turing complete?\r\nPeople who see the responses to essays I write sometimes tell me\r\nhow sorry they feel for me, but I'm not exaggerating when I reply\r\nthat it has always been like this, since the very beginning. It\r\ncomes with the territory. An essay must tell readers things they\r\ndon't already know, and some \r\npeople dislike being told such things.[11]\r\nPeople put plenty of stuff on the internet in the 90s of\r\ncourse, but putting something online is not the same as publishing\r\nit online. Publishing online means you treat the online version as\r\nthe (or at least a) primary version.[12]\r\nThere is a general lesson here that our experience with Y\r\nCombinator also teaches: Customs continue to constrain you long\r\nafter the restrictions that caused them have disappeared. Customary\r\nVC practice had once, like the customs about publishing essays,\r\nbeen based on real constraints. Startups had once been much more\r\nexpensive to start, and proportionally rare. Now they could be cheap\r\nand common, but the VCs' customs still reflected the old world,\r\njust as customs about writing essays still reflected the constraints\r\nof the print era.Which in turn implies that people who are independent-minded (i.e.\r\nless influenced by custom) will have an advantage in fields affected\r\nby rapid change (where customs are more likely to be obsolete).Here's an interesting point, though: you can't always predict which\r\nfields will be affected by rapid change. Obviously software and\r\nventure capital will be, but who would have predicted that essay\r\nwriting would be?[13]\r\nY Combinator was not the original name. At first we were\r\ncalled Cambridge Seed. But we didn't want a regional name, in case\r\nsomeone copied us in Silicon Valley, so we renamed ourselves after\r\none of the coolest tricks in the lambda calculus, the Y combinator.I picked orange as our color partly because it's the warmest, and\r\npartly because no VC used it. In 2005 all the VCs used staid colors\r\nlike maroon, navy blue, and forest green, because they were trying\r\nto appeal to LPs, not founders. The YC logo itself is an inside\r\njoke: the Viaweb logo had been a white V on a red circle, so I made\r\nthe YC logo a white Y on an orange square.[14]\r\nYC did become a fund for a couple years starting in 2009,\r\nbecause it was getting so big I could no longer afford to fund it\r\npersonally. But after Heroku got bought we had enough money to go\r\nback to being self-funded.[15]\r\nI've never liked the term \"deal flow,\" because it implies\r\nthat the number of new startups at any given time is fixed. This\r\nis not only false, but it's the purpose of YC to falsify it, by\r\ncausing startups to be founded that would not otherwise have existed.[16]\r\nShe reports that they were all different shapes and sizes,\r\nbecause there was a run on air conditioners and she had to get\r\nwhatever she could, but that they were all heavier than she could\r\ncarry now.[17]\r\nAnother problem with HN was a bizarre edge case that occurs\r\nwhen you both write essays and run a forum. When you run a forum,\r\nyou're assumed to see if not every conversation, at least every\r\nconversation involving you. And when you write essays, people post\r\nhighly imaginative misinterpretations of them on forums. Individually\r\nthese two phenomena are tedious but bearable, but the combination\r\nis disastrous. You actually have to respond to the misinterpretations,\r\nbecause the assumption that you're present in the conversation means\r\nthat not responding to any sufficiently upvoted misinterpretation\r\nreads as a tacit admission that it's correct. But that in turn\r\nencourages more; anyone who wants to pick a fight with you senses\r\nthat now is their chance.[18]\r\nThe worst thing about leaving YC was not working with Jessica\r\nanymore. We'd been working on YC almost the whole time we'd known\r\neach other, and we'd neither tried nor wanted to separate it from\r\nour personal lives, so leaving was like pulling up a deeply rooted\r\ntree.[19]\r\nOne way to get more precise about the concept of invented vs\r\ndiscovered is to talk about space aliens. Any sufficiently advanced\r\nalien civilization would certainly know about the Pythagorean\r\ntheorem, for example. I believe, though with less certainty, that\r\nthey would also know about the Lisp in McCarthy's 1960 paper.But if so there's no reason to suppose that this is the limit of\r\nthe language that might be known to them. Presumably aliens need\r\nnumbers and errors and I/O too. So it seems likely there exists at\r\nleast one path out of McCarthy's Lisp along which discoveredness\r\nis preserved.Thanks to Trevor Blackwell, John Collison, Patrick Collison, Daniel\r\nGackle, Ralph Hazell, Jessica Livingston, Robert Morris, and Harj\r\nTaggar for reading drafts of this." }, { "path": "data/PaulGrahamEssaySmall/cred.txt", "content": "April 2020I recently saw a \nvideo \nof TV journalists and politicians confidently\nsaying that the coronavirus would be no worse than the flu. What\nstruck me about it was not just how mistaken they seemed, but how\ndaring. How could they feel safe saying such things?The answer, I realized, is that they didn't think they could get\ncaught. They didn't realize there was any danger in making false\npredictions. These people constantly make false predictions, and\nget away with it, because the things they make predictions about\neither have mushy enough outcomes that they can bluster their way\nout of trouble, or happen so far in the future that few remember\nwhat they said.An epidemic is different. It falsifies your predictions rapidly and\nunequivocally.But epidemics are rare enough that these people clearly\ndidn't realize this was even a possibility. Instead they just\ncontinued to use their ordinary m.o., which, as the epidemic has\nmade clear, is to talk confidently about things they don't\nunderstand.An event like this is thus a uniquely powerful way of taking people's\nmeasure. As Warren Buffett said, \"It's only when the tide goes out\nthat you learn who's been swimming naked.\" And the tide has just\ngone out like never before.Now that we've seen the results, let's remember what we saw, because\nthis is the most accurate test of credibility we're ever likely to have. I hope." }, { "path": "data/PaulGrahamEssaySmall/disc.txt", "content": "January 2017Because biographies of famous scientists tend to \nedit out their mistakes, we underestimate the \ndegree of risk they were willing to take.\nAnd because anything a famous scientist did that\nwasn't a mistake has probably now become the\nconventional wisdom, those choices don't\nseem risky either.Biographies of Newton, for example, understandably focus\nmore on physics than alchemy or theology.\nThe impression we get is that his unerring judgment\nled him straight to truths no one else had noticed.\nHow to explain all the time he spent on alchemy\nand theology? Well, smart people are often kind of\ncrazy.But maybe there is a simpler explanation. Maybe\nthe smartness and the craziness were not as separate\nas we think. Physics seems to us a promising thing\nto work on, and alchemy and theology obvious wastes\nof time. But that's because we know how things\nturned out. In Newton's day the three problems \nseemed roughly equally promising. No one knew yet\nwhat the payoff would be for inventing what we\nnow call physics; if they had, more people would \nhave been working on it. And alchemy and theology\nwere still then in the category Marc Andreessen would \ndescribe as \"huge, if true.\"Newton made three bets. One of them worked. But \nthey were all risky." }, { "path": "data/PaulGrahamEssaySmall/fix.txt", "content": "\nKevin Kelleher suggested an interesting way to compare programming\nlanguages: to describe each in terms of the problem it\nfixes. The surprising thing is how many, and how well, languages can be\ndescribed this way.\n\nAlgol: Assembly language is too low-level.Pascal: Algol doesn't have enough data types.Modula: Pascal is too wimpy for systems programming.\nSimula: Algol isn't good enough at simulations.Smalltalk: Not everything in Simula is an object.Fortran: Assembly language is too low-level.Cobol: Fortran is scary.PL/1: Fortran doesn't have enough data types.Ada: Every existing language is missing something.Basic: Fortran is scary.APL: Fortran isn't good enough at manipulating arrays.J: APL requires its own character set.C: Assembly language is too low-level.C++: C is too low-level.Java: C++ is a kludge. And Microsoft is going to crush us.C#: Java is controlled by Sun.\nLisp: Turing Machines are an awkward way to describe computation.Scheme: MacLisp is a kludge.T: Scheme has no libraries.Common Lisp: There are too many dialects of Lisp.Dylan: Scheme has no libraries, and Lisp syntax is scary.\nPerl: Shell scripts/awk/sed are not enough like programming languages.Python: Perl is a kludge.Ruby: Perl is a kludge, and Lisp syntax is scary.Prolog: Programming is not enough like logic.\n" }, { "path": "data/PaulGrahamEssaySmall/fp.txt", "content": "December 2019I've seen the same pattern in many different fields: even though\nlots of people have worked hard in the field, only a small fraction\nof the space of possibilities has been explored, because they've\nall worked on similar things.Even the smartest, most imaginative people are surprisingly\nconservative when deciding what to work on. People who would never\ndream of being fashionable in any other way get sucked into working\non fashionable problems.If you want to try working on unfashionable problems, one of the\nbest places to look is in fields that people think have already been\nfully explored: essays, Lisp, venture funding — you may notice a\npattern here. If you can find a new approach into a big but apparently\nplayed out field, the value of whatever you discover will be\nmultiplied by its enormous surface area.The best protection against getting drawn into working on the same\nthings as everyone else may be to genuinely \nlove what you're doing.\nThen you'll continue to work on it even if you make the same mistake\nas other people and think that it's too marginal to matter." }, { "path": "data/PaulGrahamEssaySmall/getideas.txt", "content": "January 2023(Someone fed my essays into GPT to make something that could answer\nquestions based on them, then asked it where good ideas come from. The\nanswer was ok, but not what I would have said. This is what I would have said.)The way to get new ideas is to notice anomalies: what seems strange,\nor missing, or broken? You can see anomalies in everyday life (much\nof standup comedy is based on this), but the best place to look for\nthem is at the frontiers of knowledge.Knowledge grows fractally.\nFrom a distance its edges look smooth, but when you learn enough\nto get close to one, you'll notice it's full of gaps. These gaps\nwill seem obvious; it will seem inexplicable that no one has tried\nx or wondered about y. In the best case, exploring such gaps yields\nwhole new fractal buds." }, { "path": "data/PaulGrahamEssaySmall/lwba.txt", "content": "\nAfter a link to \nBeating the Averages was posted on slashdot, \nsome readers wanted to hear in more detail \nabout the specific technical advantages we got from using\nLisp in Viaweb. For those who are interested,\nhere are some excerpts from a talk I gave in April 2001 at\nBBN Labs in Cambridge, MA." }, { "path": "data/PaulGrahamEssaySmall/nft.txt", "content": "May 2021Noora Health, a nonprofit I've \nsupported for years, just launched\na new NFT. It has a dramatic name, Save Thousands of Lives,\nbecause that's what the proceeds will do.Noora has been saving lives for 7 years. They run programs in\nhospitals in South Asia to teach new mothers how to take care of\ntheir babies once they get home. They're in 165 hospitals now. And\nbecause they know the numbers before and after they start at a new\nhospital, they can measure the impact they have. It is massive.\nFor every 1000 live births, they save 9 babies.This number comes from a study\nof 133,733 families at 28 different\nhospitals that Noora conducted in collaboration with the Better\nBirth team at Ariadne Labs, a joint center for health systems\ninnovation at Brigham and Women’s Hospital and Harvard T.H. Chan\nSchool of Public Health.Noora is so effective that even if you measure their costs in the\nmost conservative way, by dividing their entire budget by the number\nof lives saved, the cost of saving a life is the lowest I've seen.\n$1,235.For this NFT, they're going to issue a public report tracking how\nthis specific tranche of money is spent, and estimating the number\nof lives saved as a result.NFTs are a new territory, and this way of using them is especially\nnew, but I'm excited about its potential. And I'm excited to see\nwhat happens with this particular auction, because unlike an NFT\nrepresenting something that has already happened,\nthis NFT gets better as the price gets higher.The reserve price was about $2.5 million, because that's what it\ntakes for the name to be accurate: that's what it costs to save\n2000 lives. But the higher the price of this NFT goes, the more\nlives will be saved. What a sentence to be able to write." }, { "path": "data/PaulGrahamEssaySmall/noob.txt", "content": "January 2020When I was young, I thought old people had everything figured out.\nNow that I'm old, I know this isn't true.I constantly feel like a noob. It seems like I'm always talking to\nsome startup working in a new field I know nothing about, or reading\na book about a topic I don't understand well enough, or visiting some new\ncountry where I don't know how things work.It's not pleasant to feel like a noob. And the word \"noob\" is\ncertainly not a compliment. And yet today I realized something\nencouraging about being a noob: the more of a noob you are locally,\nthe less of a noob you are globally.For example, if you stay in your home country, you'll feel less\nof a noob than if you move to Farawavia, where everything works\ndifferently. And yet you'll know more if you move.\nSo the feeling of being a noob is inversely correlated with actual\nignorance.But if the feeling of being a noob is good for us, why do we dislike\nit? What evolutionary purpose could such an aversion serve?I think the answer is that there are two sources of feeling like a\nnoob: being stupid, and doing something novel. Our dislike of feeling\nlike a noob is our brain telling us \"Come on, come on, figure this\nout.\" Which was the right thing to be thinking for most of human\nhistory. The life of hunter-gatherers was complex, but it didn't\nchange as much as life does now. They didn't suddenly have to figure\nout what to do about cryptocurrency. So it made sense to be biased\ntoward competence at existing problems over the discovery of new\nones. It made sense for humans to dislike the feeling of being a\nnoob, just as, in a world where food was scarce, it made sense for\nthem to dislike the feeling of being hungry.Now that too much food is more of a problem than too little, our\ndislike of feeling hungry leads us astray. And I think our dislike\nof feeling like a noob does too.Though it feels unpleasant, and people will sometimes ridicule you\nfor it, the more you feel like a noob, the better." }, { "path": "data/PaulGrahamEssaySmall/nov.txt", "content": "November 2019If you discover something new, there's a significant chance you'll be\naccused of some form of heresy.To discover new things, you have\nto work on ideas that are good but non-obvious; if an idea is\nobviously good, other people are probably already working on it.\nOne common way for a good idea to be non-obvious is for it to be hidden in the\nshadow of some mistaken assumption that people are very attached to.\nBut anything you discover from working on such an idea will tend to\ncontradict the mistaken assumption that was concealing it. And you\nwill thus get a lot of heat from people attached to the mistaken\nassumption. Galileo and Darwin are famous examples of this phenomenon,\nbut it's probably always an ingredient in the resistance to new\nideas.So it's particularly dangerous for an organization or society to\nhave a culture of pouncing on heresy. When you suppress heresies,\nyou don't just prevent people from contradicting the mistaken\nassumption you're trying to protect. You also suppress any idea\nthat implies indirectly that it's false.\nEvery cherished mistaken assumption has\na dead zone of unexplored ideas around it. And the more preposterous\nthe assumption, the bigger the dead zone it creates.There is a positive side to this phenomenon though. If you're\nlooking for new ideas, one way to find them is by looking for\nheresies. When you look at the question this way, the depressingly\nlarge dead zones around mistaken assumptions become excitingly large\nmines of new ideas." }, { "path": "data/PaulGrahamEssaySmall/pow.txt", "content": "January 2017People who are powerful but uncharismatic will tend to be disliked.\nTheir power makes them a target for criticism that they don't have\nthe charisma to disarm. That was Hillary Clinton's problem. It also\ntends to be a problem for any CEO who is more of a builder than a\nschmoozer. And yet the builder-type CEO is (like Hillary) probably\nthe best person for the job.I don't think there is any solution to this problem. It's human\nnature. The best we can do is to recognize that it's happening, and\nto understand that being a magnet for criticism is sometimes a sign\nnot that someone is the wrong person for a job, but that they're\nthe right one." }, { "path": "data/PaulGrahamEssaySmall/prop62.txt", "content": "November 2016If you're a California voter, there is an important proposition\non your ballot this year: Proposition 62, which bans the death\npenalty.When I was younger I used to think the debate about the death\npenalty was about when it's ok to take a human life. Is it ok\nto kill a killer?But that is not the issue here.The real world does not work like the version I was shown on TV growing up. The police \noften arrest the wrong person.\nDefendants' lawyers are often incompetent. And prosecutors\nare often motivated more by publicity than justice.In the real world, \nabout 4% of people sentenced to death\nare innocent.\nSo this is not about whether it's ok to kill killers. This\nis about whether it's ok to kill innocent people.A child could answer that one for you.This year, in California, you have a chance to end this, by\nvoting yes on Proposition 62. But beware, because there is another \nproposition, Proposition 66, whose goal is to make it \neasier to execute people. So yes on 62, no on 66.It's time." }, { "path": "data/PaulGrahamEssaySmall/rootsoflisp.txt", "content": "May 2001\n\n(I wrote this article to help myself understand exactly\nwhat McCarthy discovered. You don't need to know this stuff\nto program in Lisp, but it should be helpful to \nanyone who wants to\nunderstand the essence of Lisp — both in the sense of its\norigins and its semantic core. The fact that it has such a core\nis one of Lisp's distinguishing features, and the reason why,\nunlike other languages, Lisp has dialects.)In 1960, John \nMcCarthy published a remarkable paper in\nwhich he did for programming something like what Euclid did for\ngeometry. He showed how, given a handful of simple\noperators and a notation for functions, you can\nbuild a whole programming language.\nHe called this language Lisp, for \"List Processing,\"\nbecause one of his key ideas was to use a simple\ndata structure called a list for both\ncode and data.It's worth understanding what McCarthy discovered, not\njust as a landmark in the history of computers, but as\na model for what programming is tending to become in\nour own time. It seems to me that there have been\ntwo really clean, consistent models of programming so\nfar: the C model and the Lisp model.\nThese two seem points of high ground, with swampy lowlands\nbetween them. As computers have grown more powerful,\nthe new languages being developed have been moving\nsteadily toward the Lisp model. A popular recipe\nfor new programming languages in the past 20 years \nhas been to take the C model of computing and add to\nit, piecemeal, parts taken from the Lisp model,\nlike runtime typing and garbage collection.In this article I'm going to try to explain in the\nsimplest possible terms what McCarthy discovered.\nThe point is not just to learn about an interesting\ntheoretical result someone figured out forty years ago,\nbut to show where languages are heading.\nThe unusual thing about Lisp — in fact, the defining\nquality of Lisp — is that it can be written in\nitself. To understand what McCarthy meant by this,\nwe're going to retrace his steps, with his mathematical\nnotation translated into running Common Lisp code." }, { "path": "data/PaulGrahamEssaySmall/rss.txt", "content": "Aaron Swartz created a scraped\nfeed\nof the essays page." }, { "path": "data/PaulGrahamEssaySmall/todo.txt", "content": "April 2012A palliative care nurse called Bronnie Ware made a list of the\nbiggest regrets\nof the dying. Her list seems plausible. I could see\nmyself — can see myself — making at least 4 of these\n5 mistakes.If you had to compress them into a single piece of advice, it might\nbe: don't be a cog. The 5 regrets paint a portrait of post-industrial\nman, who shrinks himself into a shape that fits his circumstances,\nthen turns dutifully till he stops.The alarming thing is, the mistakes that produce these regrets are\nall errors of omission. You forget your dreams, ignore your family,\nsuppress your feelings, neglect your friends, and forget to be\nhappy. Errors of omission are a particularly dangerous type of\nmistake, because you make them by default.I would like to avoid making these mistakes. But how do you avoid\nmistakes you make by default? Ideally you transform your life so\nit has other defaults. But it may not be possible to do that\ncompletely. As long as these mistakes happen by default, you probably\nhave to be reminded not to make them. So I inverted the 5 regrets,\nyielding a list of 5 commands\n\n Don't ignore your dreams; don't work too much; say what you\n think; cultivate friendships; be happy.\n\nwhich I then put at the top of the file I use as a todo list." }, { "path": "data/PaulGrahamEssaySmall/twitter.txt", "content": "April 2009Om Malik is the most recent of many people\nto ask why Twitter is such a big deal.The reason is that it's a new messaging \nprotocol, where you don't specify the recipients.\nNew protocols are rare. Or more precisely, new\nprotocols that take off are.\nThere are only a handful of commonly used ones: TCP/IP \n(the Internet), SMTP (email), HTTP (the web), and so on. So any\nnew protocol is a big deal. But Twitter is a protocol owned\nby a private company. That's even rarer.Curiously, the fact that the founders of Twitter \nhave been slow to monetize it may in the long run\nprove to be an advantage. Because they haven't tried\nto control it too much, Twitter feels to everyone like\nprevious protocols. One forgets it's owned by a\nprivate company. That must have made it easier for\nTwitter to spread." }, { "path": "data/PaulGrahamEssays/13sentences.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\n\nWatch how this essay was\nwritten.\n\n\n\n\nFebruary 2009One of the things I always tell startups is a principle I learned\nfrom Paul Buchheit: it's better to make a few people really happy\nthan to make a lot of people semi-happy. I was saying recently to\na reporter that if I could only tell startups 10 things, this would\nbe one of them. Then I thought: what would the other 9 be?When I made the list there turned out to be 13:\n\n1. Pick good cofounders.Cofounders are for a startup what location is for real estate. You\ncan change anything about a house except where it is. In a startup\nyou can change your idea easily, but changing your cofounders is\nhard. \n[1]\nAnd the success of a startup is almost always a function\nof its founders.2. Launch fast.The reason to launch fast is not so much that it's critical to get\nyour product to market early, but that you haven't really started\nworking on it till you've launched. Launching teaches you what you\nshould have been building. Till you know that you're wasting your\ntime. So the main value of whatever you launch with is as a pretext\nfor engaging users.3. Let your idea evolve.This is the second half of launching fast. Launch fast and iterate.\nIt's a big mistake to treat a startup as if it were merely a matter\nof implementing some brilliant initial idea. As in an essay, most\nof the ideas appear in the implementing.4. Understand your users.You can envision the wealth created by a startup as a rectangle,\nwhere one side is the number of users and the other is how much you\nimprove their lives.\n[2]\nThe second dimension is the one you have\nmost control over. And indeed, the growth in the first will be\ndriven by how well you do in the second. As in science, the hard\npart is not answering questions but asking them: the hard part is\nseeing something new that users lack. The better you understand\nthem the better the odds of doing that. That's why so many successful\nstartups make something the founders needed.5. Better to make a few users love you than a lot ambivalent.Ideally you want to make large numbers of users love you, but you\ncan't expect to hit that right away. Initially you have to choose\nbetween satisfying all the needs of a subset of potential users,\nor satisfying a subset of the needs of all potential users. Take\nthe first. It's easier to expand userwise than satisfactionwise.\nAnd perhaps more importantly, it's harder to lie to yourself. If\nyou think you're 85% of the way to a great product, how do you know\nit's not 70%? Or 10%? Whereas it's easy to know how many users\nyou have.6. Offer surprisingly good customer service.Customers are used to being maltreated. Most of the companies they\ndeal with are quasi-monopolies that get away with atrocious customer\nservice. Your own ideas about what's possible have been unconsciously\nlowered by such experiences. Try making your customer service not\nmerely good, but \nsurprisingly good. Go out of your way to make\npeople happy. They'll be overwhelmed; you'll see. In the earliest\nstages of a startup, it pays to offer customer service on a level\nthat wouldn't scale, because it's a way of learning about your\nusers.7. You make what you measure.I learned this one from Joe Kraus. \n[3]\nMerely measuring something\nhas an uncanny tendency to improve it. If you want to make your\nuser numbers go up, put a big piece of paper on your wall and every\nday plot the number of users. You'll be delighted when it goes up\nand disappointed when it goes down. Pretty soon you'll start\nnoticing what makes the number go up, and you'll start to do more\nof that. Corollary: be careful what you measure.8. Spend little.I can't emphasize enough how important it is for a startup to be cheap.\nMost startups fail before they make something people want, and the\nmost common form of failure is running out of money. So being cheap\nis (almost) interchangeable with iterating rapidly.\n[4]\nBut it's\nmore than that. A culture of cheapness keeps companies young in\nsomething like the way exercise keeps people young.9. Get ramen profitable.\"Ramen profitable\" means a startup makes just enough to pay the\nfounders' living expenses. It's not rapid prototyping for business\nmodels (though it can be), but more a way of hacking the investment\nprocess. Once you cross over into ramen profitable, it completely\nchanges your relationship with investors. It's also great for\nmorale.10. Avoid distractions.Nothing kills startups like distractions. The worst type are those\nthat pay money: day jobs, consulting, profitable side-projects.\nThe startup may have more long-term potential, but you'll always\ninterrupt working on it to answer calls from people paying you now.\nParadoxically, fundraising is this type of distraction, so try to\nminimize that too.11. Don't get demoralized.Though the immediate cause of death in a startup tends to be running\nout of money, the underlying cause is usually lack of focus. Either\nthe company is run by stupid people (which can't be fixed with\nadvice) or the people are smart but got demoralized. Starting a\nstartup is a huge moral weight. Understand this and make a conscious\neffort not to be ground down by it, just as you'd be careful to\nbend at the knees when picking up a heavy box.12. Don't give up.Even if you get demoralized, don't give up. You can get surprisingly\nfar by just not giving up. This isn't true in all fields. There\nare a lot of people who couldn't become good mathematicians no\nmatter how long they persisted. But startups aren't like that.\nSheer effort is usually enough, so long as you keep morphing your\nidea.13. Deals fall through.One of the most useful skills we learned from Viaweb was not getting\nour hopes up. We probably had 20 deals of various types fall\nthrough. After the first 10 or so we learned to treat deals as\nbackground processes that we should ignore till they terminated.\nIt's very dangerous to morale to start to depend on deals closing,\nnot just because they so often don't, but because it makes them\nless likely to.\n\nHaving gotten it down to 13 sentences, I asked myself which I'd\nchoose if I could only keep one.Understand your users. That's the key. The essential task in a\nstartup is to create wealth; the dimension of wealth you have most\ncontrol over is how much you improve users' lives; and the hardest\npart of that is knowing what to make for them. Once you know what\nto make, it's mere effort to make it, and most decent hackers are\ncapable of that.Understanding your users is part of half the principles in this\nlist. That's the reason to launch early, to understand your users.\nEvolving your idea is the embodiment of understanding your users.\nUnderstanding your users well will tend to push you toward making\nsomething that makes a few people deeply happy. The most important\nreason for having surprisingly good customer service is that it\nhelps you understand your users. And understanding your users will\neven ensure your morale, because when everything else is collapsing\naround you, having just ten users who love you will keep you going.Notes[1]\nStrictly speaking it's impossible without a time machine.[2]\nIn practice it's more like a ragged comb.[3]\nJoe thinks one of the founders of Hewlett Packard said it first,\nbut he doesn't remember which.[4]\nThey'd be interchangeable if markets stood still. Since they\ndon't, working twice as fast is better than having twice as much\ntime." }, { "path": "data/PaulGrahamEssays/5founders.txt", "content": "April 2009Inc recently asked me who I thought were the 5 most\ninteresting startup founders of the last 30 years. How do\nyou decide who's the most interesting? The best test seemed\nto be influence: who are the 5\nwho've influenced me most? Who do I use as examples when I'm\ntalking to companies we fund? Who do I find myself quoting?1. Steve JobsI'd guess Steve is the most influential founder not just for me but\nfor most people you could ask. A lot of startup culture is Apple\nculture. He was the original young founder. And while the concept\nof \"insanely great\" already existed in the arts, it was a novel\nidea to introduce into a company in the 1980s.More remarkable still, he's stayed interesting for 30 years. People\nawait new Apple products the way they'd await new books by a popular\nnovelist. Steve may not literally design them, but they wouldn't\nhappen if he weren't CEO.Steve is clever and driven, but so are a lot of people in the Valley.\nWhat makes him unique is his \nsense of \ndesign. Before him, most\ncompanies treated design as a frivolous extra. Apple's competitors\nnow know better.2. TJ RodgersTJ Rodgers isn't as famous as Steve Jobs, but he may be the best\nwriter among Silicon Valley CEOs. I've probably learned more from\nhim about the startup way of thinking than from anyone else. Not\nso much from specific things he's written as by reconstructing the\nmind that produced them: brutally candid; aggressively garbage-collecting\noutdated ideas; and yet driven by pragmatism rather than ideology.The first essay of his that I read was so electrifying that I\nremember exactly where I was at the time. It was \nHigh\nTechnology Innovation: Free Markets or Government Subsidies? and\nI was downstairs in the Harvard Square T Station. It felt as if\nsomeone had flipped on a light switch inside my head.3. Larry & SergeyI'm sorry to treat Larry and Sergey as one person. I've always\nthought that was unfair to them. But it does seem as if Google was a\ncollaboration.Before Google, companies in Silicon Valley already knew it was\nimportant to have the best hackers. So they claimed, at least.\nBut Google pushed this idea further than anyone had before. Their\nhypothesis seems to have been that, in the initial stages at least,\nall you need is good hackers: if you hire all the smartest people\nand put them to work on a problem where their success can be measured,\nyou win. All the other stuff—which includes all the stuff that\nbusiness schools think business consists of—you can figure out\nalong the way. The results won't be perfect, but they'll be optimal.\nIf this was their hypothesis, it's now been verified experimentally.4. Paul BuchheitFew know this, but one person, Paul Buchheit, is responsible for\nthree of the best things Google has done. He was the original\nauthor of GMail, which is the most impressive thing Google has after\nsearch. He also wrote the first prototype of AdSense, and was the\nauthor of Google's mantra \"Don't be evil.\"PB made a point in a talk once that I now mention to every startup\nwe fund: that it's better, initially, to make a small number of\nusers really love you than a large number kind of like you. If I\ncould tell startups only \nten sentences, \nthis would be one of them.Now he's cofounder of a startup called Friendfeed. It's only a\nyear old, but already everyone in the Valley is watching them.\nSomeone responsible for three of the biggest ideas at Google is\ngoing to come up with more.5. Sam AltmanI was told I shouldn't mention founders of YC-funded companies in\nthis list. But Sam Altman can't be stopped by such flimsy rules.\nIf he wants to be on this list, he's going to be.Honestly, Sam is, along with Steve Jobs, the founder I refer to\nmost when I'm advising startups. On questions of design, I ask\n\"What would Steve do?\" but on questions of strategy or ambition I\nask \"What would Sama do?\"What I learned from meeting Sama is that the doctrine of the elect\napplies to startups. It applies way less than most people think:\nstartup investing does not consist of trying to pick winners the\nway you might in a horse race. But there are a few people with\nsuch force of will that they're going to get whatever they want." }, { "path": "data/PaulGrahamEssays/6631327.txt", "content": "March 2006, rev August 2009A couple days ago I found to my surprise that I'd been granted a\npatent.\nIt issued in 2003, but no one told me. I wouldn't know about it\nnow except that a few months ago, while visiting Yahoo, I happened\nto run into a Big Cheese I knew from working there in the late\nnineties. He brought up something called Revenue Loop, which Viaweb\nhad been working on when they bought us.The idea is basically that you sort search results not in order of\ntextual \"relevance\" (as search engines did then) nor in order of\nhow much advertisers bid (as Overture did) but in order of the bid\ntimes the number of transactions. Ordinarily you'd do this for\nshopping searches, though in fact one of the features of our scheme\nis that it automatically detects which searches are shopping searches.If you just order the results in order of bids, you can make the\nsearch results useless, because the first results could be dominated\nby lame sites that had bid the most. But if you order results by\nbid multiplied by transactions, far from selling out, you're getting\na better measure of relevance. What could be a better sign that\nsomeone was satisfied with a search result than going to the site\nand buying something?And, of course, this algorithm automatically maximizes the revenue\nof the search engine.Everyone is focused on this type of approach now, but few were in\n1998. In 1998 it was all about selling banner ads. We didn't know\nthat, so we were pretty excited when we figured out what seemed to\nus the optimal way of doing shopping searches.When Yahoo was thinking of buying us, we had a meeting with Jerry\nYang in New York. For him, I now realize, this was supposed to be\none of those meetings when you check out a company you've pretty\nmuch decided to buy, just to make sure they're ok guys. We weren't\nexpected to do more than chat and seem smart and reasonable. He\nmust have been dismayed when I jumped up to the whiteboard and\nlaunched into a presentation of our exciting new technology.I was just as dismayed when he didn't seem to care at all about it.\nAt the time I thought, \"boy, is this guy poker-faced. We present\nto him what has to be the optimal way of sorting product search\nresults, and he's not even curious.\" I didn't realize till much later\nwhy he didn't care. In 1998, advertisers were overpaying enormously\nfor ads on web sites. \nIn 1998, if advertisers paid the maximum that traffic was worth to\nthem, Yahoo's revenues would have decreased.Things are different now, of course. Now this sort of thing is all\nthe rage. So when I ran into the Yahoo exec I knew from the old\ndays in the Yahoo cafeteria a few months ago, the first thing he\nremembered was not (fortunately) all the fights I had with him, but\nRevenue Loop.\"Well,\" I said, \"I think we actually applied for a patent on it.\nI'm not sure what happened to the application after I left.\"\"Really? That would be an important patent.\"So someone investigated, and sure enough, that patent application\nhad continued in the pipeline for several years after, and finally\nissued in 2003.The main thing that struck me on reading it, actually, is that\nlawyers at some point messed up my nice clear writing. Some clever\nperson with a spell checker reduced one section to Zen-like incomprehensibility:\n\n Also, common spelling errors will tend to get fixed. For example,\n if users searching for \"compact disc player\" end up spending\n considerable money at sites offering compact disc players, then\n those pages will have a higher relevance for that search phrase,\n even though the phrase \"compact disc player\" is not present on\n those pages.\n\n(That \"compat disc player\" wasn't a typo, guys.)For the fine prose of the original, see the provisional application\nof February 1998, back when we were still Viaweb and couldn't afford\nto pay lawyers to turn every \"a lot of\" into \"considerable.\"" }, { "path": "data/PaulGrahamEssays/95.txt", "content": "December 2014American technology companies want the government to make immigration\neasier because they say they can't find enough programmers in the\nUS. Anti-immigration people say that instead of letting foreigners\ntake these jobs, we should train more Americans to be programmers.\nWho's right?The technology companies are right. What the anti-immigration people\ndon't understand is that there is a huge variation in ability between\ncompetent programmers and exceptional ones, and while you can train\npeople to be competent, you can't train them to be exceptional.\nExceptional programmers have an aptitude for and \ninterest in\nprogramming that is not merely the product of training.\n[1]The US has less than 5% of the world's population. Which means if\nthe qualities that make someone a great programmer are evenly\ndistributed, 95% of great programmers are born outside the US.The anti-immigration people have to invent some explanation to\naccount for all the effort technology companies have expended trying\nto make immigration easier. So they claim it's because they want\nto drive down salaries. But if you talk to startups, you find\npractically every one over a certain size has gone through legal\ncontortions to get programmers into the US, where they then\npaid them the same as they'd have paid an American. Why would they\ngo to extra trouble to get programmers for the same price? The\nonly explanation is that they're telling the truth: there are just\nnot enough great programmers to go around.\n[2]I asked the CEO of a startup with about 70 programmers how many\nmore he'd hire if he could get all the great programmers he wanted.\nHe said \"We'd hire 30 tomorrow morning.\" And this is one of the\nhot startups that always win recruiting battles. It's the same all\nover Silicon Valley. Startups are that constrained for talent.It would be great if more Americans were trained as programmers,\nbut no amount of training can flip a ratio as overwhelming as 95\nto 5. Especially since programmers are being trained in other\ncountries too. Barring some cataclysm, it will always be true that\nmost great programmers are born outside the US. It will always be\ntrue that most people who are great at anything are born outside\nthe US.\n[3]Exceptional performance implies immigration. A country with only\na few percent of the world's population will be exceptional in some\nfield only if there are a lot of immigrants working in it.But this whole discussion has taken something for granted: that if\nwe let more great programmers into the US, they'll want to come.\nThat's true now, and we don't realize how lucky we are that it is.\nIf we want to keep this option open, the best way to do it is to\ntake advantage of it: the more of the world's great programmers are\nhere, the more the rest will want to come here.And if we don't, the US could be seriously fucked. I realize that's\nstrong language, but the people dithering about this don't seem to\nrealize the power of the forces at work here. Technology gives the\nbest programmers huge leverage. The world market in programmers\nseems to be becoming dramatically more liquid. And since good\npeople like good colleagues, that means the best programmers could\ncollect in just a few hubs. Maybe mostly in one hub.What if most of the great programmers collected in one hub, and it\nwasn't here? That scenario may seem unlikely now, but it won't be\nif things change as much in the next 50 years as they did in the\nlast 50.We have the potential to ensure that the US remains a technology\nsuperpower just by letting in a few thousand great programmers a\nyear. What a colossal mistake it would be to let that opportunity\nslip. It could easily be the defining mistake this generation of\nAmerican politicians later become famous for. And unlike other\npotential mistakes on that scale, it costs nothing to fix.So please, get on with it.\nNotes[1]\nHow much better is a great programmer than an ordinary one?\nSo much better that you can't even measure the difference directly.\nA great programmer doesn't merely do the same work faster. A great\nprogrammer will invent things an ordinary programmer would never\neven think of. This doesn't mean a great programmer is infinitely\nmore valuable, because any invention has a finite market value.\nBut it's easy to imagine cases where a great programmer might invent\nthings worth 100x or even 1000x an average programmer's salary.[2]\nThere are a handful of consulting firms that rent out big\npools of foreign programmers they bring in on H1-B visas. By all\nmeans crack down on these. It should be easy to write legislation\nthat distinguishes them, because they are so different from technology\ncompanies. But it is dishonest of the anti-immigration people to\nclaim that companies like Google and Facebook are driven by the\nsame motives. An influx of inexpensive but mediocre programmers\nis the last thing they'd want; it would destroy them.[3]\nThough this essay talks about programmers, the group of people\nwe need to import is broader, ranging from designers to programmers\nto electrical engineers. The best one could do as a general term\nmight be \"digital talent.\" It seemed better to make the argument a\nlittle too narrow than to confuse everyone with a neologism.\nThanks to Sam Altman, John Collison, Patrick Collison, Jessica\nLivingston, Geoff Ralston, Fred Wilson, and Qasar Younis for reading\ndrafts of this." }, { "path": "data/PaulGrahamEssays/ace.txt", "content": "December 2020As I was deciding what to write about next, I was surprised to find\nthat two separate essays I'd been planning to write were actually\nthe same.The first is about how to ace your Y Combinator interview. There\nhas been so much nonsense written about this topic that I've been\nmeaning for years to write something telling founders the truth.The second is about something politicians sometimes say — that the\nonly way to become a billionaire is by exploiting people — and why\nthis is mistaken.Keep reading, and you'll learn both simultaneously.I know the politicians are mistaken because it was my job to predict\nwhich people will become billionaires. I think I can truthfully say\nthat I know as much about how to do this as anyone. If the key to\nbecoming a billionaire — the defining feature of billionaires —\nwas to exploit people, then I, as a professional billionaire scout,\nwould surely realize this and look for people who would be good at\nit, just as an NFL scout looks for speed in wide receivers.But aptitude for exploiting people is not what Y Combinator looks\nfor at all. In fact, it's the opposite of what they look for. I'll\ntell you what they do look for, by explaining how to convince \nY Combinator to fund you, and you can see for yourself.What YC looks for, above all, is founders who understand some group\nof users and can make what they want. This is so important that\nit's YC's motto: \"Make something people want.\"A big company can to some extent force unsuitable products on\nunwilling customers, but a startup doesn't have the power to do\nthat. A startup must sing for its supper, by making things that\ngenuinely delight its customers. Otherwise it will never get off\nthe ground.Here's where things get difficult, both for you as a founder and\nfor the YC partners trying to decide whether to fund you. In a\nmarket economy, it's hard to make something people want that they\ndon't already have. That's the great thing about market economies.\nIf other people both knew about this need and were able to satisfy\nit, they already would be, and there would be no room for your\nstartup.Which means the conversation during your YC interview will have to\nbe about something new: either a new need, or a new way to satisfy\none. And not just new, but uncertain. If it were certain that the\nneed existed and that you could satisfy it, that certainty would\nbe reflected in large and rapidly growing revenues, and you wouldn't\nbe seeking seed funding.So the YC partners have to guess both whether you've discovered a\nreal need, and whether you'll be able to satisfy it. That's what they\nare, at least in this part of their job: professional guessers.\nThey have 1001 heuristics for doing this, and I'm not going to tell\nyou all of them, but I'm happy to tell you the most important ones,\nbecause these can't be faked; the only way to \"hack\" them would be\nto do what you should be doing anyway as a founder.The first thing the partners will try to figure out, usually, is\nwhether what you're making will ever be something a lot of people\nwant. It doesn't have to be something a lot of people want now.\nThe product and the market will both evolve, and will influence\neach other's evolution. But in the end there has to be something\nwith a huge market. That's what the partners will be trying to\nfigure out: is there a path to a huge market?\n[1]Sometimes it's obvious there will be a huge market. If \nBoom manages\nto ship an airliner at all, international airlines will have to buy\nit. But usually it's not obvious. Usually the path to a huge market\nis by growing a small market. This idea is important enough that\nit's worth coining a phrase for, so let's call one of these small\nbut growable markets a \"larval market.\"The perfect example of a larval market might be Apple's market when\nthey were founded in 1976. In 1976, not many people wanted their\nown computer. But more and more started to want one, till now every\n10 year old on the planet wants a computer (but calls it a \"phone\").The ideal combination is the group of founders who are \n\"living in\nthe future\" in the sense of being at the leading edge of some kind\nof change, and who are building something they themselves want.\nMost super-successful startups are of this type. Steve Wozniak\nwanted a computer. Mark Zuckerberg wanted to engage online with his\ncollege friends. Larry and Sergey wanted to find things on the web.\nAll these founders were building things they and their peers wanted,\nand the fact that they were at the leading edge of change meant\nthat more people would want these things in the future.But although the ideal larval market is oneself and one's peers,\nthat's not the only kind. A larval market might also be regional,\nfor example. You build something to serve one location, and then\nexpand to others.The crucial feature of the initial market is that it exist. That\nmay seem like an obvious point, but the lack of it is the biggest\nflaw in most startup ideas. There have to be some people who want\nwhat you're building right now, and want it so urgently that they're\nwilling to use it, bugs and all, even though you're a small company\nthey've never heard of. There don't have to be many, but there have\nto be some. As long as you have some users, there are straightforward\nways to get more: build new features they want, seek out more people\nlike them, get them to refer you to their friends, and so on. But\nthese techniques all require some initial seed group of users.So this is one thing the YC partners will almost certainly dig into\nduring your interview. Who are your first users going to be, and\nhow do you know they want this? If I had to decide whether to fund\nstartups based on a single question, it would be \"How do you know\npeople want this?\"The most convincing answer is \"Because we and our friends want it.\"\nIt's even better when this is followed by the news that you've\nalready built a prototype, and even though it's very crude, your\nfriends are using it, and it's spreading by word of mouth. If you\ncan say that and you're not lying, the partners will switch from\ndefault no to default yes. Meaning you're in unless there's some\nother disqualifying flaw.That is a hard standard to meet, though. Airbnb didn't meet it.\nThey had the first part. They had made something they themselves\nwanted. But it wasn't spreading. So don't feel bad if you don't hit\nthis gold standard of convincingness. If Airbnb didn't hit it, it\nmust be too high.In practice, the YC partners will be satisfied if they feel that\nyou have a deep understanding of your users' needs. And the Airbnbs\ndid have that. They were able to tell us all about what motivated\nhosts and guests. They knew from first-hand experience, because\nthey'd been the first hosts. We couldn't ask them a question they\ndidn't know the answer to. We ourselves were not very excited about\nthe idea as users, but we knew this didn't prove anything, because\nthere were lots of successful startups we hadn't been excited about\nas users. We were able to say to ourselves \"They seem to know what\nthey're talking about. Maybe they're onto something. It's not growing\nyet, but maybe they can figure out how to make it grow during YC.\"\nWhich they did, about three weeks into the batch.The best thing you can do in a YC interview is to teach the partners\nabout your users. So if you want to prepare for your interview, one of the best \nways to do it is to go talk to your users and find out exactly what\nthey're thinking. Which is what you should be doing anyway.This may sound strangely credulous, but the YC partners want to\nrely on the founders to tell them about the market. Think about\nhow VCs typically judge the potential market for an idea. They're\nnot ordinarily domain experts themselves, so they forward the idea\nto someone who is, and ask for their opinion. YC doesn't have time\nto do this, but if the YC partners can convince themselves that the\nfounders both (a) know what they're talking about and (b) aren't\nlying, they don't need outside domain experts. They can use the\nfounders themselves as domain experts when evaluating their own\nidea.This is why YC interviews aren't pitches. To give as many founders\nas possible a chance to get funded, we made interviews as short as\nwe could: 10 minutes. That is not enough time for the partners to\nfigure out, through the indirect evidence in a pitch, whether you\nknow what you're talking about and aren't lying. They need to dig\nin and ask you questions. There's not enough time for sequential\naccess. They need random access.\n[2]The worst advice I ever heard about how to succeed in a YC interview\nis that you should take control of the interview and make sure to\ndeliver the message you want to. In other words, turn the interview\ninto a pitch. ⟨elaborate expletive⟩. It is so annoying when people\ntry to do that. You ask them a question, and instead of answering\nit, they deliver some obviously prefabricated blob of pitch. It\neats up 10 minutes really fast.There is no one who can give you accurate advice about what to do\nin a YC interview except a current or former YC partner. People\nwho've merely been interviewed, even successfully, have no idea of\nthis, but interviews take all sorts of different forms depending\non what the partners want to know about most. Sometimes they're all\nabout the founders, other times they're all about the idea. Sometimes\nsome very narrow aspect of the idea. Founders sometimes walk away\nfrom interviews complaining that they didn't get to explain their\nidea completely. True, but they explained enough.Since a YC interview consists of questions, the way to do it well\nis to answer them well. Part of that is answering them candidly.\nThe partners don't expect you to know everything. But if you don't\nknow the answer to a question, don't try to bullshit your way out\nof it. The partners, like most experienced investors, are professional\nbullshit detectors, and you are (hopefully) an amateur bullshitter.\nAnd if you try to bullshit them and fail, they may not even tell\nyou that you failed. So it's better to be honest than to try to\nsell them. If you don't know the answer to a question, say you\ndon't, and tell them how you'd go about finding it, or tell them\nthe answer to some related question.If you're asked, for example, what could go wrong, the worst possible\nanswer is \"nothing.\" Instead of convincing them that your idea is\nbullet-proof, this will convince them that you're a fool or a liar.\nFar better to go into gruesome detail. That's what experts do when\nyou ask what could go wrong. The partners know that your idea is\nrisky. That's what a good bet looks like at this stage: a tiny\nprobability of a huge outcome.Ditto if they ask about competitors. Competitors are rarely what\nkills startups. Poor execution does. But you should know who your\ncompetitors are, and tell the YC partners candidly what your relative\nstrengths and weaknesses are. Because the YC partners know that\ncompetitors don't kill startups, they won't hold competitors against\nyou too much. They will, however, hold it against you if you seem\neither to be unaware of competitors, or to be minimizing the threat\nthey pose. They may not be sure whether you're clueless or lying,\nbut they don't need to be.The partners don't expect your idea to be perfect. This is seed\ninvesting. At this stage, all they can expect are promising hypotheses.\nBut they do expect you to be thoughtful and honest. So if trying\nto make your idea seem perfect causes you to come off as glib or\nclueless, you've sacrificed something you needed for something you\ndidn't.If the partners are sufficiently convinced that there's a path to\na big market, the next question is whether you'll be able to find\nit. That in turn depends on three things: the general qualities of\nthe founders, their specific expertise in this domain, and the\nrelationship between them. How determined are the founders? Are\nthey good at building things? Are they resilient enough to keep\ngoing when things go wrong? How strong is their friendship?Though the Airbnbs only did ok in the idea department, they did\nspectacularly well in this department. The story of how they'd\nfunded themselves by making Obama- and McCain-themed breakfast\ncereal was the single most important factor in our decision to fund\nthem. They didn't realize it at the time, but what seemed to them\nan irrelevant story was in fact fabulously good evidence of their\nqualities as founders. It showed they were resourceful and determined,\nand could work together.It wasn't just the cereal story that showed that, though. The whole\ninterview showed that they cared. They weren't doing this just for\nthe money, or because startups were cool. The reason they were\nworking so hard on this company was because it was their project.\nThey had discovered an interesting new idea, and they just couldn't\nlet it go.Mundane as it sounds, that's the most powerful motivator of all,\nnot just in startups, but in most ambitious undertakings: to be\ngenuinely interested in what \nyou're building. This is what really\ndrives billionaires, or at least the ones who become billionaires\nfrom starting companies. The company is their project.One thing few people realize about billionaires is that all of them\ncould have stopped sooner. They could have gotten acquired, or found\nsomeone else to run the company. Many founders do. The ones who\nbecome really rich are the ones who keep working. And what makes\nthem keep working is not just money. What keeps them working is the\nsame thing that keeps anyone else working when they could stop if\nthey wanted to: that there's nothing else they'd rather do.That, not exploiting people, is the defining quality of people who\nbecome billionaires from starting companies. So that's what YC looks\nfor in founders: authenticity. People's motives for starting startups\nare usually mixed. They're usually doing it from some combination\nof the desire to make money, the desire to seem cool, genuine\ninterest in the problem, and unwillingness to work for someone else.\nThe last two are more powerful motivators than the first two. It's\nok for founders to want to make money or to seem cool. Most do.\nBut if the founders seem like they're doing it just to make money\nor just to seem cool, they're not likely to succeed on a big\nscale. The founders who are doing it for the money will take the\nfirst sufficiently large acquisition offer, and the ones who are\ndoing it to seem cool will rapidly discover that there are much\nless painful ways of seeming cool.\n[3]Y Combinator certainly sees founders whose m.o. is to exploit people.\nYC is a magnet for them, because they want the YC brand. But when\nthe YC partners detect someone like that, they reject them. If bad\npeople made good founders, the YC partners would face a moral\ndilemma. Fortunately they don't, because bad people make bad founders.\nThis exploitative type of founder is not going to succeed on a large\nscale, and in fact probably won't even succeed on a small one,\nbecause they're always going to be taking shortcuts. They see YC\nitself as a shortcut.Their exploitation usually begins with their own cofounders, which\nis disastrous, since the cofounders' relationship is the foundation\nof the company. Then it moves on to the users, which is also\ndisastrous, because the sort of early adopters a successful startup\nwants as its initial users are the hardest to fool. The best this\nkind of founder can hope for is to keep the edifice of deception\ntottering along until some acquirer can be tricked into buying it.\nBut that kind of acquisition is never very big.\n[4]If professional billionaire scouts know that exploiting people is\nnot the skill to look for, why do some politicians think this is\nthe defining quality of billionaires?I think they start from the feeling that it's wrong that one person\ncould have so much more money than another. It's understandable\nwhere that feeling comes from. It's in our DNA, and even in the DNA\nof other species.If they limited themselves to saying that it made them feel bad\nwhen one person had so much more money than other people, who would\ndisagree? It makes me feel bad too, and I think people who make a\nlot of money have a moral obligation to use it for the common good.\nThe mistake they make is to jump from feeling bad that some people\nare much richer than others to the conclusion that there's no\nlegitimate way to make a very large amount of money. Now we're\ngetting into statements that are not only falsifiable, but false.There are certainly some people who become rich by doing bad things.\nBut there are also plenty of people who behave badly and don't make\nthat much from it. There is no correlation — in fact, probably an\ninverse correlation — between how badly you behave and how much\nmoney you make.The greatest danger of this nonsense may not even be that it sends\npolicy astray, but that it misleads ambitious people. Can you imagine\na better way to destroy social mobility than by telling poor kids\nthat the way to get rich is by exploiting people, while the rich\nkids know, from having watched the preceding generation do it, how\nit's really done?I'll tell you how it's really done, so you can at least tell your\nown kids the truth. It's all about users. The most reliable way to\nbecome a billionaire is to start a company that \ngrows fast, and the\nway to grow fast is to make what users want. Newly started startups\nhave no choice but to delight users, or they'll never even get\nrolling. But this never stops being the lodestar, and bigger companies\ntake their eye off it at their peril. Stop delighting users, and\neventually someone else will.Users are what the partners want to\nknow about in YC interviews, and what I want to know about when I\ntalk to founders that we funded ten years ago and who are billionaires\nnow. What do users want? What new things could you build for them?\nFounders who've become billionaires are always eager to talk about\nthat topic. That's how they became billionaires.Notes[1]\nThe YC partners have so much practice doing this that they\nsometimes see paths that the founders themselves haven't seen yet.\nThe partners don't try to seem skeptical, as buyers in transactions\noften do to increase their leverage. Although the founders feel\ntheir job is to convince the partners of the potential of their\nidea, these roles are not infrequently reversed, and the founders\nleave the interview feeling their idea has more potential than they\nrealized.[2]\nIn practice, 7 minutes would be enough. You rarely change your\nmind at minute 8. But 10 minutes is socially convenient.[3]\nI myself took the first sufficiently large acquisition offer\nin my first startup, so I don't blame founders for doing this.\nThere's nothing wrong with starting a startup to make money. You\nneed to make money somehow, and for some people startups are the\nmost efficient way to do it. I'm just saying that these are not the\nstartups that get really big.[4]\nNot these days, anyway. There were some big ones during the\nInternet Bubble, and indeed some big IPOs.Thanks to Trevor Blackwell, Jessica Livingston, Robert Morris, Geoff Ralston, and\nHarj Taggar for reading drafts of this." }, { "path": "data/PaulGrahamEssays/addiction.txt", "content": "July 2010What hard liquor, cigarettes, heroin, and crack have in common is\nthat they're all more concentrated forms of less addictive predecessors.\nMost if not all the things we describe as addictive are. And the\nscary thing is, the process that created them is accelerating.We wouldn't want to stop it. It's the same process that cures\ndiseases: technological progress. Technological progress means\nmaking things do more of what we want. When the thing we want is\nsomething we want to want, we consider technological progress good.\nIf some new technique makes solar cells x% more efficient, that\nseems strictly better. When progress concentrates something we\ndon't want to want—when it transforms opium into heroin—it seems\nbad. But it's the same process at work.\n[1]No one doubts this process is accelerating, which means increasing\nnumbers of things we like will be transformed into things we like\ntoo much.\n[2]As far as I know there's no word for something we like too much.\nThe closest is the colloquial sense of \"addictive.\" That usage has\nbecome increasingly common during my lifetime. And it's clear why:\nthere are an increasing number of things we need it for. At the\nextreme end of the spectrum are crack and meth. Food has been\ntransformed by a combination of factory farming and innovations in\nfood processing into something with way more immediate bang for the\nbuck, and you can see the results in any town in America. Checkers\nand solitaire have been replaced by World of Warcraft and FarmVille.\nTV has become much more engaging, and even so it can't compete with Facebook.The world is more addictive than it was 40 years ago. And unless\nthe forms of technological progress that produced these things are\nsubject to different laws than technological progress in general,\nthe world will get more addictive in the next 40 years than it did\nin the last 40.The next 40 years will bring us some wonderful things. I don't\nmean to imply they're all to be avoided. Alcohol is a dangerous\ndrug, but I'd rather live in a world with wine than one without.\nMost people can coexist with alcohol; but you have to be careful.\nMore things we like will mean more things we have to be careful\nabout.Most people won't, unfortunately. Which means that as the world\nbecomes more addictive, the two senses in which one can live a\nnormal life will be driven ever further apart. One sense of \"normal\"\nis statistically normal: what everyone else does. The other is the\nsense we mean when we talk about the normal operating range of a\npiece of machinery: what works best.These two senses are already quite far apart. Already someone\ntrying to live well would seem eccentrically abstemious in most of\nthe US. That phenomenon is only going to become more pronounced.\nYou can probably take it as a rule of thumb from now on that if\npeople don't think you're weird, you're living badly.Societies eventually develop antibodies to addictive new things.\nI've seen that happen with cigarettes. When cigarettes first\nappeared, they spread the way an infectious disease spreads through\na previously isolated population. Smoking rapidly became a\n(statistically) normal thing. There were ashtrays everywhere. We\nhad ashtrays in our house when I was a kid, even though neither of\nmy parents smoked. You had to for guests.As knowledge spread about the dangers of smoking, customs changed.\nIn the last 20 years, smoking has been transformed from something\nthat seemed totally normal into a rather seedy habit: from something\nmovie stars did in publicity shots to something small huddles of\naddicts do outside the doors of office buildings. A lot of the\nchange was due to legislation, of course, but the legislation\ncouldn't have happened if customs hadn't already changed.It took a while though—on the order of 100 years. And unless the\nrate at which social antibodies evolve can increase to match the\naccelerating rate at which technological progress throws off new\naddictions, we'll be increasingly unable to rely on customs to\nprotect us.\n[3]\nUnless we want to be canaries in the coal mine\nof each new addiction—the people whose sad example becomes a\nlesson to future generations—we'll have to figure out for ourselves\nwhat to avoid and how. It will actually become a reasonable strategy\n(or a more reasonable strategy) to suspect \neverything new.In fact, even that won't be enough. We'll have to worry not just\nabout new things, but also about existing things becoming more\naddictive. That's what bit me. I've avoided most addictions, but\nthe Internet got me because it became addictive while I was using\nit.\n[4]Most people I know have problems with Internet addiction. We're\nall trying to figure out our own customs for getting free of it.\nThat's why I don't have an iPhone, for example; the last thing I\nwant is for the Internet to follow me out into the world.\n[5]\nMy latest trick is taking long hikes. I used to think running was a\nbetter form of exercise than hiking because it took less time. Now\nthe slowness of hiking seems an advantage, because the longer I\nspend on the trail, the longer I have to think without interruption.Sounds pretty eccentric, doesn't it? It always will when you're\ntrying to solve problems where there are no customs yet to guide\nyou. Maybe I can't plead Occam's razor; maybe I'm simply eccentric.\nBut if I'm right about the acceleration of addictiveness, then this\nkind of lonely squirming to avoid it will increasingly be the fate\nof anyone who wants to get things done. We'll increasingly be\ndefined by what we say no to.\nNotes[1]\nCould you restrict technological progress to areas where you\nwanted it? Only in a limited way, without becoming a police state.\nAnd even then your restrictions would have undesirable side effects.\n\"Good\" and \"bad\" technological progress aren't sharply differentiated,\nso you'd find you couldn't slow the latter without also slowing the\nformer. And in any case, as Prohibition and the \"war on drugs\"\nshow, bans often do more harm than good.[2]\nTechnology has always been accelerating. By Paleolithic\nstandards, technology evolved at a blistering pace in the Neolithic\nperiod.[3]\nUnless we mass produce social customs. I suspect the recent\nresurgence of evangelical Christianity in the US is partly a reaction\nto drugs. In desperation people reach for the sledgehammer; if\ntheir kids won't listen to them, maybe they'll listen to God. But\nthat solution has broader consequences than just getting kids to\nsay no to drugs. You end up saying no to \nscience as well.\nI worry we may be heading for a future in which only a few people\nplot their own itinerary through no-land, while everyone else books\na package tour. Or worse still, has one booked for them by the\ngovernment.[4]\nPeople commonly use the word \"procrastination\" to describe\nwhat they do on the Internet. It seems to me too mild to describe\nwhat's happening as merely not-doing-work. We don't call it\nprocrastination when someone gets drunk instead of working.[5]\nSeveral people have told me they like the iPad because it\nlets them bring the Internet into situations where a laptop would\nbe too conspicuous. In other words, it's a hip flask. (This is\ntrue of the iPhone too, of course, but this advantage isn't as\nobvious because it reads as a phone, and everyone's used to those.)Thanks to Sam Altman, Patrick Collison, Jessica Livingston, and\nRobert Morris for reading drafts of this." }, { "path": "data/PaulGrahamEssays/airbnb.txt", "content": "March 2011Yesterday Fred Wilson published a remarkable post about missing\nAirbnb. VCs miss good startups all the time, but it's extraordinarily\nrare for one to talk about it publicly till long afterward. So\nthat post is further evidence what a rare bird Fred is. He's\nprobably the nicest VC I know.Reading Fred's post made me go back and look at the emails I exchanged\nwith him at the time, trying to convince him to invest in Airbnb.\nIt was quite interesting to read. You can see Fred's mind at work \nas he circles the deal.Fred and the Airbnb founders have generously agreed to let me publish\nthis email exchange (with one sentence redacted about something\nthat's strategically important to Airbnb and not an important part\nof the conversation). It's an interesting illustration of an element\nof the startup ecosystem that few except the participants ever see:\ninvestors trying to convince one another to invest in their portfolio\ncompanies. Hundreds if not thousands of conversations of this type\nare happening now, but if one has ever been published, I haven't\nseen it. The Airbnbs themselves never even saw these emails at the\ntime.We do a lot of this behind the scenes stuff at YC, because we invest\nin such a large number of companies, and we invest so early that\ninvestors sometimes need a lot of convincing to see their merits.\nI don't always try as hard as this though. Fred must \nhave found me quite annoying.\n\nfrom: Paul Graham\nto: Fred Wilson, AirBedAndBreakfast Founders\ndate: Fri, Jan 23, 2009 at 11:42 AM\nsubject: meet the airbedsOne of the startups from the batch that just started, AirbedAndBreakfast,\nis in NYC right now meeting their users. (NYC is their biggest\nmarket.) I'd recommend meeting them if your schedule allows.I'd been thinking to myself that though these guys were going to\ndo really well, I should introduce them to angels, because VCs would\nnever go for it. But then I thought maybe I should give you more\ncredit. You'll certainly like meeting them. Be sure to ask about\nhow they funded themselves with breakfast cereal.There's no reason this couldn't be as big as Ebay. And this team\nis the right one to do it.--pgfrom: Brian Chesky\nto: Paul Graham\ncc: Nathan Blecharczyk, Joe Gebbia\ndate: Fri, Jan 23, 2009 at 11:40 AM\nsubject: Re: meet the airbedsPG,Thanks for the intro!Brianfrom: Paul Graham\nto: Brian Chesky\ncc: Nathan Blecharczyk, Joe Gebbia\ndate: Fri, Jan 23, 2009 at 12:38 PM\nsubject: Re: meet the airbedsIt's a longshot, at this stage, but if there was any VC who'd get\nyou guys, it would be Fred. He is the least suburban-golf-playing\nVC I know.He likes to observe startups for a while before acting, so don't\nbe bummed if he seems ambivalent.--pgfrom: Fred Wilson\nto: Paul Graham,\ndate: Sun, Jan 25, 2009 at 5:28 PM\nsubject: Re: meet the airbedsThanks PaulWe are having a bit of a debate inside our partnership about the\nairbed concept. We'll finish that debate tomorrow in our weekly\nmeeting and get back to you with our thoughtsThanksFredfrom: Paul Graham\nto: Fred Wilson\ndate: Sun, Jan 25, 2009 at 10:48 PM\nsubject: Re: meet the airbedsI'd recommend having the debate after meeting them instead of before.\nWe had big doubts about this idea, but they vanished on meeting the\nguys.from: Fred Wilson\nto: Paul Graham\ndate: Mon, Jan 26, 2009 at 11:08 AM\nsubject: RE: meet the airbedsWe are still very suspect of this idea but will take a meeting as\nyou suggestThanksfredfrom: Fred Wilson\nto: Paul Graham, AirBedAndBreakfast Founders\ndate: Mon, Jan 26, 2009 at 11:09 AM\nsubject: RE: meet the airbedsAirbed team -Are you still in NYC?We'd like to meet if you areThanksfredfrom: Paul Graham\nto: Fred Wilson\ndate: Mon, Jan 26, 2009 at 1:42 PM\nsubject: Re: meet the airbedsIdeas can morph. Practically every really big startup could say,\nfive years later, \"believe it or not, we started out doing ___.\"\nIt just seemed a very good sign to me that these guys were actually\non the ground in NYC hunting down (and understanding) their users.\nOn top of several previous good signs.--pgfrom: Fred Wilson\nto: Paul Graham\ndate: Sun, Feb 1, 2009 at 7:15 AM\nsubject: Re: meet the airbedsIt's interestingOur two junior team members were enthusiasticThe three \"old guys\" didn't get itfrom: Paul Graham\nto: Fred Wilson\ndate: Mon, Feb 9, 2009 at 5:58 PM\nsubject: airbnbThe Airbeds just won the first poll among all the YC startups in\ntheir batch by a landslide. In the past this has not been a 100%\nindicator of success (if only anything were) but much better than\nrandom.--pgfrom: Fred Wilson\nto: Paul Graham\ndate: Fri, Feb 13, 2009 at 5:29 PM\nsubject: Re: airbnbI met them todayThey have an interesting businessI'm just not sure how big it's going to befredfrom: Paul Graham\nto: Fred Wilson\ndate: Sat, Feb 14, 2009 at 9:50 AM\nsubject: Re: airbnbDid they explain the long-term goal of being the market in accommodation\nthe way eBay is in stuff? That seems like it would be huge. Hotels\nnow are like airlines in the 1970s before they figured out how to\nincrease their load factors.from: Fred Wilson\nto: Paul Graham\ndate: Tue, Feb 17, 2009 at 2:05 PM\nsubject: Re: airbnbThey did but I am not sure I buy thatABNB reminds me of Etsy in that it facilitates real commerce in a\nmarketplace model directly between two peopleSo I think it can scale all the way to the bed and breakfast marketBut I am not sure they can take on the hotel marketI could be wrongBut even so, if you include short term room rental, second home\nrental, bed and breakfast, and other similar classes of accommodations,\nyou get to a pretty big opportunityfredfrom: Paul Graham\nto: Fred Wilson\ndate: Wed, Feb 18, 2009 at 12:21 AM\nsubject: Re: airbnbSo invest in them! They're very capital efficient. They would\nmake an investor's money go a long way.It's also counter-cyclical. They just arrived back from NYC, and\nwhen I asked them what was the most significant thing they'd observed,\nit was how many of their users actually needed to do these rentals\nto pay their rents.--pgfrom: Fred Wilson\nto: Paul Graham\ndate: Wed, Feb 18, 2009 at 2:21 AM\nsubject: Re: airbnbThere's a lot to likeI've done a few things, like intro it to my friends at Foundry who\nwere investors in Service Metrics and understand this modelI am also talking to my friend Mark Pincus who had an idea like\nthis a few years ago.So we are working on itThanks for the leadFredfrom: Paul Graham\nto: Fred Wilson\ndate: Fri, Feb 20, 2009 at 10:00 PM\nsubject: airbnb already spreading to prosI know you're skeptical they'll ever get hotels, but there's a\ncontinuum between private sofas and hotel rooms, and they just moved\none step further along it.[link to an airbnb user]This is after only a few months. I bet you they will get hotels\neventually. It will start with small ones. Just wait till all the\n10-room pensiones in Rome discover this site. And once it spreads\nto hotels, where is the point (in size of chain) at which it stops?\nOnce something becomes a big marketplace, you ignore it at your\nperil.--pgfrom: Fred Wilson\nto: Paul Graham\ndate: Sat, Feb 21, 2009 at 4:26 AM\nsubject: Re: airbnb already spreading to prosThat's true. It's also true that there are quite a few marketplaces\nout there that serve this same marketIf you look at many of the people who list at ABNB, they list\nelsewhere tooI am not negative on this one, I am interested, but we are still\nin the gathering data phase.fred\n" }, { "path": "data/PaulGrahamEssays/airbnbs.txt", "content": "December 2020To celebrate Airbnb's IPO and to help future founders, I thought\nit might be useful to explain what was special about Airbnb.What was special about the Airbnbs was how earnest they were. They\ndid nothing half-way, and we could sense this even in the interview.\nSometimes after we interviewed a startup we'd be uncertain what to\ndo, and have to talk it over. Other times we'd just look at one\nanother and smile. The Airbnbs' interview was that kind. We didn't\neven like the idea that much. Nor did users, at that stage; they\nhad no growth. But the founders seemed so full of energy that it\nwas impossible not to like them.That first impression was not misleading. During the batch our\nnickname for Brian Chesky was The Tasmanian Devil, because like the\ncartoon\ncharacter he seemed a tornado of energy. All three of them were\nlike that. No one ever worked harder during YC than the Airbnbs\ndid. When you talked to the Airbnbs, they took notes. If you suggested\nan idea to them in office hours, the next time you talked to them\nthey'd not only have implemented it, but also implemented two new\nideas they had in the process. \"They probably have the best attitude\nof any startup we've funded\" I wrote to Mike Arrington during the\nbatch.They're still like that. Jessica and I had dinner with Brian in the\nsummer of 2018, just the three of us. By this point the company is\nten years old. He took a page of notes about ideas for new things\nAirbnb could do.What we didn't realize when we first met Brian and Joe and Nate was\nthat Airbnb was on its last legs. After working on the company for\na year and getting no growth, they'd agreed to give it one last\nshot. They'd try this Y Combinator thing, and if the company still\ndidn't take off, they'd give up.Any normal person would have given up already. They'd been funding\nthe company with credit cards. They had a binder full of\ncredit cards they'd maxed out. Investors didn't think much of the\nidea. One investor they met in a cafe walked out in the middle of\nmeeting with them. They thought he was going to the bathroom, but\nhe never came back. \"He didn't even finish his smoothie,\" Brian\nsaid. And now, in late 2008, it was the worst recession in decades.\nThe stock market was in free fall and wouldn't hit bottom for another\nfour months.Why hadn't they given up? This is a useful question to ask. People,\nlike matter, reveal their nature under extreme conditions. One thing\nthat's clear is that they weren't doing this just for the money.\nAs a money-making scheme, this was pretty lousy: a year's work and\nall they had to show for it was a binder full of maxed-out credit\ncards. So why were they still working on this startup? Because of\nthe experience they'd had as the first hosts.When they first tried renting out airbeds on their floor during a\ndesign convention, all they were hoping for was to make enough money\nto pay their rent that month. But something surprising happened:\nthey enjoyed having those first three guests staying with them. And\nthe guests enjoyed it too. Both they and the guests had done it\nbecause they were in a sense forced to, and yet they'd all had a\ngreat experience. Clearly there was something new here: for hosts,\na new way to make money that had literally been right under their\nnoses, and for guests, a new way to travel that was in many ways\nbetter than hotels.That experience was why the Airbnbs didn't give up. They knew they'd\ndiscovered something. They'd seen a glimpse of the future, and they\ncouldn't let it go.They knew that once people tried staying in what is now called \"an\nairbnb,\" they would also realize that this was the future. But only\nif they tried it, and they weren't. That was the problem during Y\nCombinator: to get growth started.Airbnb's goal during YC was to reach what we call ramen profitability,\nwhich means making enough money that the company can pay the founders'\nliving expenses, if they live on ramen noodles. Ramen profitability\nis not, obviously, the end goal of any startup, but it's the most\nimportant threshold on the way, because this is the point where\nyou're airborne. This is the point where you no longer need investors'\npermission to continue existing. For the Airbnbs, ramen profitability\nwas $4000 a month: $3500 for rent, and $500 for food. They taped\nthis goal to the mirror in the bathroom of their apartment.The way to get growth started in something like Airbnb is to focus\non the hottest subset of the market. If you can get growth started\nthere, it will spread to the rest. When I asked the Airbnbs where\nthere was most demand, they knew from searches: New York City. So\nthey focused on New York. They went there in person to visit their\nhosts and help them make their listings more attractive. A big part\nof that was better pictures. So Joe and Brian rented a professional\ncamera and took pictures of the hosts' places themselves.This didn't just make the listings better. It also taught them about\ntheir hosts. When they came back from their first trip to New York,\nI asked what they'd noticed about hosts that surprised them, and\nthey said the biggest surprise was how many of the hosts were in\nthe same position they'd been in: they needed this money to pay\ntheir rent. This was, remember, the worst recession in decades, and\nit had hit New York first. It definitely added to the Airbnbs' sense\nof mission to feel that people needed them.In late January 2009, about three weeks into Y Combinator, their\nefforts started to show results, and their numbers crept upward.\nBut it was hard to say for sure whether it was growth or just random\nfluctuation. By February it was clear that it was real growth. They\nmade $460 in fees in the first week of February, $897 in the second,\nand $1428 in the third. That was it: they were airborne. Brian sent\nme an email on February 22 announcing that they were ramen profitable\nand giving the last three weeks' numbers.\"I assume you know what you've now set yourself up for next week,\"\nI responded.Brian's reply was seven words: \"We are not going to slow down.\"" }, { "path": "data/PaulGrahamEssays/alien.txt", "content": "October 2022If there were intelligent beings elsewhere in the universe, they'd\r\nshare certain truths in common with us. The truths of mathematics\r\nwould be the same, because they're true by definition. Ditto for\r\nthe truths of physics; the mass of a carbon atom would be the same\r\non their planet. But I think we'd share other truths with aliens\r\nbesides the truths of math and physics, and that it would be\r\nworthwhile to think about what these might be.For example, I think we'd share the principle that a controlled\r\nexperiment testing some hypothesis entitles us to have proportionally\r\nincreased belief in it. It seems fairly likely, too, that it would\r\nbe true for aliens that one can get better at something by practicing.\r\nWe'd probably share Occam's razor. There doesn't seem anything\r\nspecifically human about any of these ideas.We can only guess, of course. We can't say for sure what forms\r\nintelligent life might take. Nor is it my goal here to explore that\r\nquestion, interesting though it is. The point of the idea of alien\r\ntruth is not that it gives us a way to speculate about what forms\r\nintelligent life might take, but that it gives us a threshold, or\r\nmore precisely a target, for truth. If you're trying to find the\r\nmost general truths short of those of math or physics, then presumably\r\nthey'll be those we'd share in common with other forms of intelligent\r\nlife.Alien truth will work best as a heuristic if we err on the side of\r\ngenerosity. If an idea might plausibly be relevant to aliens, that's\r\nenough. Justice, for example. I wouldn't want to bet that all\r\nintelligent beings would understand the concept of justice, but I\r\nwouldn't want to bet against it either.The idea of alien truth is related to Erdos's idea of God's book.\r\nHe used to describe a particularly good proof as being in God's\r\nbook, the implication being (a) that a sufficiently good proof was\r\nmore discovered than invented, and (b) that its goodness would be\r\nuniversally recognized. If there's such a thing as alien truth,\r\nthen there's more in God's book than math.What should we call the search for alien truth? The obvious choice\r\nis \"philosophy.\" Whatever else philosophy includes, it should\r\nprobably include this. I'm fairly sure Aristotle would have thought\r\nso. One could even make the case that the search for alien truth\r\nis, if not an accurate description of philosophy, a good\r\ndefinition for it. I.e. that it's what people who call\r\nthemselves philosophers should be doing, whether or not they currently\r\nare. But I'm not wedded to that; doing it is what matters, not what\r\nwe call it.We may one day have something like alien life among us in the form\r\nof AIs. And that may in turn allow us to be precise about what\r\ntruths an intelligent being would have to share with us. We might\r\nfind, for example, that it's impossible to create something we'd\r\nconsider intelligent that doesn't use Occam's razor. We might one\r\nday even be able to prove that. But though this sort of research\r\nwould be very interesting, it's not necessary for our purposes, or\r\neven the same field; the goal of philosophy, if we're going to call it that, would be\r\nto see what ideas we come up with using alien truth as a target,\r\nnot to say precisely where the threshold of it is. Those two questions might one\r\nday converge, but they'll converge from quite different directions,\r\nand till they do, it would be too constraining to restrict ourselves\r\nto thinking only about things we're certain would be alien truths.\r\nEspecially since this will probably be one of those areas where the\r\nbest guesses turn out to be surprisingly close to optimal. (Let's\r\nsee if that one does.)Whatever we call it, the attempt to discover alien truths would be\r\na worthwhile undertaking. And curiously enough, that is itself\r\nprobably an alien truth.Thanks to Trevor Blackwell, Greg Brockman, \r\nPatrick Collison, Robert Morris, and Michael Nielsen for reading drafts of this." }, { "path": "data/PaulGrahamEssays/altair.txt", "content": "February 2015One of the most valuable exercises you can try if you want to\nunderstand startups is to look at the most successful companies and\nexplain why they were not as lame as they seemed when they first\nlaunched. Because they practically all seemed lame at first. Not\njust small, lame. Not just the first step up a big mountain. More\nlike the first step into a swamp.A Basic interpreter for the Altair? How could that ever grow into\na giant company? People sleeping on airbeds in strangers' apartments?\nA web site for college students to stalk one another? A wimpy\nlittle single-board computer for hobbyists that used a TV as a\nmonitor? A new search engine, when there were already about 10,\nand they were all trying to de-emphasize search? These ideas didn't\njust seem small. They seemed wrong. They were the kind of ideas\nyou could not merely ignore, but ridicule.Often the founders themselves didn't know why their ideas were\npromising. They were attracted to these ideas by instinct, because\nthey were living in the future and\nthey sensed that something was missing. But they could not have\nput into words exactly how their ugly ducklings were going to grow\ninto big, beautiful swans.Most people's first impulse when they hear about a lame-sounding\nnew startup idea is to make fun of it. Even a lot of people who\nshould know better.When I encounter a startup with a lame-sounding idea, I ask \"What\nMicrosoft is this the Altair Basic of?\" Now it's a puzzle, and the\nburden is on me to solve it. Sometimes I can't think of an answer,\nespecially when the idea is a made-up one. But it's remarkable how\noften there does turn out to be an answer. Often it's one the\nfounders themselves hadn't seen yet.Intriguingly, there are sometimes multiple answers. I talked to a\nstartup a few days ago that could grow into 3 distinct Microsofts.\nThey'd probably vary in size by orders of magnitude. But you can\nnever predict how big a Microsoft is going to be, so in cases like\nthat I encourage founders to follow whichever path is most immediately\nexciting to them. Their instincts got them this far. Why stop now?" }, { "path": "data/PaulGrahamEssays/ambitious.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nMarch 2012One of the more surprising things I've noticed while working\non Y Combinator is how frightening the most ambitious startup\nideas are. In this essay I'm going to demonstrate\nthis phenomenon by describing some. Any one of them\ncould make you a billionaire. That might sound like an attractive\nprospect, and yet when I describe these ideas you may\nnotice you find yourself shrinking away from them.Don't worry, it's not a sign of weakness. Arguably it's a sign of\nsanity. The biggest startup ideas are terrifying. And not just\nbecause they'd be a lot of work. The biggest ideas seem to threaten\nyour identity: you wonder if you'd have enough ambition to carry\nthem through.There's a scene in Being John Malkovich where the nerdy hero\nencounters a very attractive, sophisticated woman. She says to\nhim:\n\n Here's the thing: If you ever got me, you wouldn't have a clue\n what to do with me.\n\nThat's what these ideas say to us.This phenomenon is one of the most important things you can understand\nabout startups. \n[1]\nYou'd expect big startup ideas to be\nattractive, but actually they tend to repel you. And that has a\nbunch of consequences. It means these ideas are invisible to most\npeople who try to think of startup ideas, because their subconscious\nfilters them out. Even the most ambitious people are probably best\noff approaching them obliquely.1. A New Search EngineThe best ideas are just on the right side of impossible. I don't\nknow if this one is possible, but there are signs it might be.\nMaking a new search engine means competing with Google, and recently\nI've noticed some cracks in their fortress.The point when it became clear to me that Microsoft had lost their\nway was when they decided to get into the search business. That\nwas not a natural move for Microsoft. They did it because they\nwere afraid of Google, and Google was in the search business. But\nthis meant (a) Google was now setting Microsoft's agenda, and (b)\nMicrosoft's agenda consisted of stuff they weren't good at.Microsoft : Google :: Google : Facebook.That does not by itself mean\nthere's room for a new search engine, but lately when using Google\nsearch I've found myself nostalgic for the old days, when\nGoogle was true to its own slightly aspy self. Google used to give\nme a page of the right answers, fast, with no clutter. Now the\nresults seem inspired by the Scientologist principle that what's\ntrue is what's true for you. And the pages don't have the\nclean, sparse feel they used to. Google search results used to\nlook like the output of a Unix utility. Now if I accidentally put\nthe cursor in the wrong place, anything might happen.The way to win here is to build the search engine all the hackers\nuse. A search engine whose users consisted of the top 10,000 hackers\nand no one else would be in a very powerful position despite its\nsmall size, just as Google was when it was that search engine. And\nfor the first time in over a decade the idea of switching seems\nthinkable to me.Since anyone capable of starting this company is one of those 10,000\nhackers, the route is at least straightforward: make the search\nengine you yourself want. Feel free to make it excessively hackerish.\nMake it really good for code search, for example. Would you like\nsearch queries to be Turing complete? Anything that gets you those\n10,000 users is ipso facto good.Don't worry if something you want to do will constrain you in the\nlong term, because if you don't get that initial core of users,\nthere won't be a long term. If you can just build something that\nyou and your friends genuinely prefer to Google, you're already\nabout 10% of the way to an IPO, just as Facebook was (though they\nprobably didn't realize it) when they got all the Harvard undergrads.2. Replace EmailEmail was not designed to be used the way we use it now. Email is\nnot a messaging protocol. It's a todo list. Or rather, my inbox\nis a todo list, and email is the way things get onto it. But it\nis a disastrously bad todo list.I'm open to different types of solutions to this problem, but I\nsuspect that tweaking the inbox is not enough, and that email has\nto be replaced with a new protocol. \nThis new protocol should be a todo list protocol, not\na messaging protocol, although there is a degenerate case where\nwhat someone wants you to do is: read the following text.As a todo list protocol, the new protocol should give more power\nto the recipient than email does. I want there to be more restrictions\non what someone can put on my todo list. And when someone can put\nsomething on my todo list, I want them to tell me more about what\nthey want from me. Do they want me to do something beyond just\nreading some text? How important is it? (There obviously has to\nbe some mechanism to prevent people from saying everything is\nimportant.) When does it have to be done?This is one of those ideas that's like an irresistible force meeting\nan immovable object. On one hand, entrenched protocols are impossible\nto replace. On the other, it seems unlikely that people in\n100 years will still be living in the same email hell we do now.\nAnd if email is going to get replaced eventually, why not now?If you do it right, you may be able to avoid the usual chicken \nand egg problem new protocols face, because some of the most powerful\npeople in the world will be among the first to switch to it. \nThey're all at the mercy of email too.Whatever you build, make it fast. GMail has become painfully slow.\n[2]\nIf you made something no better than GMail, but fast, that\nalone would let you start to pull users away from GMail.GMail is slow because Google can't afford to spend a lot on it.\nBut people will pay for this. I'd have no problem paying $50 a month.\nConsidering how much time I spend in email, it's kind of scary to\nthink how much I'd be justified in paying. At least $1000 a month.\nIf I spend several hours a day reading and writing email, that would\nbe a cheap way to make my life better.3. Replace UniversitiesPeople are all over this idea lately, and I think they're onto\nsomething. I'm reluctant to suggest that an institution that's\nbeen around for a millennium is finished just because of some mistakes\nthey made in the last few decades, but certainly in the last few\ndecades US universities seem to have been headed down the wrong\npath. One could do a lot better for a lot less money.I don't think universities will disappear. They won't be replaced\nwholesale. They'll just lose the de facto monopoly on certain types\nof learning that they once had. There will be many different ways\nto learn different things, and some may look quite different from\nuniversities. Y Combinator itself is arguably one of them.Learning is such a big problem that changing the way people do it\nwill have a wave of secondary effects. For example, the name of\nthe university one went to is treated by a lot of people (correctly\nor not) as a credential in its own right. If learning breaks up\ninto many little pieces, credentialling may separate from it. There\nmay even need to be replacements for campus social life (and oddly\nenough, YC even has aspects of that).You could replace high schools too, but there you face bureaucratic\nobstacles that would slow down a startup. Universities seem the\nplace to start.4. Internet DramaHollywood has been slow to embrace the Internet. That was a \nmistake, because I think we can now call a winner in the race between\ndelivery mechanisms, and it is the Internet, not cable.A lot of the reason is the horribleness of cable clients, also known\nas TVs. Our family didn't wait for Apple TV. We hated our last\nTV so much that a few months ago we replaced it with an iMac bolted\nto the wall. It's a little inconvenient to control it with a\nwireless mouse, but the overall experience is much better than the\nnightmare UI we had to deal with before.Some of the attention people currently devote to watching\nmovies and TV can be stolen by things that seem completely unrelated,\nlike social networking apps. More can be stolen by things that are\na little more closely related, like games. But there will probably\nalways remain some residual demand for conventional drama, where\nyou sit passively and watch as a plot happens. So how do you deliver\ndrama via the Internet? Whatever you make will have to be on a\nlarger scale than Youtube clips. When people sit down to watch a\nshow, they want to know what they're going to get: either part\nof a series with familiar characters, or a single longer \"movie\"\nwhose basic premise they know in advance.There are two ways delivery and payment could play out. Either\nsome company like Netflix or Apple will be the app store for\nentertainment, and you'll reach audiences through them. Or the\nwould-be app stores will be too overreaching, or too technically\ninflexible, and companies will arise to supply payment and streaming\na la carte to the producers of drama. If that's the way things\nplay out, there will also be a need for such infrastructure companies.5. The Next Steve JobsI was talking recently to someone who knew Apple well, and I asked\nhim if the people now running the company would be able to keep\ncreating new things the way Apple had under Steve Jobs. His answer\nwas simply \"no.\" I already feared that would be the answer. I\nasked more to see how he'd qualify it. But he didn't qualify it\nat all. No, there will be no more great new stuff beyond whatever's\ncurrently in the pipeline. Apple's\nrevenues may continue to rise for a long time, but as Microsoft\nshows, revenue is a lagging indicator in the technology business.So if Apple's not going to make the next iPad, who is? None of the\nexisting players. None of them are run by product visionaries, and\nempirically you can't seem to get those by hiring them. Empirically\nthe way you get a product visionary as CEO is for him to found the\ncompany and not get fired. So the company that creates the next\nwave of hardware is probably going to have to be a startup.I realize it sounds preposterously ambitious for a startup to try\nto become as big as Apple. But no more ambitious than it was for\nApple to become as big as Apple, and they did it. Plus a startup\ntaking on this problem now has an advantage the original Apple\ndidn't: the example of Apple. Steve Jobs has shown us what's\npossible. That helps would-be successors both directly, as Roger\nBannister did, by showing how much better you can do than people\ndid before, and indirectly, as Augustus did, by lodging the idea\nin users' minds that a single person could unroll the future \nfor them. \n[3]Now Steve is gone there's a vacuum we can all feel. If a new company\nled boldly into the future of hardware, users would follow. The\nCEO of that company, the \"next Steve Jobs,\" might not measure up\nto Steve Jobs. But he wouldn't have to. He'd just have to do a\nbetter job than Samsung and HP and Nokia, and that seems pretty\ndoable.6. Bring Back Moore's LawThe last 10 years have reminded us what Moore's Law actually says.\nTill about 2002 you could safely misinterpret it as promising that\nclock speeds would double every 18 months. Actually what it says\nis that circuit densities will double every 18 months. It used to\nseem pedantic to point that out. Not any more. Intel can no longer\ngive us faster CPUs, just more of them.This Moore's Law is not as good as the old one. Moore's Law used\nto mean that if your software was slow, all you had to do was wait,\nand the inexorable progress of hardware would solve your problems.\nNow if your software is slow you have to rewrite it to do more\nthings in parallel, which is a lot more work than waiting.It would be great if a startup could give us something of the old\nMoore's Law back, by writing software that could make a large number\nof CPUs look to the developer like one very fast CPU. There are\nseveral ways to approach this problem. The most ambitious is to\ntry to do it automatically: to write a compiler that will parallelize\nour code for us. There's a name for this compiler, the sufficiently\nsmart compiler, and it is a byword for impossibility. But is\nit really impossible? Is there no configuration of the bits in\nmemory of a present day computer that is this compiler? If you\nreally think so, you should try to prove it, because that would be\nan interesting result. And if it's not impossible but simply very\nhard, it might be worth trying to write it. The expected value\nwould be high even if the chance of succeeding was low.The reason the expected value is so high is web services. If you\ncould write software that gave programmers the convenience of the\nway things were in the old days, you could offer it to them as a\nweb service. And that would in turn mean that you got practically\nall the users.Imagine there was another processor manufacturer that could still translate\nincreased circuit densities into increased clock speeds. They'd\ntake most of Intel's business. And since web services mean that\nno one sees their processors anymore, by writing the sufficiently\nsmart compiler you could create a situation indistinguishable from\nyou being that manufacturer, at least for the server market.The least ambitious way of approaching the problem is to start from\nthe other end, and offer programmers more parallelizable Lego blocks\nto build programs out of, like Hadoop and MapReduce. Then the\nprogrammer still does much of the work of optimization.There's an intriguing middle ground where you build a semi-automatic\nweapon—where there's a human in the loop. You make something\nthat looks to the user like the sufficiently smart compiler, but\ninside has people, using highly developed optimization tools to\nfind and eliminate bottlenecks in users' programs. These people\nmight be your employees, or you might create a marketplace for\noptimization.An optimization marketplace would be a way to generate the sufficiently\nsmart compiler piecemeal, because participants would immediately\nstart writing bots. It would be a curious state of affairs if you\ncould get to the point where everything could be done by bots,\nbecause then you'd have made the sufficiently smart compiler, but\nno one person would have a complete copy of it.I realize how crazy all this sounds. In fact, what I like about\nthis idea is all the different ways in which it's wrong. The whole\nidea of focusing on optimization is counter to the general trend\nin software development for the last several decades. Trying to\nwrite the sufficiently smart compiler is by definition a mistake.\nAnd even if it weren't, compilers are the sort of software that's\nsupposed to be created by open source projects, not companies. Plus\nif this works it will deprive all the programmers who take pleasure\nin making multithreaded apps of so much amusing complexity. The\nforum troll I have by now internalized doesn't even know where to\nbegin in raising objections to this project. Now that's what I\ncall a startup idea.7. Ongoing DiagnosisBut wait, here's another that could face even greater resistance:\nongoing, automatic medical diagnosis.One of my tricks for generating startup ideas is to imagine the\nways in which we'll seem backward to future generations. And I'm\npretty sure that to people 50 or 100 years in the future, it will\nseem barbaric that people in our era waited till they had symptoms\nto be diagnosed with conditions like heart disease and cancer.For example, in 2004 Bill Clinton found he was feeling short of\nbreath. Doctors discovered that several of his arteries were over\n90% blocked and 3 days later he had a quadruple bypass. It seems\nreasonable to assume Bill Clinton has the best medical care available.\nAnd yet even he had to wait till his arteries were over 90% blocked\nto learn that the number was over 90%. Surely at some point in the\nfuture we'll know these numbers the way we now know something like\nour weight. Ditto for cancer. It will seem preposterous to future\ngenerations that we wait till patients have physical symptoms to\nbe diagnosed with cancer. Cancer will show up on some sort of radar\nscreen immediately.(Of course, what shows up on the radar screen may be different from\nwhat we think of now as cancer. I wouldn't be surprised if at any\ngiven time we have ten or even hundreds of microcancers going at\nonce, none of which normally amount to anything.)A lot of the obstacles to ongoing diagnosis will come from the fact\nthat it's going against the grain of the medical profession. The\nway medicine has always worked is that patients come to doctors\nwith problems, and the doctors figure out what's wrong. A lot of\ndoctors don't like the idea of going on the medical equivalent of\nwhat lawyers call a \"fishing expedition,\" where you go looking for\nproblems without knowing what you're looking for. They call the\nthings that get discovered this way \"incidentalomas,\" and they are\nsomething of a nuisance.For example, a friend of mine once had her brain scanned as part\nof a study. She was horrified when the doctors running the study\ndiscovered what appeared to be a large tumor. After further testing,\nit turned out to be a harmless cyst. But it cost her a few days\nof terror. A lot of doctors worry that if you start scanning people\nwith no symptoms, you'll get this on a giant scale: a huge number\nof false alarms that make patients panic and require expensive and\nperhaps even dangerous tests to resolve. But I think that's just\nan artifact of current limitations. If people were scanned all the\ntime and we got better at deciding what was a real problem, my\nfriend would have known about this cyst her whole life and known\nit was harmless, just as we do a birthmark.There is room for a lot of startups here. \nIn addition to the technical obstacles all\nstartups face, and the bureaucratic obstacles all medical startups\nface, they'll be going against thousands of years of medical\ntradition. But it will happen, and it will be a great thing—so\ngreat that people in the future will feel as sorry for us as we do\nfor the generations that lived before anaesthesia and antibiotics.TacticsLet me conclude with some tactical advice. If you want to take on\na problem as big as the ones I've discussed, don't make a direct\nfrontal attack on it. Don't say, for example, that you're going\nto replace email. If you do that you raise too many expectations.\nYour employees and investors will constantly be asking \"are we there\nyet?\" and you'll have an army of haters waiting to see you fail.\nJust say you're building todo-list software. That sounds harmless.\nPeople can notice you've replaced email when it's a fait accompli.\n[4]Empirically, the way to do really big things seems to be to start\nwith deceptively small things. Want to dominate microcomputer\nsoftware? Start by writing a Basic interpreter for a machine with\na few thousand users. Want to make the universal web site? Start\nby building a site for Harvard undergrads to stalk one another.Empirically, it's not just for other people that you need to start\nsmall. You need to for your own sake. Neither Bill Gates nor Mark\nZuckerberg knew at first how big their companies were going to get.\nAll they knew was that they were onto something. Maybe it's a bad\nidea to have really big ambitions initially, because the bigger\nyour ambition, the longer it's going to take, and the further you\nproject into the future, the more likely you'll get it wrong.I think the way to use these big ideas is not to try to identify a\nprecise point in the future and then ask yourself how to get from\nhere to there, like the popular image of a visionary. You'll be\nbetter off if you operate like Columbus and just head in a general\nwesterly direction. Don't try to construct the future like a\nbuilding, because your current blueprint is almost certainly mistaken.\nStart with something you know works, and when you expand, expand\nwestward.The popular image of the visionary is someone with a clear view of\nthe future, but empirically it may be better to have a blurry one.Notes[1]\nIt's also one of the most important things VCs fail to\nunderstand about startups. Most expect founders to walk in with a\nclear plan for the future, and judge them based on that. Few\nconsciously realize that in the biggest successes there is the least\ncorrelation between the initial plan and what the startup eventually\nbecomes.[2]\nThis sentence originally read \"GMail is painfully slow.\"\nThanks to Paul Buchheit for the correction.[3]\nRoger Bannister is famous as the first person to run a mile\nin under 4 minutes. But his world record only lasted 46 days. Once\nhe showed it could be done, lots of others followed. Ten years\nlater Jim Ryun ran a 3:59 mile as a high school junior.[4]\nIf you want to be the next Apple, maybe you don't even want to start\nwith consumer electronics. Maybe at first you make something hackers\nuse. Or you make something popular but apparently unimportant,\nlike a headset or router. All you need is a bridgehead.\nThanks to Sam Altman, Trevor Blackwell, \nPaul Buchheit, Patrick Collison, Aaron Iba, Jessica\nLivingston, Robert Morris, Harj Taggar and Garry Tan\nfor reading drafts of this." }, { "path": "data/PaulGrahamEssays/america.txt", "content": "May 2006(This essay is derived from a keynote at Xtech.)Startups happen in clusters. There are a lot of them in Silicon\nValley and Boston, and few in Chicago or Miami. A country that\nwants startups will probably also have to reproduce whatever makes\nthese clusters form.I've claimed that the recipe is a\ngreat university near a town smart\npeople like. If you set up those conditions within the US, startups\nwill form as inevitably as water droplets condense on a cold piece\nof metal. But when I consider what it would take to reproduce\nSilicon Valley in another country, it's clear the US is a particularly\nhumid environment. Startups condense more easily here.It is by no means a lost cause to try to create a silicon valley\nin another country. There's room not merely to equal Silicon Valley,\nbut to surpass it. But if you want to do that, you have to\nunderstand the advantages startups get from being in America.1. The US Allows Immigration.For example, I doubt it would be possible to reproduce Silicon\nValley in Japan, because one of Silicon Valley's most distinctive\nfeatures is immigration. Half the people there speak with accents.\nAnd the Japanese don't like immigration. When they think about how\nto make a Japanese silicon valley, I suspect they unconsciously\nframe it as how to make one consisting only of Japanese people.\nThis way of framing the question probably guarantees failure.A silicon valley has to be a mecca for the smart and the ambitious,\nand you can't have a mecca if you don't let people into it.Of course, it's not saying much that America is more open to\nimmigration than Japan. Immigration policy is one area where a\ncompetitor could do better.2. The US Is a Rich Country.I could see India one day producing a rival to Silicon Valley.\nObviously they have the right people: you can tell that by the\nnumber of Indians in the current Silicon Valley. The problem with\nIndia itself is that it's still so poor.In poor countries, things we take for granted are missing. A friend\nof mine visiting India sprained her ankle falling down the steps\nin a railway station. When she turned to see what had happened,\nshe found the steps were all different heights. In industrialized\ncountries we walk down steps our whole lives and never think about\nthis, because there's an infrastructure that prevents such a staircase\nfrom being built.The US has never been so poor as some countries are now. There\nhave never been swarms of beggars in the streets of American cities.\nSo we have no data about what it takes to get from the swarms-of-beggars\nstage to the silicon-valley stage. Could you have both at once,\nor does there have to be some baseline prosperity before you get a\nsilicon valley?I suspect there is some speed limit to the evolution\nof an economy. Economies are made out of people, and attitudes can\nonly change a certain amount per generation.\n[1]3. The US Is Not (Yet) a Police State.Another country I could see wanting to have a silicon valley is\nChina. But I doubt they could do it yet either. China still seems\nto be a police state, and although present rulers seem enlightened\ncompared to the last, even enlightened despotism can probably only\nget you part way toward being a great economic power.It can get you factories for building things designed elsewhere.\nCan it get you the designers, though? Can imagination flourish\nwhere people can't criticize the government? Imagination means\nhaving odd ideas, and it's hard to have odd ideas about technology\nwithout also having odd ideas about politics. And in any case,\nmany technical ideas do have political implications. So if you\nsquash dissent, the back pressure will propagate into technical\nfields. \n[2]Singapore would face a similar problem. Singapore seems very aware\nof the importance of encouraging startups. But while energetic\ngovernment intervention may be able to make a port run efficiently,\nit can't coax startups into existence. A state that bans chewing\ngum has a long way to go before it could create a San Francisco.Do you need a San Francisco? Might there not be an alternate route\nto innovation that goes through obedience and cooperation instead\nof individualism? Possibly, but I'd bet not. Most imaginative\npeople seem to share a certain prickly independence,\nwhenever and wherever they lived. You see it in Diogenes telling\nAlexander to get out of his light and two thousand years later in\nFeynman breaking into safes at Los Alamos.\n[3]\nImaginative people\ndon't want to follow or lead. They're most productive when everyone\ngets to do what they want.Ironically, of all rich countries the US has lost the most civil\nliberties recently. But I'm not too worried yet. I'm hoping once\nthe present administration is out, the natural openness of American\nculture will reassert itself.4. American Universities Are Better.You need a great university to seed a silicon valley, and so far\nthere are few outside the US. I asked a handful of American computer\nscience professors which universities in Europe were most admired,\nand they all basically said \"Cambridge\" followed by a long pause\nwhile they tried to think of others. There don't seem to be many\nuniversities elsewhere that compare with the best in America, at\nleast in technology.In some countries this is the result of a deliberate policy. The\nGerman and Dutch governments, perhaps from fear of elitism, try to\nensure that all universities are roughly equal in quality. The\ndownside is that none are especially good. The best professors\nare spread out, instead of being concentrated as they are in the\nUS. This probably makes them less productive, because they don't\nhave good colleagues to inspire them. It also means no one university\nwill be good enough to act as a mecca, attracting talent from abroad\nand causing startups to form around it.The case of Germany is a strange one. The Germans invented the\nmodern university, and up till the 1930s theirs were the best in\nthe world. Now they have none that stand out. As I was mulling\nthis over, I found myself thinking: \"I can understand why German\nuniversities declined in the 1930s, after they excluded Jews. But\nsurely they should have bounced back by now.\" Then I realized:\nmaybe not. There are few Jews left in Germany and most Jews I know\nwould not want to move there. And if you took any great American\nuniversity and removed the Jews, you'd have some pretty big gaps.\nSo maybe it would be a lost cause trying to create a silicon valley\nin Germany, because you couldn't establish the level of university\nyou'd need as a seed.\n[4]It's natural for US universities to compete with one another because\nso many are private. To reproduce the quality of American universities\nyou probably also have to reproduce this. If universities are\ncontrolled by the central government, log-rolling will pull them\nall toward the mean: the new Institute of X will end up at the\nuniversity in the district of a powerful politician, instead of\nwhere it should be.5. You Can Fire People in America.I think one of the biggest obstacles to creating startups in Europe\nis the attitude toward employment. The famously rigid labor laws\nhurt every company, but startups especially, because startups have\nthe least time to spare for bureaucratic hassles.The difficulty of firing people is a particular problem for startups\nbecause they have no redundancy. Every person has to do their\njob well.But the problem is more than just that some startup might have a\nproblem firing someone they needed to. Across industries and\ncountries, there's a strong inverse correlation between performance\nand job security. Actors and directors are fired at the end of\neach film, so they have to deliver every time. Junior professors\nare fired by default after a few years unless the university chooses\nto grant them tenure. Professional athletes know they'll be pulled\nif they play badly for just a couple games. At the other end of\nthe scale (at least in the US) are auto workers, New York City\nschoolteachers, and civil servants, who are all nearly impossible\nto fire. The trend is so clear that you'd have to be willfully\nblind not to see it.Performance isn't everything, you say? Well, are auto workers,\nschoolteachers, and civil servants happier than actors,\nprofessors, and professional athletes?European public opinion will apparently tolerate people being fired\nin industries where they really care about performance. Unfortunately\nthe only industry they care enough about so far is soccer. But\nthat is at least a precedent.6. In America Work Is Less Identified with Employment.The problem in more traditional places like Europe and Japan goes\ndeeper than the employment laws. More dangerous is the attitude\nthey reflect: that an employee is a kind of servant, whom the\nemployer has a duty to protect. It used to be that way in America\ntoo. In 1970 you were still supposed to get a job with a big\ncompany, for whom ideally you'd work your whole career. In return\nthe company would take care of you: they'd try not to fire you,\ncover your medical expenses, and support you in old age.Gradually employment has been shedding such paternalistic overtones\nand becoming simply an economic exchange. But the importance of\nthe new model is not just that it makes it easier for startups to\ngrow. More important, I think, is that it it makes it easier for\npeople to start startups.Even in the US most kids graduating from college still think they're\nsupposed to get jobs, as if you couldn't be productive without being\nsomeone's employee. But the less you identify work with employment,\nthe easier it becomes to start a startup. When you see your career\nas a series of different types of work, instead of a lifetime's\nservice to a single employer, there's less risk in starting your\nown company, because you're only replacing one segment instead of\ndiscarding the whole thing.The old ideas are so powerful that even the most successful startup\nfounders have had to struggle against them. A year after the\nfounding of Apple, Steve Wozniak still hadn't quit HP. He still\nplanned to work there for life. And when Jobs found someone to\ngive Apple serious venture funding, on the condition that Woz quit,\nhe initially refused, arguing that he'd designed both the Apple I\nand the Apple II while working at HP, and there was no reason he\ncouldn't continue.7. America Is Not Too Fussy.If there are any laws regulating businesses, you can assume larval\nstartups will break most of them, because they don't know what the\nlaws are and don't have time to find out.For example, many startups in America begin in places where it's\nnot really legal to run a business. Hewlett-Packard, Apple, and\nGoogle were all run out of garages. Many more startups, including\nours, were initially run out of apartments. If the laws against\nsuch things were actually enforced, most startups wouldn't happen.That could be a problem in fussier countries. If Hewlett and Packard\ntried running an electronics company out of their garage in\nSwitzerland, the old lady next door would report them to the municipal\nauthorities.But the worst problem in other countries is probably the effort\nrequired just to start a company. A friend of mine started a company\nin Germany in the early 90s, and was shocked to discover, among\nmany other regulations, that you needed $20,000 in capital to\nincorporate. That's one reason I'm not typing this on an Apfel\nlaptop. Jobs and Wozniak couldn't have come up with that kind of\nmoney in a company financed by selling a VW bus and an HP calculator.\nWe couldn't have started Viaweb either.\n[5]Here's a tip for governments that want to encourage startups: read\nthe stories of existing startups, and then try to simulate what\nwould have happened in your country. When you hit something that\nwould have killed Apple, prune it off.Startups are marginal. \nThey're started by the poor and the\ntimid; they begin in marginal space and spare time; they're started\nby people who are supposed to be doing something else; and though\nbusinesses, their founders often know nothing about business. Young\nstartups are fragile. A society that trims its margins sharply\nwill kill them all.8. America Has a Large Domestic Market.What sustains a startup in the beginning is the prospect of getting\ntheir initial product out. The successful ones therefore make the\nfirst version as simple as possible. In the US they usually begin\nby making something just for the local market.This works in America, because the local market is 300 million\npeople. It wouldn't work so well in Sweden. In a small country,\na startup has a harder task: they have to sell internationally from\nthe start.The EU was designed partly to simulate a single, large domestic\nmarket. The problem is that the inhabitants still speak many\ndifferent languages. So a software startup in Sweden is still at\na disadvantage relative to one in the US, because they have to deal\nwith internationalization from the beginning. It's significant\nthat the most famous recent startup in Europe, Skype, worked on a\nproblem that was intrinsically international.However, for better or worse it looks as if Europe will in a few\ndecades speak a single language. When I was a student in Italy in\n1990, few Italians spoke English. Now all educated people seem to\nbe expected to-- and Europeans do not like to seem uneducated. This\nis presumably a taboo subject, but if present trends continue,\nFrench and German will eventually go the way of Irish and Luxembourgish:\nthey'll be spoken in homes and by eccentric nationalists.9. America Has Venture Funding.Startups are easier to start in America because funding is easier\nto get. There are now a few VC firms outside the US, but startup\nfunding doesn't only come from VC firms. A more important source,\nbecause it's more personal and comes earlier in the process, is\nmoney from individual angel investors. Google might never have got\nto the point where they could raise millions from VC funds if they\nhadn't first raised a hundred thousand from Andy Bechtolsheim. And\nhe could help them because he was one of the founders of Sun. This\npattern is repeated constantly in startup hubs. It's this pattern\nthat makes them startup hubs.The good news is, all you have to do to get the process rolling is\nget those first few startups successfully launched. If they stick\naround after they get rich, startup founders will almost automatically\nfund and encourage new startups.The bad news is that the cycle is slow. It probably takes five\nyears, on average, before a startup founder can make angel investments.\nAnd while governments might be able to set up local VC funds\nby supplying the money themselves and recruiting people from existing\nfirms to run them, only organic growth can produce angel investors.Incidentally, America's private universities are one reason there's\nso much venture capital. A lot of the money in VC funds comes from\ntheir endowments. So another advantage of private universities is\nthat a good chunk of the country's wealth is managed by enlightened\ninvestors.10. America Has Dynamic Typing for Careers.Compared to other industrialized countries the US is disorganized\nabout routing people into careers. For example, in America people\noften don't decide to go to medical school till they've finished\ncollege. In Europe they generally decide in high school.The European approach reflects the old idea that each person has a\nsingle, definite occupation-- which is not far from the idea that\neach person has a natural \"station\" in life. If this were true,\nthe most efficient plan would be to discover each person's station\nas early as possible, so they could receive the training appropriate\nto it.In the US things are more haphazard. But that turns out to be an\nadvantage as an economy gets more liquid, just as dynamic typing\nturns out to work better than static for ill-defined problems. This\nis particularly true with startups. \"Startup founder\" is not the\nsort of career a high school student would choose. If you ask at\nthat age, people will choose conservatively. They'll choose\nwell-understood occupations like engineer, or doctor, or lawyer.Startups are the kind of thing people don't plan, so you're more\nlikely to get them in a society where it's ok to make career decisions\non the fly.For example, in theory the purpose of a PhD program is to train you\nto do research. But fortunately in the US this is another rule\nthat isn't very strictly enforced. In the US most people in CS PhD\nprograms are there simply because they wanted to learn more. They\nhaven't decided what they'll do afterward. So American grad schools\nspawn a lot of startups, because students don't feel they're failing\nif they don't go into research.Those worried about America's \"competitiveness\" often suggest\nspending more on public schools. But perhaps America's lousy public\nschools have a hidden advantage. Because they're so bad, the kids\nadopt an attitude of waiting for college. I did; I knew I was\nlearning so little that I wasn't even learning what the choices\nwere, let alone which to choose. This is demoralizing, but it does\nat least make you keep an open mind.Certainly if I had to choose between bad high schools and good\nuniversities, like the US, and good high schools and bad universities,\nlike most other industrialized countries, I'd take the US system.\nBetter to make everyone feel like a late bloomer than a failed child\nprodigy.AttitudesThere's one item conspicuously missing from this list: American\nattitudes. Americans are said to be more entrepreneurial, and less\nafraid of risk. But America has no monopoly on this. Indians and\nChinese seem plenty entrepreneurial, perhaps more than Americans.Some say Europeans are less energetic, but I don't believe it. I\nthink the problem with Europe is not that they lack balls, but that\nthey lack examples.Even in the US, the most successful startup founders are often\ntechnical people who are quite timid, initially, about the idea of\nstarting their own company. Few are the sort of backslapping\nextroverts one thinks of as typically American. They can usually\nonly summon up the activation energy to start a startup when they\nmeet people who've done it and realize they could too.I think what holds back European hackers is simply that they don't\nmeet so many people who've done it. You see that variation even\nwithin the US. Stanford students are more entrepreneurial than\nYale students, but not because of some difference in their characters;\nthe Yale students just have fewer examples.I admit there seem to be different attitudes toward ambition in\nEurope and the US. In the US it's ok to be overtly ambitious, and\nin most of Europe it's not. But this can't be an intrinsically\nEuropean quality; previous generations of Europeans were as ambitious\nas Americans. What happened? My hypothesis is that ambition was\ndiscredited by the terrible things ambitious people did in the first\nhalf of the twentieth century. Now swagger is out. (Even now the\nimage of a very ambitious German presses a button or two, doesn't\nit?)It would be surprising if European attitudes weren't affected by\nthe disasters of the twentieth century. It takes a while to be\noptimistic after events like that. But ambition is human nature.\nGradually it will re-emerge.\n[6]How To Do BetterI don't mean to suggest by this list that America is the perfect\nplace for startups. It's the best place so far, but the sample\nsize is small, and \"so far\" is not very long. On historical time \nscales, what we have now is just a\nprototype.So let's look at Silicon Valley the way you'd look at a product\nmade by a competitor. What weaknesses could you exploit? How could\nyou make something users would like better? The users in this case\nare those critical few thousand people you'd like to move to your\nsilicon valley.To start with, Silicon Valley is too far from San Francisco. Palo\nAlto, the original ground zero, is about thirty miles away, and the\npresent center more like forty. So people who come to work in\nSilicon Valley face an unpleasant choice: either live in the boring\nsprawl of the valley proper, or live in San Francisco and endure\nan hour commute each way.The best thing would be if the silicon valley were not merely closer\nto the interesting city, but interesting itself. And there is a\nlot of room for improvement here. Palo Alto is not so bad, but\neverything built since is the worst sort of strip development. You\ncan measure how demoralizing it is by the number of people who will\nsacrifice two hours a day commuting rather than live there.Another area in which you could easily surpass Silicon Valley is\npublic transportation. There is a train running the length of it,\nand by American standards it's not bad. Which is to say that to\nJapanese or Europeans it would seem like something out of the third\nworld.The kind of people you want to attract to your silicon valley like\nto get around by train, bicycle, and on foot. So if you want to\nbeat America, design a town that puts cars last. It will be a while\nbefore any American city can bring itself to do that.Capital GainsThere are also a couple things you could do to beat America at the\nnational level. One would be to have lower capital gains taxes.\nIt doesn't seem critical to have the lowest income taxes,\nbecause to take advantage of those, people have to move.\n[7]\nBut\nif capital gains rates vary, you move assets, not yourself, so\nchanges are reflected at market speeds. The lower the rate, the\ncheaper it is to buy stock in growing companies as opposed to real\nestate, or bonds, or stocks bought for the dividends they pay.So if you want to encourage startups you should have a low rate on\ncapital gains. Politicians are caught between a rock and a hard\nplace here, however: make the capital gains rate low and be accused\nof creating \"tax breaks for the rich,\" or make it high and starve\ngrowing companies of investment capital. As Galbraith said,\npolitics is a matter of choosing between the unpalatable and the\ndisastrous. A lot of governments experimented with the disastrous\nin the twentieth century; now the trend seems to be toward the\nmerely unpalatable.Oddly enough, the leaders now are European countries like Belgium,\nwhich has a capital gains tax rate of zero.ImmigrationThe other place you could beat the US would be with smarter immigration\npolicy. There are huge gains to be made here. Silicon valleys are\nmade of people, remember.Like a company whose software runs on Windows, those in the current\nSilicon Valley are all too aware of the shortcomings of the INS,\nbut there's little they can do about it. They're hostages of the\nplatform.America's immigration system has never been well run, and since\n2001 there has been an additional admixture of paranoia. What\nfraction of the smart people who want to come to America can even\nget in? I doubt even half. Which means if you made a competing\ntechnology hub that let in all smart people, you'd immediately get\nmore than half the world's top talent, for free.US immigration policy is particularly ill-suited to startups, because\nit reflects a model of work from the 1970s. It assumes good technical\npeople have college degrees, and that work means working for a big\ncompany.If you don't have a college degree you can't get an H1B visa, the\ntype usually issued to programmers. But a test that excludes Steve\nJobs, Bill Gates, and Michael Dell can't be a good one. Plus you\ncan't get a visa for working on your own company, only for working\nas an employee of someone else's. And if you want to apply for\ncitizenship you daren't work for a startup at all, because if your\nsponsor goes out of business, you have to start over.American immigration policy keeps out most smart people, and channels\nthe rest into unproductive jobs. It would be easy to do better.\nImagine if, instead, you treated immigration like recruiting-- if\nyou made a conscious effort to seek out the smartest people and get\nthem to come to your country.A country that got immigration right would have a huge advantage.\nAt this point you could become a mecca for smart people simply by\nhaving an immigration system that let them in.A Good VectorIf you look at the kinds of things you have to do to create an\nenvironment where startups condense, none are great sacrifices.\nGreat universities? Livable towns? Civil liberties? Flexible\nemployment laws? Immigration policies that let in smart people?\nTax laws that encourage growth? It's not as if you have to risk\ndestroying your country to get a silicon valley; these are all good\nthings in their own right.And then of course there's the question, can you afford not to? I\ncan imagine a future in which the default choice of ambitious young\npeople is to start their own company\nrather than work for someone else's. I'm not sure that will happen,\nbut it's where the trend points now. And if that is the future,\nplaces that don't have startups will be a whole step behind,\nlike those that missed the Industrial Revolution.Notes[1]\nOn the verge of the Industrial Revolution, England was already\nthe richest country in the world. As far as such things can be\ncompared, per capita income in England in 1750 was higher than\nIndia's in 1960.Deane, Phyllis, The First Industrial Revolution, Cambridge\nUniversity Press, 1965.[2]\n This has already happened once in China, during the Ming\nDynasty, when the country turned its back on industrialization at\nthe command of the court. One of Europe's advantages was that it\nhad no government powerful enough to do that.[3]\nOf course, Feynman and Diogenes were from adjacent traditions,\nbut Confucius, though more polite, was no more willing to be told\nwhat to think.[4]\nFor similar reasons it might be a lost cause to try to establish\na silicon valley in Israel. Instead of no Jews moving there, only\nJews would move there, and I don't think you could build a silicon\nvalley out of just Jews any more than you could out of just Japanese.(This is not a remark about the qualities of these groups, just their\nsizes. Japanese are only about 2% of the world population, and\nJews about .2%.)[5]\nAccording to the World Bank, the initial capital requirement\nfor German companies is 47.6% of the per capita income. Doh.World Bank, Doing Business in 2006, http://doingbusiness.org[6]\nFor most of the twentieth century, Europeans looked back on\nthe summer of 1914 as if they'd been living in a dream world. It\nseems more accurate (or at least, as accurate) to call the years\nafter 1914 a nightmare than to call those before a dream. A lot\nof the optimism Europeans consider distinctly American is simply\nwhat they too were feeling in 1914.[7]\nThe point where things start to go wrong seems to be about\n50%. Above that people get serious about tax avoidance. The reason\nis that the payoff for avoiding tax grows hyperexponentially (x/1-x\nfor 0 < x < 1). If your income tax rate is 10%, moving to Monaco\nwould only give you 11% more income, which wouldn't even cover the\nextra cost. If it's 90%, you'd get ten times as much income. And\nat 98%, as it was briefly in Britain in the 70s, moving to Monaco\nwould give you fifty times as much income. It seems quite likely\nthat European governments of the 70s never drew this curve.Thanks to Trevor Blackwell, Matthias Felleisen, Jessica\nLivingston, Robert Morris, Neil Rimer, Hugues Steinier, Brad \nTempleton, Fred Wilson, and Stephen Wolfram for reading\ndrafts of this, and to Ed Dumbill for inviting me to speak." }, { "path": "data/PaulGrahamEssays/angelinvesting.txt", "content": "March 2009(This essay is derived from a talk at AngelConf.)When we sold our startup in 1998 I thought one day I'd do some angel\ninvesting. Seven years later I still hadn't started. I put it off\nbecause it seemed mysterious and complicated. It turns out to be \neasier than I expected, and also more interesting.The part I thought was hard, the mechanics of investing, really\nisn't. You give a startup money and they give you stock. You'll\nprobably get either preferred stock, which means stock with extra\nrights like getting your money back first in a sale, or convertible\ndebt, which means (on paper) you're lending the company money, and\nthe debt converts to stock at the next sufficiently big funding\nround. \n[1]There are sometimes minor tactical advantages to using one or the\nother. The paperwork for convertible debt is simpler. But really\nit doesn't matter much which you use. Don't spend much time worrying\nabout the details of deal terms, especially when you first start\nangel investing. That's not how you win at this game. When you\nhear people talking about a successful angel investor, they're not\nsaying \"He got a 4x liquidation preference.\" They're saying \"He\ninvested in Google.\"That's how you win: by investing in the right startups. That is\nso much more important than anything else that I worry I'm misleading\nyou by even talking about other things.MechanicsAngel investors often syndicate deals, which means they join together\nto invest on the same terms. In a syndicate there is usually a\n\"lead\" investor who negotiates the terms with the startup. But not\nalways: sometimes the startup cobbles together a syndicate of\ninvestors who approach them independently, and the startup's lawyer\nsupplies the paperwork.The easiest way to get started in angel investing is to find a\nfriend who already does it, and try to get included in his syndicates.\nThen all you have to do is write checks.Don't feel like you have to join a syndicate, though. It's not that\nhard to do it yourself. You can just use the standard \nseries AA\ndocuments Wilson Sonsini and Y Combinator published online.\nYou should of course have your lawyer review everything. Both you\nand the startup should have lawyers. But the lawyers don't have\nto create the agreement from scratch. \n[2]\nWhen you negotiate terms with a startup, there are two numbers you\ncare about: how much money you're putting in, and the valuation of\nthe company. The valuation determines how much stock you get. If\nyou put $50,000 into a company at a pre-money valuation of $1\nmillion, then the post-money valuation is $1.05 million, and you\nget .05/1.05, or 4.76% of the company's stock.If the company raises more money later, the new investor will take\na chunk of the company away from all the existing shareholders just\nas you did. If in the next round they sell 10% of the company to\na new investor, your 4.76% will be reduced to 4.28%.That's ok. Dilution is normal. What saves you from being mistreated\nin future rounds, usually, is that you're in the same boat as the\nfounders. They can't dilute you without diluting themselves just\nas much. And they won't dilute themselves unless they end up \nnet ahead. So in theory, each further \nround of investment leaves you\nwith a smaller share of an even more valuable company, till after\nseveral more rounds you end up with .5% of the company at the point\nwhere it IPOs, and you are very happy because your $50,000 has\nbecome $5 million. \n[3]The agreement by which you invest should have provisions that \nlet you contribute to\nfuture rounds to maintain your percentage. So it's your choice\nwhether you get diluted. \n[4]\nIf the company does really well,\nyou eventually will, because eventually the valuations will get so\nhigh it's not worth it for you.How much does an angel invest? That varies enormously, from $10,000\nto hundreds of thousands or in rare cases even millions. The upper\nbound is obviously the total amount the founders want to raise.\nThe lower bound is 5-10% of the total or $10,000, whichever\nis greater. A typical angel round these days might be $150,000\nraised from 5 people.Valuations don't vary as much. For angel rounds it's rare to see\na valuation lower than half a million or higher than 4 or 5 million.\n4 million is starting to be VC territory.How do you decide what valuation to offer? If you're part of a\nround led by someone else, that problem is solved for you. But\nwhat if you're investing by yourself? There's no real answer.\nThere is no rational way to value an early stage startup. The\nvaluation reflects nothing more than the strength of the company's\nbargaining position. If they really want you, either because they\ndesperately need money, or you're someone who can help them a lot,\nthey'll let you invest at a low valuation. If they don't need you,\nit will be higher. So guess. The startup may not have any more\nidea what the number should be than you do. \n[5]Ultimately it doesn't matter much. When angels make a lot of money\nfrom a deal, it's not because they invested at a valuation of $1.5\nmillion instead of $3 million. It's because the company was really\nsuccessful.I can't emphasize that too much. Don't get hung up on mechanics\nor deal terms. What you should spend your time thinking about is\nwhether the company is good.(Similarly, founders also should not get hung up on deal\nterms, but should spend their time thinking about how to make the\ncompany good.)There's a second less obvious component of an angel investment: how\nmuch you're expected to help the startup. Like the amount you\ninvest, this can vary a lot. You don't have to do anything if you\ndon't want to; you could simply be a source of money. Or you can\nbecome a de facto employee of the company. Just make sure that you\nand the startup agree in advance about roughly how much you'll do\nfor them.Really hot companies sometimes have high standards for angels. The\nones everyone wants to invest in practically audition investors,\nand only take money from people who are famous and/or will work\nhard for them. But don't feel like you have to put in a lot of\ntime or you won't get to invest in any good startups. There is a\nsurprising lack of correlation between how hot a deal a startup is\nand how well it ends up doing. Lots of hot startups will end up\nfailing, and lots of startups no one likes will end up succeeding.\nAnd the latter are so desperate for money that they'll take it from\nanyone at a low valuation. \n[6]Picking WinnersIt would be nice to be able to pick those out, wouldn't it? The\npart of angel investing that has most effect on your returns, picking\nthe right companies, is also the hardest. So you should practically\nignore (or more precisely, archive, in the Gmail sense) everything\nI've told you so far. You may need to refer to it at some point,\nbut it is not the central issue.The central issue is picking the right startups. What \"Make something\npeople want\" is for startups, \"Pick the right startups\" is for\ninvestors. Combined they yield \"Pick the startups that will make\nsomething people want.\"How do you do that? It's not as simple as picking startups that\nare already making something wildly popular. By then it's\ntoo late for angels. VCs will already be onto them. As an angel,\nyou have to pick startups before they've got a hit—either\nbecause they've made something great but users don't realize it\nyet, like Google early on, or because they're still an iteration\nor two away from the big hit, like Paypal when they were making\nsoftware for transferring money between PDAs.To be a good angel investor, you have to be a good judge of potential.\nThat's what it comes down to. VCs can be fast followers. Most of\nthem don't try to predict what will win. They just try to notice\nquickly when something already is winning. But angels have to be\nable to predict. \n[7]One interesting consequence of this fact is that there are a lot\nof people out there who have never even made an angel investment\nand yet are already better angel investors than they realize.\nSomeone who doesn't know the first thing about the mechanics of\nventure funding but knows what a successful startup founder looks\nlike is actually far ahead of someone who knows termsheets inside\nout, but thinks \n\"hacker\" means someone who breaks into computers.\nIf you can recognize good startup founders by empathizing with\nthem—if you both resonate at the same frequency—then\nyou may already be a better startup picker than the median professional\nVC. \n[8]Paul Buchheit, for example, started angel investing about a year\nafter me, and he was pretty much immediately as good as me at picking\nstartups. My extra year of experience was rounding error compared\nto our ability to empathize with founders.What makes a good founder? If there were a word that meant the\nopposite of hapless, that would be the one. Bad founders seem\nhapless. They may be smart, or not, but somehow events overwhelm\nthem and they get discouraged and give up. Good founders make\nthings happen the way they want. Which is not to say they force\nthings to happen in a predefined way. Good founders have a healthy\nrespect for reality. But they are relentlessly resourceful. That's\nthe closest I can get to the opposite of hapless. You want to fund\npeople who are relentlessly resourceful.Notice we started out talking about things, and now we're talking\nabout people. There is an ongoing debate between investors which\nis more important, the people, or the idea—or more precisely,\nthe market. Some, like Ron Conway, say it's the people—that\nthe idea will change, but the people are the foundation of the\ncompany. Whereas Marc Andreessen says he'd back ok founders in a\nhot market over great founders in a bad one. \n[9]These two positions are not so far apart as they seem, because good\npeople find good markets. Bill Gates would probably have ended up\npretty rich even if IBM hadn't happened to drop the PC standard in\nhis lap.I've thought a lot about the disagreement between the investors who\nprefer to bet on people and those who prefer to bet on markets.\nIt's kind of surprising that it even exists. You'd expect opinions\nto have converged more.But I think I've figured out what's going on. The three most\nprominent people I know who favor markets are Marc, Jawed Karim,\nand Joe Kraus. And all three of them, in their own startups,\nbasically flew into a thermal: they hit a market growing so fast\nthat it was all they could do to keep up with it. That kind of\nexperience is hard to ignore. Plus I think they underestimate\nthemselves: they think back to how easy it felt to ride that huge\nthermal upward, and they think \"anyone could have done it.\" But\nthat isn't true; they are not ordinary people.So as an angel investor I think you want to go with Ron Conway and\nbet on people. Thermals happen, yes, but no one can predict\nthem—not even the founders, and certainly not you as an\ninvestor. And only good people can ride the thermals if they hit\nthem anyway.Deal FlowOf course the question of how to choose startups presumes you\nhave startups to choose between. How do you find them? This is\nyet another problem that gets solved for you by syndicates. If you\ntag along on a friend's investments, you don't have to find startups.The problem is not finding startups, exactly, but finding a stream\nof reasonably high quality ones. The traditional way to do this\nis through contacts. If you're friends with a lot of investors and\nfounders, they'll send deals your way. The Valley basically runs\non referrals. And once you start to become known as reliable,\nuseful investor, people will refer lots of deals to you. I certainly\nwill.There's also a newer way to find startups, which is to come to\nevents like Y Combinator's Demo Day, where a batch of newly created\nstartups presents to investors all at once. We have two Demo Days\na year, one in March and one in August. These are basically mass\nreferrals.But events like Demo Day only account for a fraction of matches\nbetween startups and investors. The personal referral is still the\nmost common route. So if you want to hear about new startups, the\nbest way to do it is to get lots of referrals.The best way to get lots of referrals is to invest in startups. No\nmatter how smart and nice you seem, insiders will be reluctant to\nsend you referrals until you've proven yourself by doing a couple\ninvestments. Some smart, nice guys turn out to be flaky,\nhigh-maintenance investors. But once you prove yourself as a good\ninvestor, the deal flow, as they call it, will increase rapidly in\nboth quality and quantity. At the extreme, for someone like Ron\nConway, it is basically identical with the deal flow of the whole\nValley.So if you want to invest seriously, the way to get started is to\nbootstrap yourself off your existing connections, be a good investor\nin the startups you meet that way, and eventually you'll start a\nchain reaction. Good investors are rare, even in Silicon Valley.\nThere probably aren't more than a couple hundred serious angels in the whole\nValley, and yet they're probably the single most important ingredient\nin making the Valley what it is. Angels are the limiting reagent\nin startup formation.If there are only a couple hundred serious angels in the Valley, \nthen by deciding to become one you could single-handedly make the pipeline\nfor startups in Silicon Valley significantly wider. That is kind\nof mind-blowing.Being GoodHow do you be a good angel investor? The first thing you need is\nto be decisive. When we talk to founders about good and bad\ninvestors, one of the ways we describe the good ones is to say \"he\nwrites checks.\" That doesn't mean the investor says yes to everyone.\nFar from it. It means he makes up his mind quickly,\nand follows through. You may be thinking, how hard could that be?\nYou'll see when you try it. It follows from the nature of angel\ninvesting that the decisions are hard. You have to guess early,\nat the stage when the most promising ideas still seem counterintuitive,\nbecause if they were obviously good, VCs would already have funded\nthem.Suppose it's 1998. You come across a startup founded by a couple\ngrad students. They say they're going to work on Internet search.\nThere are already a bunch of big public companies doing search.\nHow can these grad students possibly compete with them? And does\nsearch even matter anyway? All the search engines are trying to\nget people to start calling them \"portals\" instead. Why would you\nwant to invest in a startup run by a couple of nobodies who are\ntrying to compete with large, aggressive companies in an area they\nthemselves have declared passe? And yet the grad students seem\npretty smart. What do you do?There's a hack for being decisive when you're inexperienced: ratchet\ndown the size of your investment till it's an amount you wouldn't\ncare too much about losing. For every rich person (you probably\nshouldn't try angel investing unless you think of yourself as rich)\nthere's some amount that would be painless, though annoying, to\nlose. Till you feel comfortable investing, don't invest more than\nthat per startup.For example, if you have $5 million in investable assets, it would\nprobably be painless (though annoying) to lose $15,000. That's\nless than .3% of your net worth. So start by making 3 or 4 $15,000\ninvestments. Nothing will teach you about angel investing like\nexperience. Treat the first few as an educational expense. $60,000\nis less than a lot of graduate programs. Plus you get equity.What's really uncool is to be strategically indecisive: to string\nfounders along while trying to gather more information about the\nstartup's trajectory. \n[10]\n There's always a temptation to do that,\nbecause you just have so little to go on, but you have to consciously\nresist it. In the long term it's to your advantage to be good.The other component of being a good angel investor is simply to be\na good person. Angel investing is not a business where you make\nmoney by screwing people over. Startups create wealth, and\ncreating wealth is not a zero sum game. No one has to lose for you\nto win. In fact, if you mistreat the founders you invest in, they'll\njust get demoralized and the company will do worse. Plus your\nreferrals will dry up. So I recommend being good.The most successful angel investors I know are all basically good\npeople. Once they invest in a company, all they want to do is help\nit. And they'll help people they haven't invested in too. When\nthey do favors they don't seem to keep track of them. It's too\nmuch overhead. They just try to help everyone, and assume good\nthings will flow back to them somehow. Empirically that seems to\nwork.\nNotes[1]\nConvertible debt can be either capped at a particular valuation,\nor can be done at a discount to whatever the valuation turns out\nto be when it converts. E.g. convertible debt at a discount of 30%\nmeans when it converts you get stock as if you'd invested at a 30%\nlower valuation. That can be useful in cases where you can't or\ndon't want to figure out what the valuation should be. You leave\nit to the next investor. On the other hand, a lot of investors\nwant to know exactly what they're getting, so they will only do\nconvertible debt with a cap.[2]\nThe expensive part of creating an agreement from scratch is\nnot writing the agreement, but bickering at several hundred\ndollars an hour over the details. That's why the series AA paperwork\naims at a middle ground. You can just start from the compromise\nyou'd have reached after lots of back and forth.When you fund a startup, both your lawyers should be specialists\nin startups. Do not use ordinary corporate lawyers for this. Their\ninexperience makes them overbuild: they'll create huge, overcomplicated\nagreements, and spend hours arguing over irrelevant things.In the Valley, the top startup law firms are Wilson Sonsini, Orrick,\nFenwick & West, Gunderson Dettmer, and Cooley Godward. In Boston\nthe best are Goodwin Procter, Wilmer Hale, and Foley Hoag.[3]\nYour mileage may vary.[4]\nThese anti-dilution provisions also protect you against\ntricks like a later investor trying to steal the company by doing\nanother round that values the company at $1. If you have a competent\nstartup lawyer handle the deal for you, you should be protected\nagainst such tricks initially. But it could become a problem later.\nIf a big VC firm wants to invest in the startup after you, they may\ntry to make you take out your anti-dilution protections. And if\nthey do the startup will be pressuring you to agree. They'll tell\nyou that if you don't, you're going to kill their deal with the VC.\nI recommend you solve this problem by having a gentlemen's agreement\nwith the founders: agree with them in advance that you're not going\nto give up your anti-dilution protections. Then it's up to them\nto tell VCs early on.The reason you don't want to give them up is the following scenario.\nThe VCs recapitalize the company, meaning they give it additional\nfunding at a pre-money valuation of zero. This wipes out the\nexisting shareholders, including both you and the founders. They\nthen grant the founders lots of options, because they need them to\nstay around, but you get nothing.Obviously this is not a nice thing to do. It doesn't happen often.\nBrand-name VCs wouldn't recapitalize a company just to steal a few\npercent from an angel. But there's a continuum here. A less\nupstanding, lower-tier VC might be tempted to do it to steal a big\nchunk of stock.I'm not saying you should always absolutely refuse to give up your\nanti-dilution protections. Everything is a negotiation. If you're\npart of a powerful syndicate, you might be able to give up legal\nprotections and rely on social ones. If you invest in a deal led\nby a big angel like Ron Conway, for example, you're pretty well\nprotected against being mistreated, because any VC would think twice\nbefore crossing him. This kind of protection is one of the reasons\nangels like to invest in syndicates.[5]\nDon't invest so much, or at such a low valuation, that you\nend up with an excessively large share of a startup, unless you're\nsure your money will be the last they ever need. Later stage\ninvestors won't invest in a company if the founders don't have\nenough equity left to motivate them. I talked to a VC recently who\nsaid he'd met with a company he really liked, but he turned\nthem down because investors already owned more than half of it.\nThose investors probably thought they'd been pretty clever by getting\nsuch a large chunk of this desirable company, but in fact they were\nshooting themselves in the foot.[6]\nAt any given time I know of at least 3 or 4 YC alumni who I\nbelieve will be big successes but who are running on vapor,\nfinancially, because investors don't yet get what they're doing.\n(And no, unfortunately, I can't tell you who they are. I can't\nrefer a startup to an investor I don't know.)[7]\nThere are some VCs who can predict instead of reacting. Not\nsurprisingly, these are the most successful ones.[8]\nIt's somewhat sneaky of me to put it this way, because the\nmedian VC loses money. That's one of the most surprising things\nI've learned about VC while working on Y Combinator. Only a fraction\nof VCs even have positive returns. The rest exist to satisfy demand\namong fund managers for venture capital as an asset class. Learning\nthis explained a lot about some of the VCs I encountered when we\nwere working on Viaweb.[9]\nVCs also generally say they prefer great markets to great\npeople. But what they're really saying is they want both. They're\nso selective that they only even consider great people. So when\nthey say they care above all about big markets, they mean that's\nhow they choose between great people.[10]\nFounders rightly dislike the sort of investor who says he's\ninterested in investing but doesn't want to lead. There are\ncircumstances where this is an acceptable excuse, but more often\nthan not what it means is \"No, but if you turn out to be a hot deal,\nI want to be able to claim retroactively I said yes.\"If you like a startup enough to invest in it, then invest in it.\nJust use the standard series \nAA terms and write them a check.\nThanks to Sam Altman, Paul Buchheit, Jessica Livingston,\nRobert Morris, and Fred Wilson for reading drafts of this.\nComment on this essay." }, { "path": "data/PaulGrahamEssays/aord.txt", "content": "October 2015When I talk to a startup that's been operating for more than 8 or\n9 months, the first thing I want to know is almost always the same.\nAssuming their expenses remain constant and their revenue growth\nis what it has been over the last several months, do they make it to\nprofitability on the money they have left? Or to put it more\ndramatically, by default do they live or die?The startling thing is how often the founders themselves don't know.\nHalf the founders I talk to don't know whether they're default alive\nor default dead.If you're among that number, Trevor Blackwell has made a handy\ncalculator you can use to find out.The reason I want to know first whether a startup is default alive\nor default dead is that the rest of the conversation depends on the\nanswer. If the company is default alive, we can talk about ambitious\nnew things they could do. If it's default dead, we probably need\nto talk about how to save it. We know the current trajectory ends\nbadly. How can they get off that trajectory?Why do so few founders know whether they're default alive or default\ndead? Mainly, I think, because they're not used to asking that.\nIt's not a question that makes sense to ask early on, any more than\nit makes sense to ask a 3 year old how he plans to support\nhimself. But as the company grows older, the question switches from\nmeaningless to critical. That kind of switch often takes people\nby surprise.I propose the following solution: instead of starting to ask too\nlate whether you're default alive or default dead, start asking too\nearly. It's hard to say precisely when the question switches\npolarity. But it's probably not that dangerous to start worrying\ntoo early that you're default dead, whereas it's very dangerous to\nstart worrying too late.The reason is a phenomenon I wrote about earlier: the\nfatal pinch.\nThe fatal pinch is default dead + slow growth + not enough\ntime to fix it. And the way founders end up in it is by not realizing\nthat's where they're headed.There is another reason founders don't ask themselves whether they're\ndefault alive or default dead: they assume it will be easy to raise\nmore money. But that assumption is often false, and worse still, the\nmore you depend on it, the falser it becomes.Maybe it will help to separate facts from hopes. Instead of thinking\nof the future with vague optimism, explicitly separate the components.\nSay \"We're default dead, but we're counting on investors to save\nus.\" Maybe as you say that, it will set off the same alarms in your\nhead that it does in mine. And if you set off the alarms sufficiently\nearly, you may be able to avoid the fatal pinch.It would be safe to be default dead if you could count on investors\nsaving you. As a rule their interest is a function of\ngrowth. If you have steep revenue growth, say over 5x a year, you\ncan start to count on investors being interested even if you're not\nprofitable.\n[1]\nBut investors are so fickle that you can never\ndo more than start to count on them. Sometimes something about your\nbusiness will spook investors even if your growth is great. So no\nmatter how good your growth is, you can never safely treat fundraising\nas more than a plan A. You should always have a plan B as well: you\nshould know (as in write down) precisely what you'll need to do to\nsurvive if you can't raise more money, and precisely when you'll \nhave to switch to plan B if plan A isn't working.In any case, growing fast versus operating cheaply is far from the\nsharp dichotomy many founders assume it to be. In practice there\nis surprisingly little connection between how much a startup spends\nand how fast it grows. When a startup grows fast, it's usually\nbecause the product hits a nerve, in the sense of hitting some big\nneed straight on. When a startup spends a lot, it's usually because\nthe product is expensive to develop or sell, or simply because\nthey're wasteful.If you're paying attention, you'll be asking at this point not just\nhow to avoid the fatal pinch, but how to avoid being default dead.\nThat one is easy: don't hire too fast. Hiring too fast is by far\nthe biggest killer of startups that raise money.\n[2]Founders tell themselves they need to hire in order to grow. But\nmost err on the side of overestimating this need rather than\nunderestimating it. Why? Partly because there's so much work to\ndo. Naive founders think that if they can just hire enough\npeople, it will all get done. Partly because successful startups have\nlots of employees, so it seems like that's what one does in order\nto be successful. In fact the large staffs of successful startups\nare probably more the effect of growth than the cause. And\npartly because when founders have slow growth they don't want to\nface what is usually the real reason: the product is not appealing\nenough.Plus founders who've just raised money are often encouraged to\noverhire by the VCs who funded them. Kill-or-cure strategies are\noptimal for VCs because they're protected by the portfolio effect.\nVCs want to blow you up, in one sense of the phrase or the other.\nBut as a founder your incentives are different. You want above all\nto survive.\n[3]Here's a common way startups die. They make something moderately\nappealing and have decent initial growth. They raise their first\nround fairly easily, because the founders seem smart and the idea\nsounds plausible. But because the product is only moderately\nappealing, growth is ok but not great. The founders convince\nthemselves that hiring a bunch of people is the way to boost growth.\nTheir investors agree. But (because the product is only moderately\nappealing) the growth never comes. Now they're rapidly running out\nof runway. They hope further investment will save them. But because\nthey have high expenses and slow growth, they're now unappealing\nto investors. They're unable to raise more, and the company dies.What the company should have done is address the fundamental problem:\nthat the product is only moderately appealing. Hiring people is\nrarely the way to fix that. More often than not it makes it harder.\nAt this early stage, the product needs to evolve more than to be\n\"built out,\" and that's usually easier with fewer people.\n[4]Asking whether you're default alive or default dead may save you\nfrom this. Maybe the alarm bells it sets off will counteract the\nforces that push you to overhire. Instead you'll be compelled to\nseek growth in other ways. For example, by doing\nthings that don't scale, or by redesigning the product in the\nway only founders can.\nAnd for many if not most startups, these paths to growth will be\nthe ones that actually work.Airbnb waited 4 months after raising money at the end of Y Combinator\nbefore they hired their first employee. In the meantime the founders\nwere terribly overworked. But they were overworked evolving Airbnb\ninto the astonishingly successful organism it is now.Notes[1]\nSteep usage growth will also interest investors. Revenue\nwill ultimately be a constant multiple of usage, so x% usage growth\npredicts x% revenue growth. But in practice investors discount\nmerely predicted revenue, so if you're measuring usage you need a\nhigher growth rate to impress investors.[2]\nStartups that don't raise money are saved from hiring too\nfast because they can't afford to. But that doesn't mean you should\navoid raising money in order to avoid this problem, any more than\nthat total abstinence is the only way to avoid becoming an alcoholic.[3]\nI would not be surprised if VCs' tendency to push founders\nto overhire is not even in their own interest. They don't know how\nmany of the companies that get killed by overspending might have\ndone well if they'd survived. My guess is a significant number.[4]\nAfter reading a draft, Sam Altman wrote:\"I think you should make the hiring point more strongly. I think\nit's roughly correct to say that YC's most successful companies\nhave never been the fastest to hire, and one of the marks of a great\nfounder is being able to resist this urge.\"Paul Buchheit adds:\"A related problem that I see a lot is premature scaling—founders\ntake a small business that isn't really working (bad unit economics,\ntypically) and then scale it up because they want impressive growth\nnumbers. This is similar to over-hiring in that it makes the business\nmuch harder to fix once it's big, plus they are bleeding cash really\nfast.\"\nThanks to Sam Altman, Paul Buchheit, Joe Gebbia, Jessica Livingston,\nand Geoff Ralston for reading drafts of this." }, { "path": "data/PaulGrahamEssays/apple.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nNovember 2009I don't think Apple realizes how badly the App Store approval process\nis broken. Or rather, I don't think they realize how much it matters\nthat it's broken.The way Apple runs the App Store has harmed their reputation with\nprogrammers more than anything else they've ever done. \nTheir reputation with programmers used to be great.\nIt used to be the most common complaint you heard\nabout Apple was that their fans admired them too uncritically.\nThe App Store has changed that. Now a lot of programmers\nhave started to see Apple as evil.How much of the goodwill Apple once had with programmers have they\nlost over the App Store? A third? Half? And that's just so far.\nThe App Store is an ongoing karma leak.* * *How did Apple get into this mess? Their fundamental problem is\nthat they don't understand software.They treat iPhone apps the way they treat the music they sell through\niTunes. Apple is the channel; they own the user; if you want to\nreach users, you do it on their terms. The record labels agreed,\nreluctantly. But this model doesn't work for software. It doesn't\nwork for an intermediary to own the user. The software business\nlearned that in the early 1980s, when companies like VisiCorp showed\nthat although the words \"software\" and \"publisher\" fit together,\nthe underlying concepts don't. Software isn't like music or books.\nIt's too complicated for a third party to act as an intermediary\nbetween developer and user. And yet that's what Apple is trying\nto be with the App Store: a software publisher. And a particularly\noverreaching one at that, with fussy tastes and a rigidly enforced\nhouse style.If software publishing didn't work in 1980, it works even less now\nthat software development has evolved from a small number of big\nreleases to a constant stream of small ones. But Apple doesn't\nunderstand that either. Their model of product development derives\nfrom hardware. They work on something till they think it's finished,\nthen they release it. You have to do that with hardware, but because\nsoftware is so easy to change, its design can benefit from evolution.\nThe standard way to develop applications now is to launch fast and\niterate. Which means it's a disaster to have long, random delays\neach time you release a new version.Apparently Apple's attitude is that developers should be more careful\nwhen they submit a new version to the App Store. They would say\nthat. But powerful as they are, they're not powerful enough to\nturn back the evolution of technology. Programmers don't use\nlaunch-fast-and-iterate out of laziness. They use it because it\nyields the best results. By obstructing that process, Apple is\nmaking them do bad work, and programmers hate that as much as Apple\nwould.How would Apple like it if when they discovered a serious bug in\nOS X, instead of releasing a software update immediately, they had\nto submit their code to an intermediary who sat on it for a month\nand then rejected it because it contained an icon they didn't like?By breaking software development, Apple gets the opposite of what\nthey intended: the version of an app currently available in the App\nStore tends to be an old and buggy one. One developer told me:\n\n As a result of their process, the App Store is full of half-baked\n applications. I make a new version almost every day that I release\n to beta users. The version on the App Store feels old and crappy.\n I'm sure that a lot of developers feel this way: One emotion is\n \"I'm not really proud about what's in the App Store\", and it's\n combined with the emotion \"Really, it's Apple's fault.\"\n\nAnother wrote:\n\n I believe that they think their approval process helps users by\n ensuring quality. In reality, bugs like ours get through all the\n time and then it can take 4-8 weeks to get that bug fix approved,\n leaving users to think that iPhone apps sometimes just don't work.\n Worse for Apple, these apps work just fine on other platforms\n that have immediate approval processes.\n\nActually I suppose Apple has a third misconception: that all the\ncomplaints about App Store approvals are not a serious problem.\nThey must hear developers complaining. But partners and suppliers\nare always complaining. It would be a bad sign if they weren't;\nit would mean you were being too easy on them. Meanwhile the iPhone\nis selling better than ever. So why do they need to fix anything?They get away with maltreating developers, in the short term, because\nthey make such great hardware. I just bought a new 27\" iMac a\ncouple days ago. It's fabulous. The screen's too shiny, and the\ndisk is surprisingly loud, but it's so beautiful that you can't\nmake yourself care.So I bought it, but I bought it, for the first time, with misgivings.\nI felt the way I'd feel buying something made in a country with a\nbad human rights record. That was new. In the past when I bought\nthings from Apple it was an unalloyed pleasure. Oh boy! They make\nsuch great stuff. This time it felt like a Faustian bargain. They\nmake such great stuff, but they're such assholes. Do I really want\nto support this company?* * *Should Apple care what people like me think? What difference does\nit make if they alienate a small minority of their users?There are a couple reasons they should care. One is that these\nusers are the people they want as employees. If your company seems\nevil, the best programmers won't work for you. That hurt Microsoft\na lot starting in the 90s. Programmers started to feel sheepish\nabout working there. It seemed like selling out. When people from\nMicrosoft were talking to other programmers and they mentioned where\nthey worked, there were a lot of self-deprecating jokes about having\ngone over to the dark side. But the real problem for Microsoft\nwasn't the embarrassment of the people they hired. It was the\npeople they never got. And you know who got them? Google and\nApple. If Microsoft was the Empire, they were the Rebel Alliance.\nAnd it's largely because they got more of the best people that\nGoogle and Apple are doing so much better than Microsoft today.Why are programmers so fussy about their employers' morals? Partly\nbecause they can afford to be. The best programmers can work\nwherever they want. They don't have to work for a company they\nhave qualms about.But the other reason programmers are fussy, I think, is that evil\nbegets stupidity. An organization that wins by exercising power\nstarts to lose the ability to win by doing better work. And it's\nnot fun for a smart person to work in a place where the best ideas\naren't the ones that win. I think the reason Google embraced \"Don't\nbe evil\" so eagerly was not so much to impress the outside world\nas to inoculate themselves against arrogance.\n[1]That has worked for Google so far. They've become more\nbureaucratic, but otherwise they seem to have held true to their\noriginal principles. With Apple that seems less the case. When you\nlook at the famous \n1984 ad \nnow, it's easier to imagine Apple as the\ndictator on the screen than the woman with the hammer.\n[2]\nIn fact, if you read the dictator's speech it sounds uncannily like a\nprophecy of the App Store.\n\n We have triumphed over the unprincipled dissemination of facts.We have created, for the first time in all history, a garden of\n pure ideology, where each worker may bloom secure from the pests\n of contradictory and confusing truths.\n\nThe other reason Apple should care what programmers think of them\nis that when you sell a platform, developers make or break you. If\nanyone should know this, Apple should. VisiCalc made the Apple II.And programmers build applications for the platforms they use. Most\napplications—most startups, probably—grow out of personal projects.\nApple itself did. Apple made microcomputers because that's what\nSteve Wozniak wanted for himself. He couldn't have afforded a\nminicomputer. \n[3]\n Microsoft likewise started out making interpreters\nfor little microcomputers because\nBill Gates and Paul Allen were interested in using them. It's a\nrare startup that doesn't build something the founders use.The main reason there are so many iPhone apps is that so many programmers\nhave iPhones. They may know, because they read it in an article,\nthat Blackberry has such and such market share. But in practice\nit's as if RIM didn't exist. If they're going to build something,\nthey want to be able to use it themselves, and that means building\nan iPhone app.So programmers continue to develop iPhone apps, even though Apple\ncontinues to maltreat them. They're like someone stuck in an abusive\nrelationship. They're so attracted to the iPhone that they can't\nleave. But they're looking for a way out. One wrote:\n\n While I did enjoy developing for the iPhone, the control they\n place on the App Store does not give me the drive to develop\n applications as I would like. In fact I don't intend to make any\n more iPhone applications unless absolutely necessary.\n[4]\n\nCan anything break this cycle? No device I've seen so far could.\nPalm and RIM haven't a hope. The only credible contender is Android.\nBut Android is an orphan; Google doesn't really care about it, not\nthe way Apple cares about the iPhone. Apple cares about the iPhone\nthe way Google cares about search.* * *Is the future of handheld devices one locked down by Apple? It's\na worrying prospect. It would be a bummer to have another grim\nmonoculture like we had in the 1990s. In 1995, writing software\nfor end users was effectively identical with writing Windows\napplications. Our horror at that prospect was the single biggest\nthing that drove us to start building web apps.At least we know now what it would take to break Apple's lock.\nYou'd have to get iPhones out of programmers' hands. If programmers\nused some other device for mobile web access, they'd start to develop\napps for that instead.How could you make a device programmers liked better than the iPhone?\nIt's unlikely you could make something better designed. Apple\nleaves no room there. So this alternative device probably couldn't\nwin on general appeal. It would have to win by virtue of some\nappeal it had to programmers specifically.One way to appeal to programmers is with software. If you\ncould think of an application programmers had to have, but that\nwould be impossible in the circumscribed world of the iPhone, \nyou could presumably get them to switch.That would definitely happen if programmers started to use handhelds\nas development machines—if handhelds displaced laptops the\nway laptops displaced desktops. You need more control of a development\nmachine than Apple will let you have over an iPhone.Could anyone make a device that you'd carry around in your pocket\nlike a phone, and yet would also work as a development machine?\nIt's hard to imagine what it would look like. But I've learned\nnever to say never about technology. A phone-sized device that\nwould work as a development machine is no more miraculous by present\nstandards than the iPhone itself would have seemed by the standards\nof 1995.My current development machine is a MacBook Air, which I use with\nan external monitor and keyboard in my office, and by itself when\ntraveling. If there was a version half the size I'd prefer it.\nThat still wouldn't be small enough to carry around everywhere like\na phone, but we're within a factor of 4 or so. Surely that gap is\nbridgeable. In fact, let's make it an\nRFS. Wanted: \nWoman with hammer.Notes[1]\nWhen Google adopted \"Don't be evil,\" they were still so small\nthat no one would have expected them to be, yet.\n[2]\nThe dictator in the 1984 ad isn't Microsoft, incidentally;\nit's IBM. IBM seemed a lot more frightening in those days, but\nthey were friendlier to developers than Apple is now.[3]\nHe couldn't even afford a monitor. That's why the Apple\nI used a TV as a monitor.[4]\nSeveral people I talked to mentioned how much they liked the\niPhone SDK. The problem is not Apple's products but their policies.\nFortunately policies are software; Apple can change them instantly\nif they want to. Handy that, isn't it?Thanks to Sam Altman, Trevor Blackwell, Ross Boucher, \nJames Bracy, Gabor Cselle,\nPatrick Collison, Jason Freedman, John Gruber, Joe Hewitt, Jessica Livingston,\nRobert Morris, Teng Siong Ong, Nikhil Pandit, Savraj Singh, and Jared Tame for reading drafts of this." }, { "path": "data/PaulGrahamEssays/artistsship.txt", "content": "November 2008One of the differences between big companies and startups is that\nbig companies tend to have developed procedures to protect themselves\nagainst mistakes. A startup walks like a toddler, bashing\ninto things and falling over all the time. A big company is more\ndeliberate.The gradual accumulation of checks in an organization is a kind of\nlearning, based on disasters that have happened to it or others\nlike it. After giving a contract to a supplier who goes bankrupt\nand fails to deliver, for example, a company might require all\nsuppliers to prove they're solvent before submitting bids.As companies grow they invariably get more such checks, either in\nresponse to disasters they've suffered, or (probably more often)\nby hiring people from bigger companies who bring with them customs\nfor protecting against new types of disasters.It's natural for organizations to learn from mistakes. The problem\nis, people who propose new checks almost never consider that the\ncheck itself has a cost.Every check has a cost. For example, consider the case of making\nsuppliers verify their solvency. Surely that's mere prudence? But\nin fact it could have substantial costs. There's obviously the\ndirect cost in time of the people on both sides who supply and check\nproofs of the supplier's solvency. But the real costs are the ones\nyou never hear about: the company that would be the best supplier,\nbut doesn't bid because they can't spare the effort to get verified.\nOr the company that would be the best supplier, but falls just short\nof the threshold for solvency—which will of course have been set\non the high side, since there is no apparent cost of increasing it.Whenever someone in an organization proposes to add a new check,\nthey should have to explain not just the benefit but the cost. No\nmatter how bad a job they did of analyzing it, this meta-check would\nat least remind everyone there had to be a cost, and send them\nlooking for it.If companies started doing that, they'd find some surprises. Joel\nSpolsky recently spoke at Y Combinator about selling software to\ncorporate customers. He said that in most companies software costing\nup to about $1000 could be bought by individual managers without\nany additional approvals. Above that threshold, software purchases\ngenerally had to be approved by a committee. But babysitting this\nprocess was so expensive for software vendors that it didn't make\nsense to charge less than $50,000. Which means if you're making\nsomething you might otherwise have charged $5000 for, you have to\nsell it for $50,000 instead.The purpose of the committee is presumably to ensure that the company\ndoesn't waste money. And yet the result is that the company pays\n10 times as much.Checks on purchases will always be expensive, because the harder\nit is to sell something to you, the more it has to cost. And not\nmerely linearly, either. If you're hard enough to sell to, the\npeople who are best at making things don't want to bother. The\nonly people who will sell to you are companies that specialize in\nselling to you. Then you've sunk to a whole new level of inefficiency.\nMarket mechanisms no longer protect you, because the good suppliers\nare no longer in the market.Such things happen constantly to the biggest organizations of all,\ngovernments. But checks instituted by governments can cause much\nworse problems than merely overpaying. Checks instituted by\ngovernments can cripple a country's whole economy. Up till about\n1400, China was richer and more technologically advanced than Europe.\nOne reason Europe pulled ahead was that the Chinese government\nrestricted long trading voyages. So it was left to the Europeans\nto explore and eventually to dominate the rest of the world, including\nChina.In more recent times, Sarbanes-Oxley has practically destroyed the\nUS IPO market. That wasn't the intention of the legislators who\nwrote it. They just wanted to add a few more checks on public\ncompanies. But they forgot to consider the cost. They forgot that\ncompanies about to go public are usually rather stretched, and that\nthe weight of a few extra checks that might be easy for General\nElectric to bear are enough to prevent younger companies from being\npublic at all.Once you start to think about the cost of checks, you can start to\nask other interesting questions. Is the cost increasing or decreasing?\nIs it higher in some areas than others? Where does it increase\ndiscontinuously? If large organizations started to ask questions\nlike that, they'd learn some frightening things.I think the cost of checks may actually be increasing. The reason\nis that software plays an increasingly important role in companies,\nand the people who write software are particularly harmed by checks.Programmers are unlike many types of workers in that the best ones\nactually prefer to work hard. This doesn't seem to be the case in\nmost types of work. When I worked in fast food, we didn't prefer\nthe busy times. And when I used to mow lawns, I definitely didn't\nprefer it when the grass was long after a week of rain.Programmers, though, like it better when they write more code. Or\nmore precisely, when they release more code. Programmers like to\nmake a difference. Good ones, anyway.For good programmers, one of the best things about working for a\nstartup is that there are few checks on releases. In true startups,\nthere are no external checks at all. If you have an idea for a new\nfeature in the morning, you can write it and push it to the production\nservers before lunch. And when you can do that, you have more\nideas.At big companies, software has to go through various approvals\nbefore it can be launched. And the cost of doing this can be\nenormous—in fact, discontinuous. I was talking recently to a\ngroup of three programmers whose startup had been acquired a few\nyears before by a big company. When they'd been independent, they\ncould release changes instantly. Now, they said, the absolute\nfastest they could get code released on the production servers was\ntwo weeks.This didn't merely make them less productive. It made them hate\nworking for the acquirer.Here's a sign of how much programmers like to be able to work hard:\nthese guys would have paid to be able to release code immediately,\nthe way they used to. I asked them if they'd trade 10% of the\nacquisition price for the ability to release code immediately, and\nall three instantly said yes. Then I asked what was the maximum\npercentage of the acquisition price they'd trade for it. They said\nthey didn't want to think about it, because they didn't want to\nknow how high they'd go, but I got the impression it might be as\nmuch as half.They'd have sacrificed hundreds of thousands of dollars, perhaps\nmillions, just to be able to deliver more software to users. And\nyou know what? It would have been perfectly safe to let them. In\nfact, the acquirer would have been better off; not only wouldn't\nthese guys have broken anything, they'd have gotten a lot more done.\nSo the acquirer is in fact getting worse performance at greater\ncost. Just like the committee approving software purchases.And just as the greatest danger of being hard to sell to is not\nthat you overpay but that the best suppliers won't even sell to\nyou, the greatest danger of applying too many checks to your\nprogrammers is not that you'll make them unproductive, but that\ngood programmers won't even want to work for you.Steve Jobs's famous maxim \"artists ship\" works both ways. Artists\naren't merely capable of shipping. They insist on it. So if you\ndon't let people ship, you won't have any artists." }, { "path": "data/PaulGrahamEssays/avg.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nApril 2001, rev. April 2003(This article is derived from a talk given at the 2001 Franz\nDeveloper Symposium.)\nIn the summer of 1995, my friend Robert Morris and I\nstarted a startup called \nViaweb. \nOur plan was to write\nsoftware that would let end users build online stores.\nWhat was novel about this software, at the time, was\nthat it ran on our server, using ordinary Web pages\nas the interface.A lot of people could have been having this idea at the\nsame time, of course, but as far as I know, Viaweb was\nthe first Web-based application. It seemed such\na novel idea to us that we named the company after it:\nViaweb, because our software worked via the Web,\ninstead of running on your desktop computer.Another unusual thing about this software was that it\nwas written primarily in a programming language called\nLisp. It was one of the first big end-user\napplications to be written in Lisp, which up till then\nhad been used mostly in universities and research labs. [1]The Secret WeaponEric Raymond has written an essay called \"How to Become a Hacker,\"\nand in it, among other things, he tells would-be hackers what\nlanguages they should learn. He suggests starting with Python and\nJava, because they are easy to learn. The serious hacker will also\nwant to learn C, in order to hack Unix, and Perl for system\nadministration and cgi scripts. Finally, the truly serious hacker\nshould consider learning Lisp:\n\n Lisp is worth learning for the profound enlightenment experience\n you will have when you finally get it; that experience will make\n you a better programmer for the rest of your days, even if you\n never actually use Lisp itself a lot.\n\nThis is the same argument you tend to hear for learning Latin. It\nwon't get you a job, except perhaps as a classics professor, but\nit will improve your mind, and make you a better writer in languages\nyou do want to use, like English.But wait a minute. This metaphor doesn't stretch that far. The\nreason Latin won't get you a job is that no one speaks it. If you\nwrite in Latin, no one can understand you. But Lisp is a computer\nlanguage, and computers speak whatever language you, the programmer,\ntell them to.So if Lisp makes you a better programmer, like he says, why wouldn't\nyou want to use it? If a painter were offered a brush that would\nmake him a better painter, it seems to me that he would want to\nuse it in all his paintings, wouldn't he? I'm not trying to make\nfun of Eric Raymond here. On the whole, his advice is good. What\nhe says about Lisp is pretty much the conventional wisdom. But\nthere is a contradiction in the conventional wisdom: Lisp will\nmake you a better programmer, and yet you won't use it.Why not? Programming languages are just tools, after all. If Lisp\nreally does yield better programs, you should use it. And if it\ndoesn't, then who needs it?This is not just a theoretical question. Software is a very\ncompetitive business, prone to natural monopolies. A company that\ngets software written faster and better will, all other things\nbeing equal, put its competitors out of business. And when you're\nstarting a startup, you feel this very keenly. Startups tend to\nbe an all or nothing proposition. You either get rich, or you get\nnothing. In a startup, if you bet on the wrong technology, your\ncompetitors will crush you.Robert and I both knew Lisp well, and we couldn't see any reason\nnot to trust our instincts and go with Lisp. We knew that everyone\nelse was writing their software in C++ or Perl. But we also knew\nthat that didn't mean anything. If you chose technology that way,\nyou'd be running Windows. When you choose technology, you have to\nignore what other people are doing, and consider only what will\nwork the best.This is especially true in a startup. In a big company, you can\ndo what all the other big companies are doing. But a startup can't\ndo what all the other startups do. I don't think a lot of people\nrealize this, even in startups.The average big company grows at about ten percent a year. So if\nyou're running a big company and you do everything the way the\naverage big company does it, you can expect to do as well as the\naverage big company-- that is, to grow about ten percent a year.The same thing will happen if you're running a startup, of course.\nIf you do everything the way the average startup does it, you should\nexpect average performance. The problem here is, average performance\nmeans that you'll go out of business. The survival rate for startups\nis way less than fifty percent. So if you're running a startup,\nyou had better be doing something odd. If not, you're in trouble.Back in 1995, we knew something that I don't think our competitors\nunderstood, and few understand even now: when you're writing\nsoftware that only has to run on your own servers, you can use\nany language you want. When you're writing desktop software,\nthere's a strong bias toward writing applications in the same\nlanguage as the operating system. Ten years ago, writing applications\nmeant writing applications in C. But with Web-based software,\nespecially when you have the source code of both the language and\nthe operating system, you can use whatever language you want.This new freedom is a double-edged sword, however. Now that you\ncan use any language, you have to think about which one to use.\nCompanies that try to pretend nothing has changed risk finding that\ntheir competitors do not.If you can use any language, which do you use? We chose Lisp.\nFor one thing, it was obvious that rapid development would be\nimportant in this market. We were all starting from scratch, so\na company that could get new features done before its competitors\nwould have a big advantage. We knew Lisp was a really good language\nfor writing software quickly, and server-based applications magnify\nthe effect of rapid development, because you can release software\nthe minute it's done.If other companies didn't want to use Lisp, so much the better.\nIt might give us a technological edge, and we needed all the help\nwe could get. When we started Viaweb, we had no experience in\nbusiness. We didn't know anything about marketing, or hiring\npeople, or raising money, or getting customers. Neither of us had\never even had what you would call a real job. The only thing we\nwere good at was writing software. We hoped that would save us.\nAny advantage we could get in the software department, we would\ntake.So you could say that using Lisp was an experiment. Our hypothesis\nwas that if we wrote our software in Lisp, we'd be able to get\nfeatures done faster than our competitors, and also to do things\nin our software that they couldn't do. And because Lisp was so\nhigh-level, we wouldn't need a big development team, so our costs\nwould be lower. If this were so, we could offer a better product\nfor less money, and still make a profit. We would end up getting\nall the users, and our competitors would get none, and eventually\ngo out of business. That was what we hoped would happen, anyway.What were the results of this experiment? Somewhat surprisingly,\nit worked. We eventually had many competitors, on the order of\ntwenty to thirty of them, but none of their software could compete\nwith ours. We had a wysiwyg online store builder that ran on the\nserver and yet felt like a desktop application. Our competitors\nhad cgi scripts. And we were always far ahead of them in features.\nSometimes, in desperation, competitors would try to introduce\nfeatures that we didn't have. But with Lisp our development cycle\nwas so fast that we could sometimes duplicate a new feature within\na day or two of a competitor announcing it in a press release. By\nthe time journalists covering the press release got round to calling\nus, we would have the new feature too.It must have seemed to our competitors that we had some kind of\nsecret weapon-- that we were decoding their Enigma traffic or\nsomething. In fact we did have a secret weapon, but it was simpler\nthan they realized. No one was leaking news of their features to\nus. We were just able to develop software faster than anyone\nthought possible.When I was about nine I happened to get hold of a copy of The Day\nof the Jackal, by Frederick Forsyth. The main character is an\nassassin who is hired to kill the president of France. The assassin\nhas to get past the police to get up to an apartment that overlooks\nthe president's route. He walks right by them, dressed up as an\nold man on crutches, and they never suspect him.Our secret weapon was similar. We wrote our software in a weird\nAI language, with a bizarre syntax full of parentheses. For years\nit had annoyed me to hear Lisp described that way. But now it\nworked to our advantage. In business, there is nothing more valuable\nthan a technical advantage your competitors don't understand. In\nbusiness, as in war, surprise is worth as much as force.And so, I'm a little embarrassed to say, I never said anything\npublicly about Lisp while we were working on Viaweb. We never\nmentioned it to the press, and if you searched for Lisp on our Web\nsite, all you'd find were the titles of two books in my bio. This\nwas no accident. A startup should give its competitors as little\ninformation as possible. If they didn't know what language our\nsoftware was written in, or didn't care, I wanted to keep it that\nway.[2]The people who understood our technology best were the customers.\nThey didn't care what language Viaweb was written in either, but\nthey noticed that it worked really well. It let them build great\nlooking online stores literally in minutes. And so, by word of\nmouth mostly, we got more and more users. By the end of 1996 we\nhad about 70 stores online. At the end of 1997 we had 500. Six\nmonths later, when Yahoo bought us, we had 1070 users. Today, as\nYahoo Store, this software continues to dominate its market. It's\none of the more profitable pieces of Yahoo, and the stores built\nwith it are the foundation of Yahoo Shopping. I left Yahoo in\n1999, so I don't know exactly how many users they have now, but\nthe last I heard there were about 20,000.\nThe Blub ParadoxWhat's so great about Lisp? And if Lisp is so great, why doesn't\neveryone use it? These sound like rhetorical questions, but actually\nthey have straightforward answers. Lisp is so great not because\nof some magic quality visible only to devotees, but because it is\nsimply the most powerful language available. And the reason everyone\ndoesn't use it is that programming languages are not merely\ntechnologies, but habits of mind as well, and nothing changes\nslower. Of course, both these answers need explaining.I'll begin with a shockingly controversial statement: programming\nlanguages vary in power.Few would dispute, at least, that high level languages are more\npowerful than machine language. Most programmers today would agree\nthat you do not, ordinarily, want to program in machine language.\nInstead, you should program in a high-level language, and have a\ncompiler translate it into machine language for you. This idea is\neven built into the hardware now: since the 1980s, instruction sets\nhave been designed for compilers rather than human programmers.Everyone knows it's a mistake to write your whole program by hand\nin machine language. What's less often understood is that there\nis a more general principle here: that if you have a choice of\nseveral languages, it is, all other things being equal, a mistake\nto program in anything but the most powerful one. [3]There are many exceptions to this rule. If you're writing a program\nthat has to work very closely with a program written in a certain\nlanguage, it might be a good idea to write the new program in the\nsame language. If you're writing a program that only has to do\nsomething very simple, like number crunching or bit manipulation,\nyou may as well use a less abstract language, especially since it\nmay be slightly faster. And if you're writing a short, throwaway\nprogram, you may be better off just using whatever language has\nthe best library functions for the task. But in general, for\napplication software, you want to be using the most powerful\n(reasonably efficient) language you can get, and using anything\nelse is a mistake, of exactly the same kind, though possibly in a\nlesser degree, as programming in machine language.You can see that machine language is very low level. But, at least\nas a kind of social convention, high-level languages are often all\ntreated as equivalent. They're not. Technically the term \"high-level\nlanguage\" doesn't mean anything very definite. There's no dividing\nline with machine languages on one side and all the high-level\nlanguages on the other. Languages fall along a continuum [4] of\nabstractness, from the most powerful all the way down to machine\nlanguages, which themselves vary in power.Consider Cobol. Cobol is a high-level language, in the sense that\nit gets compiled into machine language. Would anyone seriously\nargue that Cobol is equivalent in power to, say, Python? It's\nprobably closer to machine language than Python.Or how about Perl 4? Between Perl 4 and Perl 5, lexical closures\ngot added to the language. Most Perl hackers would agree that Perl\n5 is more powerful than Perl 4. But once you've admitted that,\nyou've admitted that one high level language can be more powerful\nthan another. And it follows inexorably that, except in special\ncases, you ought to use the most powerful you can get.This idea is rarely followed to its conclusion, though. After a\ncertain age, programmers rarely switch languages voluntarily.\nWhatever language people happen to be used to, they tend to consider\njust good enough.Programmers get very attached to their favorite languages, and I\ndon't want to hurt anyone's feelings, so to explain this point I'm\ngoing to use a hypothetical language called Blub. Blub falls right\nin the middle of the abstractness continuum. It is not the most\npowerful language, but it is more powerful than Cobol or machine\nlanguage.And in fact, our hypothetical Blub programmer wouldn't use either\nof them. Of course he wouldn't program in machine language. That's\nwhat compilers are for. And as for Cobol, he doesn't know how\nanyone can get anything done with it. It doesn't even have x (Blub\nfeature of your choice).As long as our hypothetical Blub programmer is looking down the\npower continuum, he knows he's looking down. Languages less powerful\nthan Blub are obviously less powerful, because they're missing some\nfeature he's used to. But when our hypothetical Blub programmer\nlooks in the other direction, up the power continuum, he doesn't\nrealize he's looking up. What he sees are merely weird languages.\nHe probably considers them about equivalent in power to Blub, but\nwith all this other hairy stuff thrown in as well. Blub is good\nenough for him, because he thinks in Blub.When we switch to the point of view of a programmer using any of\nthe languages higher up the power continuum, however, we find that\nhe in turn looks down upon Blub. How can you get anything done in\nBlub? It doesn't even have y.By induction, the only programmers in a position to see all the\ndifferences in power between the various languages are those who\nunderstand the most powerful one. (This is probably what Eric\nRaymond meant about Lisp making you a better programmer.) You can't\ntrust the opinions of the others, because of the Blub paradox:\nthey're satisfied with whatever language they happen to use, because\nit dictates the way they think about programs.I know this from my own experience, as a high school kid writing\nprograms in Basic. That language didn't even support recursion.\nIt's hard to imagine writing programs without using recursion, but\nI didn't miss it at the time. I thought in Basic. And I was a\nwhiz at it. Master of all I surveyed.The five languages that Eric Raymond recommends to hackers fall at\nvarious points on the power continuum. Where they fall relative\nto one another is a sensitive topic. What I will say is that I\nthink Lisp is at the top. And to support this claim I'll tell you\nabout one of the things I find missing when I look at the other\nfour languages. How can you get anything done in them, I think,\nwithout macros? [5]Many languages have something called a macro. But Lisp macros are\nunique. And believe it or not, what they do is related to the\nparentheses. The designers of Lisp didn't put all those parentheses\nin the language just to be different. To the Blub programmer, Lisp\ncode looks weird. But those parentheses are there for a reason.\nThey are the outward evidence of a fundamental difference between\nLisp and other languages.Lisp code is made out of Lisp data objects. And not in the trivial\nsense that the source files contain characters, and strings are\none of the data types supported by the language. Lisp code, after\nit's read by the parser, is made of data structures that you can\ntraverse.If you understand how compilers work, what's really going on is\nnot so much that Lisp has a strange syntax as that Lisp has no\nsyntax. You write programs in the parse trees that get generated\nwithin the compiler when other languages are parsed. But these\nparse trees are fully accessible to your programs. You can write\nprograms that manipulate them. In Lisp, these programs are called\nmacros. They are programs that write programs.Programs that write programs? When would you ever want to do that?\nNot very often, if you think in Cobol. All the time, if you think\nin Lisp. It would be convenient here if I could give an example\nof a powerful macro, and say there! how about that? But if I did,\nit would just look like gibberish to someone who didn't know Lisp;\nthere isn't room here to explain everything you'd need to know to\nunderstand what it meant. In \nAnsi Common Lisp I tried to move\nthings along as fast as I could, and even so I didn't get to macros\nuntil page 160.But I think I can give a kind of argument that might be convincing.\nThe source code of the Viaweb editor was probably about 20-25%\nmacros. Macros are harder to write than ordinary Lisp functions,\nand it's considered to be bad style to use them when they're not\nnecessary. So every macro in that code is there because it has to\nbe. What that means is that at least 20-25% of the code in this\nprogram is doing things that you can't easily do in any other\nlanguage. However skeptical the Blub programmer might be about my\nclaims for the mysterious powers of Lisp, this ought to make him\ncurious. We weren't writing this code for our own amusement. We\nwere a tiny startup, programming as hard as we could in order to\nput technical barriers between us and our competitors.A suspicious person might begin to wonder if there was some\ncorrelation here. A big chunk of our code was doing things that\nare very hard to do in other languages. The resulting software\ndid things our competitors' software couldn't do. Maybe there was\nsome kind of connection. I encourage you to follow that thread.\nThere may be more to that old man hobbling along on his crutches\nthan meets the eye.Aikido for StartupsBut I don't expect to convince anyone \n(over 25) \nto go out and learn\nLisp. The purpose of this article is not to change anyone's mind,\nbut to reassure people already interested in using Lisp-- people\nwho know that Lisp is a powerful language, but worry because it\nisn't widely used. In a competitive situation, that's an advantage.\nLisp's power is multiplied by the fact that your competitors don't\nget it.If you think of using Lisp in a startup, you shouldn't worry that\nit isn't widely understood. You should hope that it stays that\nway. And it's likely to. It's the nature of programming languages\nto make most people satisfied with whatever they currently use.\nComputer hardware changes so much faster than personal habits that\nprogramming practice is usually ten to twenty years behind the\nprocessor. At places like MIT they were writing programs in\nhigh-level languages in the early 1960s, but many companies continued\nto write code in machine language well into the 1980s. I bet a\nlot of people continued to write machine language until the processor,\nlike a bartender eager to close up and go home, finally kicked them\nout by switching to a risc instruction set.Ordinarily technology changes fast. But programming languages are\ndifferent: programming languages are not just technology, but what\nprogrammers think in. They're half technology and half religion.[6]\nAnd so the median language, meaning whatever language the median\nprogrammer uses, moves as slow as an iceberg. Garbage collection,\nintroduced by Lisp in about 1960, is now widely considered to be\na good thing. Runtime typing, ditto, is growing in popularity.\nLexical closures, introduced by Lisp in the early 1970s, are now,\njust barely, on the radar screen. Macros, introduced by Lisp in the\nmid 1960s, are still terra incognita.Obviously, the median language has enormous momentum. I'm not\nproposing that you can fight this powerful force. What I'm proposing\nis exactly the opposite: that, like a practitioner of Aikido, you\ncan use it against your opponents.If you work for a big company, this may not be easy. You will have\na hard time convincing the pointy-haired boss to let you build\nthings in Lisp, when he has just read in the paper that some other\nlanguage is poised, like Ada was twenty years ago, to take over\nthe world. But if you work for a startup that doesn't have\npointy-haired bosses yet, you can, like we did, turn the Blub\nparadox to your advantage: you can use technology that your\ncompetitors, glued immovably to the median language, will never be\nable to match.If you ever do find yourself working for a startup, here's a handy\ntip for evaluating competitors. Read their job listings. Everything\nelse on their site may be stock photos or the prose equivalent,\nbut the job listings have to be specific about what they want, or\nthey'll get the wrong candidates.During the years we worked on Viaweb I read a lot of job descriptions.\nA new competitor seemed to emerge out of the woodwork every month\nor so. The first thing I would do, after checking to see if they\nhad a live online demo, was look at their job listings. After a\ncouple years of this I could tell which companies to worry about\nand which not to. The more of an IT flavor the job descriptions\nhad, the less dangerous the company was. The safest kind were the\nones that wanted Oracle experience. You never had to worry about\nthose. You were also safe if they said they wanted C++ or Java\ndevelopers. If they wanted Perl or Python programmers, that would\nbe a bit frightening-- that's starting to sound like a company\nwhere the technical side, at least, is run by real hackers. If I\nhad ever seen a job posting looking for Lisp hackers, I would have\nbeen really worried.\nNotes[1] Viaweb at first had two parts: the editor, written in Lisp,\nwhich people used to build their sites, and the ordering system,\nwritten in C, which handled orders. The first version was mostly\nLisp, because the ordering system was small. Later we added two\nmore modules, an image generator written in C, and a back-office\nmanager written mostly in Perl.In January 2003, Yahoo released a new version of the editor \nwritten in C++ and Perl. It's hard to say whether the program is no\nlonger written in Lisp, though, because to translate this program\ninto C++ they literally had to write a Lisp interpreter: the source\nfiles of all the page-generating templates are still, as far as I\nknow, Lisp code. (See Greenspun's Tenth Rule.)[2] Robert Morris says that I didn't need to be secretive, because\neven if our competitors had known we were using Lisp, they wouldn't\nhave understood why: \"If they were that smart they'd already be\nprogramming in Lisp.\"[3] All languages are equally powerful in the sense of being Turing\nequivalent, but that's not the sense of the word programmers care\nabout. (No one wants to program a Turing machine.) The kind of\npower programmers care about may not be formally definable, but\none way to explain it would be to say that it refers to features\nyou could only get in the less powerful language by writing an\ninterpreter for the more powerful language in it. If language A\nhas an operator for removing spaces from strings and language B\ndoesn't, that probably doesn't make A more powerful, because you\ncan probably write a subroutine to do it in B. But if A supports,\nsay, recursion, and B doesn't, that's not likely to be something\nyou can fix by writing library functions.[4] Note to nerds: or possibly a lattice, narrowing toward the top;\nit's not the shape that matters here but the idea that there is at\nleast a partial order.[5] It is a bit misleading to treat macros as a separate feature.\nIn practice their usefulness is greatly enhanced by other Lisp\nfeatures like lexical closures and rest parameters.[6] As a result, comparisons of programming languages either take\nthe form of religious wars or undergraduate textbooks so determinedly\nneutral that they're really works of anthropology. People who\nvalue their peace, or want tenure, avoid the topic. But the question\nis only half a religious one; there is something there worth\nstudying, especially if you want to design new languages." }, { "path": "data/PaulGrahamEssays/badeconomy.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nOctober 2008The economic situation is apparently so grim that some experts fear\nwe may be in for a stretch as bad as the mid seventies.When Microsoft and Apple were founded.As those examples suggest, a recession may not be such a bad time\nto start a startup. I'm not claiming it's a particularly good time\neither. The truth is more boring: the state of the economy doesn't\nmatter much either way.If we've learned one thing from funding so many startups, it's that\nthey succeed or fail based on the qualities of the founders. The\neconomy has some effect, certainly, but as a predictor of success\nit's rounding error compared to the founders.Which means that what matters is who you are, not when you do it.\nIf you're the right sort of person, you'll win even in a bad economy.\nAnd if you're not, a good economy won't save you. Someone who\nthinks \"I better not start a startup now, because the economy is\nso bad\" is making the same mistake as the people who thought during\nthe Bubble \"all I have to do is start a startup, and I'll be rich.\"So if you want to improve your chances, you should think far more\nabout who you can recruit as a cofounder than the state of the\neconomy. And if you're worried about threats to the survival of\nyour company, don't look for them in the news. Look in the mirror.But for any given team of founders, would it not pay to wait till\nthe economy is better before taking the leap? If you're starting\na restaurant, maybe, but not if you're working on technology.\nTechnology progresses more or less independently of the stock market.\nSo for any given idea, the payoff for acting fast in a bad economy\nwill be higher than for waiting. Microsoft's first product was a\nBasic interpreter for the Altair. That was exactly what the world\nneeded in 1975, but if Gates and Allen had decided to wait a few\nyears, it would have been too late.Of course, the idea you have now won't be the last you have. There\nare always new ideas. But if you have a specific idea you want to\nact on, act now.That doesn't mean you can ignore the economy. Both customers and investors\nwill be feeling pinched. It's not necessarily a problem if customers\nfeel pinched: you may even be able to benefit from it, by making\nthings that save money. \nStartups often make things cheaper, so in\nthat respect they're better positioned to prosper in a recession\nthan big companies.Investors are more of a problem. Startups generally need to raise\nsome amount of external funding, and investors tend to be less\nwilling to invest in bad times. They shouldn't be. Everyone knows\nyou're supposed to buy when times are bad and sell when times are\ngood. But of course what makes investing so counterintuitive is\nthat in equity markets, good times are defined as everyone thinking\nit's time to buy. You have to be a contrarian to be correct, and\nby definition only a minority of investors can be.So just as investors in 1999 were tripping over one another trying\nto buy into lousy startups, investors in 2009 will presumably be\nreluctant to invest even in good ones.You'll have to adapt to this. But that's nothing new: startups\nalways have to adapt to the whims of investors. Ask any founder\nin any economy if they'd describe investors as fickle, and watch\nthe face they make. Last year you had to be prepared to explain\nhow your startup was viral. Next year you'll have to explain how\nit's recession-proof.(Those are both good things to be. The mistake investors make is\nnot the criteria they use but that they always tend to focus on one\nto the exclusion of the rest.)Fortunately the way to make a startup recession-proof is to do\nexactly what you should do anyway: run it as cheaply as possible.\nFor years I've been telling founders that the surest route to success\nis to be the cockroaches of the corporate world. The immediate\ncause of death in a startup is always running out of money. So the\ncheaper your company is to operate, the harder it is to kill.\nAnd fortunately it has gotten very cheap to run a startup. A recession\nwill if anything make it cheaper still.If nuclear winter really is here, it may be safer to be a cockroach\neven than to keep your job. Customers may drop off individually\nif they can no longer afford you, but you're not going to lose them\nall at once; markets don't \"reduce headcount.\"What if you quit your job to start a startup that fails, and you\ncan't find another? That could be a problem if you work in sales or\nmarketing. In those fields it can take months to find a new\njob in a bad economy. But hackers seem to be more liquid. Good\nhackers can always get some kind of job. It might not be your dream\njob, but you're not going to starve.Another advantage of bad times is that there's less competition.\nTechnology trains leave the station at regular intervals. If \neveryone else is cowering in a corner, you may have a whole car to\nyourself.You're an investor too. As a founder, you're buying stock with\nwork: the reason Larry and Sergey are so rich is not so much that\nthey've done work worth tens of billions of dollars, but that they\nwere the first investors in Google. And like any investor you\nshould buy when times are bad.Were you nodding in agreement, thinking \"stupid investors\" a few\nparagraphs ago when I was talking about how investors are reluctant\nto put money into startups in bad markets, even though that's the\ntime they should rationally be most willing to buy? Well, founders\naren't much better. When times get bad, hackers go to grad school.\nAnd no doubt that will happen this time too. In fact, what makes\nthe preceding paragraph true is that most readers won't believe\nit—at least to the extent of acting on it.So maybe a recession is a good time to start a startup. It's hard\nto say whether advantages like lack of competition outweigh\ndisadvantages like reluctant investors. But it doesn't matter much\neither way. It's the people that matter. And for a given set of\npeople working on a given technology, the time to act is always\nnow." }, { "path": "data/PaulGrahamEssays/before.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nOctober 2014(This essay is derived from a guest lecture in Sam Altman's startup class at\nStanford. It's intended for college students, but much of it is\napplicable to potential founders at other ages.)One of the advantages of having kids is that when you have to give\nadvice, you can ask yourself \"what would I tell my own kids?\" My\nkids are little, but I can imagine what I'd tell them about startups\nif they were in college, and that's what I'm going to tell you.Startups are very counterintuitive. I'm not sure why. Maybe it's\njust because knowledge about them hasn't permeated our culture yet.\nBut whatever the reason, starting a startup is a task where you\ncan't always trust your instincts.It's like skiing in that way. When you first try skiing and you\nwant to slow down, your instinct is to lean back. But if you lean\nback on skis you fly down the hill out of control. So part of\nlearning to ski is learning to suppress that impulse. Eventually\nyou get new habits, but at first it takes a conscious effort. At\nfirst there's a list of things you're trying to remember as you\nstart down the hill.Startups are as unnatural as skiing, so there's a similar list for\nstartups. Here I'm going to give you the first part of it — the things\nto remember if you want to prepare yourself to start a startup.\nCounterintuitiveThe first item on it is the fact I already mentioned: that startups\nare so weird that if you trust your instincts, you'll make a lot\nof mistakes. If you know nothing more than this, you may at least\npause before making them.When I was running Y Combinator I used to joke that our function\nwas to tell founders things they would ignore. It's really true.\nBatch after batch, the YC partners warn founders about mistakes\nthey're about to make, and the founders ignore them, and then come\nback a year later and say \"I wish we'd listened.\"Why do the founders ignore the partners' advice? Well, that's the\nthing about counterintuitive ideas: they contradict your intuitions.\nThey seem wrong. So of course your first impulse is to disregard\nthem. And in fact my joking description is not merely the curse\nof Y Combinator but part of its raison d'etre. If founders' instincts\nalready gave them the right answers, they wouldn't need us. You\nonly need other people to give you advice that surprises you. That's\nwhy there are a lot of ski instructors and not many running\ninstructors.\n[1]You can, however, trust your instincts about people. And in fact\none of the most common mistakes young founders make is not to\ndo that enough. They get involved with people who seem impressive,\nbut about whom they feel some misgivings personally. Later when\nthings blow up they say \"I knew there was something off about him,\nbut I ignored it because he seemed so impressive.\"If you're thinking about getting involved with someone — as a\ncofounder, an employee, an investor, or an acquirer — and you\nhave misgivings about them, trust your gut. If someone seems\nslippery, or bogus, or a jerk, don't ignore it.This is one case where it pays to be self-indulgent. Work with\npeople you genuinely like, and you've known long enough to be sure.\nExpertiseThe second counterintuitive point is that it's not that important\nto know a lot about startups. The way to succeed in a startup is\nnot to be an expert on startups, but to be an expert on your users\nand the problem you're solving for them.\nMark Zuckerberg didn't succeed because he was an expert on startups.\nHe succeeded despite being a complete noob at startups, because he\nunderstood his users really well.If you don't know anything about, say, how to raise an angel round,\ndon't feel bad on that account. That sort of thing you can learn\nwhen you need to, and forget after you've done it.In fact, I worry it's not merely unnecessary to learn in great\ndetail about the mechanics of startups, but possibly somewhat\ndangerous. If I met an undergrad who knew all about convertible\nnotes and employee agreements and (God forbid) class FF stock, I\nwouldn't think \"here is someone who is way ahead of their peers.\"\nIt would set off alarms. Because another of the characteristic\nmistakes of young founders is to go through the motions of starting\na startup. They make up some plausible-sounding idea, raise money\nat a good valuation, rent a cool office, hire a bunch of people.\nFrom the outside that seems like what startups do. But the next\nstep after rent a cool office and hire a bunch of people is: gradually\nrealize how completely fucked they are, because while imitating all\nthe outward forms of a startup they have neglected the one thing\nthat's actually essential: making something people want.\nGameWe saw this happen so often that we made up a name for it: playing\nhouse. Eventually I realized why it was happening. The reason\nyoung founders go through the motions of starting a startup is\nbecause that's what they've been trained to do for their whole lives\nup to that point. Think about what you have to do to get into\ncollege, for example. Extracurricular activities, check. Even in\ncollege classes most of the work is as artificial as running laps.I'm not attacking the educational system for being this way. There\nwill always be a certain amount of fakeness in the work you do when\nyou're being taught something, and if you measure their performance\nit's inevitable that people will exploit the difference to the point\nwhere much of what you're measuring is artifacts of the fakeness.I confess I did it myself in college. I found that in a lot of\nclasses there might only be 20 or 30 ideas that were the right shape\nto make good exam questions. The way I studied for exams in these\nclasses was not (except incidentally) to master the material taught\nin the class, but to make a list of potential exam questions and\nwork out the answers in advance. When I walked into the final, the\nmain thing I'd be feeling was curiosity about which of my questions\nwould turn up on the exam. It was like a game.It's not surprising that after being trained for their whole lives\nto play such games, young founders' first impulse on starting a\nstartup is to try to figure out the tricks for winning at this new\ngame. Since fundraising appears to be the measure of success for\nstartups (another classic noob mistake), they always want to know what the\ntricks are for convincing investors. We tell them the best way to\nconvince investors is to make a startup\nthat's actually doing well, meaning growing fast, and then simply\ntell investors so. Then they want to know what the tricks are for\ngrowing fast. And we have to tell them the best way to do that is\nsimply to make something people want.So many of the conversations YC partners have with young founders\nbegin with the founder asking \"How do we...\" and the partner replying\n\"Just...\"Why do the founders always make things so complicated? The reason,\nI realized, is that they're looking for the trick.So this is the third counterintuitive thing to remember about\nstartups: starting a startup is where gaming the system stops\nworking. Gaming the system may continue to work if you go to work\nfor a big company. Depending on how broken the company is, you can\nsucceed by sucking up to the right people, giving the impression\nof productivity, and so on. \n[2]\nBut that doesn't work with startups.\nThere is no boss to trick, only users, and all users care about is\nwhether your product does what they want. Startups are as impersonal\nas physics. You have to make something people want, and you prosper\nonly to the extent you do.The dangerous thing is, faking does work to some degree on investors.\nIf you're super good at sounding like you know what you're talking\nabout, you can fool investors for at least one and perhaps even two\nrounds of funding. But it's not in your interest to. The company\nis ultimately doomed. All you're doing is wasting your own time\nriding it down.So stop looking for the trick. There are tricks in startups, as\nthere are in any domain, but they are an order of magnitude less\nimportant than solving the real problem. A founder who knows nothing\nabout fundraising but has made something users love will have an\neasier time raising money than one who knows every trick in the\nbook but has a flat usage graph. And more importantly, the founder\nwho has made something users love is the one who will go on to\nsucceed after raising the money.Though in a sense it's bad news in that you're deprived of one of\nyour most powerful weapons, I think it's exciting that gaming the\nsystem stops working when you start a startup. It's exciting that\nthere even exist parts of the world where you win by doing good\nwork. Imagine how depressing the world would be if it were all\nlike school and big companies, where you either have to spend a lot\nof time on bullshit things or lose to people who do.\n[3]\nI would\nhave been delighted if I'd realized in college that there were parts\nof the real world where gaming the system mattered less than others,\nand a few where it hardly mattered at all. But there are, and this\nvariation is one of the most important things to consider when\nyou're thinking about your future. How do you win in each type of\nwork, and what would you like to win by doing?\n[4]\nAll-ConsumingThat brings us to our fourth counterintuitive point: startups are\nall-consuming. If you start a startup, it will take over your life\nto a degree you cannot imagine. And if your startup succeeds, it\nwill take over your life for a long time: for several years at the\nvery least, maybe for a decade, maybe for the rest of your working\nlife. So there is a real opportunity cost here.Larry Page may seem to have an enviable life, but there are aspects\nof it that are unenviable. Basically at 25 he started running as\nfast as he could and it must seem to him that he hasn't stopped to\ncatch his breath since. Every day new shit happens in the Google\nempire that only the CEO can deal with, and he, as CEO, has to deal\nwith it. If he goes on vacation for even a week, a whole week's\nbacklog of shit accumulates. And he has to bear this uncomplainingly,\npartly because as the company's daddy he can never show fear or\nweakness, and partly because billionaires get less than zero sympathy\nif they talk about having difficult lives. Which has the strange\nside effect that the difficulty of being a successful startup founder\nis concealed from almost everyone except those who've done it.Y Combinator has now funded several companies that can be called\nbig successes, and in every single case the founders say the same\nthing. It never gets any easier. The nature of the problems change.\nYou're worrying about construction delays at your London office\ninstead of the broken air conditioner in your studio apartment.\nBut the total volume of worry never decreases; if anything it\nincreases.Starting a successful startup is similar to having kids in that\nit's like a button you push that changes your life irrevocably.\nAnd while it's truly wonderful having kids, there are a lot of\nthings that are easier to do before you have them than after. Many\nof which will make you a better parent when you do have kids. And\nsince you can delay pushing the button for a while, most people in\nrich countries do.Yet when it comes to startups, a lot of people seem to think they're\nsupposed to start them while they're still in college. Are you\ncrazy? And what are the universities thinking? They go out of\ntheir way to ensure their students are well supplied with contraceptives,\nand yet they're setting up entrepreneurship programs and startup\nincubators left and right.To be fair, the universities have their hand forced here. A lot\nof incoming students are interested in startups. Universities are,\nat least de facto, expected to prepare them for their careers. So\nstudents who want to start startups hope universities can teach\nthem about startups. And whether universities can do this or not,\nthere's some pressure to claim they can, lest they lose applicants\nto other universities that do.Can universities teach students about startups? Yes and no. They\ncan teach students about startups, but as I explained before, this\nis not what you need to know. What you need to learn about are the\nneeds of your own users, and you can't do that until you actually\nstart the company.\n[5]\nSo starting a startup is intrinsically\nsomething you can only really learn by doing it. And it's impossible\nto do that in college, for the reason I just explained: startups\ntake over your life. You can't start a startup for real as a\nstudent, because if you start a startup for real you're not a student\nanymore. You may be nominally a student for a bit, but you won't even\nbe that for long.\n[6]Given this dichotomy, which of the two paths should you take? Be\na real student and not start a startup, or start a real startup and\nnot be a student? I can answer that one for you. Do not start a\nstartup in college. How to start a startup is just a subset of a\nbigger problem you're trying to solve: how to have a good life.\nAnd though starting a startup can be part of a good life for a lot\nof ambitious people, age 20 is not the optimal time to do it.\nStarting a startup is like a brutally fast depth-first search. Most\npeople should still be searching breadth-first at 20.You can do things in your early 20s that you can't do as well before\nor after, like plunge deeply into projects on a whim and travel\nsuper cheaply with no sense of a deadline. For unambitious people,\nthis sort of thing is the dreaded \"failure to launch,\" but for the\nambitious ones it can be an incomparably valuable sort of exploration.\nIf you start a startup at 20 and you're sufficiently successful,\nyou'll never get to do it.\n[7]Mark Zuckerberg will never get to bum around a foreign country. He\ncan do other things most people can't, like charter jets to fly him\nto foreign countries. But success has taken a lot of the serendipity\nout of his life. Facebook is running him as much as he's running\nFacebook. And while it can be very cool to be in the grip of a\nproject you consider your life's work, there are advantages to\nserendipity too, especially early in life. Among other things it\ngives you more options to choose your life's work from.There's not even a tradeoff here. You're not sacrificing anything\nif you forgo starting a startup at 20, because you're more likely\nto succeed if you wait. In the unlikely case that you're 20 and\none of your side projects takes off like Facebook did, you'll face\na choice of running with it or not, and it may be reasonable to run\nwith it. But the usual way startups take off is for the founders\nto make them take off, and it's gratuitously\nstupid to do that at 20.\nTryShould you do it at any age? I realize I've made startups sound\npretty hard. If I haven't, let me try again: starting a startup\nis really hard. What if it's too hard? How can you tell if you're\nup to this challenge?The answer is the fifth counterintuitive point: you can't tell. Your\nlife so far may have given you some idea what your prospects might\nbe if you tried to become a mathematician, or a professional football\nplayer. But unless you've had a very strange life you haven't done\nmuch that was like being a startup founder.\nStarting a startup will change you a lot. So what you're trying\nto estimate is not just what you are, but what you could grow into,\nand who can do that?For the past 9 years it was my job to predict whether people would\nhave what it took to start successful startups. It was easy to\ntell how smart they were, and most people reading this will be over\nthat threshold. The hard part was predicting how tough and ambitious they would become. There\nmay be no one who has more experience at trying to predict that,\nso I can tell you how much an expert can know about it, and the\nanswer is: not much. I learned to keep a completely open mind about\nwhich of the startups in each batch would turn out to be the stars.The founders sometimes think they know. Some arrive feeling sure\nthey will ace Y Combinator just as they've aced every one of the (few,\nartificial, easy) tests they've faced in life so far. Others arrive\nwondering how they got in, and hoping YC doesn't discover whatever\nmistake caused it to accept them. But there is little correlation\nbetween founders' initial attitudes and how well their companies\ndo.I've read that the same is true in the military — that the\nswaggering recruits are no more likely to turn out to be really\ntough than the quiet ones. And probably for the same reason: that\nthe tests involved are so different from the ones in their previous\nlives.If you're absolutely terrified of starting a startup, you probably\nshouldn't do it. But if you're merely unsure whether you're up to\nit, the only way to find out is to try. Just not now.\nIdeasSo if you want to start a startup one day, what should you do in\ncollege? There are only two things you need initially: an idea and\ncofounders. And the m.o. for getting both is the same. Which leads\nto our sixth and last counterintuitive point: that the way to get\nstartup ideas is not to try to think of startup ideas.I've written a whole essay on this,\nso I won't repeat it all here. But the short version is that if\nyou make a conscious effort to think of startup ideas, the ideas\nyou come up with will not merely be bad, but bad and plausible-sounding,\nmeaning you'll waste a lot of time on them before realizing they're\nbad.The way to come up with good startup ideas is to take a step back.\nInstead of making a conscious effort to think of startup ideas,\nturn your mind into the type that startup ideas form in without any\nconscious effort. In fact, so unconsciously that you don't even\nrealize at first that they're startup ideas.This is not only possible, it's how Apple, Yahoo, Google, and\nFacebook all got started. None of these companies were even meant\nto be companies at first. They were all just side projects. The\nbest startups almost have to start as side projects, because great\nideas tend to be such outliers that your conscious mind would reject\nthem as ideas for companies.Ok, so how do you turn your mind into the type that startup ideas\nform in unconsciously? (1) Learn a lot about things that matter,\nthen (2) work on problems that interest you (3) with people you\nlike and respect. The third part, incidentally, is how you get\ncofounders at the same time as the idea.The first time I wrote that paragraph, instead of \"learn a lot about\nthings that matter,\" I wrote \"become good at some technology.\" But\nthat prescription, though sufficient, is too narrow. What was\nspecial about Brian Chesky and Joe Gebbia was not that they were\nexperts in technology. They were good at design, and perhaps even\nmore importantly, they were good at organizing groups and making\nprojects happen. So you don't have to work on technology per se,\nso long as you work on problems demanding enough to stretch you.What kind of problems are those? That is very hard to answer in\nthe general case. History is full of examples of young people who\nwere working on important problems that no\none else at the time thought were important, and in particular\nthat their parents didn't think were important. On the other hand,\nhistory is even fuller of examples of parents who thought their\nkids were wasting their time and who were right. So how do you\nknow when you're working on real stuff?\n[8]I know how I know. Real problems are interesting, and I am\nself-indulgent in the sense that I always want to work on interesting\nthings, even if no one else cares about them (in fact, especially\nif no one else cares about them), and find it very hard to make\nmyself work on boring things, even if they're supposed to be\nimportant.My life is full of case after case where I worked on something just\nbecause it seemed interesting, and it turned out later to be useful\nin some worldly way. Y\nCombinator itself was something I only did because it seemed\ninteresting. So I seem to have some sort of internal compass that\nhelps me out. But I don't know what other people have in their\nheads. Maybe if I think more about this I can come up with heuristics\nfor recognizing genuinely interesting problems, but for the moment\nthe best I can offer is the hopelessly question-begging advice that\nif you have a taste for genuinely interesting problems, indulging\nit energetically is the best way to prepare yourself for a startup.\nAnd indeed, probably also the best way to live.\n[9]But although I can't explain in the general case what counts as an\ninteresting problem, I can tell you about a large subset of them.\nIf you think of technology as something that's spreading like a\nsort of fractal stain, every moving point on the edge represents\nan interesting problem. So one guaranteed way to turn your mind\ninto the type that has good startup ideas is to get yourself to the\nleading edge of some technology — to cause yourself, as Paul\nBuchheit put it, to \"live in the future.\" When you reach that point,\nideas that will seem to other people uncannily prescient will seem\nobvious to you. You may not realize they're startup ideas, but\nyou'll know they're something that ought to exist.For example, back at Harvard in the mid 90s a fellow grad student\nof my friends Robert and Trevor wrote his own voice over IP software.\nHe didn't mean it to be a startup, and he never tried to turn it\ninto one. He just wanted to talk to his girlfriend in Taiwan without\npaying for long distance calls, and since he was an expert on\nnetworks it seemed obvious to him that the way to do it was turn\nthe sound into packets and ship it over the Internet. He never did\nany more with his software than talk to his girlfriend, but this\nis exactly the way the best startups get started.So strangely enough the optimal thing to do in college if you want\nto be a successful startup founder is not some sort of new, vocational\nversion of college focused on \"entrepreneurship.\" It's the classic\nversion of college as education for its own sake. If you want to\nstart a startup after college, what you should do in college is\nlearn powerful things. And if you have genuine intellectual\ncuriosity, that's what you'll naturally tend to do if you just\nfollow your own inclinations.\n[10]The component of entrepreneurship that really matters is domain\nexpertise. The way to become Larry Page was to become an expert\non search. And the way to become an expert on search was to be\ndriven by genuine curiosity, not some ulterior motive.At its best, starting a startup is merely an ulterior motive for\ncuriosity. And you'll do it best if you introduce the ulterior\nmotive toward the end of the process.So here is the ultimate advice for young would-be startup founders,\nboiled down to two words: just learn.\nNotes[1]\nSome founders listen more than others, and this tends to be a\npredictor of success. One of the things I\nremember about the Airbnbs during YC is how intently they listened.[2]\nIn fact, this is one of the reasons startups are possible. If\nbig companies weren't plagued by internal inefficiencies, they'd\nbe proportionately more effective, leaving less room for startups.[3]\nIn a startup you have to spend a lot of time on schleps, but this sort of work is merely\nunglamorous, not bogus.[4]\nWhat should you do if your true calling is gaming the system?\nManagement consulting.[5]\nThe company may not be incorporated, but if you start to get\nsignificant numbers of users, you've started it, whether you realize\nit yet or not.[6]\nIt shouldn't be that surprising that colleges can't teach\nstudents how to be good startup founders, because they can't teach\nthem how to be good employees either.The way universities \"teach\" students how to be employees is to\nhand off the task to companies via internship programs. But you\ncouldn't do the equivalent thing for startups, because by definition\nif the students did well they would never come back.[7]\nCharles Darwin was 22 when he received an invitation to travel\naboard the HMS Beagle as a naturalist. It was only because he was\notherwise unoccupied, to a degree that alarmed his family, that he\ncould accept it. And yet if he hadn't we probably would not know\nhis name.[8]\nParents can sometimes be especially conservative in this\ndepartment. There are some whose definition of important problems\nincludes only those on the critical path to med school.[9]\nI did manage to think of a heuristic for detecting whether you\nhave a taste for interesting ideas: whether you find known boring\nideas intolerable. Could you endure studying literary theory, or\nworking in middle management at a large company?[10]\nIn fact, if your goal is to start a startup, you can stick\neven more closely to the ideal of a liberal education than past\ngenerations have. Back when students focused mainly on getting a\njob after college, they thought at least a little about how the\ncourses they took might look to an employer. And perhaps even\nworse, they might shy away from taking a difficult class lest they\nget a low grade, which would harm their all-important GPA. Good\nnews: users don't care what your GPA\nwas. And I've never heard of investors caring either. Y Combinator\ncertainly never asks what classes you took in college or what grades\nyou got in them.\nThanks to Sam Altman, Paul Buchheit, John Collison, Patrick\nCollison, Jessica Livingston, Robert Morris, Geoff Ralston, and\nFred Wilson for reading drafts of this." }, { "path": "data/PaulGrahamEssays/better.txt", "content": "January 2003(This article was given as a talk at the 2003 Spam Conference.\nIt describes the work I've done to improve the performance of\nthe algorithm described in A Plan for Spam,\nand what I plan to do in the future.)The first discovery I'd like to present here is an algorithm for\nlazy evaluation of research papers. Just\nwrite whatever you want and don't cite any previous work, and\nindignant readers will send you references to all the papers you\nshould have cited. I discovered this algorithm\nafter ``A Plan for Spam'' [1] was on Slashdot.Spam filtering is a subset of text classification,\nwhich is a well established field, but the first papers about\nBayesian\nspam filtering per se seem to have been two\ngiven at the same conference in 1998,\none by Pantel and Lin [2],\nand another by a group from\nMicrosoft Research [3].When I heard about this work I was a bit surprised. If\npeople had been onto Bayesian filtering four years ago,\nwhy wasn't everyone using it?\nWhen I read the papers I found out why. Pantel and Lin's filter was the\nmore effective of the two, but it\nonly caught 92% of spam, with 1.16% false positives.When I tried writing a Bayesian spam filter,\nit caught 99.5% of spam with less than .03% false\npositives [4].\nIt's always alarming when two people\ntrying the same experiment get widely divergent results.\nIt's especially alarming here because those two sets of numbers\nmight yield opposite conclusions.\nDifferent users have different requirements, but I think for\nmany people a filtering rate of 92% with 1.16% false positives means\nthat filtering is not an acceptable solution, whereas\n99.5% with less than .03% false positives means that it is.So why did we get such different numbers?\nI haven't tried to reproduce Pantel and Lin's results, but\nfrom reading the paper I see five things that probably account\nfor the difference.One is simply that they trained their filter on very little\ndata: 160 spam and 466 nonspam mails.\nFilter performance should still be climbing with data\nsets that small. So their numbers may not even be an accurate\nmeasure of the performance of their algorithm, let alone of\nBayesian spam filtering in general.But I think the most important difference is probably\nthat they ignored message headers. To anyone who has worked\non spam filters, this will seem a perverse decision.\nAnd yet in the very first filters I tried writing, I ignored the\nheaders too. Why? Because I wanted to keep the problem neat.\nI didn't know much about mail headers then, and they seemed to me\nfull of random stuff. There is a lesson here for filter\nwriters: don't ignore data. You'd think this lesson would\nbe too obvious to mention, but I've had to learn it several times.Third, Pantel and Lin stemmed the tokens, meaning they reduced e.g. both\n``mailing'' and ``mailed'' to the root ``mail''. They may\nhave felt they were forced to do this by the small size\nof their corpus, but if so this is a kind of premature \noptimization.Fourth, they calculated probabilities differently.\nThey used all the tokens, whereas I only\nuse the 15 most significant. If you use all the tokens\nyou'll tend to miss longer spams, the type where someone tells you their life\nstory up to the point where they got rich from some multilevel\nmarketing scheme. And such an algorithm\nwould be easy for spammers to spoof: just add a big\nchunk of random text to counterbalance the spam terms.Finally, they didn't bias against false positives.\nI think\nany spam filtering algorithm ought to have a convenient\nknob you can twist to decrease the\nfalse positive rate at the expense of the filtering rate.\nI do this by counting the occurrences\nof tokens in the nonspam corpus double. \nI don't think it's a good idea to treat spam filtering as\na straight text classification problem. You can use\ntext classification techniques, but solutions can and should\nreflect the fact that the text is email, and spam\nin particular. Email is not just text; it has structure.\nSpam filtering is not just classification, because\nfalse positives are so much worse than false negatives\nthat you should treat them as a different kind of error.\nAnd the source of error is not just random variation, but\na live human spammer working actively to defeat your filter.TokensAnother project I heard about\nafter the Slashdot article was Bill Yerazunis' \nCRM114 [5].\nThis is the counterexample to the design principle I\njust mentioned. It's a straight text classifier,\nbut such a stunningly effective one that it manages to filter\nspam almost perfectly without even knowing that's\nwhat it's doing.Once I understood how CRM114 worked, it seemed\ninevitable that I would eventually have to move from filtering based\non single words to an approach like this. But first, I thought,\nI'll see how far I can get with single words. And the answer is,\nsurprisingly far.Mostly I've been working on smarter tokenization. On\ncurrent spam, I've been able to achieve filtering rates that\napproach CRM114's. These techniques are mostly orthogonal to Bill's;\nan optimal solution might incorporate both.``A Plan for Spam'' uses a very simple\ndefinition of a token. Letters, digits, dashes, apostrophes,\nand dollar signs are constituent characters, and everything\nelse is a token separator. I also ignored case.Now I have a more complicated definition of a token:\n\n Case is preserved. Exclamation points are constituent characters. Periods and commas are constituents if they occur\n between two digits. This lets me get ip addresses\n and prices intact. A price range like $20-25 yields two tokens,\n $20 and $25. Tokens that occur within the\n To, From, Subject, and Return-Path lines, or within urls,\n get marked accordingly. E.g. ``foo'' in the Subject line\n becomes ``Subject*foo''. (The asterisk could\n be any character you don't allow as a constituent.)\n\nSuch measures increase the filter's vocabulary, which\nmakes it more discriminating. For example, in the current\nfilter, ``free'' in the Subject line\nhas a spam probability of 98%, whereas the same token\nin the body has a spam probability of only 65%.Here are some of the current probabilities [6]:\nSubject*FREE 0.9999\nfree!! 0.9999\nTo*free 0.9998\nSubject*free 0.9782\nfree! 0.9199\nFree 0.9198\nUrl*free 0.9091\nFREE 0.8747\nFrom*free 0.7636\nfree 0.6546\n\nIn the Plan for Spam filter, all these tokens would have had the\nsame probability, .7602. That filter recognized about 23,000\ntokens. The current one recognizes about 187,000.The disadvantage of having a larger universe of tokens\nis that there is more\nchance of misses.\nSpreading your corpus out over more tokens\nhas the same effect as making it smaller.\nIf you consider exclamation points as\nconstituents, for example, then you could end up\nnot having a spam probability for free with seven exclamation\npoints, even though you know that free with just two \nexclamation points has a probability of 99.99%.One solution to this is what I call degeneration. If you\ncan't find an exact match for a token,\ntreat it as if it were a less specific\nversion. I consider terminal exclamation\npoints, uppercase letters, and occurring in one of the\nfive marked contexts as making a token more specific.\nFor example, if I don't find a probability for\n``Subject*free!'', I look for probabilities for\n``Subject*free'', ``free!'', and ``free'', and take whichever one\nis farthest from .5.Here are the alternatives [7]\nconsidered if the filter sees ``FREE!!!'' in the\nSubject line and doesn't have a probability for it.\nSubject*Free!!!\nSubject*free!!!\nSubject*FREE!\nSubject*Free!\nSubject*free!\nSubject*FREE\nSubject*Free\nSubject*free\nFREE!!!\nFree!!!\nfree!!!\nFREE!\nFree!\nfree!\nFREE\nFree\nfree \n\nIf you do this, be sure to consider versions with initial\ncaps as well as all uppercase and all lowercase. Spams\ntend to have more sentences in imperative mood, and in\nthose the first word is a verb. So verbs with initial caps\nhave higher spam probabilities than they would in all \nlowercase. In my filter, the spam probability of ``Act''\nis 98% and for ``act'' only 62%.If you increase your filter's vocabulary, you can end up\ncounting the same word multiple times, according to your old\ndefinition of ``same''.\nLogically, they're not the\nsame token anymore. But if this still bothers you, let\nme add from experience that the words you seem to be\ncounting multiple times tend to be exactly the ones you'd\nwant to.Another effect of a larger vocabulary is that when you\nlook at an incoming mail you find more interesting tokens,\nmeaning those with probabilities far from .5. I use the\n15 most interesting to decide if mail is spam.\nBut you can run into a problem when you use a fixed number\nlike this. If you find a lot of maximally interesting tokens,\nthe result can end up being decided by whatever random factor\ndetermines the ordering of equally interesting tokens.\nOne way to deal with this is to treat some\nas more interesting than others.For example, the\ntoken ``dalco'' occurs 3 times in my spam corpus and never\nin my legitimate corpus. The token ``Url*optmails''\n(meaning ``optmails'' within a url) occurs 1223 times.\nAnd yet, as I used to calculate probabilities for tokens,\nboth would have the same spam probability, the threshold of .99.That doesn't feel right. There are theoretical\narguments for giving these two tokens substantially different\nprobabilities (Pantel and Lin do), but I haven't tried that yet.\nIt does seem at least that if we find more than 15 tokens\nthat only occur in one corpus or the other, we ought to\ngive priority to the ones that occur a lot. So now\nthere are two threshold values. For tokens that occur only\nin the spam corpus, the probability is .9999 if they\noccur more than 10 times and .9998 otherwise. Ditto\nat the other end of the scale for tokens found\nonly in the legitimate corpus.I may later scale token probabilities substantially,\nbut this tiny amount of scaling at least ensures that \ntokens get sorted the right way.Another possibility would be to consider not\njust 15 tokens, but all the tokens over a certain\nthreshold of interestingness. Steven Hauser does this\nin his statistical spam filter [8].\nIf you use a threshold, make it very high, or\nspammers could spoof you by packing messages with\nmore innocent words.Finally, what should one do\nabout html? I've tried the whole spectrum of options, from\nignoring it to parsing it all. Ignoring html is a bad idea,\nbecause it's full of useful spam signs. But if you parse \nit all, your filter might degenerate into a mere html \nrecognizer. The most effective approach\nseems to be the middle course, to notice some tokens but not\nothers. I look at a, img, and font tags, and ignore the\nrest. Links and images you should certainly look at, because\nthey contain urls.I could probably be smarter about dealing with html, but I\ndon't think it's worth putting a lot of time into this.\nSpams full of html are easy to filter. The smarter\nspammers already avoid it. So\nperformance in the future should not depend much on how\nyou deal with html.PerformanceBetween December 10 2002 and January 10 2003 I got about\n1750 spams. \nOf these, 4 got through. That's a filtering\nrate of about 99.75%.Two of the four spams I missed got through because they\nhappened to use words that occur often in my legitimate\nemail.The third was one of those that exploit\nan insecure cgi script to send mail to third parties.\nThey're hard to filter based just\non the content because the headers are innocent and \nthey're careful about the words they use. Even so I can\nusually catch them. This one squeaked by with a\nprobability of .88, just under the threshold of .9.Of course, looking at multiple token sequences\nwould catch it easily. ``Below is the result of\nyour feedback form'' is an instant giveaway.The fourth spam was what I call\na spam-of-the-future, because this is what I expect spam to\nevolve into: some completely neutral\ntext followed by a url. In this case it was was from\nsomeone saying they had finally finished their homepage\nand would I go look at it. (The page was of course an \nad for a porn site.)If the spammers are careful about the headers and use a\nfresh url, there is nothing in spam-of-the-future for filters\nto notice. We can of course counter by sending a\ncrawler to look at the page. But that might not be necessary.\nThe response rate for spam-of-the-future must\nbe low, or everyone would be doing it.\nIf it's low enough,\nit won't pay for spammers to send it, and we won't \nhave to work too hard on filtering it.Now for the really shocking news: during that same one-month\nperiod I got three false positives.In a way it's\na relief to get some false positives. When I wrote ``A Plan\nfor Spam'' I hadn't had any, and I didn't know what they'd\nbe like. Now that I've had a few, I'm relieved to find\nthey're not as bad as I feared.\nFalse positives yielded by statistical\nfilters turn out to be mails that sound a lot like spam, and\nthese tend to be the ones you would least mind missing [9].Two of the false positives were newsletters\nfrom companies I've bought things from. I never\nasked to receive them, so arguably they\nwere spams, but I count them as false positives because\nI hadn't been deleting them as spams before. The reason\nthe filters caught them was that both companies in \nJanuary switched to commercial email senders\ninstead of sending the mails from their own servers, \nand both the headers and the bodies became much spammier.The third false positive was a bad one, though. It was \nfrom someone in Egypt and written in all uppercase. This was\na direct result of making tokens case sensitive; the Plan\nfor Spam filter wouldn't have caught it.It's hard to say what the overall false positive rate is,\nbecause we're up in the noise, statistically.\nAnyone who has worked on filters (at least, effective filters) will\nbe aware of this problem.\nWith some emails it's\nhard to say whether they're spam or not, and these are\nthe ones you end up looking at when you get filters \nreally tight. For example, so far the filter has\ncaught two emails that were sent to my address because\nof a typo, and one sent to me in the belief that I was \nsomeone else. Arguably, these are neither my spam\nnor my nonspam mail.Another false positive was from a vice president at Virtumundo.\nI wrote to them pretending to be a customer,\nand since the reply came back through Virtumundo's \nmail servers it had the most incriminating\nheaders imaginable. Arguably this isn't a real false\npositive either, but a sort of Heisenberg uncertainty\neffect: I only got it because I was writing about spam \nfiltering.Not counting these, I've had a total of five false positives\nso far, out of about 7740 legitimate emails, a rate of .06%.\nThe other two were a notice that something I bought\nwas back-ordered, and a party reminder from Evite.I don't think this number can be trusted, partly\nbecause the sample is so small, and partly because\nI think I can fix the filter not to catch\nsome of these.False positives seem to me a different kind of error from\nfalse negatives.\nFiltering rate is a measure of performance. False\npositives I consider more like bugs. I approach improving the\nfiltering rate as optimization, and decreasing false\npositives as debugging.So these five false positives are my bug list. For example, \nthe mail from Egypt got nailed because the uppercase text\nmade it look to the filter like a Nigerian spam.\nThis really is kind of a bug. As with\nhtml, the email being all uppercase is really conceptually one\nfeature, not one for each word. I need to handle case in a\nmore sophisticated way.So what to make of this .06%? Not much, I think. You could\ntreat it as an upper bound, bearing in mind the small sample size.\nBut at this stage it is more a measure of the bugs\nin my implementation than some intrinsic false positive rate\nof Bayesian filtering.FutureWhat next? Filtering is an optimization problem,\nand the key to optimization is profiling. Don't\ntry to guess where your code is slow, because you'll\nguess wrong. Look at where your code is slow,\nand fix that. In filtering, this translates to: \nlook at the spams you miss, and figure out what you\ncould have done to catch them.For example, spammers are now working aggressively to \nevade filters, and one of the things they're doing is\nbreaking up and misspelling words to prevent filters from\nrecognizing them. But working on this is not my first\npriority, because I still have no trouble catching these\nspams [10].There are two kinds of spams I currently do\nhave trouble with.\nOne is the type that pretends to be an email from \na woman inviting you to go chat with her or see her profile on a dating\nsite. These get through because they're the one type of\nsales pitch you can make without using sales talk. They use\nthe same vocabulary as ordinary email.The other kind of spams I have trouble filtering are those\nfrom companies in e.g. Bulgaria offering contract programming \nservices. These get through because I'm a programmer too, and\nthe spams are full of the same words as my real mail.I'll probably focus on the personal ad type first. I think if\nI look closer I'll be able to find statistical differences\nbetween these and my real mail. The style of writing is\ncertainly different, though it may take multiword filtering\nto catch that.\nAlso, I notice they tend to repeat the url,\nand someone including a url in a legitimate mail wouldn't do that [11].The outsourcing type are going to be hard to catch. Even if \nyou sent a crawler to the site, you wouldn't find a smoking\nstatistical gun.\nMaybe the only answer is a central list of\ndomains advertised in spams [12]. But there can't be that\nmany of this type of mail. If the only\nspams left were unsolicited offers of contract programming\nservices from Bulgaria, we could all probably move on to\nworking on something else.Will statistical filtering actually get us to that point?\nI don't know. Right now, for me personally, spam is\nnot a problem. But spammers haven't yet made a serious\neffort to spoof statistical filters. What will happen when they do?I'm not optimistic about filters that work at the\nnetwork level [13].\nWhen there is a static obstacle worth getting past, spammers\nare pretty efficient at getting past it. There\nis already a company called Assurance Systems that will\nrun your mail through Spamassassin and tell you whether \nit will get filtered out.Network-level filters won't be completely useless.\nThey may be enough to kill all the \"opt-in\"\nspam, meaning spam from companies like Virtumundo and\nEqualamail who claim that they're really running opt-in lists.\nYou can filter those based just on the headers, no\nmatter what they say in the body. But anyone willing to\nfalsify headers or use open relays, presumably including\nmost porn spammers, should be able to get some message past\nnetwork-level filters if they want to. (By no means the\nmessage they'd like to send though, which is something.)The kind of filters I'm optimistic about are ones that\ncalculate probabilities based on each individual user's mail.\nThese can be much more effective, not only in\navoiding false positives, but in filtering too: for example,\nfinding the recipient's email address base-64 encoded anywhere in\na message is a very good spam indicator.But the real advantage of individual filters is that they'll all be\ndifferent. If everyone's filters have different probabilities,\nit will make the spammers' optimization loop, what programmers\nwould call their edit-compile-test cycle, appallingly slow. \nInstead of just tweaking a spam till it gets through a copy of\nsome filter they have on their desktop, they'll have to do a\ntest mailing for each tweak. It would be like programming in\na language without an interactive toplevel, \nand I wouldn't wish that\non anyone.Notes[1]\nPaul Graham. ``A Plan for Spam.'' August 2002.\nhttp://paulgraham.com/spam.html.Probabilities in this algorithm are\ncalculated using a degenerate case of Bayes' Rule. There are\ntwo simplifying assumptions: that the probabilities\nof features (i.e. words) are independent, and that we know\nnothing about the prior probability of an email being\nspam.The first assumption is widespread in text classification.\nAlgorithms that use it are called ``naive Bayesian.''The second assumption I made because the proportion of spam in\nmy incoming mail fluctuated so much from day to day (indeed,\nfrom hour to hour) that the overall prior ratio seemed\nworthless as a predictor. If you assume that P(spam) and\nP(nonspam) are both .5, they cancel out and you can\nremove them from the formula.If you were doing Bayesian filtering in a situation where \nthe ratio of spam to nonspam was consistently very high or\n(especially) very low, you could probably improve filter\nperformance by incorporating prior probabilities. To do\nthis right you'd have to track ratios by time of day, because\nspam and legitimate mail volume both have distinct daily\npatterns.[2]\nPatrick Pantel and Dekang Lin. ``SpamCop-- A Spam\nClassification & Organization Program.'' Proceedings of AAAI-98\nWorkshop on Learning for Text Categorization.[3]\nMehran Sahami, Susan Dumais, David Heckerman and Eric Horvitz.\n``A Bayesian Approach to Filtering Junk E-Mail.'' Proceedings of AAAI-98\nWorkshop on Learning for Text Categorization.[4] At the time I had zero false positives out of about 4,000 \nlegitimate emails. If the next legitimate email was\na false positive, this would give us .03%. These false positive\nrates are untrustworthy, as I explain later. I quote\na number here only to emphasize that whatever the false positive rate\nis, it is less than 1.16%.\n[5] Bill Yerazunis. ``Sparse Binary Polynomial Hash Message\nFiltering and The CRM114 Discriminator.'' Proceedings of 2003\nSpam Conference.[6] In ``A Plan for Spam'' I used thresholds of .99 and .01.\nIt seems justifiable to use thresholds proportionate to the\nsize of the corpora. Since I now have on the order of 10,000 of each\ntype of mail, I use .9999 and .0001.[7] There is a flaw here I should probably fix. Currently,\nwhen ``Subject*foo'' degenerates to just ``foo'', what that means is\nyou're getting the stats for occurrences of ``foo'' in\nthe body or header lines other than those I mark.\nWhat I should do is keep track of statistics for ``foo''\noverall as well as specific versions, and degenerate from\n``Subject*foo'' not to ``foo'' but to ``Anywhere*foo''. Ditto for\ncase: I should degenerate from uppercase to any-case, not\nlowercase.It would probably be a win to do this with prices\ntoo, e.g. to degenerate from ``$129.99'' to ``$--9.99'', ``$--.99'',\nand ``$--''.You could also degenerate from words to their stems,\nbut this would probably only improve filtering rates early on \nwhen you had small corpora.[8] Steven Hauser. ``Statistical Spam Filter Works for Me.''\nhttp://www.sofbot.com.[9] False positives are not all equal, and we should remember\nthis when comparing techniques for stopping spam.\nWhereas many of the false positives caused by filters\nwill be near-spams that you wouldn't mind missing,\nfalse positives caused by blacklists, for example, will be just\nmail from people who chose the wrong ISP. In both\ncases you catch mail that's near spam, but for blacklists nearness\nis physical, and for filters it's textual.\n[10] If spammers get good enough at obscuring tokens \nfor this to be a problem, we can respond by simply removing\nwhitespace, periods, commas, etc. and using a dictionary to\npick the words out of the resulting sequence.\nAnd of course finding words this way that weren't visible in\nthe original text would in itself be evidence of spam.Picking out the words won't be trivial. It will require \nmore than just reconstructing word boundaries; spammers\nboth add (``xHot nPorn cSite'') and omit (``P#rn'') letters.\nVision research may be useful here, since human vision is\nthe limit that such tricks will approach.[11] \nIn general, spams are more repetitive than regular email. \nThey want to pound that message home. I currently don't\nallow duplicates in the top 15 tokens, because\nyou could get a false positive if the sender happens to use\nsome bad word multiple times. (In my current filter, ``dick'' has\na spam probabilty of .9999, but it's also a name.)\nIt seems we should at least notice duplication though,\nso I may try allowing up to two of each token, as Brian Burton does in\nSpamProbe.[12] This is what approaches like Brightmail's will\ndegenerate into once spammers are pushed into using mad-lib\ntechniques to generate everything else in the message.[13]\nIt's sometimes argued that we should be working on filtering\nat the network level, because it is more efficient. What people\nusually mean when they say this is: we currently filter at the\nnetwork level, and we don't want to start over from scratch.\nBut you can't dictate the problem to fit your solution.Historically, scarce-resource arguments have been the losing\nside in debates about software design.\nPeople only tend to use them to justify choices\n(inaction in particular) made for other reasons.Thanks to Sarah Harlin, Trevor Blackwell, and\nDan Giffin for reading drafts of this paper, and to Dan again\nfor most of the infrastructure that this filter runs on.Related:" }, { "path": "data/PaulGrahamEssays/bias.txt", "content": "October 2015This will come as a surprise to a lot of people, but in some cases\nit's possible to detect bias in a selection process without knowing\nanything about the applicant pool. Which is exciting because among\nother things it means third parties can use this technique to detect\nbias whether those doing the selecting want them to or not.You can use this technique whenever (a) you have at least\na random sample of the applicants that were selected, (b) their\nsubsequent performance is measured, and (c) the groups of\napplicants you're comparing have roughly equal distribution of ability.How does it work? Think about what it means to be biased. What\nit means for a selection process to be biased against applicants\nof type x is that it's harder for them to make it through. Which\nmeans applicants of type x have to be better to get selected than\napplicants not of type x.\n[1]\nWhich means applicants of type x\nwho do make it through the selection process will outperform other\nsuccessful applicants. And if the performance of all the successful\napplicants is measured, you'll know if they do.Of course, the test you use to measure performance must be a valid\none. And in particular it must not be invalidated by the bias you're\ntrying to measure.\nBut there are some domains where performance can be measured, and\nin those detecting bias is straightforward. Want to know if the\nselection process was biased against some type of applicant? Check\nwhether they outperform the others. This is not just a heuristic\nfor detecting bias. It's what bias means.For example, many suspect that venture capital firms are biased\nagainst female founders. This would be easy to detect: among their\nportfolio companies, do startups with female founders outperform\nthose without? A couple months ago, one VC firm (almost certainly\nunintentionally) published a study showing bias of this type. First\nRound Capital found that among its portfolio companies, startups\nwith female founders outperformed\nthose without by 63%. \n[2]The reason I began by saying that this technique would come as a\nsurprise to many people is that we so rarely see analyses of this\ntype. I'm sure it will come as a surprise to First Round that they\nperformed one. I doubt anyone there realized that by limiting their\nsample to their own portfolio, they were producing a study not of\nstartup trends but of their own biases when selecting companies.I predict we'll see this technique used more in the future. The\ninformation needed to conduct such studies is increasingly available.\nData about who applies for things is usually closely guarded by the\norganizations selecting them, but nowadays data about who gets\nselected is often publicly available to anyone who takes the trouble\nto aggregate it.\nNotes[1]\nThis technique wouldn't work if the selection process looked\nfor different things from different types of applicants—for\nexample, if an employer hired men based on their ability but women\nbased on their appearance.[2]\nAs Paul Buchheit points out, First Round excluded their most \nsuccessful investment, Uber, from the study. And while it \nmakes sense to exclude outliers from some types of studies, \nstudies of returns from startup investing, which is all about \nhitting outliers, are not one of them.\nThanks to Sam Altman, Jessica Livingston, and Geoff Ralston for reading\ndrafts of this." }, { "path": "data/PaulGrahamEssays/boss.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nMarch 2008, rev. June 2008Technology tends to separate normal from natural. Our bodies\nweren't designed to eat the foods that people in rich countries eat, or\nto get so little exercise. \nThere may be a similar problem with the way we work: \na normal job may be as bad for us intellectually as white flour\nor sugar is for us physically.I began to suspect this after spending several years working \nwith startup founders. I've now worked with over 200 of them, and I've\nnoticed a definite difference between programmers working on their\nown startups and those working for large organizations.\nI wouldn't say founders seem happier, necessarily;\nstarting a startup can be very stressful. Maybe the best way to put\nit is to say that they're happier in the sense that your body is\nhappier during a long run than sitting on a sofa eating\ndoughnuts.Though they're statistically abnormal, startup founders seem to be\nworking in a way that's more natural for humans.I was in Africa last year and saw a lot of animals in the wild that\nI'd only seen in zoos before. It was remarkable how different they\nseemed. Particularly lions. Lions in the wild seem about ten times\nmore alive. They're like different animals. I suspect that working\nfor oneself feels better to humans in much the same way that living\nin the wild must feel better to a wide-ranging predator like a lion.\nLife in a zoo is easier, but it isn't the life they were designed\nfor.\nTreesWhat's so unnatural about working for a big company? The root of\nthe problem is that humans weren't meant to work in such large\ngroups.Another thing you notice when you see animals in the wild is that\neach species thrives in groups of a certain size. A herd of impalas\nmight have 100 adults; baboons maybe 20; lions rarely 10. Humans\nalso seem designed to work in groups, and what I've read about\nhunter-gatherers accords with research on organizations and my own\nexperience to suggest roughly what the ideal size is: groups of 8\nwork well; by 20 they're getting hard to manage; and a group of 50\nis really unwieldy.\n[1]\nWhatever the upper limit is, we are clearly not meant to work in\ngroups of several hundred. And yet—for reasons having more\nto do with technology than human nature—a great many people\nwork for companies with hundreds or thousands of employees.Companies know groups that large wouldn't work, so they divide\nthemselves into units small enough to work together. But to\ncoordinate these they have to introduce something new: bosses.These smaller groups are always arranged in a tree structure. Your\nboss is the point where your group attaches to the tree. But when\nyou use this trick for dividing a large group into smaller ones,\nsomething strange happens that I've never heard anyone mention\nexplicitly. In the group one level up from yours, your boss\nrepresents your entire group. A group of 10 managers is not merely\na group of 10 people working together in the usual way. It's really\na group of groups. Which means for a group of 10 managers to work\ntogether as if they were simply a group of 10 individuals, the group\nworking for each manager would have to work as if they were a single\nperson—the workers and manager would each share only one\nperson's worth of freedom between them.In practice a group of people are never able to act as if they were\none person. But in a large organization divided into groups in\nthis way, the pressure is always in that direction. Each group\ntries its best to work as if it were the small group of individuals\nthat humans were designed to work in. That was the point of creating\nit. And when you propagate that constraint, the result is that\neach person gets freedom of action in inverse proportion to the\nsize of the entire tree.\n[2]Anyone who's worked for a large organization has felt this. You\ncan feel the difference between working for a company with 100\nemployees and one with 10,000, even if your group has only 10 people.\nCorn SyrupA group of 10 people within a large organization is a kind of fake\ntribe. The number of people you interact with is about right. But\nsomething is missing: individual initiative. Tribes of hunter-gatherers\nhave much more freedom. The leaders have a little more power than other\nmembers of the tribe, but they don't generally tell them what to\ndo and when the way a boss can.It's not your boss's fault. The real problem is that in the group\nabove you in the hierarchy, your entire group is one virtual person.\nYour boss is just the way that constraint is imparted to you.So working in a group of 10 people within a large organization feels\nboth right and wrong at the same time. On the surface it feels\nlike the kind of group you're meant to work in, but something major\nis missing. A job at a big company is like high fructose corn\nsyrup: it has some of the qualities of things you're meant to like,\nbut is disastrously lacking in others.Indeed, food is an excellent metaphor to explain what's wrong with\nthe usual sort of job.For example, working for a big company is the default thing to do,\nat least for programmers. How bad could it be? Well, food shows\nthat pretty clearly. If you were dropped at a random point in\nAmerica today, nearly all the food around you would be bad for you.\nHumans were not designed to eat white flour, refined sugar, high\nfructose corn syrup, and hydrogenated vegetable oil. And yet if\nyou analyzed the contents of the average grocery store you'd probably\nfind these four ingredients accounted for most of the calories.\n\"Normal\" food is terribly bad for you. The only people who eat\nwhat humans were actually designed to eat are a few Birkenstock-wearing\nweirdos in Berkeley.If \"normal\" food is so bad for us, why is it so common? There are\ntwo main reasons. One is that it has more immediate appeal. You\nmay feel lousy an hour after eating that pizza, but eating the first\ncouple bites feels great. The other is economies of scale.\nProducing junk food scales; producing fresh vegetables doesn't.\nWhich means (a) junk food can be very cheap, and (b) it's worth\nspending a lot to market it.If people have to choose between something that's cheap, heavily\nmarketed, and appealing in the short term, and something that's\nexpensive, obscure, and appealing in the long term, which do you\nthink most will choose?It's the same with work. The average MIT graduate wants to work\nat Google or Microsoft, because it's a recognized brand, it's safe,\nand they'll get paid a good salary right away. It's the job\nequivalent of the pizza they had for lunch. The drawbacks will\nonly become apparent later, and then only in a vague sense of\nmalaise.And founders and early employees of startups, meanwhile, are like\nthe Birkenstock-wearing weirdos of Berkeley: though a tiny minority\nof the population, they're the ones living as humans are meant to.\nIn an artificial world, only extremists live naturally.\nProgrammersThe restrictiveness of big company jobs is particularly hard on\nprogrammers, because the essence of programming is to build new\nthings. Sales people make much the same pitches every day; support\npeople answer much the same questions; but once you've written a\npiece of code you don't need to write it again. So a programmer\nworking as programmers are meant to is always making new things.\nAnd when you're part of an organization whose structure gives each\nperson freedom in inverse proportion to the size of the tree, you're\ngoing to face resistance when you do something new.This seems an inevitable consequence of bigness. It's true even\nin the smartest companies. I was talking recently to a founder who\nconsidered starting a startup right out of college, but went to\nwork for Google instead because he thought he'd learn more there.\nHe didn't learn as much as he expected. Programmers learn by doing,\nand most of the things he wanted to do, he couldn't—sometimes\nbecause the company wouldn't let him, but often because the company's\ncode wouldn't let him. Between the drag of legacy code, the overhead\nof doing development in such a large organization, and the restrictions\nimposed by interfaces owned by other groups, he could only try a\nfraction of the things he would have liked to. He said he has\nlearned much more in his own startup, despite the fact that he has\nto do all the company's errands as well as programming, because at\nleast when he's programming he can do whatever he wants.An obstacle downstream propagates upstream. If you're not allowed\nto implement new ideas, you stop having them. And vice versa: when\nyou can do whatever you want, you have more ideas about what to do.\nSo working for yourself makes your brain more powerful in the same\nway a low-restriction exhaust system makes an engine more powerful.Working for yourself doesn't have to mean starting a startup, of\ncourse. But a programmer deciding between a regular job at a big\ncompany and their own startup is probably going to learn more doing\nthe startup.You can adjust the amount of freedom you get by scaling the size\nof company you work for. If you start the company, you'll have the\nmost freedom. If you become one of the first 10 employees you'll\nhave almost as much freedom as the founders. Even a company with\n100 people will feel different from one with 1000.Working for a small company doesn't ensure freedom. The tree\nstructure of large organizations sets an upper bound on freedom,\nnot a lower bound. The head of a small company may still choose\nto be a tyrant. The point is that a large organization is compelled\nby its structure to be one.\nConsequencesThat has real consequences for both organizations and individuals.\nOne is that companies will inevitably slow down as they grow larger,\nno matter how hard they try to keep their startup mojo. It's a\nconsequence of the tree structure that every large organization is\nforced to adopt.Or rather, a large organization could only avoid slowing down if\nthey avoided tree structure. And since human nature limits the\nsize of group that can work together, the only way I can imagine\nfor larger groups to avoid tree structure would be to have no\nstructure: to have each group actually be independent, and to work\ntogether the way components of a market economy do.That might be worth exploring. I suspect there are already some\nhighly partitionable businesses that lean this way. But I don't\nknow any technology companies that have done it.There is one thing companies can do short of structuring themselves\nas sponges: they can stay small. If I'm right, then it really\npays to keep a company as small as it can be at every stage.\nParticularly a technology company. Which means it's doubly important\nto hire the best people. Mediocre hires hurt you twice: they get\nless done, but they also make you big, because you need more of\nthem to solve a given problem.For individuals the upshot is the same: aim small. It will always\nsuck to work for large organizations, and the larger the organization,\nthe more it will suck.In an essay I wrote a couple years ago \nI advised graduating seniors\nto work for a couple years for another company before starting their\nown. I'd modify that now. Work for another company if you want\nto, but only for a small one, and if you want to start your own\nstartup, go ahead.The reason I suggested college graduates not start startups immediately\nwas that I felt most would fail. And they will. But ambitious\nprogrammers are better off doing their own thing and failing than\ngoing to work at a big company. Certainly they'll learn more. They\nmight even be better off financially. A lot of people in their\nearly twenties get into debt, because their expenses grow even\nfaster than the salary that seemed so high when they left school.\nAt least if you start a startup and fail your net worth will be\nzero rather than negative. \n[3]We've now funded so many different types of founders that we have\nenough data to see patterns, and there seems to be no benefit from\nworking for a big company. The people who've worked for a few years\ndo seem better than the ones straight out of college, but only\nbecause they're that much older.The people who come to us from big companies often seem kind of\nconservative. It's hard to say how much is because big companies\nmade them that way, and how much is the natural conservatism that\nmade them work for the big companies in the first place. But\ncertainly a large part of it is learned. I know because I've seen\nit burn off.Having seen that happen so many times is one of the things that\nconvinces me that working for oneself, or at least for a small\ngroup, is the natural way for programmers to live. Founders arriving\nat Y Combinator often have the downtrodden air of refugees. Three\nmonths later they're transformed: they have so much more \nconfidence\nthat they seem as if they've grown several inches taller. \n[4]\nStrange as this sounds, they seem both more worried and happier at the same\ntime. Which is exactly how I'd describe the way lions seem in the\nwild.Watching employees get transformed into founders makes it clear\nthat the difference between the two is due mostly to environment—and\nin particular that the environment in big companies is toxic to\nprogrammers. In the first couple weeks of working on their own\nstartup they seem to come to life, because finally they're working\nthe way people are meant to.Notes[1]\nWhen I talk about humans being meant or designed to live a\ncertain way, I mean by evolution.[2]\nIt's not only the leaves who suffer. The constraint propagates\nup as well as down. So managers are constrained too; instead of\njust doing things, they have to act through subordinates.[3]\nDo not finance your startup with credit cards. Financing a\nstartup with debt is usually a stupid move, and credit card debt\nstupidest of all. Credit card debt is a bad idea, period. It is\na trap set by evil companies for the desperate and the foolish.[4]\nThe founders we fund used to be younger (initially we encouraged\nundergrads to apply), and the first couple times I saw this I used\nto wonder if they were actually getting physically taller.Thanks to Trevor Blackwell, Ross Boucher, Aaron Iba, Abby\nKirigin, Ivan Kirigin, Jessica Livingston, and Robert Morris for\nreading drafts of this." }, { "path": "data/PaulGrahamEssays/bronze.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nApril 2005This summer, as an \nexperiment, some \nfriends and I are giving seed\nfunding to a bunch of new startups. It's an experiment because\nwe're prepared to fund younger founders than most investors would.\nThat's why we're doing it during the summer—so even college\nstudents can participate.We know from Google and Yahoo that grad students can start successful\nstartups. And we know from experience that some undergrads are as\ncapable as most grad students. The accepted age for startup founders\nhas been creeping downward. We're trying to find the lower bound.\nThe deadline has now passed, and we're sifting through 227 applications.\n\nWe expected to divide them into two categories, promising\nand unpromising. But we soon saw we needed a third: promising\npeople with unpromising ideas.\n[1]The Artix PhaseWe should have expected this. It's very common for a group of\nfounders to go through one lame idea before realizing that a startup\nhas to make something people will pay for. In fact, we ourselves\ndid.Viaweb wasn't the first startup Robert Morris and I started. In\nJanuary 1995, we and a couple friends started a company called\nArtix. The plan was to put art galleries on the Web. In retrospect,\nI wonder how we could have wasted our time on anything so stupid.\nGalleries are not especially excited about being on\nthe Web even now, ten years later. They don't want to have their\nstock visible to any random visitor, like an antique store. \n[2]Besides which, art dealers are the most technophobic people on\nearth. They didn't become art dealers after a difficult choice\nbetween that and a career in the hard sciences. Most of them had\nnever seen the Web before we came to tell them why they should be\non it. Some didn't even have computers. It doesn't do justice to\nthe situation to describe it as a hard sell; we soon sank\nto building sites for free, and it was hard to convince galleries\neven to do that.Gradually it dawned on us that \ninstead of trying to make Web sites for\npeople who didn't want them, we could make sites for\npeople who did. In fact, software that would let people who wanted\nsites make their own. So we ditched Artix and\nstarted a new company, Viaweb, to make software for building online stores.\nThat one succeeded.We're in good company here. Microsoft was not the first company\nPaul Allen and Bill Gates started either. The first was called\nTraf-o-data. It does not seem to have done as well as Micro-soft.\nIn Robert's defense, he was skeptical about Artix. I dragged him\ninto it. \n[3]\nBut there were moments when he was optimistic. And\nif we, who were 29 and 30 at the time, could get excited about such\na thoroughly boneheaded idea, we should not be surprised that hackers\naged 21 or 22 are pitching us ideas with little hope of making money.The Still Life EffectWhy does this happen? Why do good hackers have bad business ideas?Let's look at our case. One reason we had such a lame idea was\nthat it was the first thing we thought of. I was in New York trying\nto be a starving artist at the time (the starving part is actually\nquite easy), so I was haunting galleries anyway. When I learned\nabout the Web, it seemed natural to mix the two. Make Web sites\nfor galleries—that's the ticket!If you're going to spend years working on something, you'd think\nit might be wise to spend at least a couple days considering different\nideas, instead of going with the first that comes into your head.\nYou'd think. But people don't. In fact, this is a constant problem\nwhen you're painting still lifes. You plonk down a bunch of stuff\non a table, and maybe spend five or ten minutes rearranging it to \nlook interesting. But you're so impatient to get started painting\nthat ten minutes of rearranging feels very long. So you start\npainting. Three days later, having spent twenty hours staring at\nit, you're kicking yourself for having set up such an awkward and \nboring composition, but by then it's too late.Part of the problem is that big projects tend to grow out of small\nones. You set up a still life to make a quick sketch when you have\na spare hour, and days later you're still working on it. I once\nspent a month painting three versions of a still life I set up in\nabout four minutes. At each point (a day, a week, a month) I thought\nI'd already put in so much time that it was too late to change.So the biggest cause of bad ideas is the still life effect: you \ncome up with a random idea, plunge into it, and then at each point\n(a day, a week, a month) feel you've put so much time into it that\nthis must be the idea.How do we fix that? I don't think we should discard plunging. \nPlunging into an idea is a good thing. The solution is at the other\nend: to realize that having invested time in something doesn't make\nit good.This is clearest in the case of names. Viaweb was originally\ncalled Webgen, but we discovered someone else had a product called\nthat. We were so attached to our name that we offered him 5%\nof the company if he'd let us have it. But he wouldn't, so\nwe had to think of another. \n[4]\nThe best we could do was Viaweb,\nwhich we disliked at first. It was like having a new mother. But \nwithin three days we loved it, and Webgen sounded lame and\nold-fashioned.If it's hard to change something so simple as a name, imagine\nhow hard it is to garbage-collect an idea. A name only has one \npoint of attachment into your head. An idea for a company gets\nwoven into your thoughts. So you must consciously discount for \nthat. Plunge in, by all means, but remember later to look at your \nidea in the harsh light of morning and ask: is this something people\nwill pay for? Is this, of all the things we could make, the thing\npeople will pay most for?MuckThe second mistake we made with Artix is also very common. Putting\ngalleries on the Web seemed cool.One of the most valuable things my father taught me is an old\nYorkshire saying: where there's muck, there's brass. Meaning that \nunpleasant work pays. And more to the point here, vice versa. Work\npeople like doesn't pay well, for reasons of supply and demand.\nThe most extreme case is developing programming languages, which\ndoesn't pay at all, because people like it so much they do it for \nfree.When we started Artix, I was still ambivalent about business. I\nwanted to keep one foot in the art world. Big, big, mistake. Going\ninto business is like a hang-glider launch: you'd better do it \nwholeheartedly, or not at all. The purpose of a company, and a\nstartup especially, is to make money. You can't have divided\nloyalties.Which is not to say that you have to do the most disgusting sort \nof work, like spamming, or starting a company whose only purpose \nis patent litigation. What I mean is, if you're starting a company\nthat will do something cool, the aim had better be to make money \nand maybe be cool, not to be cool and maybe make money.It's hard enough to make money that you can't do it by accident.\nUnless it's your first priority, it's unlikely to happen at all.HyenasWhen I probe our motives with Artix, I see a third mistake: timidity.\nIf you'd proposed at the time that we go into the e-commerce business,\nwe'd have found the idea terrifying. Surely a field like that would\nbe dominated by fearsome startups with five million dollars of VC\nmoney each. Whereas we felt pretty sure that we could hold our own\nin the slightly less competitive business of generating Web sites \nfor art galleries.We erred ridiculously far on the side of safety. As it turns out,\nVC-backed startups are not that fearsome. They're too busy trying\nto spend all that \nmoney to get software written. In 1995, the\ne-commerce business was very competitive as measured in press\nreleases, but not as measured in software. And really it never\nwas. The big fish like Open Market (rest their souls) were just\nconsulting companies pretending to be product companies \n[5], and \nthe offerings at our end of the market were a couple hundred lines\nof Perl scripts. Or could have been implemented as a couple hundred\nlines of Perl; in fact they were probably tens of thousands of lines\nof C++ or Java. Once we actually took the plunge into e-commerce,\nit turned out to be surprisingly easy to compete.So why were we afraid? We felt we were good at programming, but\nwe lacked confidence in our ability to do a mysterious, undifferentiated\nthing we called \"business.\" In fact there is no such thing as\n\"business.\" There's selling, promotion, figuring out what people\nwant, deciding how much to charge, customer support, paying your\nbills, getting customers to pay you, getting incorporated, raising\nmoney, and so on. And the combination is not as hard as it seems, \nbecause some tasks (like raising money and getting incorporated)\nare an O(1) pain in the ass, whether you're big or small, and others\n(like selling and promotion) depend more on energy and imagination\nthan any kind of special training.Artix was like a hyena, content to survive on carrion because we\nwere afraid of the lions. Except the lions turned out not to have \nany teeth, and the business of putting galleries online barely\nqualified as carrion.A Familiar ProblemSum up all these sources of error, and it's no wonder we had such\na bad idea for a company. We did the first thing we thought of;\nwe were ambivalent about being in business at all; and we deliberately\nchose an impoverished market to avoid competition.Looking at the applications for the Summer Founders Program, I see\nsigns of all three. But the first is by far the biggest problem. \nMost of the groups applying have not stopped to ask: of all the \nthings we could do, is this the one with the best chance of\nmaking money?If they'd already been through their Artix phase, they'd have learned\nto ask that. After the reception we got from art dealers, we were\nready to. This time, we thought, let's make something people want.Reading the Wall Street Journal for a week should give anyone\nideas for two or three new startups. The articles are full of\ndescriptions of problems that need to be solved. But most of the\napplicants don't seem to have looked far for ideas.We expected the most common proposal to be for multiplayer games.\nWe were not far off: this was the second most common. \nThe most common was some combination of a blog, a calendar,\na dating site, and Friendster. Maybe there is some new killer app\nto be discovered here, but it seems perverse to go poking around\nin this fog when there are valuable, unsolved problems lying about\nin the open for anyone to see. Why did no one propose a new scheme \nfor micropayments? An ambitious project, perhaps, but I can't \nbelieve we've considered every alternative. And newspapers and\nmagazines are (literally) dying for a solution.Why did so few applicants really think about what customers want?\nI think the problem with many, as with people in their early twenties\ngenerally, is that they've been trained their whole lives to jump\nthrough predefined hoops. They've spent 15-20 years solving problems\nother people have set for them. And how much time deciding what \nproblems would be good to solve? Two or three course projects? \n\nThey're good at solving problems, but bad at choosing them.But that, I'm convinced, is just the effect of training. Or more\nprecisely, the effect of grading. To make grading efficient,\neveryone has to solve the same problem, and that means it has to\nbe decided in advance. It would be great if schools taught students\nhow to choose problems as well as how to solve them, but I don't\nknow how you'd run such a class in practice.Copper and TinThe good news is, choosing problems is something that can be learned.\nI know that from experience. Hackers can learn to make things\ncustomers want. \n[6]This is a controversial view. One expert on \"entrepreneurship\"\ntold me that any startup had to include business people, because\nonly they could focus on what customers wanted. I'll probably\nalienate this guy forever by quoting him, but I have to risk it,\nbecause his email was such a perfect example of this view:\n \n 80% of MIT spinoffs succeed provided they \n have at least one management person in the team at the start. The \n business person represents the \"voice of the customer\" and that's\n what keeps the engineers and product development on track.\n\nThis is, in my opinion, a crock. Hackers are perfectly capable of\nhearing the voice of the customer without a business person to\namplify the signal for them. Larry Page and Sergey Brin were grad\nstudents in computer science, which presumably makes them \"engineers.\"\nDo you suppose Google is only good because they had some business\nguy whispering in their ears what customers wanted? It seems to \nme the business guys who did the most for Google were the ones who \nobligingly flew Altavista into a hillside just as Google was getting\nstarted.The hard part about figuring out what customers want is figuring \nout that you need to figure it out. But that's something you can\nlearn quickly. It's like seeing the other interpretation of an\nambiguous picture. As soon as someone tells you there's a rabbit\nas well as a duck, it's hard not to see it.And compared to the sort of problems hackers are used to solving,\ngiving customers what they want is easy. Anyone who can write an \noptimizing compiler can design a UI that doesn't confuse users, \nonce they choose to focus on that problem. And once you \napply that kind of brain power to petty but profitable questions, \nyou can create wealth very rapidly.That's the essence of a startup: having brilliant people do work\nthat's beneath them. Big companies try to hire the right person\nfor the job. Startups win because they don't—because they take\npeople so smart that they would in a big company be doing \"research,\"\nand set them to work instead on problems of the most immediate and\nmundane sort. Think Einstein designing refrigerators.\n[7]If you want to learn what people want, read\nDale Carnegie's How to Win Friends and Influence People.\n[8]\nWhen a friend recommended this book, I couldn't believe he was\nserious. But he insisted it was good, so I read it, and he was \nright. It deals with the most difficult problem in human experience:\nhow to see things from other people's point of view, instead of\nthinking only of yourself.Most smart people don't do that very well. But adding this ability\nto raw brainpower is like adding tin to copper. The result is\nbronze, which is so much harder that it seems a different metal.A hacker who has learned what to make, and not just how to make,\nis extraordinarily powerful. And not just at making money: look\nwhat a small group of volunteers has achieved with Firefox.Doing an Artix teaches you to make something people want in the\nsame way that not drinking anything would teach you how much you\ndepend on water. But it would be more convenient for all involved\nif the Summer Founders didn't learn this on our dime—if they could\nskip the Artix phase and go right on to make something customers\nwanted. That, I think, is going to be the real experiment this \nsummer. How long will it take them to grasp this? We decided\nwe ought to have T-Shirts for the SFP, and we'd been thinking about \nwhat to print on the back. Till now we'd been planning to use\nIf you can read this, I should be working.\nbut now we've decided it's going to be\nMake something people want.\nNotes[1] \nSFP applicants: please don't assume that not being accepted\nmeans we think your idea is bad. Because we want to keep the\nnumber of startups small this first summer, we're going to have \nto turn down some good proposals too.[2] \nDealers try to give each customer the impression that the stuff\nthey're showing him is something special that only a few people \nhave seen, when in fact it may have been sitting in their racks for\nyears while they tried to unload it on buyer after buyer.[3] \nOn the other hand, he was skeptical about Viaweb too. I have\na precise measure of that, because at one point in the first couple\nmonths we made a bet: if he ever made a million dollars out of \nViaweb, he'd get his ear pierced. We didn't let him \noff, either.[4] \nI wrote a program to generate all the combinations of \"Web\" \nplus a three letter word. I learned from this that most three \nletter words are bad: Webpig, Webdog, Webfat, Webzit, Webfug. But\none of them was Webvia; I swapped them to make Viaweb.[5] \nIt's much easier to sell services than a product, just as it's\neasier to make a living playing at weddings than by selling recordings. \nBut the margins are greater on products. So during the \nBubble a lot of companies used consulting to generate revenues\nthey could attribute to the sale of products, because it made a\nbetter story for an IPO.[6] \nTrevor Blackwell presents the following recipe for a startup: \n\"Watch people who have money to spend, see what they're wasting\ntheir time on, cook up a solution, and try selling it to them. It's \nsurprising how small a problem can be and still provide a profitable\nmarket for a solution.\"[7] \nYou need to offer especially large rewards to get great people\nto do tedious work. That's why startups always pay equity rather\nthan just salary.[8] \nBuy an old \ncopy from the 1940s or 50s instead of the current edition, which has been\nrewritten to suit present fashions. The original edition contained\na few unPC ideas, but it's always better to read an original book,\nbearing in mind that it's a book from a past era, than to read a\nnew version sanitized for your protection.Thanks to Bill Birch, Trevor Blackwell, Jessica Livingston,\nand Robert Morris for reading drafts of this." }, { "path": "data/PaulGrahamEssays/bubble.txt", "content": "September 2004(This essay is derived from an invited talk at ICFP 2004.)I had a front row seat for the Internet Bubble,\nbecause I worked at Yahoo during 1998 and 1999. One day,\nwhen the stock was trading around $200, I sat down and calculated\nwhat I thought the price should be. The \nanswer I got was $12. I went to\nthe next cubicle and told my friend Trevor. \"Twelve!\" he said.\nHe tried to sound indignant, but he didn't quite manage it. He\nknew as well as I did that our valuation was crazy.Yahoo was a special case. It was not just our price to earnings\nratio that was bogus. Half our earnings were too. Not in\nthe Enron way, of course. The finance guys seemed\nscrupulous about reporting earnings. What made our\nearnings bogus was that Yahoo was, in effect, the center of\na Ponzi scheme. Investors looked at Yahoo's earnings\nand said to themselves, here is proof that Internet companies can make\nmoney. So they invested in new\nstartups that promised to be the next Yahoo. And as soon as these startups\ngot the money, what did they do with it?\nBuy millions of dollars worth of advertising on Yahoo to promote\ntheir brand. Result: a capital investment in a startup this\nquarter shows up as Yahoo earnings next quarter—stimulating\nanother round of investments in startups.As in a Ponzi scheme, what seemed to be the returns of this system\nwere simply the latest round of investments in it.\nWhat made it not a Ponzi scheme was that it was unintentional. \nAt least, I think it was. The venture capital business is pretty incestuous,\nand there were presumably people in a position, if not to create\nthis situation, to realize what was happening and to milk it.A year later the game was up. Starting in January 2000, Yahoo's\nstock price began to crash, ultimately losing 95% of its\nvalue.Notice, though, that even with all the fat trimmed off its market\ncap, Yahoo was still worth a lot. Even at the morning-after\nvaluations of March and April 2001, the people at Yahoo had managed\nto create a company worth about $8 billion in just six years.The fact is, despite all the nonsense we heard\nduring the Bubble about the \"new economy,\" there was a\ncore of truth. You need\nthat to get a really big bubble: you need to have something\nsolid at the center, so that even smart people are sucked in.\n(Isaac Newton and Jonathan Swift both lost money\nin the South Sea Bubble of 1720.)Now the pendulum has swung the other way. Now anything that\nbecame fashionable during the Bubble is ipso facto unfashionable.\nBut that's a mistake—an even bigger mistake than believing\nwhat everyone was saying in 1999. Over the long term,\nwhat the Bubble got right will be more important than what\nit got wrong.1. Retail VCAfter the excesses of the Bubble, it's now\nconsidered dubious to take companies public before they have earnings.\nBut there is nothing intrinsically wrong with\nthat idea. Taking a company public at an early stage is simply\nretail VC: instead of going to venture capital firms for the last round of\nfunding, you go to the public markets.By the end of the Bubble, companies going public with no\nearnings were being derided as \"concept stocks,\" as if it\nwere inherently stupid to invest in them.\nBut investing in concepts isn't stupid; it's what VCs do,\nand the best of them are far from stupid.The stock of a company that doesn't yet have earnings is \nworth something.\nIt may take a while for the market to learn\nhow to value such companies, just as it had to learn to\nvalue common stocks in the early 20th century. But markets\nare good at solving that kind of problem. I wouldn't be\nsurprised if the market ultimately did a better\njob than VCs do now.Going public early will not be the right plan\nfor every company.\nAnd it can of course be\ndisruptive—by distracting the management, or by making the early\nemployees suddenly rich. But just as the market will learn\nhow to value startups, startups will learn how to minimize\nthe damage of going public.2. The InternetThe Internet genuinely is a big deal. That was one reason\neven smart people were fooled by the Bubble. Obviously \nit was going to have a huge effect. Enough of an effect to\ntriple the value of Nasdaq companies in two years? No, as it\nturned out. But it was hard to say for certain at the time. [1]The same thing happened during the Mississippi and South Sea Bubbles.\nWhat drove them was the invention of organized public finance\n(the South Sea Company, despite its name, was really a competitor\nof the Bank of England). And that did turn out to be\na big deal, in the long run.Recognizing an important trend turns out to be easier than \nfiguring out how to profit from it. The mistake\ninvestors always seem to make is to take the trend too literally.\nSince the Internet was the big new thing, investors supposed\nthat the more Internettish the company, the better. Hence\nsuch parodies as Pets.Com.In fact most of the money to be made from big trends is made\nindirectly. It was not the railroads themselves that \nmade the most money during the railroad boom, but the companies\non either side, like Carnegie's steelworks, which made the rails,\nand Standard Oil, which used railroads to get oil to the East Coast,\nwhere it could be shipped to Europe.I think the Internet will have great effects,\nand that what we've seen so far is nothing compared to what's\ncoming. But most of the winners will only indirectly be\nInternet companies; for every Google there will be ten\nJetBlues.3. ChoicesWhy will the Internet have great effects? The general \nargument is that new forms of communication always do. They happen\nrarely (till industrial times there were just speech, writing, and printing),\nbut when they do, they always cause a big splash.The specific argument, or one of them, is the Internet gives us \nmore choices. In the \"old\" economy,\nthe high cost of presenting information to people meant they\nhad only a narrow range of options to choose from. The tiny,\nexpensive pipeline to consumers was tellingly named \"the channel.\"\nControl the channel and you\ncould feed them what you wanted, on your terms. And it\nwas not just big corporations that depended\non this principle. So, in their way, did\nlabor unions, the traditional news media,\nand the art and literary establishments.\nWinning depended not on doing good work, but on gaining control\nof some bottleneck.There are signs that this is changing.\nGoogle has over 82 million unique users a month and\nannual revenues of about three billion dollars. [2]\nAnd yet have you ever seen\na Google ad?\nSomething is going on here.Admittedly, Google is an extreme case. It's very easy for\npeople to switch to a new search engine. It costs little\neffort and no money to try a new one, and it's easy to\nsee if the results are better. And so Google doesn't have\nto advertise. In a business like theirs, being the best is\nenough.The exciting thing about the Internet is that it's\nshifting everything in that direction.\nThe hard part, if you want to win by making the best stuff,\nis the beginning. Eventually everyone\nwill learn by word of mouth that you're the best,\nbut how do you survive to that point? And it is in this crucial\nstage that the Internet has the most effect. First, the\nInternet lets anyone find you at almost zero cost.\nSecond, it dramatically speeds up the rate at which\nreputation spreads by word of mouth. Together these mean that in many\nfields the rule will be: Build it, and they will come.\nMake something great and put it online.\nThat is a big change from the recipe for winning in the\npast century.4. YouthThe aspect of the Internet Bubble that the press seemed most\ntaken with was the youth of some of the startup founders.\nThis too is a trend that will last.\nThere is a huge standard deviation among 26 year olds. Some\nare fit only for entry level jobs, but others are\nready to rule the world if they can find someone to handle\nthe paperwork for them.A 26 year old may not be very good at managing people or\ndealing with the SEC. Those require experience.\nBut those are also commodities, which can be handed off to\nsome lieutenant. The most important quality in a CEO is his\nvision for the company's future. What will they build next?\nAnd in that department, there are 26 year olds who can\ncompete with anyone.In 1970 a company president meant someone in his fifties, at\nleast. If he had technologists working for him, they were \ntreated like a racing stable: prized, but not powerful. But \nas technology has grown more important, the power of nerds\nhas grown to reflect it. Now it's not enough for a CEO to\nhave someone smart he can ask about technical matters. Increasingly,\nhe has to be that person himself.As always, business has clung to old forms. VCs still seem\nto want to install a legitimate-looking \ntalking head as the CEO. But increasingly the founders of\nthe company are the real powers, and the grey-headed man\ninstalled by the VCs more like a\nmusic group's manager than a general.5. InformalityIn New York, the Bubble had dramatic consequences:\nsuits went out of fashion. They made one seem old. So in\n1998 powerful New York types were suddenly wearing\nopen-necked shirts and khakis and oval wire-rimmed glasses,\njust like guys in Santa Clara.The pendulum has swung back a bit, driven in part by a panicked\nreaction by the clothing industry. But I'm betting on the\nopen-necked shirts. And this is not as frivolous a question\nas it might seem. Clothes are important, as all nerds can sense,\nthough they may not realize it consciously.If you're a nerd, you can understand how important clothes are\nby asking yourself how you'd feel about a company\nthat made you wear a suit and tie to work. The idea sounds\nhorrible, doesn't it? In fact, horrible far out of proportion\nto the mere discomfort of wearing such clothes. A company that\nmade programmers wear suits would have something deeply wrong\nwith it.And what would be wrong would be that how one presented oneself\ncounted more than the quality of one's ideas. That's\nthe problem with formality. Dressing up is not so much bad in\nitself. The problem is the receptor it binds to: dressing\nup is inevitably a substitute\nfor good ideas. It is no coincidence that technically\ninept business types are known as \"suits.\"Nerds don't just happen to dress informally. They do it too\nconsistently. Consciously or not, they dress informally as\na prophylactic measure against stupidity.6. NerdsClothing is only the most visible battleground in the war\nagainst formality. Nerds tend to eschew formality of any sort.\nThey're not impressed by one's job title, for example,\nor any of the other appurtenances of authority.Indeed, that's practically the definition of a nerd. I found\nmyself talking recently to someone from Hollywood who was planning\na show about nerds. I thought it would be useful if I\nexplained what a nerd was. What I came up with was: someone who\ndoesn't expend any effort on marketing himself.A nerd, in other words, is someone who concentrates on substance.\nSo what's the connection between nerds and technology? Roughly\nthat you can't fool mother nature. In technical matters, you\nhave to get the right answers. If your software miscalculates\nthe path of a space probe, you can't finesse your way out of\ntrouble by saying that your code is patriotic, or avant-garde,\nor any of the other dodges people use in nontechnical\nfields.And as technology becomes increasingly important in the\neconomy, nerd culture is \nrising with it. Nerds are already\na lot cooler than they were when I was a kid. When I was in\ncollege in the mid-1980s, \"nerd\" was still an insult. People\nwho majored in computer science generally tried to conceal it.\nNow women ask me where they can meet nerds. (The answer that\nsprings to mind is \"Usenix,\" but that would be like drinking\nfrom a firehose.)I have no illusions about why nerd culture is becoming\nmore accepted. It's not because people are\nrealizing that substance is more important than marketing.\nIt's because the nerds are getting \nrich. But that is not going\nto change.7. OptionsWhat makes the nerds rich, usually, is stock options. Now there\nare moves afoot to make it harder for companies to grant \noptions. To the extent there's some genuine accounting abuse \ngoing on, by all means correct it. But don't kill the golden \ngoose. Equity is the fuel that drives technical innovation.Options are a good idea because (a) they're fair, and (b) they\nwork. Someone who goes to work for a company is (one hopes) \nadding to its value, and it's only fair to give them a share\nof it. And as a purely practical measure, people work a lot\nharder when they have options. I've seen that first hand.The fact that a few crooks during the Bubble robbed their\ncompanies by granting themselves options doesn't mean options\nare a bad idea. During the railroad boom, some executives\nenriched themselves by selling watered stock—by issuing more\nshares than they said were outstanding. But that doesn't \nmake common stock a bad idea. Crooks just use whatever\nmeans are available.If there is a problem with options, it's that they reward\nslightly the wrong thing. Not surprisingly, people do what you\npay them to. If you pay them by the hour, they'll work a lot of\nhours. If you pay them by the volume of work done, they'll\nget a lot of work done (but only as you defined work).\nAnd if you pay them to raise the\nstock price, which is what options amount to, they'll raise\nthe stock price.But that's not quite what you want. What you want is to\nincrease the actual value of the company, not its market cap.\nOver time the two inevitably meet, but not always as quickly\nas options vest. Which means options tempt employees, if\nonly unconsciously, to \"pump and dump\"—to do things\nthat will make the company seem valuable.\nI found that when I was at Yahoo, I couldn't help thinking, \n\"how will this sound to investors?\" when I should have been\nthinking \"is this a good idea?\"So maybe the standard option deal needs to be tweaked slightly.\nMaybe options should be replaced with something tied more\ndirectly to earnings. It's still early days.8. StartupsWhat made the options valuable, for the most part, is\nthat they were options on the stock of \nstartups. Startups \nwere not of course a creation of the Bubble, but they\nwere more visible during the Bubble than ever before.One thing most people did learn about for the first time\nduring the Bubble was the startup\ncreated with the intention of selling it.\nOriginally a\nstartup meant a small company that hoped to grow into a\nbig one. But increasingly startups are evolving into a\nvehicle for developing technology on spec.As I wrote in\nHackers & Painters, employees seem to be most\nproductive when they're paid in proportion to the wealth\nthey generate. And the advantage of a startup—indeed, \nalmost its raison d'etre—is that it offers something\notherwise impossible to obtain: a way of measuring that.In many businesses, it just makes more sense for companies\nto get technology by buying startups rather than developing \nit in house. You pay more, but there is less risk,\nand risk is what big companies don't want. It makes the\nguys developing the technology more accountable, because they\nonly get paid if they build the winner. And you end up \nwith better technology, created faster, because things are\nmade in the innovative atmosphere of startups instead of \nthe bureaucratic atmosphere of big companies.Our startup, Viaweb, was built to be sold. We were open\nwith investors about that from the start. And we were \ncareful to create something that could slot easily into a\nlarger company. That is the pattern for the future.9. CaliforniaThe Bubble was a California phenomenon. When I showed up\nin Silicon Valley in 1998, I felt like an immigrant from\nEastern Europe arriving in America in 1900. Everyone\nwas so cheerful and healthy and rich. It seemed a new\nand improved world.The press, ever eager to exaggerate small trends, now gives \none the impression that Silicon Valley is a ghost town.\nNot at all. When I drive down 101 from the airport,\nI still feel a buzz of energy, as if there were a giant\ntransformer nearby. Real estate is still more expensive\nthan just about anywhere else in the country. The people \nstill look healthy, and the weather is still fabulous.\nThe future is there.\n(I say \"there\" because I moved back to the East Coast after\nYahoo. I still wonder if this was a smart idea.)What makes the Bay Area superior is the attitude of the\npeople. I notice that when I come home to Boston.\nThe first thing I see when I walk out of the airline terminal\nis the fat, grumpy guy in\ncharge of the taxi line. I brace myself for rudeness:\nremember, you're back on the East Coast now.The atmosphere varies from city to city, and fragile\norganisms like startups are exceedingly sensitive to such variation.\nIf it hadn't already been hijacked as a new euphemism\nfor liberal, the word to describe the atmosphere in\nthe Bay Area would be \"progressive.\" People there are trying\nto build the future.\nBoston has MIT and Harvard, but it also has a lot of\ntruculent, unionized employees like the police who\nrecently held the Democratic National Convention for \nransom, and a lot of people trying to be\n Thurston Howell.\nTwo sides of an obsolete coin.Silicon Valley may not be the next Paris or London, but it\nis at least the next Chicago. For the next fifty years, \nthat's where new wealth will come from.10. ProductivityDuring the Bubble, optimistic analysts used to justify high\nprice to earnings ratios by saying that technology was going \nto increase productivity dramatically. They were wrong about\nthe specific companies, but not so wrong about the underlying\nprinciple. I think one of the big trends we'll see in the\ncoming century is a huge increase in productivity.Or more precisely, a huge increase in variation in\nproductivity. Technology is a lever. It doesn't add; \nit multiplies. If the present range of productivity is \n0 to 100, introducing a multiple of 10 increases the range\nfrom 0 to 1000.One upshot of which is that the companies of the future may\nbe surprisingly small. I sometimes daydream about how big\nyou could grow a company (in revenues) without ever having\nmore than ten people. What would happen if you outsourced\neverything except product development? If you tried this experiment,\nI think you'd be surprised at how far you could get. \nAs Fred Brooks pointed out, small groups are\nintrinsically more productive, because the\ninternal friction in a group grows as the\nsquare of its size.Till quite recently, running a major company\nmeant managing an army of workers. Our standards about how\nmany employees a company should have are still influenced by\nold patterns. Startups are perforce small, because they can't\nafford to hire a lot of people. But I think it's a big mistake for\ncompanies to loosen their belts as revenues increase. The\nquestion is not whether you can afford the extra salaries. \nCan you afford the loss in productivity that comes from making\nthe company bigger?The prospect of technological leverage will of course raise the\nspecter of unemployment. I'm surprised people still worry about\nthis.\nAfter centuries of supposedly job-killing innovations,\nthe number of jobs is within ten percent of the number of people\nwho want them. This can't be a coincidence. There must be some\nkind of balancing mechanism.What's NewWhen one looks over these trends, is there any overall theme?\nThere does seem to be: that in the coming century, good ideas\nwill count for more. That 26\nyear olds with good ideas will increasingly have an edge over 50\nyear olds with powerful connections. That doing good work will\nmatter more than dressing up—or advertising, which is the\nsame thing for companies. That people\nwill be rewarded a bit more in proportion to the value of what\nthey create.If so, this is good news indeed.\nGood ideas always tend to win eventually. The problem is,\nit can take a very long time.\nIt took decades for relativity to be accepted, and the\ngreater part of a century to establish that central planning didn't work.\nSo even a small increase in the\nrate at which good ideas win would be a momentous\nchange—big enough, probably, to justify a name like\nthe \"new economy.\"Notes[1] Actually it's hard to say now. As Jeremy Siegel points\nout, if the value of a stock is its future earnings, you \ncan't tell if it was overvalued till you see what the earnings\nturn out to be. While certain famous Internet stocks were\nalmost certainly overvalued in 1999, it is still hard to say for sure\nwhether, e.g., the Nasdaq index was.Siegel, Jeremy J. \"What Is an Asset Price Bubble? An\nOperational Definition.\" European Financial Management,\n9:1, 2003.[2] The number of users comes from a 6/03 Nielsen\nstudy quoted on Google's site. (You'd think they'd have\nsomething more recent.) The revenue estimate is based on\nrevenues of $1.35 billion for the first half of 2004, as\nreported in their IPO filing.Thanks to Chris Anderson, Trevor Blackwell, Sarah Harlin, Jessica\nLivingston, and Robert Morris for reading drafts of this." }, { "path": "data/PaulGrahamEssays/charisma.txt", "content": "\nNovember 2004, corrected June 2006Occam's razor says we should prefer the simpler of two explanations.\nI begin by reminding readers of this principle because I'm about\nto propose a theory that will offend both liberals and conservatives.\nBut Occam's razor means, in effect, that if you want to disagree\nwith it, you have a hell of a coincidence to explain.Theory: In US presidential elections, the more \ncharismatic candidate wins.People who write about politics, whether on the left or the right,\nhave a consistent bias: they take politics seriously. When one\ncandidate beats another they look for political explanations. The\ncountry is shifting to the left, or the right. And that sort of\nshift can certainly be the result of a presidential election, which\nmakes it easy to believe it was the cause.But when I think about why I voted for Clinton over the first George\nBush, it wasn't because I was shifting to the left. Clinton just\nseemed more dynamic. He seemed to want the job more. Bush seemed\nold and tired. I suspect it was the same for a lot of voters.Clinton didn't represent any national shift leftward.\n[1]\nHe was\njust more charismatic than George Bush or (God help us) Bob Dole.\nIn 2000 we practically got a controlled experiment to prove it:\nGore had Clinton's policies, but not his charisma, and he suffered\nproportionally. \n[2]\nSame story in 2004. Kerry was smarter and more\narticulate than Bush, but rather a stiff. And Kerry lost.As I looked further back, I kept finding the same pattern. \nPundits said Carter beat Ford\nbecause the country distrusted the Republicans after Watergate.\nAnd yet it also happened that Carter was famous for his big grin\nand folksy ways, and Ford for being a boring klutz. Four years\nlater, pundits said the country had lurched to the right. But\nReagan, a former actor, also happened to be even more charismatic\nthan Carter (whose grin was somewhat less cheery after four stressful\nyears in office). In 1984 the charisma gap between Reagan and\nMondale was like that between Clinton and Dole, with similar results.\nThe first George Bush managed to win in 1988, though he would later\nbe vanquished by one of the most charismatic presidents ever, because\nin 1988 he was up against the notoriously uncharismatic\nMichael Dukakis.These are the elections I remember personally, but apparently the\nsame pattern played out in 1964 and 1972. The most recent\ncounterexample appears to be 1968, when Nixon beat the more charismatic Hubert\nHumphrey. But when you examine that election, it tends to support\nthe charisma theory more than contradict it. As Joe McGinnis\nrecounts in his famous book The Selling of the President 1968,\nNixon knew he had less charisma than Humphrey, and thus simply\nrefused to debate him on TV. He knew he couldn't afford to let the\ntwo of them be seen side by side.Now a candidate probably couldn't get away with refusing to debate.\nBut in 1968 the custom of televised debates was still evolving. In\neffect, Nixon won in 1968 because voters were never allowed to see\nthe real Nixon. All they saw were carefully scripted campaign\nspots.Oddly enough, the most recent true counterexample is probably 1960.\nThough this election is usually given as an example of the power\nof TV, Kennedy apparently would not have won without fraud by party\nmachines in Illinois and Texas. But TV was still young in 1960;\nonly 87% of households had it.\n[3]\nUndoubtedly TV helped Kennedy,\nso historians are correct in regarding this election as a\nwatershed. TV required a new kind of candidate. There would be no\nmore Calvin Coolidges.The charisma theory may also explain why Democrats tend to lose\npresidential elections. The core of the Democrats' ideology seems\nto be a belief in government. Perhaps this tends to attract people\nwho are earnest, but dull. Dukakis, Gore, and Kerry were so similar\nin that respect that they might have been brothers. Good thing for\nthe Democrats that their screen lets through an occasional Clinton,\neven if some scandal results. \n[4]One would like to believe elections are won and lost on issues, if\nonly fake ones like Willie Horton. And yet, if they are, we have\na remarkable coincidence to explain. In every presidential election\nsince TV became widespread, the apparently more charismatic candidate\nhas won. Surprising, isn't it, that voters' opinions on the issues\nhave lined up with charisma for 11 elections in a row?The political commentators who come up with shifts to the left or\nright in their morning-after analyses are like the financial reporters\nstuck writing stories day after day about the random fluctuations\nof the stock market. Day ends, market closes up or down, reporter\nlooks for good or bad news respectively, and writes that the market\nwas up on news of Intel's earnings, or down on fears of instability\nin the Middle East. Suppose we could somehow feed these reporters\nfalse information about market closes, but give them all the other\nnews intact. Does anyone believe they would notice the anomaly,\nand not simply write that stocks were up (or down) on whatever good\n(or bad) news there was that day? That they would say, hey, wait\na minute, how can stocks be up with all this unrest in the Middle\nEast?I'm not saying that issues don't matter to voters. Of course they\ndo. But the major parties know so well which issues matter how\nmuch to how many voters, and adjust their message so precisely in\nresponse, that they tend to split the difference on the issues,\nleaving the election to be decided by the one factor they can't\ncontrol: charisma.If the Democrats had been running a candidate as charismatic as\nClinton in the 2004 election, he'd have won. And we'd be reading\nthat the election was a referendum on the war in Iraq, instead of\nthat the Democrats are out of touch with evangelical Christians in\nmiddle America.During the 1992 election, the Clinton campaign staff had a big sign\nin their office saying \"It's the economy, stupid.\" Perhaps it was\neven simpler than they thought.PostscriptOpinions seem to be divided about the charisma theory. Some say\nit's impossible, others say it's obvious. This seems a good sign.\nPerhaps it's in the sweet spot midway between.As for it being impossible, I reply: here's the data; here's the\ntheory; theory explains data 100%. To a scientist, at least, that\nmeans it deserves attention, however implausible it seems.You can't believe voters are so superficial that they just choose\nthe most charismatic guy? My theory doesn't require that. I'm not\nproposing that charisma is the only factor, just that it's the only\none left after the efforts of the two parties cancel one\nanother out.As for the theory being obvious, as far as I know, no one has\nproposed it before. Election forecasters are proud when they can\nachieve the same results with much more complicated models.Finally, to the people who say that the theory is probably true,\nbut rather depressing: it's not so bad as it seems. The phenomenon\nis like a pricing anomaly; once people realize it's there, it will\ndisappear. Once both parties realize it's a waste of time to\nnominate uncharismatic candidates, they'll tend to nominate only\nthe most charismatic ones. And if the candidates are equally\ncharismatic, charisma will cancel out, and elections will be decided\non issues, as political commentators like to think they are now.Notes[1]\nAs Clinton himself discovered to his surprise when, in one of\nhis first acts as president, he tried to shift the military leftward.\nAfter a bruising fight he escaped with a face-saving compromise.[2]\nTrue, Gore won the popular vote. But politicians know the electoral\nvote decides the election, so that's what they campaign for. If Bush\nhad been campaigning for the popular vote he would presumably have\ngot more of it. (Thanks to judgmentalist for this point.)[3]\nSource: Nielsen Media Research. Of the remaining 13%, 11 didn't\nhave TV because they couldn't afford it. I'd argue that the missing\n11% were probably also the 11% most susceptible to charisma.[4]\nOne implication of this theory is that parties shouldn't be too\nquick to reject candidates with skeletons in their closets.\nCharismatic candidates will tend to have more skeletons than squeaky\nclean dullards, but in practice that doesn't seem to lose elections.\nThe current Bush, for example, probably did more drugs in his\ntwenties than any preceding president, and yet managed to get elected\nwith a base of evangelical Christians. All you have to do is say\nyou've reformed, and stonewall about the details.Thanks to Trevor Blackwell, Maria Daniels, Jessica Livingston,\nJackie McDonough, and Robert Morris for reading drafts of this, and\nto Eric Raymond for pointing out that I was wrong about 1968.\n\n\nComment on this essay." }, { "path": "data/PaulGrahamEssays/cities.txt", "content": "May 2008\nGreat cities attract ambitious people. You can sense it when you\nwalk around one. In a hundred subtle ways, the city sends you a\nmessage: you could do more; you should try harder.The surprising thing is how different these messages can be. New\nYork tells you, above all: you should make more money. There are\nother messages too, of course. You should be hipper. You should\nbe better looking. But the clearest message is that you should be\nricher.What I like about Boston (or rather Cambridge) is that the message\nthere is: you should be smarter. You really should get around to\nreading all those books you've been meaning to.When you ask what message a city sends, you sometimes get surprising\nanswers. As much as they respect brains in Silicon Valley, the\nmessage the Valley sends is: you should be more powerful.That's not quite the same message New York sends. Power matters\nin New York too of course, but New York is pretty impressed by a\nbillion dollars even if you merely inherited it. In Silicon Valley\nno one would care except a few real estate agents. What matters\nin Silicon Valley is how much effect you have on the world. The\nreason people there care about Larry and Sergey is not their wealth\nbut the fact that they control Google, which affects practically\neveryone._____How much does it matter what message a city sends? Empirically,\nthe answer seems to be: a lot. You might think that if you had\nenough strength of mind to do great things, you'd be able to transcend\nyour environment. Where you live should make at most a couple\npercent difference. But if you look at the historical evidence,\nit seems to matter more than that. Most people who did great things\nwere clumped together in a few places where that sort of thing was\ndone at the time.You can see how powerful cities are from something I wrote about\nearlier: the case of the Milanese Leonardo. \nPractically every\nfifteenth century Italian painter you've heard of was from Florence,\neven though Milan was just as big. People in Florence weren't\ngenetically different, so you have to assume there was someone born\nin Milan with as much natural ability as Leonardo. What happened\nto him?If even someone with the same natural ability as Leonardo\ncouldn't beat the force of environment, do you suppose you can?I don't. I'm fairly stubborn, but I wouldn't try to fight this\nforce. I'd rather use it. So I've thought a lot about where to\nlive.I'd always imagined Berkeley would be the ideal place — that\nit would basically be Cambridge with good weather. But when I\nfinally tried living there a couple years ago, it turned out not\nto be. The message Berkeley sends is: you should live better. Life\nin Berkeley is very civilized. It's probably the place in America\nwhere someone from Northern Europe would feel most at home. But\nit's not humming with ambition.In retrospect it shouldn't have been surprising that a place so\npleasant would attract people interested above all in quality of\nlife. Cambridge with good weather, it turns out, is not Cambridge.\nThe people you find in Cambridge are not there by accident. You\nhave to make sacrifices to live there. It's expensive and somewhat\ngrubby, and the weather's often bad. So the kind of people you\nfind in Cambridge are the kind of people who want to live where the\nsmartest people are, even if that means living in an expensive,\ngrubby place with bad weather.As of this writing, Cambridge seems to be the intellectual capital\nof the world. I realize that seems a preposterous claim. What\nmakes it true is that it's more preposterous to claim about anywhere\nelse. American universities currently seem to be the best, judging\nfrom the flow of ambitious students. And what US city has a stronger\nclaim? New York? A fair number of smart people, but diluted by a\nmuch larger number of neanderthals in suits. The Bay Area has a\nlot of smart people too, but again, diluted; there are two great\nuniversities, but they're far apart. Harvard and MIT are practically\nadjacent by West Coast standards, and they're surrounded by about\n20 other colleges and universities.\n[1]Cambridge as a result feels like a town whose main industry is\nideas, while New York's is finance and Silicon Valley's is startups._____When you talk about cities in the sense we are, what you're really\ntalking about is collections of people. For a long time cities\nwere the only large collections of people, so you could use the two\nideas interchangeably. But we can see how much things are changing\nfrom the examples I've mentioned. New York is a classic great city.\nBut Cambridge is just part of a city, and Silicon Valley is not\neven that. (San Jose is not, as it sometimes claims, the capital\nof Silicon Valley. It's just 178 square miles at one end of it.)Maybe the Internet will change things further. Maybe one day the\nmost important community you belong to will be a virtual one, and\nit won't matter where you live physically. But I wouldn't bet on\nit. The physical world is very high bandwidth, and some of the\nways cities send you messages are quite subtle.One of the exhilarating things about coming back to Cambridge every\nspring is walking through the streets at dusk, when you can see\ninto the houses. When you walk through Palo Alto in the evening,\nyou see nothing but the blue glow of TVs. In Cambridge you see\nshelves full of promising-looking books. Palo Alto was probably\nmuch like Cambridge in 1960, but you'd never guess now that there\nwas a university nearby. Now it's just one of the richer neighborhoods\nin Silicon Valley. \n[2]A city speaks to you mostly by accident — in things you see\nthrough windows, in conversations you overhear. It's not something\nyou have to seek out, but something you can't turn off. One of the\noccupational hazards of living in Cambridge is overhearing the\nconversations of people who use interrogative intonation in declarative\nsentences. But on average I'll take Cambridge conversations over\nNew York or Silicon Valley ones.A friend who moved to Silicon Valley in the late 90s said the worst\nthing about living there was the low quality of the eavesdropping.\nAt the time I thought she was being deliberately eccentric. Sure,\nit can be interesting to eavesdrop on people, but is good quality\neavesdropping so important that it would affect where you chose to\nlive? Now I understand what she meant. The conversations you\noverhear tell you what sort of people you're among._____No matter how determined you are, it's hard not to be influenced\nby the people around you. It's not so much that you do whatever a\ncity expects of you, but that you get discouraged when no one around\nyou cares about the same things you do.There's an imbalance between encouragement and discouragement like\nthat between gaining and losing money. Most people overvalue\nnegative amounts of money: they'll work much harder to avoid losing\na dollar than to gain one. Similarly, although there are plenty of\npeople strong enough to resist doing something just because that's\nwhat one is supposed to do where they happen to be, there are few\nstrong enough to keep working on something no one around them cares\nabout.Because ambitions are to some extent incompatible and admiration\nis a zero-sum game, each city tends to focus on one type of ambition.\nThe reason Cambridge is the intellectual capital is not just that\nthere's a concentration of smart people there, but that there's\nnothing else people there care about more. Professors in\nNew York and the Bay area are second class citizens — till they\nstart hedge funds or startups respectively.This suggests an answer to a question people in New York have\nwondered about since the Bubble: whether New York could grow into\na startup hub to rival Silicon Valley. One reason that's unlikely\nis that someone starting a startup in New York would feel like a\nsecond class citizen. \n[3]\nThere's already something else people in New York admire more.In the long term, that could be a bad thing for New York. The power\nof an important new technology does eventually convert to money.\nSo by caring more about money and less about power than Silicon\nValley, New York is recognizing the same thing, but slower.\n[4]\nAnd in fact it has been losing to Silicon Valley at its own game:\nthe ratio of New York to California residents in the Forbes 400 has\ndecreased from 1.45 (81:56) when the list was first published in\n1982 to .83 (73:88) in 2007._____Not all cities send a message. Only those that are centers for\nsome type of ambition do. And it can be hard to tell exactly what\nmessage a city sends without living there. I understand the messages\nof New York, Cambridge, and Silicon Valley because I've lived for\nseveral years in each of them. DC and LA seem to send messages\ntoo, but I haven't spent long enough in either to say for sure what\nthey are.The big thing in LA seems to be fame. There's an A List of people\nwho are most in demand right now, and what's most admired is to be\non it, or friends with those who are. Beneath that, the message is\nmuch like New York's, though perhaps with more emphasis on physical\nattractiveness.In DC the message seems to be that the most important thing is who\nyou know. You want to be an insider. In practice this seems to\nwork much as in LA. There's an A List and you want to be on it or\nclose to those who are. The only difference is how the A List is\nselected. And even that is not that different.At the moment, San Francisco's message seems to be the same as\nBerkeley's: you should live better. But this will change if enough\nstartups choose SF over the Valley. During the Bubble that was a\npredictor of failure — a self-indulgent choice, like buying\nexpensive office furniture. Even now I'm suspicious when startups\nchoose SF. But if enough good ones do, it stops being a self-indulgent\nchoice, because the center of gravity of Silicon Valley will shift\nthere.I haven't found anything like Cambridge for intellectual ambition.\nOxford and Cambridge (England) feel like Ithaca or Hanover: the\nmessage is there, but not as strong.Paris was once a great intellectual center. If you went there in\n1300, it might have sent the message Cambridge does now. But I\ntried living there for a bit last year, and the ambitions of the\ninhabitants are not intellectual ones. The message Paris sends now\nis: do things with style. I liked that, actually. Paris is the\nonly city I've lived in where people genuinely cared about art. In\nAmerica only a few rich people buy original art, and even the more\nsophisticated ones rarely get past judging it by the brand name of\nthe artist. But looking through windows at dusk in Paris you can\nsee that people there actually care what paintings look like.\nVisually, Paris has the best eavesdropping I know. \n[5]There's one more message I've heard from cities: in London you can\nstill (barely) hear the message that one should be more aristocratic.\nIf you listen for it you can also hear it in Paris, New York, and\nBoston. But this message is everywhere very faint. It would have\nbeen strong 100 years ago, but now I probably wouldn't have picked\nit up at all if I hadn't deliberately tuned in to that wavelength\nto see if there was any signal left._____So far the complete list of messages I've picked up from cities is:\nwealth, style, hipness, physical attractiveness, fame, political\npower, economic power, intelligence, social class, and quality of\nlife.My immediate reaction to this list is that it makes me slightly\nqueasy. I'd always considered ambition a good thing, but I realize\nnow that was because I'd always implicitly understood it to mean\nambition in the areas I cared about. When you list everything\nambitious people are ambitious about, it's not so pretty.On closer examination I see a couple things on the list that are\nsurprising in the light of history. For example, physical\nattractiveness wouldn't have been there 100 years ago (though it\nmight have been 2400 years ago). It has always mattered for women,\nbut in the late twentieth century it seems to have started to matter\nfor men as well. I'm not sure why — probably some combination\nof the increasing power of women, the increasing influence of actors\nas models, and the fact that so many people work in offices now:\nyou can't show off by wearing clothes too fancy to wear in a factory,\nso you have to show off with your body instead.Hipness is another thing you wouldn't have seen on the list 100\nyears ago. Or wouldn't you? What it means is to know what's what.\nSo maybe it has simply replaced the component of social class that\nconsisted of being \"au fait.\" That could explain why hipness seems\nparticularly admired in London: it's version 2 of the traditional\nEnglish delight in obscure codes that only insiders understand.Economic power would have been on the list 100 years ago, but what\nwe mean by it is changing. It used to mean the control of vast\nhuman and material resources. But increasingly it means the ability\nto direct the course of technology, and some of the people in a\nposition to do that are not even rich — leaders of important\nopen source projects, for example. The Captains of Industry of\ntimes past had laboratories full of clever people cooking up new\ntechnologies for them. The new breed are themselves those people.As this force gets more attention, another is dropping off the list:\nsocial class. I think the two changes are related. Economic power,\nwealth, and social class are just names for the same thing at\ndifferent stages in its life: economic power converts to wealth,\nand wealth to social class. So the focus of admiration is simply\nshifting upstream._____Does anyone who wants to do great work have to live in a great city?\nNo; all great cities inspire some sort of ambition, but they aren't\nthe only places that do. For some kinds of work, all you need is\na handful of talented colleagues.What cities provide is an audience, and a funnel for peers. These\naren't so critical in something like math or physics, where no\naudience matters except your peers, and judging ability is sufficiently\nstraightforward that hiring and admissions committees can do it\nreliably. In a field like math or physics all you need is a\ndepartment with the right colleagues in it. It could be anywhere — in\nLos Alamos, New Mexico, for example.It's in fields like the arts or writing or technology that the\nlarger environment matters. In these the best practitioners aren't\nconveniently collected in a few top university departments and\nresearch labs — partly because talent is harder to judge, and\npartly because people pay for these things, so one doesn't need to\nrely on teaching or research funding to support oneself. It's in\nthese more chaotic fields that it helps most to be in a great city:\nyou need the encouragement of feeling that people around you care\nabout the kind of work you do, and since you have to find peers for\nyourself, you need the much larger intake mechanism of a great city.You don't have to live in a great city your whole life to benefit\nfrom it. The critical years seem to be the early and middle ones\nof your career. Clearly you don't have to grow up in a great city.\nNor does it seem to matter if you go to college in one. To most\ncollege students a world of a few thousand people seems big enough.\nPlus in college you don't yet have to face the hardest kind of\nwork — discovering new problems to solve.It's when you move on to the next and much harder step that it helps\nmost to be in a place where you can find peers and encouragement.\nYou seem to be able to leave, if you want, once you've found both.\nThe Impressionists show the typical pattern: they were born all\nover France (Pissarro was born in the Carribbean) and died all over\nFrance, but what defined them were the years they spent together\nin Paris._____Unless you're sure what you want to do and where the leading center\nfor it is, your best bet is probably to try living in several\nplaces when you're young. You can never tell what message a city\nsends till you live there, or even whether it still sends one.\nOften your information will be wrong: I tried living in Florence\nwhen I was 25, thinking it would be an art center, but it turned\nout I was 450 years too late.Even when a city is still a live center of ambition, you won't know\nfor sure whether its message will resonate with you till you hear\nit. When I moved to New York, I was very excited at first. It's\nan exciting place. So it took me quite a while to realize I just\nwasn't like the people there. I kept searching for the Cambridge\nof New York. It turned out it was way, way uptown: an hour uptown\nby air.Some people know at 16 what sort of work they're going to do, but\nin most ambitious kids, ambition seems to precede anything specific\nto be ambitious about. They know they want to do something great.\nThey just haven't decided yet whether they're going to be a rock\nstar or a brain surgeon. There's nothing wrong with that. But it\nmeans if you have this most common type of ambition, you'll probably\nhave to figure out where to live by trial and error. You'll\nprobably have to find the city where you feel at home to know what sort of\nambition you have.Notes[1]\nThis is one of the advantages of not having the universities\nin your country controlled by the government. When governments\ndecide how to allocate resources, political deal-making causes\nthings to be spread out geographically. No central goverment would\nput its two best universities in the same town, unless it was the\ncapital (which would cause other problems). But scholars seem to\nlike to cluster together as much as people in any other field, and\nwhen given the freedom to they derive the same advantages from it.[2]\nThere are still a few old professors in Palo Alto, but one by\none they die and their houses are transformed by developers into\nMcMansions and sold to VPs of Bus Dev.[3]\nHow many times have you read about startup founders who continued\nto live inexpensively as their companies took off? Who continued\nto dress in jeans and t-shirts, to drive the old car they had in\ngrad school, and so on? If you did that in New York, people would\ntreat you like shit. If you walk into a fancy restaurant in San\nFrancisco wearing a jeans and a t-shirt, they're nice to you; who\nknows who you might be? Not in New York.One sign of a city's potential as a technology center is the number\nof restaurants that still require jackets for men. According to\nZagat's there are none in San Francisco, LA, Boston, or Seattle, \n4 in DC, 6 in Chicago, 8 in London, 13 in New York, and 20 in Paris.(Zagat's lists the Ritz Carlton Dining Room in SF as requiring jackets\nbut I couldn't believe it, so I called to check and in fact they\ndon't. Apparently there's only one restaurant left on the entire West\nCoast that still requires jackets: The French Laundry in Napa Valley.)[4]\nIdeas are one step upstream from economic power, so it's\nconceivable that intellectual centers like Cambridge will one day\nhave an edge over Silicon Valley like the one the Valley has over\nNew York.This seems unlikely at the moment; if anything Boston is falling\nfurther and further behind. The only reason I even mention the\npossibility is that the path from ideas to startups has recently\nbeen getting smoother. It's a lot easier now for a couple of hackers\nwith no business experience to start a startup than it was 10 years\nago. If you extrapolate another 20 years, maybe the balance of\npower will start to shift back. I wouldn't bet on it, but I wouldn't\nbet against it either.[5]\nIf Paris is where people care most about art, why is New York\nthe center of gravity of the art business? Because in the twentieth\ncentury, art as brand split apart from art as stuff. New York is\nwhere the richest buyers are, but all they demand from art is brand,\nand since you can base brand on anything with a sufficiently\nidentifiable style, you may as well use the local stuff.Thanks to Trevor Blackwell, Sarah Harlin, Jessica Livingston,\nJackie McDonough, Robert Morris, and David Sloo for reading drafts\nof this." }, { "path": "data/PaulGrahamEssays/college.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\n\nMarch 2005(Parts of this essay began as replies to students who wrote to\nme with questions.)Recently I've had several emails from computer science\nundergrads asking what to do in college. I might not\nbe the best source of advice, because I was a philosophy major in\ncollege. But I took so many CS classes that most CS majors thought\nI was one. I was certainly a hacker, at least.HackingWhat should you do in college to become a \ngood hacker? There are two\nmain things you can do: become very good at programming, and learn\na lot about specific, cool problems. These turn out to be equivalent,\nbecause each drives you to do the other.The way to be good at programming is to work (a) a lot (b) on hard\nproblems. And the way to make yourself work on hard problems is\nto work on some very engaging project.\nOdds are this project won't be a class assignment. My friend Robert\nlearned a lot by writing network software when he was an\nundergrad. One of his projects was to connect Harvard to the\nArpanet; it had been one of the original nodes, but by 1984 the\nconnection had died. [1] Not only was this\nwork not for a class, but because he spent all his time on it\nand neglected his studies, he was kicked out of\nschool for a year. [2] It all evened out in the end, and now he's\na professor at MIT. But you'll probably be happier if you don't\ngo to that extreme; it caused him a lot of worry at the time.Another way to be good at programming is to find other people who\nare good at it, and learn what they know. Programmers tend to sort\nthemselves into tribes according to the type of work they do and\nthe tools they use, and some tribes are \nsmarter than others. Look\naround you and see what the smart people seem to be working on;\nthere's usually a reason.Some of the smartest people around you are professors. So one way\nto find interesting work is to volunteer as a research assistant.\nProfessors are especially interested in people who can solve tedious\nsystem-administration type problems for them, so that is a way to\nget a foot in the door. What they fear are\nflakes and resume padders. It's all too\ncommon for an assistant to result in a net increase in work. So\nyou have to make it clear you'll mean a net decrease.Don't be put off if they say no. Rejection is almost always less\npersonal than the rejectee imagines. Just move on to the next.\n(This applies to dating too.)Beware, because although most professors are smart, not all of them\nwork on interesting stuff. Professors have to publish novel results\nto advance their careers, but there is more competition in more\ninteresting areas of research. So what less ambitious professors\ndo is turn out a series of papers whose conclusions are novel because\nno one else cares about them. You're better off avoiding these.I never worked as a research assistant, so I feel a bit dishonest\nrecommending that route. I learned to program by writing stuff of\nmy own, particularly by trying to reverse-engineer Winograd's\nSHRDLU. I was as obsessed with that program as a mother with a new baby.Whatever the disadvantages of working by yourself, the advantage\nis that the project is all your own. You never have to compromise\nor ask anyone's permission, and if you have a new idea you can just\nsit down and start implementing it.In your own projects you don't have to worry about novelty (as\nprofessors do) or profitability (as businesses do). All that matters\nis how hard the project is technically, and that has no correlation\nto the nature of the application. \"Serious\" applications like \ndatabases are often trivial and dull technically (if you ever suffer\nfrom insomnia, try reading the technical literature about databases)\nwhile \"frivolous\" applications like games are often very sophisticated.\nI'm sure there are game companies out there working on products\nwith more intellectual content than the research at the\nbottom nine tenths of university CS departments.If I were in college now I'd probably work on\ngraphics: a network game, for example, or a tool for 3D animation.\nWhen I was an undergrad there weren't enough cycles around to make\ngraphics interesting, but it's hard to imagine anything more fun\nto work on now.MathWhen I was in college, a lot of the professors believed (or at least\nwished) that \ncomputer science was a branch of math. This idea was\nstrongest at Harvard, where there wasn't even a CS major till the\n1980s; till then one had to major in applied math. But it was\nnearly as bad at Cornell. When I told the fearsome Professor Conway\nthat I was interested in AI (a hot topic then), he told me I should\nmajor in math. I'm still not sure whether he thought AI required\nmath, or whether he thought AI was nonsense and that majoring in\nsomething rigorous would cure me of such stupid ambitions.In fact, the amount of math you need as a hacker is a lot less \nthan most university departments like to admit. I don't think you \nneed much more than high school math plus a few concepts from the\ntheory of computation. (You have to know what an n^2 algorithm is\nif you want to avoid writing them.) Unless you're planning to write\nmath applications, of course. Robotics, for example, is all math.But while you don't literally need math for most kinds of hacking,\nin the sense of knowing 1001 tricks for differentiating formulas, \nmath is very much worth studying for its own sake. It's a \nvaluable source of metaphors for almost any kind of work.[3] I wish \nI'd studied more math in college for that reason.Like a lot of people, I was mathematically abused as a child. I \nlearned to think of math as a collection of formulas that were\nneither beautiful nor had any relation to my life (despite attempts\nto translate them into \"word problems\"), but had to be memorized \nin order to do well on tests.One of the most valuable things you could do in college would be\nto learn what math is really about. This may not be easy, because\na lot of good mathematicians are bad teachers. And while there are\nmany popular books on math, few seem good. The best I can think\nof are W. W. Sawyer's. And of course Euclid. [4]EverythingThomas Huxley said \"Try to learn something about everything and \neverything about something.\" Most universities aim at this\nideal.But what's everything? To me it means, all that people\nlearn in the course of working honestly on hard problems. All such \nwork tends to be related, in that ideas and techniques from one \nfield can often be transplanted successfully to others. Even others\nthat seem quite distant. For example, I write \nessays the same way\nI write software: I sit down and blow out a lame version 1 as fast\nas I can type, then spend several weeks rewriting it.Working on hard problems is not, by itself, enough. Medieval \nalchemists were working on a hard problem, but their approach was \nso bogus that there was little\nto learn from studying it, except possibly about people's ability \nto delude themselves. Unfortunately the sort of AI I was trying \nto learn in college had the same flaw: a very hard problem, blithely\napproached with hopelessly inadequate techniques. Bold? Closer \nto fraudulent.\nThe social sciences are also fairly bogus, because they're so much \ninfluenced by intellectual fashions. If a \nphysicist met a colleague\nfrom 100 years ago, he could teach him some new things; if a psychologist\nmet a colleague from 100 years ago, they'd just get into an\nideological argument.\nYes, of course, you'll learn something by taking a\npsychology class. The point is, you'll learn more by taking\na class in another department.The worthwhile departments, in my opinion, are math, the hard\nsciences, engineering, history (especially economic and social \nhistory, and the history of science), architecture, and the classics.\nA survey course in art history may be worthwhile. Modern literature\nis important, but the way to learn about it is just to read. I\ndon't know enough about music to say.You can skip the social sciences, philosophy, and the various\ndepartments created recently in response to political pressures.\nMany of these fields talk about important problems, certainly. But\nthe way they talk about them is useless. For example, philosophy \ntalks, among other things, about our obligations to one another; \nbut you can learn more about this from a wise grandmother or E. B.\nWhite than from an academic philosopher.I speak here from experience. I should probably have been offended \nwhen people laughed at Clinton for saying \"It depends on what the \nmeaning of the word 'is' is.\" I took about five classes in college\non what the meaning of \"is\" is.Another way to figure out which fields are worth studying is to \ncreate the dropout graph. For example, I know many people \nwho switched from math to computer science because they found math \ntoo hard, and no one who did the opposite. People don't do hard\nthings gratuitously; no one will work on a harder problem unless \nit is proportionately (or at least log(n)) more rewarding. So\nprobably math is more worth studying than computer science. By\nsimilar comparisons you can make a graph of all the departments in\na university. At the bottom you'll find the subjects with least \nintellectual content.If you use this method, you'll get roughly the same answer I just \ngave.Language courses are an anomaly. I think they're better considered\nas extracurricular activities, like pottery classes. They'd be far\nmore useful when combined with some time living in a country where \nthe language is spoken. On a whim I studied Arabic as a freshman.\nIt was a lot of work, and the only lasting benefits were a weird \nability to identify semitic roots and some insights into how people\nrecognize words.Studio art and creative writing courses are wildcards. Usually \nyou don't get taught much: you just work (or don't work) on whatever\nyou want, and then sit around offering \"crits\" of one another's\ncreations under the vague supervision of the teacher. But writing and\nart are both very hard problems that (some) people work honestly\nat, so they're worth doing, especially if you can find a good\nteacher.JobsOf course college students have to think about more than just\nlearning. There are also two practical problems to consider: jobs,\nand graduate school.In theory a liberal education is not supposed to supply job training.\nBut everyone knows this is a bit of a fib. Hackers at every college\nlearn practical skills, and not by accident.What you should learn to get a job depends on the kind you want.\nIf you want to work in a big company, learn how to hack \nBlub on\nWindows. If you want to work at a cool little company or research \nlab, you'll do better to learn Ruby on Linux. And if you want to \nstart your own company, which I think will be more and more common,\nmaster the most powerful tools you can find, because you're going\nto be in a race against your competitors, and they'll be your horse.There is not a direct correlation between the skills you should \nlearn in college and those you'll use in a job. You should aim \nslightly high in college.In workouts a football player may bench press 300 pounds, even\nthough he may never have to exert anything like that much force in\nthe course of a game. Likewise, if your professors try to make you\nlearn stuff that's more advanced than you'll need in a job, it may\nnot just be because they're academics, detached from the real world.\nThey may be trying to make you lift weights with your brain.The programs you write in classes differ in three critical ways\nfrom the ones you'll write in the real world: they're small; you\nget to start from scratch; and the problem is usually artificial \nand predetermined. In the real world, programs are bigger, tend \nto involve existing code, and often require you to figure out what \nthe problem is before you can solve it.You don't have to wait to leave (or even enter) college to learn \nthese skills. If you want to learn how to deal with existing code,\nfor example, you can contribute to open-source projects. The sort\nof employer you want to work for will be as impressed by that as \ngood grades on class assignments.In existing open-source projects you don't get much practice at\nthe third skill, deciding what problems to solve. But there's \nnothing to stop you starting new projects of your own. And good\nemployers will be even more impressed\nwith that.What sort of problem should you try to solve? One way to answer\nthat is to ask what you need as a user. For example, I stumbled\non a good algorithm for spam filtering because I wanted to stop \ngetting spam. Now what I wish I had was a mail reader that somehow\nprevented my inbox from filling up. I tend to use my inbox as a\ntodo list. But that's like using a screwdriver to open\nbottles; what one really wants is a bottle opener.Grad SchoolWhat about grad school? Should you go? And how do you get into a \ngood one?In principle, grad school is professional training in research, and\nyou shouldn't go unless you want to do research as a career. And \nyet half the people who get PhDs in CS don't go into research.\nI didn't go to grad school to become a professor. I went because \nI wanted to learn more.So if you're mainly interested in hacking and you go to grad school,\nyou'll find a lot of other people who are similarly out of their \nelement. And if half the people around you are out of their element in the\nsame way you are, are you really out of your element?There's a fundamental problem in \"computer science,\" and it surfaces\nin situations like this. No one is sure what \"research\" is supposed to be. \nA lot\nof research is hacking that had to be crammed into the form of an\nacademic paper to yield one more quantum of publication.So it's kind of misleading to ask whether you'll be at home in grad\nschool, because very few people are quite at home in computer\nscience. The whole field is uncomfortable in its own skin. So\nthe fact that you're mainly interested in hacking shouldn't deter \nyou from going to grad school. Just be warned you'll have to do a lot of stuff \nyou don't like.Number one will be your dissertation. Almost everyone hates their\ndissertation by the time they're done with it. The\nprocess inherently tends to produce an unpleasant result, like a cake made out\nof whole wheat flour and baked for twelve hours. Few dissertations \nare read with pleasure, especially by their authors.But thousands before you have suffered through writing a dissertation.\nAnd aside from that, grad school is close to paradise. Many people\nremember it as the happiest time of their lives. And nearly all\nthe rest, including me, remember it as a period that would have \nbeen, if they hadn't had to write a dissertation. [5]The danger with grad school is that you don't see the scary part\nupfront. PhD programs start out as college part 2, with several\nyears of classes. So by the time you face the horror of writing a \ndissertation, you're already several years in. If you quit now,\nyou'll be a grad-school dropout, and you probably won't like that\nidea. When Robert got kicked out of grad school for writing the\nInternet worm of 1988, I envied him enormously for finding a way out\nwithout the stigma of failure. On the whole, grad school is probably better than most alternatives. You meet a \nlot of smart people, and your glum procrastination will at least \nbe a powerful common bond. And of course you have a PhD at the\nend. I forgot about that. I suppose that's worth something.The greatest advantage of a PhD (besides being the union card of\nacademia, of course) may be that it gives you some baseline confidence.\nFor example, the Honeywell thermostats in my house have the most\natrocious UI. My mother, who has the same model, diligently spent\na day reading the user's manual to learn how to operate hers. She\nassumed the problem was with her. But I can think to myself \"If\nsomeone with a PhD in computer science can't understand this\nthermostat, it must be badly \ndesigned.\"If you still want to go to grad school after this equivocal\nrecommendation, I can give you solid advice about how to get in. \nA lot of my friends are CS professors now, so I have the inside\nstory about admissions. It's quite different from college. At\nmost colleges, admissions officers decide who gets in. For PhD\nprograms, the professors do. And they try to do\nit well, because the people they admit are going to be working for\nthem.Apparently only recommendations really matter at the best schools.\nStandardized tests count for nothing, and grades for little. The\nessay is mostly an opportunity to disqualify yourself by saying \nsomething stupid. The only thing professors\ntrust is recommendations, preferably from people they know. [6]So if you want to get into a PhD program, the key is to impress\nyour professors. And from my friends who are professors I know \nwhat impresses them: not merely trying to impress them. They're\nnot impressed by students who get good grades or want to be their\nresearch assistants so they can get into grad school. They're\nimpressed by students who get good grades and want to be their \nresearch assistants because they're genuinely interested in the \ntopic.So the best thing you can do in college, whether you want to get\ninto grad school or just be good at hacking, is figure out what you\ntruly like. It's hard to trick professors into letting you into\ngrad school, and impossible to trick problems into letting you solve\nthem. College is where faking stops working. From this point,\nunless you want to go work for a big company, which is like reverting\nto high school, the only way forward is through doing what you \nlove.Notes\n[1] No one seems to have minded, which shows how unimportant\nthe Arpanet (which became the Internet) was as late as\n1984.[2] This is why, when I became an employer, I didn't care\nabout GPAs. In fact, we actively sought out people \nwho'd failed out of school. We once put up posters around Harvard\nsaying \"Did you just get kicked out for doing badly in your classes\nbecause you spent all your time working on some project of your \nown? Come work for us!\" We managed to find a kid who had been, \nand he was a great hacker.When Harvard kicks undergrads out for a year, they have to get jobs.\nThe idea is to show them how awful the real world is, so they'll \nunderstand how lucky they are to be in college. This plan backfired\nwith the guy who came to work for us, because he had more fun than\nhe'd had in school, and made more that year from stock options than\nany of his professors did in salary. So instead of crawling back\nrepentant at the end of the year, he took another year off and went\nto Europe. He did eventually graduate at about 26.[3] Eric Raymond says the best metaphors for hackers are\nin set theory, combinatorics, and graph theory.Trevor Blackwell reminds you to take math classes intended for math majors.\n\"'Math for engineers' classes sucked mightily. In fact any 'x for\nengineers' sucks, where x includes math, law, writing and visual\ndesign.\"[4] Other highly recommended books: What is Mathematics?, by\nCourant and Robbins; Geometry and the Imagination by Hilbert and \nCohn-Vossen.\nAnd for those interested in graphic design,\nByrne's Euclid.\n[5] If you wanted to have the perfect life, the thing to do would\nbe to go to grad school, secretly write your dissertation in the\nfirst year or two, and then just enjoy yourself for the next three\nyears, dribbling out a chapter at a time. This prospect will make\ngrad students' mouths water, but I know of no one who's had the\ndiscipline to pull it off.[6] One professor friend says that 15-20% of the grad students they\nadmit each year are \"long shots.\" But what he means by long shots\nare people whose applications are perfect in every way, except\nthat no one on the admissions committee knows the professors who\nwrote the recommendations.So if you want to get into\ngrad school in the sciences, you need to go to college somewhere with\nreal research professors. Otherwise you'll seem a risky bet\nto admissions committees, no matter how good you are.Which implies\na surprising but apparently inevitable consequence:\nlittle liberal arts colleges are doomed.\n Most smart\nhigh school kids at least consider going into the sciences, even\nif they ultimately choose not to.\nWhy go to a college that limits their options?Thanks to Trevor Blackwell, Alex Lewin, Jessica Livingston,\nRobert Morris, Eric\nRaymond, and several \nanonymous CS professors \nfor reading drafts of this, and to the students whose questions\nbegan it." }, { "path": "data/PaulGrahamEssays/colleges.txt", "content": "September 2007A few weeks ago I had a thought so heretical that it really surprised\nme. It may not matter all that much where you go to college.For me, as for a lot of middle class kids, getting into a good\ncollege was more or less the meaning of life when I was growing up.\nWhat was I? A student. To do that well meant to get good grades.\nWhy did one have to get good grades? To get into a good college.\nAnd why did one want to do that? There seemed to be several reasons:\nyou'd learn more, get better jobs, make more money. But it didn't\nmatter exactly what the benefits would be. College was a bottleneck\nthrough which all your future prospects passed; everything would\nbe better if you went to a better college.A few weeks ago I realized that somewhere along the line I had\nstopped believing that.What first set me thinking about this was the new trend of worrying\nobsessively about what \nkindergarten\nyour kids go to. It seemed to\nme this couldn't possibly matter. Either it won't help your kid\nget into Harvard, or if it does, getting into Harvard won't mean\nmuch anymore. And then I thought: how much does it mean even now?It turns out I have a lot of data about that. My three partners\nand I run a seed stage investment firm called \nY Combinator. We\ninvest when the company is just a couple guys and an idea. The\nidea doesn't matter much; it will change anyway. Most of our\ndecision is based on the founders. The average founder is three\nyears out of college. Many have just graduated; a few are still\nin school. So we're in much the same position as a graduate program,\nor a company hiring people right out of college. Except our choices\nare immediately and visibly tested. There are two possible outcomes\nfor a startup: success or failure—and usually you know within a\nyear which it will be.The test applied to a startup is among the purest of real world\ntests. A startup succeeds or fails depending almost entirely on\nthe efforts of the founders. Success is decided by the market: you\nonly succeed if users like what you've built. And users don't care\nwhere you went to college.As well as having precisely measurable results, we have a lot of\nthem. Instead of doing a small number of large deals like a\ntraditional venture capital fund, we do a large number of small\nones. We currently fund about 40 companies a year, selected from\nabout 900 applications representing a total of about 2000 people. \n[1]Between the volume of people we judge and the rapid, unequivocal\ntest that's applied to our choices, Y Combinator has been an\nunprecedented opportunity for learning how to pick winners. One\nof the most surprising things we've learned is how little it matters\nwhere people went to college.I thought I'd already been cured of caring about that. There's\nnothing like going to grad school at Harvard to cure you of any\nillusions you might have about the average Harvard undergrad. And\nyet Y Combinator showed us we were still overestimating people who'd\nbeen to elite colleges. We'd interview people from MIT or Harvard\nor Stanford and sometimes find ourselves thinking: they must be\nsmarter than they seem. It took us a few iterations to learn to\ntrust our senses.Practically everyone thinks that someone who went to MIT or Harvard\nor Stanford must be smart. Even people who hate you for it believe\nit.But when you think about what it means to have gone to an elite\ncollege, how could this be true? We're talking about a decision\nmade by admissions officers—basically, HR people—based on a\ncursory examination of a huge pile of depressingly similar applications\nsubmitted by seventeen year olds. And what do they have to go on?\nAn easily gamed standardized test; a short essay telling you what\nthe kid thinks you want to hear; an interview with a random alum;\na high school record that's largely an index of obedience. Who\nwould rely on such a test?And yet a lot of companies do. A lot of companies are very much\ninfluenced by where applicants went to college. How could they be?\nI think I know the answer to that.There used to be a saying in the corporate world: \"No one ever got\nfired for buying IBM.\" You no longer hear this about IBM specifically,\nbut the idea is very much alive; there is a whole category of\n\"enterprise\" software companies that exist to take advantage of it.\nPeople buying technology for large organizations don't care if they\npay a fortune for mediocre software. It's not their money. They\njust want to buy from a supplier who seems safe—a company with\nan established name, confident salesmen, impressive offices, and\nsoftware that conforms to all the current fashions. Not necessarily\na company that will deliver so much as one that, if they do let you\ndown, will still seem to have been a prudent choice. So companies\nhave evolved to fill that niche.A recruiter at a big company is in much the same position as someone\nbuying technology for one. If someone went to Stanford and is not\nobviously insane, they're probably a safe bet. And a safe bet is\nenough. No one ever measures recruiters by the later performance\nof people they turn down. \n[2]I'm not saying, of course, that elite colleges have evolved to prey\nupon the weaknesses of large organizations the way enterprise\nsoftware companies have. But they work as if they had. In addition\nto the power of the brand name, graduates of elite colleges have\ntwo critical qualities that plug right into the way large organizations\nwork. They're good at doing what they're asked, since that's what\nit takes to please the adults who judge you at seventeen. And\nhaving been to an elite college makes them more confident.Back in the days when people might spend their whole career at one\nbig company, these qualities must have been very valuable. Graduates\nof elite colleges would have been capable, yet amenable to authority.\nAnd since individual performance is so hard to measure in large\norganizations, their own confidence would have been the starting\npoint for their reputation.Things are very different in the new world of startups. We couldn't\nsave someone from the market's judgement even if we wanted to. And\nbeing charming and confident counts for nothing with users. All\nusers care about is whether you make something they like. If you\ndon't, you're dead.Knowing that test is coming makes us work a lot harder to get the\nright answers than anyone would if they were merely hiring people.\nWe can't afford to have any illusions about the predictors of\nsuccess. And what we've found is that the variation between schools\nis so much smaller than the variation between individuals that it's\nnegligible by comparison. We can learn more about someone in the\nfirst minute of talking to them than by knowing where they went to\nschool.It seems obvious when you put it that way. Look at the individual,\nnot where they went to college. But that's a weaker statement than\nthe idea I began with, that it doesn't matter much where a given\nindividual goes to college. Don't you learn things at the best\nschools that you wouldn't learn at lesser places?Apparently not. Obviously you can't prove this in the case of a\nsingle individual, but you can tell from aggregate evidence: you\ncan't, without asking them, distinguish people who went to one\nschool from those who went to another three times as far down the\nUS News list. \n[3]\nTry it and see.How can this be? Because how much you learn in college depends a\nlot more on you than the college. A determined party animal can\nget through the best school without learning anything. And someone\nwith a real thirst for knowledge will be able to find a few smart\npeople to learn from at a school that isn't prestigious at all.\nThe other students are the biggest advantage of going to an elite\ncollege; you learn more from them than the professors. But\nyou should be able to reproduce this at most colleges if you make\na conscious effort to find smart friends. At\nmost colleges you can find at least a handful of other smart students,\nand most people have only a handful of close friends in college\nanyway. \n[4]\nThe odds of finding smart professors are even better.\nThe curve for faculty is a lot flatter than for students, especially\nin math and the hard sciences; you have to go pretty far down the\nlist of colleges before you stop finding smart professors in the\nmath department.So it's not surprising that we've found the relative prestige of\ndifferent colleges useless in judging individuals. There's a lot\nof randomness in how colleges select people, and what they learn\nthere depends much more on them than the college. Between these\ntwo sources of variation, the college someone went to doesn't mean\na lot. It is to some degree a predictor of ability, but so weak\nthat we regard it mainly as a source of error and try consciously\nto ignore it.I doubt what we've discovered is an anomaly specific to startups.\nProbably people have always overestimated the importance of where\none goes to college. We're just finally able to measure it.The unfortunate thing is not just that people are judged by such a\nsuperficial test, but that so many judge themselves by it. A lot\nof people, probably the majority of people in America, have\nsome amount of insecurity about where, or whether, they went to\ncollege. The tragedy of the situation is that by far the greatest\nliability of not having gone to the college you'd have liked is\nyour own feeling that you're thereby lacking something. Colleges\nare a bit like exclusive clubs in this respect. There is only one\nreal advantage to being a member of most exclusive clubs: you know\nyou wouldn't be missing much if you weren't. When you're excluded,\nyou can only imagine the advantages of being an insider. But\ninvariably they're larger in your imagination than in real life.So it is with colleges. Colleges differ, but they're nothing like\nthe stamp of destiny so many imagine them to be. People aren't\nwhat some admissions officer decides about them at seventeen.\nThey're what they make themselves.Indeed, the great advantage of not caring where people went to\ncollege is not just that you can stop judging them (and yourself)\nby superficial measures, but that you can focus instead on what\nreally matters. What matters is what you make of yourself. \nI think that's what we\nshould tell kids. Their job isn't to get good grades so they can\nget into a good college, but to learn and do. And not just because\nthat's more rewarding than worldly success. That will increasingly\nbe the route to worldly success.\nNotes[1] \nIs what we measure worth measuring? I think so. You can get\nrich simply by being energetic and unscrupulous, but getting rich\nfrom a technology startup takes some amount of brains. It is just\nthe kind of work the upper middle class values; it has about the\nsame intellectual component as being a doctor.[2] \nActually, someone did, once. Mitch Kapor's wife Freada was\nin charge of HR at Lotus in the early years. (As he is at pains\nto point out, they did not become romantically involved till\nafterward.) At one point they worried Lotus was losing its startup\nedge and turning into a big company. So as an experiment she sent\ntheir recruiters the resumes of the first 40 employees, with\nidentifying details changed. These were the people who had made\nLotus into the star it was. Not one got an interview.[3] \nThe US News list? Surely no one trusts that. Even if the\nstatistics they consider are useful, how do they decide on the\nrelative weights? The reason the US News list is meaningful is\nprecisely because they are so intellectually dishonest in that\nrespect. There is no external source they can use to calibrate the\nweighting of the statistics they use; if there were, we could just\nuse that instead. What they must do is adjust the weights till the\ntop schools are the usual suspects in about the right order. So\nin effect what the US News list tells us is what the editors think\nthe top schools are, which is probably not far from the conventional\nwisdom on the matter. The amusing thing is, because some schools\nwork hard to game the system, the editors will have to keep tweaking\ntheir algorithm to get the rankings they want.[4] \nPossible doesn't mean easy, of course. A smart student at a party school\nwill inevitably be something of an outcast, just as he or\nshe would be in most high schools.\nThanks to Trevor Blackwell, Sarah Harlin, Jessica Livingston, Jackie\nMcDonough, Peter Norvig, and Robert Morris for reading drafts of\nthis." }, { "path": "data/PaulGrahamEssays/conformism.txt", "content": "July 2020One of the most revealing ways to classify people is by the degree\nand aggressiveness of their conformism. Imagine a Cartesian coordinate\nsystem whose horizontal axis runs from conventional-minded on the\nleft to independent-minded on the right, and whose vertical axis\nruns from passive at the bottom to aggressive at the top. The\nresulting four quadrants define four types of people. Starting in\nthe upper left and going counter-clockwise: aggressively\nconventional-minded, passively conventional-minded, passively\nindependent-minded, and aggressively independent-minded.I think that you'll find all four types in most societies, and that\nwhich quadrant people fall into depends more on their own personality\nthan the beliefs prevalent in their society.\n[1]Young children offer some of the best evidence for both points.\nAnyone who's been to primary school has seen the four types, and\nthe fact that school rules are so arbitrary is strong evidence that\nwhich quadrant people fall into depends more on them than the rules.The kids in the upper left quadrant, the aggressively conventional-minded\nones, are the tattletales. They believe not only that rules must\nbe obeyed, but that those who disobey them must be punished.The kids in the lower left quadrant, the passively conventional-minded,\nare the sheep. They're careful to obey the rules, but when other\nkids break them, their impulse is to worry that those kids will be\npunished, not to ensure that they will.The kids in the lower right quadrant, the passively independent-minded,\nare the dreamy ones. They don't care much about rules and probably\naren't 100% sure what the rules even are.And the kids in the upper right quadrant, the aggressively\nindependent-minded, are the naughty ones. When they see a rule,\ntheir first impulse is to question it. Merely being told what to\ndo makes them inclined to do the opposite.When measuring conformism, of course, you have to say with respect\nto what, and this changes as kids get older. For younger kids it's\nthe rules set by adults. But as kids get older, the source of rules\nbecomes their peers. So a pack of teenagers who all flout school\nrules in the same way are not independent-minded; rather the opposite.In adulthood we can recognize the four types by their distinctive\ncalls, much as you could recognize four species of birds. The call\nof the aggressively conventional-minded is \"Crush !\" (It's\nrather alarming to see an exclamation point after a variable, but\nthat's the whole problem with the aggressively conventional-minded.)\nThe call of the passively conventional-minded is \"What will the\nneighbors think?\" The call of the passively independent-minded is\n\"To each his own.\" And the call of the aggressively independent-minded\nis \"Eppur si muove.\"The four types are not equally common. There are more passive people\nthan aggressive ones, and far more conventional-minded people than\nindependent-minded ones. So the passively conventional-minded are\nthe largest group, and the aggressively independent-minded the\nsmallest.Since one's quadrant depends more on one's personality than the\nnature of the rules, most people would occupy the same quadrant\neven if they'd grown up in a quite different society.Princeton professor Robert George recently wrote:\n\n I sometimes ask students what their position on slavery would\n have been had they been white and living in the South before\n abolition. Guess what? They all would have been abolitionists!\n They all would have bravely spoken out against slavery, and\n worked tirelessly against it.\n\nHe's too polite to say so, but of course they wouldn't. And indeed,\nour default assumption should not merely be that his students would,\non average, have behaved the same way people did at the time, but\nthat the ones who are aggressively conventional-minded today would\nhave been aggressively conventional-minded then too. In other words,\nthat they'd not only not have fought against slavery, but that\nthey'd have been among its staunchest defenders.I'm biased, I admit, but it seems to me that aggressively\nconventional-minded people are responsible for a disproportionate\namount of the trouble in the world, and that a lot of the customs\nwe've evolved since the Enlightenment have been designed to protect\nthe rest of us from them. In particular, the retirement of the\nconcept of heresy and its replacement by the principle of freely\ndebating all sorts of different ideas, even ones that are currently\nconsidered unacceptable, without any punishment for those who try\nthem out to see if they work.\n[2]Why do the independent-minded need to be protected, though? Because\nthey have all the new ideas. To be a successful scientist, for\nexample, it's not enough just to be right. You have to be right\nwhen everyone else is wrong. Conventional-minded people can't do\nthat. For similar reasons, all successful startup CEOs are not\nmerely independent-minded, but aggressively so. So it's no coincidence\nthat societies prosper only to the extent that they have customs\nfor keeping the conventional-minded at bay.\n[3]In the last few years, many of us have noticed that the customs\nprotecting free inquiry have been weakened. Some say we're overreacting\n— that they haven't been weakened very much, or that they've been\nweakened in the service of a greater good. The latter I'll dispose\nof immediately. When the conventional-minded get the upper hand,\nthey always say it's in the service of a greater good. It just\nhappens to be a different, incompatible greater good each time.As for the former worry, that the independent-minded are being\noversensitive, and that free inquiry hasn't been shut down that\nmuch, you can't judge that unless you are yourself independent-minded.\nYou can't know how much of the space of ideas is being lopped off\nunless you have them, and only the independent-minded have the ones\nat the edges. Precisely because of this, they tend to be very\nsensitive to changes in how freely one can explore ideas. They're\nthe canaries in this coalmine.The conventional-minded say, as they always do, that they don't\nwant to shut down the discussion of all ideas, just the bad ones.You'd think it would be obvious just from that sentence what a\ndangerous game they're playing. But I'll spell it out. There are\ntwo reasons why we need to be able to discuss even \"bad\" ideas.The first is that any process for deciding which ideas to ban is\nbound to make mistakes. All the more so because no one intelligent\nwants to undertake that kind of work, so it ends up being done by\nthe stupid. And when a process makes a lot of mistakes, you need\nto leave a margin for error. Which in this case means you need to\nban fewer ideas than you'd like to. But that's hard for the\naggressively conventional-minded to do, partly because they enjoy\nseeing people punished, as they have since they were children, and\npartly because they compete with one another. Enforcers of orthodoxy\ncan't allow a borderline idea to exist, because that gives other\nenforcers an opportunity to one-up them in the moral purity department,\nand perhaps even to turn enforcer upon them. So instead of getting\nthe margin for error we need, we get the opposite: a race to the\nbottom in which any idea that seems at all bannable ends up being\nbanned. \n[4]The second reason it's dangerous to ban the discussion of ideas is\nthat ideas are more closely related than they look. Which means if\nyou restrict the discussion of some topics, it doesn't only affect\nthose topics. The restrictions propagate back into any topic that\nyields implications in the forbidden ones. And that is not an edge\ncase. The best ideas do exactly that: they have consequences\nin fields far removed from their origins. Having ideas in a world\nwhere some ideas are banned is like playing soccer on a pitch that\nhas a minefield in one corner. You don't just play the same game\nyou would have, but on a different shaped pitch. You play a much\nmore subdued game even on the ground that's safe.In the past, the way the independent-minded protected themselves\nwas to congregate in a handful of places — first in courts, and\nlater in universities — where they could to some extent make their\nown rules. Places where people work with ideas tend to have customs\nprotecting free inquiry, for the same reason wafer fabs have powerful\nair filters, or recording studios good sound insulation. For the\nlast couple centuries at least, when the aggressively conventional-minded\nwere on the rampage for whatever reason, universities were the\nsafest places to be.That may not work this time though, due to the unfortunate fact\nthat the latest wave of intolerance began in universities. It began\nin the mid 1980s, and by 2000 seemed to have died down, but it has\nrecently flared up again with the arrival of social media. This\nseems, unfortunately, to have been an own goal by Silicon Valley.\nThough the people who run Silicon Valley are almost all independent-minded,\nthey've handed the aggressively conventional-minded a tool such as\nthey could only have dreamed of.On the other hand, perhaps the decline in the spirit of free inquiry\nwithin universities is as much the symptom of the departure of the\nindependent-minded as the cause. People who would have become\nprofessors 50 years ago have other options now. Now they can become\nquants or start startups. You have to be independent-minded to\nsucceed at either of those. If these people had been professors,\nthey'd have put up a stiffer resistance on behalf of academic\nfreedom. So perhaps the picture of the independent-minded fleeing\ndeclining universities is too gloomy. Perhaps the universities are\ndeclining because so many have already left.\n[5]Though I've spent a lot of time thinking about this situation, I\ncan't predict how it plays out. Could some universities reverse the\ncurrent trend and remain places where the independent-minded want\nto congregate? Or will the independent-minded gradually abandon\nthem? I worry a lot about what we might lose if that happened.But I'm hopeful long term. The independent-minded are good at\nprotecting themselves. If existing institutions are compromised,\nthey'll create new ones. That may require some imagination. But\nimagination is, after all, their specialty.\nNotes[1]\nI realize of course that if people's personalities vary in any\ntwo ways, you can use them as axes and call the resulting four\nquadrants personality types. So what I'm really claiming is that\nthe axes are orthogonal and that there's significant variation in\nboth.[2]\nThe aggressively conventional-minded aren't responsible for all\nthe trouble in the world. Another big source of trouble is the sort\nof charismatic leader who gains power by appealing to them. They\nbecome much more dangerous when such leaders emerge.[3]\nI never worried about writing things that offended the\nconventional-minded when I was running Y Combinator. If YC were a\ncookie company, I'd have faced a difficult moral choice.\nConventional-minded people eat cookies too. But they don't start\nsuccessful startups. So if I deterred them from applying to YC, the\nonly effect was to save us work reading applications.[4]\nThere has been progress in one area: the punishments for talking\nabout banned ideas are less severe than in the past. There's little\ndanger of being killed, at least in richer countries. The aggressively\nconventional-minded are mostly satisfied with getting people fired.[5]\nMany professors are independent-minded — especially in math,\nthe hard sciences, and engineering, where you have to be to succeed.\nBut students are more representative of the general population, and\nthus mostly conventional-minded. So when professors and students\nare in conflict, it's not just a conflict between generations but\nalso between different types of people.Thanks to Sam Altman, Trevor Blackwell, Nicholas Christakis, Patrick\nCollison, Sam Gichuru, Jessica Livingston, Patrick McKenzie, Geoff\nRalston, and Harj Taggar for reading drafts of this." }, { "path": "data/PaulGrahamEssays/control.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nDecember 2010Someone we funded is talking to VCs now, and asked me how common\nit was for a startup's founders to retain control of the board after\na series A round. He said VCs told him this almost never happened.Ten years ago that was true. In the past, founders rarely kept\ncontrol of the board through a series A. The traditional series A\nboard consisted of two founders, two VCs, and one independent member.\nMore recently the recipe is often one founder, one VC, and one\nindependent. In either case the founders lose their majority.But not always. Mark Zuckerberg kept control of Facebook's board\nthrough the series A and still has it today. Mark Pincus has kept\ncontrol of Zynga's too. But are these just outliers? How common\nis it for founders to keep control after an A round? I'd heard of\nseveral cases among the companies we've funded, but I wasn't sure\nhow many there were, so I emailed the ycfounders list.The replies surprised me. In a dozen companies we've funded, the\nfounders still had a majority of the board seats after the series\nA round.I feel like we're at a tipping point here. A lot of VCs still act\nas if founders retaining board control after a series A is unheard-of.\nA lot of them try to make you feel bad if you even ask — as if\nyou're a noob or a control freak for wanting such a thing. But the\nfounders I heard from aren't noobs or control freaks. Or if they\nare, they are, like Mark Zuckerberg, the kind of noobs and control\nfreaks VCs should be trying to fund more of.Founders retaining control after a series A is clearly heard-of.\nAnd barring financial catastrophe, I think in the coming year it\nwill become the norm.Control of a company is a more complicated matter than simply\noutvoting other parties in board meetings. Investors usually get\nvetos over certain big decisions, like selling the company, regardless\nof how many board seats they have. And board votes are rarely\nsplit. Matters are decided in the discussion preceding the vote,\nnot in the vote itself, which is usually unanimous. But if opinion\nis divided in such discussions, the side that knows it would lose\nin a vote will tend to be less insistent. That's what board control\nmeans in practice. You don't simply get to do whatever you want;\nthe board still has to act in the interest of the shareholders; but\nif you have a majority of board seats, then your opinion about\nwhat's in the interest of the shareholders will tend to prevail.So while board control is not total control, it's not imaginary\neither. There's inevitably a difference in how things feel within\nthe company. Which means if it becomes the norm for founders to\nretain board control after a series A, that will change the way\nthings feel in the whole startup world.The switch to the new norm may be surprisingly fast, because the\nstartups that can retain control tend to be the best ones. They're\nthe ones that set the trends, both for other startups and for VCs.A lot of the reason VCs are harsh when negotiating with startups\nis that they're embarrassed to go back to their partners looking\nlike they got beaten. When they sign a termsheet, they want to be\nable to brag about the good terms they got. A lot of them don't\ncare that much personally about whether founders keep board control.\nThey just don't want to seem like they had to make concessions.\nWhich means if letting the founders keep control stops being perceived\nas a concession, it will rapidly become much more common.Like a lot of changes that have been forced on VCs, this change\nwon't turn out to be as big a problem as they might think. VCs will\nstill be able to convince; they just won't be able to compel. And\nthe startups where they have to resort to compulsion are not the\nones that matter anyway. VCs make most of their money from a few\nbig hits, and those aren't them.Knowing that founders will keep control of the board may even help\nVCs pick better. If they know they can't fire the founders, they'll\nhave to choose founders they can trust. And that's who they should\nhave been choosing all along.Thanks to Sam Altman, John Bautista, Trevor Blackwell, Paul\nBuchheit, Brian Chesky, Bill Clerico, Patrick Collison, Adam\nGoldstein, James Lindenbaum, Jessica Livingston, and Fred Wilson\nfor reading drafts of this." }, { "path": "data/PaulGrahamEssays/convergence.txt", "content": "March 2009About twenty years ago people noticed computers and TV were on a\ncollision course and started to speculate about what they'd produce\nwhen they converged. We now know the answer: computers. It's clear\nnow that even by using the word \"convergence\" we were giving TV too\nmuch credit. This won't be convergence so much as replacement.\nPeople may still watch things they call \"TV shows,\" but they'll\nwatch them mostly on computers.What decided the contest for computers? Four forces, three of which\none could have predicted, and one that would have been harder to.One predictable cause of victory is that the Internet is an open\nplatform. Anyone can build whatever they want on it, and the market\npicks the winners. So innovation happens at hacker speeds instead\nof big company speeds.The second is Moore's Law, which has worked its usual magic on\nInternet bandwidth. \n[1]The third reason computers won is piracy. Users prefer it \nnot just because it's free, but because it's\nmore convenient. Bittorrent and YouTube have already trained a new\ngeneration of viewers that the place to watch shows is on a computer\nscreen.\n[2]The somewhat more surprising force was one specific type of innovation:\nsocial applications. The average teenage kid has a pretty much\ninfinite capacity for talking to their friends. But they can't\nphysically be with them all the time. When I was in high school\nthe solution was the telephone. Now it's social networks, multiplayer\ngames, and various messaging applications. The way you reach them\nall is through a computer.\n[3]\nWhich means every teenage kid (a)\nwants a computer with an Internet connection, (b) has an incentive\nto figure out how to use it, and (c) spends countless hours in front\nof it.This was the most powerful force of all. This was what made everyone\nwant computers. Nerds got computers because they liked them. Then\ngamers got them to play games on. But it was connecting to other\npeople that got everyone else: that's what made even grandmas and\n14 year old girls want computers.\nAfter decades of running an IV drip right into their audience,\npeople in the entertainment business had understandably come to\nthink of them as rather passive. They thought they'd be able to\ndictate the way shows reached audiences. But they underestimated\nthe force of their desire to connect with one another.Facebook killed TV. That is wildly oversimplified, of course, but\nprobably as close to the truth as you can get in three words.___The TV networks already seem, grudgingly, to see where things are\ngoing, and have responded by putting their stuff, grudgingly, online.\nBut they're still dragging their heels. They still seem to wish\npeople would watch shows on TV instead, just as newspapers that put\ntheir stories online still seem to wish people would wait till the\nnext morning and read them printed on paper. They should both just\nface the fact that the Internet is the primary medium.They'd be in a better position if they'd done that earlier. When\na new medium arises that's powerful enough to make incumbents\nnervous, then it's probably powerful enough to win, and the best\nthing they can do is jump in immediately.Whether they like it or not, big changes are coming, because the\nInternet dissolves the two cornerstones of broadcast media:\nsynchronicity and locality. On the Internet, you don't have to\nsend everyone the same signal, and you don't have to send it to\nthem from a local source. People will watch what they want when\nthey want it, and group themselves according to whatever shared\ninterest they feel most strongly. Maybe their strongest shared\ninterest will be their physical location, but I'm guessing not.\nWhich means local TV is probably dead. It was an artifact of\nlimitations imposed by old technology. If someone were creating\nan Internet-based TV company from scratch now, they might have some\nplan for shows aimed at specific regions, but it wouldn't be a top\npriority.Synchronicity and locality are tied together. TV network affiliates\ncare what's on at 10 because that delivers viewers for local news\nat 11. This connection adds more brittleness than strength, however:\npeople don't watch what's on at 10 because they want to watch the\nnews afterward.TV networks will fight these trends, because they don't have\nsufficient flexibility to adapt to them. They're hemmed in by local\naffiliates in much the same way car companies are hemmed in by\ndealers and unions. Inevitably, the people running the networks\nwill take the easy route and try to keep the old model running for\na couple more years, just as the record labels have done.A recent article in the Wall Street Journal described how TV networks\nwere trying to add more live shows, partly as a way to make viewers\nwatch TV synchronously instead of watching recorded shows when it\nsuited them. Instead of delivering what viewers want, they're\ntrying to force them to change their habits to suit the networks'\nobsolete business model. That never works unless you have a monopoly\nor cartel to enforce it, and even then it only works temporarily.The other reason networks like live shows is that they're cheaper\nto produce. There they have the right idea, but they haven't\nfollowed it to its conclusion. Live content can be way cheaper\nthan networks realize, and the way to take advantage of dramatic\ndecreases in cost is to \nincrease volume. The networks are prevented\nfrom seeing this whole line of reasoning because they still think\nof themselves as being in the broadcast business—as sending one\nsignal to everyone.\n[4]___Now would be a good time to start any company that competes with\nTV networks. That's what a lot of Internet startups are, though\nthey may not have had this as an explicit goal. People only have\nso many leisure hours a day, and TV is premised on such long sessions\n(unlike Google, which prides itself on sending users on their way\nquickly) that anything that takes up their time is competing with\nit. But in addition to such indirect competitors, I think TV\ncompanies will increasingly face direct ones.Even in cable TV, the long tail was lopped off prematurely by the\nthreshold you had to get over to start a new channel. It will be\nlonger on the Internet, and there will be more mobility within it.\nIn this new world, the existing players will only have the advantages\nany big company has in its market.That will change the balance of power between the networks and the\npeople who produce shows. The networks used to be gatekeepers.\nThey distributed your work, and sold advertising on it. Now the\npeople who produce a show can distribute it themselves. The main\nvalue networks supply now is ad sales. Which will tend to put them\nin the position of service providers rather than publishers.Shows will change even more. On the Internet there's no reason to\nkeep their current format, or even the fact that they have a single\nformat. Indeed, the more interesting sort of convergence that's\ncoming is between shows and games. But on the question of what\nsort of entertainment gets distributed on the Internet in 20 years,\nI wouldn't dare to make any predictions, except that things will\nchange a lot. We'll get whatever the most imaginative people can\ncook up. That's why the Internet won.\nNotes[1]\nThanks to Trevor Blackwell for this point. He adds: \"I\nremember the eyes of phone companies gleaming in the early 90s when\nthey talked about convergence. They thought most programming would\nbe on demand, and they would implement it and make a lot of money.\nIt didn't work out. They assumed that their local network infrastructure\nwould be critical to do video on-demand, because you couldn't\npossibly stream it from a few data centers over the internet. At\nthe time (1992) the entire cross-country Internet bandwidth wasn't\nenough for one video stream. But wide-area bandwidth increased more\nthan they expected and they were beaten by iTunes and Hulu.\"[2]\nCopyright owners tend to focus on the aspect they see of\npiracy, which is the lost revenue. They therefore think what drives\nusers to do it is the desire to get something for free. But iTunes\nshows that people will pay for stuff online, if you make it easy.\nA significant component of piracy is simply that it offers a better\nuser experience.[3]\nOr a phone that is actually a computer. I'm not making any\npredictions about the size of the device that will replace TV, just\nthat it will have a browser and get data via the Internet.[4]\nEmmett Shear writes: \"I'd argue the long tail for sports may\nbe even larger than the long tail for other kinds of content. Anyone\ncan broadcast a high school football game that will be interesting\nto 10,000 people or so, even if the quality of production is not\nso good.\"\nThanks to Sam Altman, Trevor Blackwell, Nancy Cook, Michael Seibel,\nEmmett Shear, and Fred Wilson for reading drafts of this." }, { "path": "data/PaulGrahamEssays/convince.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nAugust 2013When people hurt themselves lifting heavy things, it's usually\nbecause they try to lift with their back. The right way to lift\nheavy things is to let your legs do the work. Inexperienced founders\nmake the same mistake when trying to convince investors. They try\nto convince with their pitch. Most would be better off if they let\ntheir startup do the work — if they started by understanding why\ntheir startup is worth investing in, then simply explained this\nwell to investors.Investors are looking for startups that will be very successful.\nBut that test is not as simple as it sounds. In startups, as in a\nlot of other domains, the distribution of outcomes follows a power\nlaw, but in startups the curve is startlingly steep. The big\nsuccesses are so big they \ndwarf the rest. And since there are only\na handful each year (the conventional wisdom is 15), investors treat\n\"big success\" as if it were binary. Most are interested in you if\nyou seem like you have a chance, however small, of being one of the\n15 big successes, and otherwise not.\n[1](There are a handful of angels who'd be interested in a company\nwith a high probability of being moderately successful. But angel\ninvestors like big successes too.)How do you seem like you'll be one of the big successes? You need\nthree things: formidable founders, a promising market, and (usually)\nsome evidence of success so far.FormidableThe most important ingredient is formidable founders. Most investors\ndecide in the first few minutes whether you seem like a winner or\na loser, and once their opinion is set it's hard to change. [2]\nEvery startup has reasons both to invest and not to invest. If\ninvestors think you're a winner they focus on the former, and if\nnot they focus on the latter. For example, it might be a rich\nmarket, but with a slow sales cycle. If investors are impressed\nwith you as founders, they say they want to invest because it's a\nrich market, and if not, they say they can't invest because of the\nslow sales cycle.They're not necessarily trying to mislead you. Most investors are\ngenuinely unclear in their own minds why they like or dislike\nstartups. If you seem like a winner, they'll like your idea more.\nBut don't be too smug about this weakness of theirs, because you\nhave it too; almost everyone does.There is a role for ideas of course. They're fuel for the fire\nthat starts with liking the founders. Once investors like you,\nyou'll see them reaching for ideas: they'll be saying \"yes, and you\ncould also do x.\" (Whereas when they don't like you, they'll be\nsaying \"but what about y?\")But the foundation of convincing investors is to seem formidable,\nand since this isn't a word most people use in conversation much,\nI should explain what it means. A formidable person is one who\nseems like they'll get what they want, regardless of whatever\nobstacles are in the way. Formidable is close to confident, except\nthat someone could be confident and mistaken. Formidable is roughly\njustifiably confident.There are a handful of people who are really good at seeming\nformidable — some because they actually are very formidable and\njust let it show, and others because they are more or less con\nartists.\n[3]\nBut most founders, including many who will go on\nto start very successful companies, are not that good at seeming\nformidable the first time they try fundraising. What should they\ndo?\n[4]What they should not do is try to imitate the swagger of more\nexperienced founders. Investors are not always that good at judging\ntechnology, but they're good at judging confidence. If you try to\nact like something you're not, you'll just end up in an uncanny\nvalley. You'll depart from sincere, but never arrive at convincing.TruthThe way to seem most formidable as an inexperienced founder is to\nstick to the truth. How formidable you seem isn't a constant. It\nvaries depending on what you're saying. Most people can seem\nconfident when they're saying \"one plus one is two,\" because they\nknow it's true. The most diffident person would be puzzled and\neven slightly contemptuous if they told a VC \"one plus one is two\"\nand the VC reacted with skepticism. The magic ability of people\nwho are good at seeming formidable is that they can do this with\nthe sentence \"we're going to make a billion dollars a year.\" But\nyou can do the same, if not with that sentence with some fairly\nimpressive ones, so long as you convince yourself first.That's the secret. Convince yourself that your startup is worth\ninvesting in, and then when you explain this to investors they'll\nbelieve you. And by convince yourself, I don't mean play mind games\nwith yourself to boost your confidence. I mean truly evaluate\nwhether your startup is worth investing in. If it isn't, don't try\nto raise money.\n[5]\nBut if it is, you'll be telling the truth\nwhen you tell investors it's worth investing in, and they'll sense\nthat. You don't have to be a smooth presenter if you understand\nsomething well and tell the truth about it.To evaluate whether your startup is worth investing in, you have\nto be a domain expert. If you're not a domain expert, you can be\nas convinced as you like about your idea, and it will seem to\ninvestors no more than an instance of the Dunning-Kruger effect.\nWhich in fact it will usually be. And investors can tell fairly\nquickly whether you're a domain expert by how well you answer their\nquestions. Know everything about your market.\n[6]Why do founders persist in trying to convince investors of things\nthey're not convinced of themselves? Partly because we've all been\ntrained to.When my friends Robert Morris and Trevor Blackwell were in grad\nschool, one of their fellow students was on the receiving end of a\nquestion from their faculty advisor that we still quote today. When\nthe unfortunate fellow got to his last slide, the professor burst\nout:\n\n Which one of these conclusions do you actually believe?\n\nOne of the artifacts of the way schools are organized is that we\nall get trained to talk even when we have nothing to say. If you\nhave a ten page paper due, then ten pages you must write, even if\nyou only have one page of ideas. Even if you have no ideas. You\nhave to produce something. And all too many startups go into\nfundraising in the same spirit. When they think it's time to raise\nmoney, they try gamely to make the best case they can for their\nstartup. Most never think of pausing beforehand to ask whether\nwhat they're saying is actually convincing, because they've all\nbeen trained to treat the need to present as a given — as an area\nof fixed size, over which however much truth they have must needs\nbe spread, however thinly.The time to raise money is not when you need it, or when you reach\nsome artificial deadline like a Demo Day. It's when you can convince\ninvestors, and not before. \n[7]And unless you're a good con artist, you'll never convince investors\nif you're not convinced yourself. They're far better at detecting\nbullshit than you are at producing it, even if you're producing it\nunknowingly. If you try to convince investors before you've convinced\nyourself, you'll be wasting both your time.But pausing first to convince yourself will do more than save you\nfrom wasting your time. It will force you to organize your thoughts.\nTo convince yourself that your startup is worth investing in, you'll\nhave to figure out why it's worth investing in. And if you can\ndo that you'll end up with more than added confidence. You'll also\nhave a provisional roadmap of how to succeed.MarketNotice I've been careful to talk about whether a startup is worth\ninvesting in, rather than whether it's going to succeed. No one\nknows whether a startup is going to succeed. And it's a good thing\nfor investors that this is so, because if you could know in advance\nwhether a startup would succeed, the stock price would already be\nthe future price, and there would be no room for investors to make\nmoney. Startup investors know that every investment is a bet, and\nagainst pretty long odds.So to prove you're worth investing in, you don't have to prove\nyou're going to succeed, just that you're a sufficiently good bet.\nWhat makes a startup a sufficiently good bet? In addition to\nformidable founders, you need a plausible path to owning a big piece\nof a big market. Founders think of startups as ideas, but investors\nthink of them as markets. If there are x number of customers who'd\npay an average of $y per year for what you're making, then the total\naddressable market, or TAM, of your company is $xy. Investors don't\nexpect you to collect all that money, but it's an upper bound on\nhow big you can get.Your target market has to be big, and it also has to be capturable\nby you. But the market doesn't have to be big yet, nor do you\nnecessarily have to be in it yet. Indeed, it's often better to\nstart in a small market that will either turn into a big one or\nfrom which you can move into a big one. There just has to be some\nplausible sequence of hops that leads to dominating a big market a\nfew years down the line.The standard of plausibility varies dramatically depending on the\nage of the startup. A three month old company at Demo Day only\nneeds to be a promising experiment that's worth funding to see how\nit turns out. Whereas a two year old company raising a series A\nround needs to be able to show the experiment worked. \n[8]But every company that gets really big is \"lucky\" in the sense that\ntheir growth is due mostly to some external wave they're riding,\nso to make a convincing case for becoming huge, you have to identify\nsome specific trend you'll benefit from. Usually you can find this\nby asking \"why now?\" If this is such a great idea, why hasn't\nsomeone else already done it? Ideally the answer is that it only\nrecently became a good idea, because something changed, and no one\nelse has noticed yet.Microsoft for example was not going to grow huge selling Basic\ninterpreters. But by starting there they were perfectly poised to\nexpand up the stack of microcomputer software as microcomputers\ngrew powerful enough to support one. And microcomputers turned out\nto be a really huge wave, bigger than even the most optimistic\nobservers would have predicted in 1975.But while Microsoft did really well and there is thus a temptation\nto think they would have seemed a great bet a few months in, they\nprobably didn't. Good, but not great. No company, however successful,\never looks more than a pretty good bet a few months in. Microcomputers\nturned out to be a big deal, and Microsoft both executed well and\ngot lucky. But it was by no means obvious that this was how things\nwould play out. Plenty of companies seem as good a bet a few months\nin. I don't know about startups in general, but at least half the\nstartups we fund could make as good a case as Microsoft could have\nfor being on a path to dominating a large market. And who can\nreasonably expect more of a startup than that?RejectionIf you can make as good a case as Microsoft could have, will you\nconvince investors? Not always. A lot of VCs would have rejected\nMicrosoft.\n[9]\nCertainly some rejected Google. And getting\nrejected will put you in a slightly awkward position, because as\nyou'll see when you start fundraising, the most common question\nyou'll get from investors will be \"who else is investing?\" What do\nyou say if you've been fundraising for a while and no one has\ncommitted yet? \n[10]The people who are really good at acting formidable often solve\nthis problem by giving investors the impression that while no\ninvestors have committed yet, several are about to. This is arguably\na permissible tactic. It's slightly dickish of investors to care\nmore about who else is investing than any other aspect of your\nstartup, and misleading them about how far along you are with other\ninvestors seems the complementary countermove. It's arguably an\ninstance of scamming a scammer. But I don't recommend this approach\nto most founders, because most founders wouldn't be able to carry\nit off. This is the single most common lie told to investors, and\nyou have to be really good at lying to tell members of some profession\nthe most common lie they're told.If you're not a master of negotiation (and perhaps even if you are)\nthe best solution is to tackle the problem head-on, and to explain\nwhy investors have turned you down and why they're mistaken. If\nyou know you're on the right track, then you also know why investors\nwere wrong to reject you. Experienced investors are well aware that\nthe best ideas are also the scariest. They all know about the VCs\nwho rejected Google. If instead of seeming evasive and ashamed\nabout having been turned down (and thereby implicitly agreeing with\nthe verdict) you talk candidly about what scared investors about\nyou, you'll seem more confident, which they like, and you'll probably\nalso do a better job of presenting that aspect of your startup. At\nthe very least, that worry will now be out in the open instead of\nbeing a gotcha left to be discovered by the investors you're currently\ntalking to, who will be proud of and thus attached to their discovery.\n[11]This strategy will work best with the best investors, who are both\nhard to bluff and who already believe most other investors are\nconventional-minded drones doomed always to miss the big outliers.\nRaising money is not like applying to college, where you can assume\nthat if you can get into MIT, you can also get into Foobar State.\nBecause the best investors are much smarter than the rest, and the\nbest startup ideas look initially like \nbad ideas, it's not uncommon\nfor a startup to be rejected by all the VCs except the best ones.\nThat's what happened to Dropbox. Y Combinator started in Boston,\nand for the first 3 years we ran alternating batches in Boston and\nSilicon Valley. Because Boston investors were so few and so timid,\nwe used to ship Boston batches out for a second Demo Day in Silicon\nValley. Dropbox was part of a Boston batch, which means all those\nBoston investors got the first look at Dropbox, and none of them\nclosed the deal. Yet another backup and syncing thing, they all\nthought. A couple weeks later, Dropbox raised a series A round\nfrom Sequoia.\n[12]DifferentNot understanding that investors view investments as bets combines\nwith the ten page paper mentality to prevent founders from even\nconsidering the possibility of being certain of what they're saying.\nThey think they're trying to convince investors of something very\nuncertain — that their startup will be huge — and convincing anyone\nof something like that must obviously entail some wild feat of\nsalesmanship. But in fact when you raise money you're trying to\nconvince investors of something so much less speculative — whether\nthe company has all the elements of a good bet — that you can\napproach the problem in a qualitatively different way. You can\nconvince yourself, then convince them.And when you convince them, use the same matter-of-fact language\nyou used to convince yourself. You wouldn't use vague, grandiose\nmarketing-speak among yourselves. Don't use it with investors\neither. It not only doesn't work on them, but seems a mark of\nincompetence. Just be concise. Many investors explicitly use that\nas a test, reasoning (correctly) that if you can't explain your\nplans concisely, you don't really understand them. But even investors\nwho don't have a rule about this will be bored and frustrated by\nunclear explanations.\n[13]So here's the recipe for impressing investors when you're not already\ngood at seeming formidable:\n\n Make something worth investing in. Understand why it's worth investing in. Explain that clearly to investors.\n\nIf you're saying something you know is true, you'll seem confident\nwhen you're saying it. Conversely, never let pitching draw you\ninto bullshitting. As long as you stay on the territory of truth,\nyou're strong. Make the truth good, then just tell it.Notes[1]\nThere's no reason to believe this number is a constant. In\nfact it's our explicit goal at Y Combinator to increase it, by\nencouraging people to start startups who otherwise wouldn't have.[2]\nOr more precisely, investors decide whether you're a loser\nor possibly a winner. If you seem like a winner, they may then,\ndepending on how much you're raising, have several more meetings\nwith you to test whether that initial impression holds up.But if you seem like a loser they're done, at least for the next\nyear or so. And when they decide you're a loser they usually decide\nin way less than the 50 minutes they may have allotted for the first\nmeeting. Which explains the astonished stories one always hears\nabout VC inattentiveness. How could these people make investment\ndecisions well when they're checking their messages during startups'\npresentations? The solution to that mystery is that they've already\nmade the decision.[3]\nThe two are not mutually exclusive. There are people who are\nboth genuinely formidable, and also really good at acting that way.[4]\nHow can people who will go on to create giant companies not\nseem formidable early on? I think the main reason is that their\nexperience so far has trained them to keep their wings folded, as\nit were. Family, school, and jobs encourage cooperation, not\nconquest. And it's just as well they do, because even being Genghis\nKhan is probably 99% cooperation. But the result is that most\npeople emerge from the tube of their upbringing in their early\ntwenties compressed into the shape of the tube. Some find they\nhave wings and start to spread them. But this takes a few years.\nIn the beginning even they don't know yet what they're capable of.[5]\nIn fact, change what you're doing. You're investing your own\ntime in your startup. If you're not convinced that what you're\nworking on is a sufficiently good bet, why are you even working on\nthat?[6]\nWhen investors ask you a question you don't know the answer\nto, the best response is neither to bluff nor give up, but instead\nto explain how you'd figure out the answer. If you can work out a\npreliminary answer on the spot, so much the better, but explain\nthat's what you're doing.[7]\nAt YC we try to ensure startups are ready to raise money on\nDemo Day by encouraging them to ignore investors and instead focus\non their companies till about a week before. That way most reach\nthe stage where they're sufficiently convincing well before Demo\nDay. But not all do, so we also give any startup that wants to the\noption of deferring to a later Demo Day.[8]\nFounders are often surprised by how much harder it is to raise\nthe next round. There is a qualitative difference in investors'\nattitudes. It's like the difference between being judged as a kid\nand as an adult. The next time you raise money, it's not enough\nto be promising. You have to be delivering results.So although it works well to show growth graphs at either stage,\ninvestors treat them differently. At three months, a growth graph\nis mostly evidence that the founders are effective. At two years,\nit has to be evidence of a promising market and a company tuned to\nexploit it.[9]\nBy this I mean that if the present day equivalent of the 3\nmonth old Microsoft presented at a Demo Day, there would be investors\nwho turned them down. Microsoft itself didn't raise outside money,\nand indeed the venture business barely existed when they got started\nin 1975.[10]\nThe best investors rarely care who else is investing, but\nmediocre investors almost all do. So you can use this question as\na test of investor quality.[11]\nTo use this technique, you'll have to find out why investors\nwho rejected you did so, or at least what they claim was the reason.\nThat may require asking, because investors don't always volunteer\na lot of detail. Make it clear when you ask that you're not trying\nto dispute their decision — just that if there is some weakness in\nyour plans, you need to know about it. You won't always get a real\nreason out of them, but you should at least try.[12]\nDropbox wasn't rejected by all the East Coast VCs. There was\none firm that wanted to invest but tried to lowball them.[13]\nAlfred Lin points out that it's doubly important for the\nexplanation of a startup to be clear and concise, because it has\nto convince at one remove: it has to work not just on the partner\nyou talk to, but when that partner re-tells it to colleagues.We consciously optimize for this at YC. When we work with founders\ncreate a Demo Day pitch, the last step is to imagine how an investor\nwould sell it to colleagues.\nThanks to Marc Andreessen, Sam Altman, Patrick Collison, Ron Conway,\nChris Dixon, Alfred Lin, Ben Horowitz, Steve Huffman, Jessica\nLivingston, Greg Mcadoo, Andrew Mason, Geoff Ralston, Yuri Sagalov,\nEmmett Shear, Rajat Suri, Garry Tan, Albert Wenger, Fred Wilson,\nand Qasar Younis for reading drafts of this." }, { "path": "data/PaulGrahamEssays/copy.txt", "content": "July 2006\nWhen I was in high school I spent a lot of time imitating bad\nwriters. What we studied in English classes was mostly fiction,\nso I assumed that was the highest form of writing. Mistake number\none. The stories that seemed to be most admired were ones in which\npeople suffered in complicated ways. Anything funny or\ngripping was ipso facto suspect, unless it was old enough to be hard to\nunderstand, like Shakespeare or Chaucer. Mistake number two. The\nideal medium seemed the short story, which I've since learned had\nquite a brief life, roughly coincident with the peak of magazine\npublishing. But since their size made them perfect for use in\nhigh school classes, we read a lot of them, which gave us the\nimpression the short story was flourishing. Mistake number three.\nAnd because they were so short, nothing really had to happen; you\ncould just show a randomly truncated slice of life, and that was\nconsidered advanced. Mistake number four. The result was that I\nwrote a lot of stories in which nothing happened except that someone\nwas unhappy in a way that seemed deep.For most of college I was a philosophy major. I was very impressed\nby the papers published in philosophy journals. They were so\nbeautifully typeset, and their tone was just captivating—alternately\ncasual and buffer-overflowingly technical. A fellow would be walking\nalong a street and suddenly modality qua modality would spring upon\nhim. I didn't ever quite understand these papers, but I figured\nI'd get around to that later, when I had time to reread them more\nclosely. In the meantime I tried my best to imitate them. This\nwas, I can now see, a doomed undertaking, because they weren't\nreally saying anything. No philosopher ever refuted another, for\nexample, because no one said anything definite enough to refute.\nNeedless to say, my imitations didn't say anything either.In grad school I was still wasting time imitating the wrong things.\nThere was then a fashionable type of program called an expert system,\nat the core of which was something called an inference engine. I\nlooked at what these things did and thought \"I could write that in\na thousand lines of code.\" And yet eminent professors were writing\nbooks about them, and startups were selling them for a year's salary\na copy. What an opportunity, I thought; these impressive things\nseem easy to me; I must be pretty sharp. Wrong. It was simply a\nfad. The books the professors wrote about expert systems are now\nignored. They were not even on a path to anything interesting.\nAnd the customers paying so much for them were largely the same\ngovernment agencies that paid thousands for screwdrivers and toilet\nseats.How do you avoid copying the wrong things? Copy only what you\ngenuinely like. That would have saved me in all three cases. I\ndidn't enjoy the short stories we had to read in English classes;\nI didn't learn anything from philosophy papers; I didn't use expert\nsystems myself. I believed these things were good because they\nwere admired.It can be hard to separate the things you like from the things\nyou're impressed with. One trick is to ignore presentation. Whenever\nI see a painting impressively hung in a museum, I ask myself: how\nmuch would I pay for this if I found it at a garage sale, dirty and\nframeless, and with no idea who painted it? If you walk around a\nmuseum trying this experiment, you'll find you get some truly\nstartling results. Don't ignore this data point just because it's\nan outlier.Another way to figure out what you like is to look at what you enjoy\nas guilty pleasures. Many things people like, especially if they're\nyoung and ambitious, they like largely for the feeling of virtue\nin liking them. 99% of people reading Ulysses are thinking\n\"I'm reading Ulysses\" as they do it. A guilty pleasure is\nat least a pure one. What do you read when you don't feel up to being\nvirtuous? What kind of book do you read and feel sad that there's\nonly half of it left, instead of being impressed that you're half\nway through? That's what you really like.Even when you find genuinely good things to copy, there's another\npitfall to be avoided. Be careful to copy what makes them good,\nrather than their flaws. It's easy to be drawn into imitating\nflaws, because they're easier to see, and of course easier to copy\ntoo. For example, most painters in the eighteenth and nineteenth\ncenturies used brownish colors. They were imitating the great\npainters of the Renaissance, whose paintings by that time were brown\nwith dirt. Those paintings have since been cleaned, revealing\nbrilliant colors; their imitators are of course still brown.It was painting, incidentally, that cured me of copying the wrong\nthings. Halfway through grad school I decided I wanted to try being\na painter, and the art world was so manifestly corrupt that it\nsnapped the leash of credulity. These people made philosophy\nprofessors seem as scrupulous as mathematicians. It was so clearly\na choice of doing good work xor being an insider that I was forced\nto see the distinction. It's there to some degree in almost every\nfield, but I had till then managed to avoid facing it.That was one of the most valuable things I learned from painting:\nyou have to figure out for yourself what's \ngood. You can't trust\nauthorities. They'll lie to you on this one.\n\nComment on this essay." }, { "path": "data/PaulGrahamEssays/corpdev.txt", "content": "January 2015Corporate Development, aka corp dev, is the group within companies\nthat buys other companies. If you're talking to someone from corp\ndev, that's why, whether you realize it yet or not.It's usually a mistake to talk to corp dev unless (a) you want to\nsell your company right now and (b) you're sufficiently likely to\nget an offer at an acceptable price. In practice that means startups\nshould only talk to corp dev when they're either doing really well\nor really badly. If you're doing really badly, meaning the company\nis about to die, you may as well talk to them, because you have\nnothing to lose. And if you're doing really well, you can safely\ntalk to them, because you both know the price will have to be high,\nand if they show the slightest sign of wasting your time, you'll\nbe confident enough to tell them to get lost.The danger is to companies in the middle. Particularly to young\ncompanies that are growing fast, but haven't been doing it for long\nenough to have grown big yet. It's usually a mistake for a promising\ncompany less than a year old even to talk to corp dev.But it's a mistake founders constantly make. When someone from\ncorp dev wants to meet, the founders tell themselves they should\nat least find out what they want. Besides, they don't want to\noffend Big Company by refusing to meet.Well, I'll tell you what they want. They want to talk about buying\nyou. That's what the title \"corp dev\" means. So before agreeing\nto meet with someone from corp dev, ask yourselves, \"Do we want to\nsell the company right now?\" And if the answer is no, tell them\n\"Sorry, but we're focusing on growing the company.\" They won't be\noffended. And certainly the founders of Big Company won't be\noffended. If anything they'll think more highly of you. You'll\nremind them of themselves. They didn't sell either; that's why\nthey're in a position now to buy other companies.\n[1]Most founders who get contacted by corp dev already know what it\nmeans. And yet even when they know what corp dev does and know\nthey don't want to sell, they take the meeting. Why do they do it?\nThe same mix of denial and wishful thinking that underlies most\nmistakes founders make. It's flattering to talk to someone who wants\nto buy you. And who knows, maybe their offer will be surprisingly\nhigh. You should at least see what it is, right?No. If they were going to send you an offer immediately by email,\nsure, you might as well open it. But that is not how conversations\nwith corp dev work. If you get an offer at all, it will be at the\nend of a long and unbelievably distracting process. And if the\noffer is surprising, it will be surprisingly low.Distractions are the thing you can least afford in a startup. And\nconversations with corp dev are the worst sort of distraction,\nbecause as well as consuming your attention they undermine your\nmorale. One of the tricks to surviving a grueling process is not\nto stop and think how tired you are. Instead you get into a sort\nof flow. \n[2]\nImagine what it would do to you if at mile 20 of a\nmarathon, someone ran up beside you and said \"You must feel really\ntired. Would you like to stop and take a rest?\" Conversations\nwith corp dev are like that but worse, because the suggestion of\nstopping gets combined in your mind with the imaginary high price\nyou think they'll offer.And then you're really in trouble. If they can, corp dev people\nlike to turn the tables on you. They like to get you to the point\nwhere you're trying to convince them to buy instead of them trying\nto convince you to sell. And surprisingly often they succeed.This is a very slippery slope, greased with some of the most powerful\nforces that can work on founders' minds, and attended by an experienced\nprofessional whose full time job is to push you down it.Their tactics in pushing you down that slope are usually fairly\nbrutal. Corp dev people's whole job is to buy companies, and they\ndon't even get to choose which. The only way their performance is\nmeasured is by how cheaply they can buy you, and the more ambitious\nones will stop at nothing to achieve that. For example, they'll\nalmost always start with a lowball offer, just to see if you'll\ntake it. Even if you don't, a low initial offer will demoralize you\nand make you easier to manipulate.And that is the most innocent of their tactics. Just wait till\nyou've agreed on a price and think you have a done deal, and then\nthey come back and say their boss has vetoed the deal and won't do\nit for more than half the agreed upon price. Happens all the time.\nIf you think investors can behave badly, it's nothing compared to\nwhat corp dev people can do. Even corp dev people at companies\nthat are otherwise benevolent.I remember once complaining to a\nfriend at Google about some nasty trick their corp dev people had\npulled on a YC startup.\"What happened to Don't be Evil?\" I asked.\"I don't think corp dev got the memo,\" he replied.The tactics you encounter in M&A conversations can be like nothing\nyou've experienced in the otherwise comparatively \nupstanding world\nof Silicon Valley. It's as if a chunk of genetic material from the\nold-fashioned robber baron business world got incorporated into the\nstartup world.\n[3]The simplest way to protect yourself is to use the trick that John\nD. Rockefeller, whose grandfather was an alcoholic, used to protect\nhimself from becoming one. He once told a Sunday school class\n\n Boys, do you know why I never became a drunkard? Because I never\n took the first drink.\n\nDo you want to sell your company right now? Not eventually, right\nnow. If not, just don't take the first meeting. They won't be\noffended. And you in turn will be guaranteed to be spared one of\nthe worst experiences that can happen to a startup.If you do want to sell, there's another set of \ntechniques\n for doing\nthat. But the biggest mistake founders make in dealing with corp\ndev is not doing a bad job of talking to them when they're ready\nto, but talking to them before they are. So if you remember only\nthe title of this essay, you already know most of what you need to\nknow about M&A in the first year.Notes[1]\nI'm not saying you should never sell. I'm saying you should\nbe clear in your own mind about whether you want to sell or not,\nand not be led by manipulation or wishful thinking into trying to\nsell earlier than you otherwise would have.[2]\nIn a startup, as in most competitive sports, the task at hand\nalmost does this for you; you're too busy to feel tired. But when\nyou lose that protection, e.g. at the final whistle, the fatigue\nhits you like a wave. To talk to corp dev is to let yourself feel\nit mid-game.[3]\nTo be fair, the apparent misdeeds of corp dev people are magnified\nby the fact that they function as the face of a large organization\nthat often doesn't know its own mind. Acquirers can be surprisingly\nindecisive about acquisitions, and their flakiness is indistinguishable\nfrom dishonesty by the time it filters down to you.Thanks to Marc Andreessen, Jessica Livingston, Geoff\nRalston, and Qasar Younis for reading drafts of this." }, { "path": "data/PaulGrahamEssays/cred.txt", "content": "April 2020I recently saw a \nvideo \nof TV journalists and politicians confidently\nsaying that the coronavirus would be no worse than the flu. What\nstruck me about it was not just how mistaken they seemed, but how\ndaring. How could they feel safe saying such things?The answer, I realized, is that they didn't think they could get\ncaught. They didn't realize there was any danger in making false\npredictions. These people constantly make false predictions, and\nget away with it, because the things they make predictions about\neither have mushy enough outcomes that they can bluster their way\nout of trouble, or happen so far in the future that few remember\nwhat they said.An epidemic is different. It falsifies your predictions rapidly and\nunequivocally.But epidemics are rare enough that these people clearly\ndidn't realize this was even a possibility. Instead they just\ncontinued to use their ordinary m.o., which, as the epidemic has\nmade clear, is to talk confidently about things they don't\nunderstand.An event like this is thus a uniquely powerful way of taking people's\nmeasure. As Warren Buffett said, \"It's only when the tide goes out\nthat you learn who's been swimming naked.\" And the tide has just\ngone out like never before.Now that we've seen the results, let's remember what we saw, because\nthis is the most accurate test of credibility we're ever likely to have. I hope." }, { "path": "data/PaulGrahamEssays/credentials.txt", "content": "December 2008A few months ago I read a New York Times article on South\nKorean cram schools that said \n Admission to the right university can make or break an ambitious\n young South Korean.\n A parent added: \n \"In our country, college entrance exams determine 70 to 80 percent\n of a person's future.\"\n It was striking how old fashioned this sounded. And\nyet when I was in high school it wouldn't have seemed too far off\nas a description of the US. Which means things must have been\nchanging here.The course of people's lives in the US now seems to be determined\nless by credentials and more by performance than it was 25 years\nago. Where you go to college still matters, but not like it used\nto.What happened?_____Judging people by their academic credentials was in its time an\nadvance. The practice seems to have begun in China, where starting\nin 587 candidates for the imperial civil service had to take an\nexam on classical literature. [1] It was also a test of wealth,\nbecause the knowledge it tested was so specialized that passing\nrequired years of expensive training. But though wealth was a\nnecessary condition for passing, it was not a sufficient one. By\nthe standards of the rest of the world in 587, the Chinese system\nwas very enlightened. Europeans didn't introduce formal civil\nservice exams till the nineteenth century, and even then they seem\nto have been influenced by the Chinese example.Before credentials, government positions were obtained mainly by\nfamily influence, if not outright bribery. It was a great step\nforward to judge people by their performance on a test. But by no\nmeans a perfect solution. When you judge people that way, you tend\nto get cram schools—which they did in Ming China and nineteenth\ncentury England just as much as in present day South Korea.What cram schools are, in effect, is leaks in a seal. The use of\ncredentials\nwas an attempt to seal off the direct transmission of power between\ngenerations, and cram schools represent that power finding holes\nin the seal. Cram schools turn wealth in one generation into\ncredentials in the next.It's hard to beat this phenomenon, because the schools adjust to suit\nwhatever the tests measure. When the tests are narrow and\npredictable, you get cram schools on the classic model, like those\nthat prepared candidates for Sandhurst (the British West Point) or\nthe classes American students take now to improve their SAT scores.\nBut as the tests get broader, the schools do too. Preparing a\ncandidate for the Chinese imperial civil service exams took years,\nas prep school does today. But the raison d'etre of all these\ninstitutions has been the same: to beat the system. [2]_____History suggests that, all other things being equal, a society\nprospers in proportion to its ability to prevent parents from\ninfluencing their children's success directly. It's a fine thing\nfor parents to help their children indirectly—for example,\nby helping them to become smarter or more disciplined, which then\nmakes them more successful. The problem comes when parents use\ndirect methods: when they are able to use their own wealth or power\nas a substitute for their children's qualities.Parents will tend to do this when they can. Parents will die for\ntheir kids, so it's not surprising to find they'll also push their\nscruples to the limits for them. Especially if other parents are\ndoing it.Sealing off this force has a double advantage. Not only does a\nsociety get \"the best man for the job,\" but\nparents' ambitions are diverted from direct methods to indirect\nones—to actually trying to raise their kids well.But we should expect it to be very hard to contain parents' efforts\nto obtain an unfair advantage for their kids. We're dealing with\none of the most powerful forces in human nature. We shouldn't expect\nnaive solutions to work, any more than we'd expect naive solutions\nfor keeping heroin out of a prison to work._____The obvious way to solve the problem is to make credentials better.\nIf the tests a society uses are currently hackable, we can study\nthe way people beat them and try to plug the holes. You can use\nthe cram schools to show you where most of the holes are. They\nalso tell you when you're succeeding in fixing them: when cram\nschools become less popular.A more general solution\nwould be to push for increased transparency, especially at critical\nsocial bottlenecks like college admissions. In the US this process\nstill shows many outward signs of corruption. For example, legacy\nadmissions. The official story is that legacy status doesn't carry\nmuch weight, because all it does is break ties: applicants are\nbucketed by ability, and legacy status is only used to decide between\nthe applicants in the bucket that straddles the cutoff. But what\nthis means is that a university can make legacy status have as much\nor as little weight as they want, by adjusting the size of the\nbucket that straddles the cutoff.By gradually chipping away at the abuse of credentials, you could\nprobably make them more airtight. But what a long fight it would\nbe. Especially when the institutions administering the tests don't\nreally want them to be airtight._____Fortunately there's a better way to prevent the direct transmission\nof power between generations. Instead of trying to make credentials\nharder to hack, we can also make them matter less.Let's think about what credentials are for. What they are,\nfunctionally, is a way of predicting performance. If you could\nmeasure actual performance, you wouldn't need them.So why did they even evolve? Why haven't we just been measuring\nactual performance? Think about where credentialism first appeared:\nin selecting candidates for large organizations. Individual\nperformance is hard to measure in large organizations, and the\nharder performance is to measure, the more important it is\nto predict it. If an organization could immediately and cheaply\nmeasure the performance of recruits, they wouldn't need to examine\ntheir credentials. They could take everyone and keep just the good\nones.Large organizations can't do this. But a bunch of small organizations\nin a market can come close. A market takes every organization and\nkeeps just the good ones. As organizations get smaller, this\napproaches taking every person and keeping just the good ones. So\nall other things being equal, a society consisting of more, smaller\norganizations will care less about credentials._____That's what's been happening in the US. That's why those quotes\nfrom Korea sound so old fashioned. They're talking about an economy\nlike America's a few decades ago, dominated by a few big companies.\nThe route for the ambitious in that sort of environment is to join\none and climb to the top. Credentials matter a lot then. In the \nculture of a large organization, an elite pedigree becomes a self-fulfilling\nprophecy.This doesn't work in small companies. Even if your colleagues were\nimpressed by your credentials, they'd soon be parted from you if\nyour performance didn't match, because the company would go out of\nbusiness and the people would be dispersed.In a world of small companies, performance is all anyone cares\nabout. People hiring for a startup don't care whether you've even\ngraduated from college, let alone which one. All they care about\nis what you can do. Which is in fact all that should matter, even\nin a large organization. The reason credentials have such prestige\nis that for so long the large organizations\nin a society tended to be the most powerful. But in the US at least\nthey don't have the monopoly on power they once did, precisely\nbecause they can't measure (and thus reward) individual performance.\nWhy spend twenty years climbing the corporate ladder when you can\nget rewarded directly by the market?I realize I see a more exaggerated version of the change than most\nother people. As a partner at an early stage venture funding firm,\nI'm like a jumpmaster shoving people out of the old world of\ncredentials and into the new one of performance. I'm an agent of\nthe change I'm seeing. But I don't think I'm imagining it. It was\nnot so easy 25 years ago for an ambitious person to choose to be\njudged directly by the market. You had to go through bosses, and\nthey were influenced by where you'd been to college._____What made it possible for small organizations to succeed in America?\nI'm still not entirely sure. Startups are certainly a large part\nof it. Small organizations can develop new ideas faster than large\nones, and new ideas are increasingly valuable.But I don't think startups account for all the shift from credentials\nto measurement. My friend Julian Weber told me that when he went\nto work for a New York law firm in the 1950s they paid associates\nfar less than firms do today. Law firms then made no pretense of\npaying people according to the value of the work they'd done. Pay\nwas based on seniority. The younger employees were paying their\ndues. They'd be rewarded later.The same principle prevailed at industrial companies. When my\nfather was working at Westinghouse in the 1970s, he had people\nworking for him who made more than he did, because they'd been there\nlonger.Now companies increasingly have to pay employees market price for\nthe work they do. One reason is that employees no longer trust\ncompanies to deliver \ndeferred rewards: why work to accumulate\ndeferred rewards at a company that might go bankrupt, or be taken\nover and have all its implicit obligations wiped out? The other\nis that some companies broke ranks and started to pay young employees\nlarge amounts. This was particularly true in consulting, law, and\nfinance, where it led to the phenomenon of yuppies. The word is\nrarely used today because it's no longer surprising to see a 25\nyear old with money, but in 1985 the sight of a 25 year old\nprofessional able to afford a new BMW was so novel that it\ncalled forth a new word.The classic yuppie worked for a small organization. He didn't work\nfor General Widget, but for the law firm that handled General\nWidget's acquisitions or the investment bank that floated their\nbond issues.Startups and yuppies entered the American conceptual vocabulary\nroughly simultaneously in the late 1970s and early 1980s. I don't\nthink there was a causal connection. Startups happened because\ntechnology started to change so fast that big companies could no\nlonger keep a lid on the smaller ones. I don't think the rise of\nyuppies was inspired by it; it seems more as if there was a change\nin the social conventions (and perhaps the laws) governing the way\nbig companies worked. But the two phenomena rapidly fused to produce\na principle that now seems obvious: paying energetic young people\nmarket rates, and getting correspondingly high performance from\nthem.At about the same time the US economy rocketed out of the doldrums\nthat had afflicted it for most of the 1970s. Was there a connection?\nI don't know enough to say, but it felt like it at the time. There\nwas a lot of energy released._____Countries worried about their competitiveness are right to be\nconcerned about the number of startups started within them. But\nthey would do even better to examine the underlying principle. Do\nthey let energetic young people get paid market rate for the work\nthey do? The young are the test, because when people aren't rewarded\naccording to performance, they're invariably rewarded according to\nseniority instead.All it takes is a few beachheads in your economy that pay for\nperformance. Measurement spreads like heat. If one part of a\nsociety is better at measurement than others, it tends to push the\nothers to do better. If people who are young but smart and driven\ncan make more by starting their own companies than by working for\nexisting ones, the existing companies are forced to pay more to\nkeep them. So market rates gradually permeate every organization,\neven the government. [3]The measurement of performance will tend to push even the organizations\nissuing credentials into line. When we were kids I used to annoy\nmy sister by ordering her to do things I knew she was about to do\nanyway. As credentials are superseded by performance, a similar\nrole is the best former gatekeepers can hope for. Once credential\ngranting institutions are no longer in the self-fullfilling prophecy\nbusiness, they'll have to work harder to predict the future._____Credentials are a step beyond bribery and influence. But they're\nnot the final step. There's an even better way to block the\ntransmission of power between generations: to encourage the trend\ntoward an economy made of more, smaller units. Then you can measure\nwhat credentials merely predict.No one likes the transmission of power between generations—not\nthe left or the right. But the market forces favored by the right\nturn out to be a better way of preventing it than the credentials\nthe left are forced to fall back on.The era of credentials began to end when the power of large\norganizations peaked \nin the late twentieth century. Now we seem\nto be entering a new era based on measurement. The reason the new\nmodel has advanced so rapidly is that it works so much better. It\nshows no sign of slowing.Notes[1] Miyazaki, Ichisada\n(Conrad Schirokauer trans.), China's Examination Hell: The Civil\nService Examinations of Imperial China, Yale University Press,\n1981.Scribes in ancient Egypt took exams, but they were more the type\nof proficiency test any apprentice might have to pass.[2] When I say the\nraison d'etre of prep schools is to get kids into better colleges,\nI mean this in the narrowest sense. I'm not saying that's all prep\nschools do, just that if they had zero effect on college admissions\nthere would be far less demand for them.[3] Progressive tax\nrates will tend to damp this effect, however, by decreasing the\ndifference between good and bad measurers.Thanks to Trevor Blackwell, Sarah Harlin, Jessica Livingston, and David\nSloo for reading drafts of this." }, { "path": "data/PaulGrahamEssays/desres.txt", "content": "January 2003(This article is derived from a keynote talk at the fall 2002 meeting\nof NEPLS.)Visitors to this country are often surprised to find that\nAmericans like to begin a conversation by asking \"what do you do?\"\nI've never liked this question. I've rarely had a\nneat answer to it. But I think I have finally solved the problem.\nNow, when someone asks me what I do, I look them straight\nin the eye and say \"I'm designing a \nnew dialect of Lisp.\" \nI recommend this answer to anyone who doesn't like being asked what\nthey do. The conversation will turn immediately to other topics.I don't consider myself to be doing research on programming languages.\nI'm just designing one, in the same way that someone might design\na building or a chair or a new typeface.\nI'm not trying to discover anything new. I just want\nto make a language that will be good to program in. In some ways,\nthis assumption makes life a lot easier.The difference between design and research seems to be a question\nof new versus good. Design doesn't have to be new, but it has to \nbe good. Research doesn't have to be good, but it has to be new.\nI think these two paths converge at the top: the best design\nsurpasses its predecessors by using new ideas, and the best research\nsolves problems that are not only new, but actually worth solving.\nSo ultimately we're aiming for the same destination, just approaching\nit from different directions.What I'm going to talk about today is what your target looks like\nfrom the back. What do you do differently when you treat\nprogramming languages as a design problem instead of a research topic?The biggest difference is that you focus more on the user.\nDesign begins by asking, who is this\nfor and what do they need from it? A good architect,\nfor example, does not begin by creating a design that he then\nimposes on the users, but by studying the intended users and figuring\nout what they need.Notice I said \"what they need,\" not \"what they want.\" I don't mean\nto give the impression that working as a designer means working as \na sort of short-order cook, making whatever the client tells you\nto. This varies from field to field in the arts, but\nI don't think there is any field in which the best work is done by\nthe people who just make exactly what the customers tell them to.The customer is always right in\nthe sense that the measure of good design is how well it works\nfor the user. If you make a novel that bores everyone, or a chair\nthat's horribly uncomfortable to sit in, then you've done a bad\njob, period. It's no defense to say that the novel or the chair \nis designed according to the most advanced theoretical principles.And yet, making what works for the user doesn't mean simply making\nwhat the user tells you to. Users don't know what all the choices\nare, and are often mistaken about what they really want.The answer to the paradox, I think, is that you have to design\nfor the user, but you have to design what the user needs, not simply \nwhat he says he wants.\nIt's much like being a doctor. You can't just treat a patient's\nsymptoms. When a patient tells you his symptoms, you have to figure\nout what's actually wrong with him, and treat that.This focus on the user is a kind of axiom from which most of the\npractice of good design can be derived, and around which most design\nissues center.If good design must do what the user needs, who is the user? When\nI say that design must be for users, I don't mean to imply that good \ndesign aims at some kind of \nlowest common denominator. You can pick any group of users you\nwant. If you're designing a tool, for example, you can design it\nfor anyone from beginners to experts, and what's good design\nfor one group might be bad for another. The point\nis, you have to pick some group of users. I don't think you can\neven talk about good or bad design except with\nreference to some intended user.You're most likely to get good design if the intended users include\nthe designer himself. When you design something\nfor a group that doesn't include you, it tends to be for people\nyou consider to be less sophisticated than you, not more sophisticated.That's a problem, because looking down on the user, however benevolently,\nseems inevitably to corrupt the designer.\nI suspect that very few housing\nprojects in the US were designed by architects who expected to live\nin them. You can see the same thing\nin programming languages. C, Lisp, and Smalltalk were created for\ntheir own designers to use. Cobol, Ada, and Java, were created \nfor other people to use.If you think you're designing something for idiots, the odds are\nthat you're not designing something good, even for idiots.\nEven if you're designing something for the most sophisticated\nusers, though, you're still designing for humans. It's different \nin research. In math you\ndon't choose abstractions because they're\neasy for humans to understand; you choose whichever make the\nproof shorter. I think this is true for the sciences generally.\nScientific ideas are not meant to be ergonomic.Over in the arts, things are very different. Design is\nall about people. The human body is a strange\nthing, but when you're designing a chair,\nthat's what you're designing for, and there's no way around it.\nAll the arts have to pander to the interests and limitations\nof humans. In painting, for example, all other things being\nequal a painting with people in it will be more interesting than\none without. It is not merely an accident of history that\nthe great paintings of the Renaissance are all full of people.\nIf they hadn't been, painting as a medium wouldn't have the prestige\nthat it does.Like it or not, programming languages are also for people,\nand I suspect the human brain is just as lumpy and idiosyncratic\nas the human body. Some ideas are easy for people to grasp\nand some aren't. For example, we seem to have a very limited\ncapacity for dealing with detail. It's this fact that makes\nprograming languages a good idea in the first place; if we\ncould handle the detail, we could just program in machine\nlanguage.Remember, too, that languages are not\nprimarily a form for finished programs, but something that\nprograms have to be developed in. Anyone in the arts could\ntell you that you might want different mediums for the\ntwo situations. Marble, for example, is a nice, durable\nmedium for finished ideas, but a hopelessly inflexible one\nfor developing new ideas.A program, like a proof,\nis a pruned version of a tree that in the past has had\nfalse starts branching off all over it. So the test of\na language is not simply how clean the finished program looks\nin it, but how clean the path to the finished program was.\nA design choice that gives you elegant finished programs\nmay not give you an elegant design process. For example, \nI've written a few macro-defining macros full of nested\nbackquotes that look now like little gems, but writing them\ntook hours of the ugliest trial and error, and frankly, I'm still\nnot entirely sure they're correct.We often act as if the test of a language were how good\nfinished programs look in it.\nIt seems so convincing when you see the same program\nwritten in two languages, and one version is much shorter.\nWhen you approach the problem from the direction of the\narts, you're less likely to depend on this sort of\ntest. You don't want to end up with a programming\nlanguage like marble.For example, it is a huge win in developing software to\nhave an interactive toplevel, what in Lisp is called a\nread-eval-print loop. And when you have one this has\nreal effects on the design of the language. It would not\nwork well for a language where you have to declare\nvariables before using them, for example. When you're\njust typing expressions into the toplevel, you want to be \nable to set x to some value and then start doing things\nto x. You don't want to have to declare the type of x\nfirst. You may dispute either of the premises, but if\na language has to have a toplevel to be convenient, and\nmandatory type declarations are incompatible with a\ntoplevel, then no language that makes type declarations \nmandatory could be convenient to program in.In practice, to get good design you have to get close, and stay\nclose, to your users. You have to calibrate your ideas on actual\nusers constantly, especially in the beginning. One of the reasons\nJane Austen's novels are so good is that she read them out loud to\nher family. That's why she never sinks into self-indulgently arty\ndescriptions of landscapes,\nor pretentious philosophizing. (The philosophy's there, but it's\nwoven into the story instead of being pasted onto it like a label.)\nIf you open an average \"literary\" novel and imagine reading it out loud\nto your friends as something you'd written, you'll feel all too\nkeenly what an imposition that kind of thing is upon the reader.In the software world, this idea is known as Worse is Better.\nActually, there are several ideas mixed together in the concept of\nWorse is Better, which is why people are still arguing about\nwhether worse\nis actually better or not. But one of the main ideas in that\nmix is that if you're building something new, you should get a\nprototype in front of users as soon as possible.The alternative approach might be called the Hail Mary strategy.\nInstead of getting a prototype out quickly and gradually refining\nit, you try to create the complete, finished, product in one long\ntouchdown pass. As far as I know, this is a\nrecipe for disaster. Countless startups destroyed themselves this\nway during the Internet bubble. I've never heard of a case\nwhere it worked.What people outside the software world may not realize is that\nWorse is Better is found throughout the arts.\nIn drawing, for example, the idea was discovered during the\nRenaissance. Now almost every drawing teacher will tell you that\nthe right way to get an accurate drawing is not to\nwork your way slowly around the contour of an object, because errors will\naccumulate and you'll find at the end that the lines don't meet.\nInstead you should draw a few quick lines in roughly the right place,\nand then gradually refine this initial sketch.In most fields, prototypes\nhave traditionally been made out of different materials.\nTypefaces to be cut in metal were initially designed \nwith a brush on paper. Statues to be cast in bronze \nwere modelled in wax. Patterns to be embroidered on tapestries\nwere drawn on paper with ink wash. Buildings to be\nconstructed from stone were tested on a smaller scale in wood.What made oil paint so exciting, when it\nfirst became popular in the fifteenth century, was that you\ncould actually make the finished work from the prototype.\nYou could make a preliminary drawing if you wanted to, but you\nweren't held to it; you could work out all the details, and\neven make major changes, as you finished the painting.You can do this in software too. A prototype doesn't have to\nbe just a model; you can refine it into the finished product.\nI think you should always do this when you can. It lets you\ntake advantage of new insights you have along the way. But\nperhaps even more important, it's good for morale.Morale is key in design. I'm surprised people\ndon't talk more about it. One of my first\ndrawing teachers told me: if you're bored when you're\ndrawing something, the drawing will look boring.\nFor example, suppose you have to draw a building, and you\ndecide to draw each brick individually. You can do this\nif you want, but if you get bored halfway through and start\nmaking the bricks mechanically instead of observing each one, \nthe drawing will look worse than if you had merely suggested\nthe bricks.Building something by gradually refining a prototype is good\nfor morale because it keeps you engaged. In software, my \nrule is: always have working code. If you're writing\nsomething that you'll be able to test in an hour, then you\nhave the prospect of an immediate reward to motivate you.\nThe same is true in the arts, and particularly in oil painting.\nMost painters start with a blurry sketch and gradually\nrefine it.\nIf you work this way, then in principle\nyou never have to end the day with something that actually\nlooks unfinished. Indeed, there is even a saying among\npainters: \"A painting is never finished, you just stop\nworking on it.\" This idea will be familiar to anyone who\nhas worked on software.Morale is another reason that it's hard to design something\nfor an unsophisticated user. It's hard to stay interested in\nsomething you don't like yourself. To make something \ngood, you have to be thinking, \"wow, this is really great,\"\nnot \"what a piece of shit; those fools will love it.\"Design means making things for humans. But it's not just the\nuser who's human. The designer is human too.Notice all this time I've been talking about \"the designer.\"\nDesign usually has to be under the control of a single person to\nbe any good. And yet it seems to be possible for several people\nto collaborate on a research project. This seems to\nme one of the most interesting differences between research and\ndesign.There have been famous instances of collaboration in the arts,\nbut most of them seem to have been cases of molecular bonding rather\nthan nuclear fusion. In an opera it's common for one person to\nwrite the libretto and another to write the music. And during the Renaissance, \njourneymen from northern\nEurope were often employed to do the landscapes in the\nbackgrounds of Italian paintings. But these aren't true collaborations.\nThey're more like examples of Robert Frost's\n\"good fences make good neighbors.\" You can stick instances\nof good design together, but within each individual project,\none person has to be in control.I'm not saying that good design requires that one person think\nof everything. There's nothing more valuable than the advice\nof someone whose judgement you trust. But after the talking is\ndone, the decision about what to do has to rest with one person.Why is it that research can be done by collaborators and \ndesign can't? This is an interesting question. I don't \nknow the answer. Perhaps,\nif design and research converge, the best research is also\ngood design, and in fact can't be done by collaborators.\nA lot of the most famous scientists seem to have worked alone.\nBut I don't know enough to say whether there\nis a pattern here. It could be simply that many famous scientists\nworked when collaboration was less common.Whatever the story is in the sciences, true collaboration\nseems to be vanishingly rare in the arts. Design by committee is a\nsynonym for bad design. Why is that so? Is there some way to\nbeat this limitation?I'm inclined to think there isn't-- that good design requires\na dictator. One reason is that good design has to \nbe all of a piece. Design is not just for humans, but\nfor individual humans. If a design represents an idea that \nfits in one person's head, then the idea will fit in the user's\nhead too.Related:" }, { "path": "data/PaulGrahamEssays/determination.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nSeptember 2009Like all investors, we spend a lot of time trying to learn how to\npredict which startups will succeed. We probably spend more time\nthinking about it than most, because we invest the earliest.\nPrediction is usually all we have to rely on.We learned quickly that the most important predictor of success is\ndetermination. At first we thought it might be intelligence.\nEveryone likes to believe that's what makes startups succeed. It\nmakes a better story that a company won because its founders were\nso smart. The PR people and reporters who spread such stories\nprobably believe them themselves. But while it certainly helps to\nbe smart, it's not the deciding factor. There are plenty of people\nas smart as Bill Gates who achieve nothing.In most domains, talent is overrated compared to determination—partly\nbecause it makes a better story, partly because it gives onlookers\nan excuse for being lazy, and partly because after a while determination\nstarts to look like talent.I can't think of any field in which determination is overrated, but\nthe relative importance of determination and talent probably do\nvary somewhat. Talent probably matters more in types of work that\nare purer, in the sense that one is solving mostly a single type\nof problem instead of many different types. I suspect determination\nwould not take you as far in math as it would in, say, organized\ncrime.I don't mean to suggest by this comparison that types of work that\ndepend more on talent are always more admirable. Most people would\nagree it's more admirable to be good at math than memorizing long\nstrings of digits, even though the latter depends more on natural\nability.Perhaps one reason people believe startup founders win by being\nsmarter is that intelligence does matter more in technology startups\nthan it used to in earlier types of companies. You probably do\nneed to be a bit smarter to dominate Internet search than you had\nto be to dominate railroads or hotels or newspapers. And that's\nprobably an ongoing trend. But even in the highest of high tech\nindustries, success still depends more on determination than brains.If determination is so important, can we isolate its components?\nAre some more important than others? Are there some you can\ncultivate?The simplest form of determination is sheer willfulness. When you\nwant something, you must have it, no matter what.A good deal of willfulness must be inborn, because it's common to\nsee families where one sibling has much more of it than another.\nCircumstances can alter it, but at the high end of the scale, nature\nseems to be more important than nurture. Bad circumstances can\nbreak the spirit of a strong-willed person, but I don't think there's\nmuch you can do to make a weak-willed person stronger-willed.Being strong-willed is not enough, however. You also have to be\nhard on yourself. Someone who was strong-willed but self-indulgent\nwould not be called determined. Determination implies your willfulness\nis balanced by discipline.That word balance is a significant one. The more willful you are,\nthe more disciplined you have to be. The stronger your will, the\nless anyone will be able to argue with you except yourself. And\nsomeone has to argue with you, because everyone has base impulses,\nand if you have more will than discipline you'll just give into\nthem and end up on a local maximum like drug addiction.We can imagine will and discipline as two fingers squeezing a\nslippery melon seed. The harder they squeeze, the further the seed\nflies, but they must both squeeze equally or the seed spins off\nsideways.If this is true it has interesting implications, because discipline\ncan be cultivated, and in fact does tend to vary quite a lot in the\ncourse of an individual's life. If determination is effectively\nthe product of will and discipline, then you can become more\ndetermined by being more disciplined.\n[1]Another consequence of the melon seed model is that the more willful\nyou are, the more dangerous it is to be undisciplined. There seem\nto be plenty of examples to confirm that. In some very energetic\npeople's lives you see something like wing flutter, where they\nalternate between doing great work and doing absolutely nothing.\nExternally this would look a lot like bipolar disorder.The melon seed model is inaccurate in at least one respect, however:\nit's static. In fact the dangers of indiscipline increase with\ntemptation. Which means, interestingly, that determination tends\nto erode itself. If you're sufficiently determined to achieve great\nthings, this will probably increase the number of temptations around\nyou. Unless you become proportionally more disciplined, willfulness\nwill then get the upper hand, and your achievement will revert to\nthe mean.That's why Shakespeare's Caesar thought thin men so dangerous. They weren't\ntempted by the minor perquisites of power.The melon seed model implies it's possible to be too disciplined.\nIs it? I think there probably are people whose willfulness is\ncrushed down by excessive discipline, and who would achieve more\nif they weren't so hard on themselves. One reason the young sometimes\nsucceed where the old fail is that they don't realize how incompetent\nthey are. This lets them do a kind of deficit spending. When they\nfirst start working on something, they overrate their achievements.\nBut that gives them confidence to keep working, and their performance\nimproves. Whereas someone clearer-eyed would see their initial\nincompetence for what it was, and perhaps be discouraged from\ncontinuing.There's one other major component of determination: ambition. If\nwillfulness and discipline are what get you to your destination,\nambition is how you choose it.I don't know if it's exactly right to say that ambition is a component\nof determination, but they're not entirely orthogonal. It would\nseem a misnomer if someone said they were very determined to do\nsomething trivially easy.And fortunately ambition seems to be quite malleable; there's a lot\nyou can do to increase it. Most people don't know how ambitious\nto be, especially when they're young. They don't know what's hard,\nor what they're capable of. And this problem is exacerbated by\nhaving few peers. Ambitious people are rare, so if everyone is\nmixed together randomly, as they tend to be early in people's lives,\nthen the ambitious ones won't have many ambitious peers. When you\ntake people like this and put them together with other ambitious\npeople, they bloom like dying plants given water. Probably most\nambitious people are starved for the sort of encouragement they'd\nget from ambitious peers, whatever their age.\n[2]Achievements also tend to increase your ambition. With each step\nyou gain confidence to stretch further next time.So here in sum is how determination seems to work: it consists of\nwillfulness balanced with discipline, aimed by ambition. And\nfortunately at least two of these three qualities can be cultivated.\nYou may be able to increase your strength of will somewhat; you can\ndefinitely learn self-discipline; and almost everyone is practically\nmalnourished when it comes to ambition.I feel like I understand determination a bit better now. But only\na bit: willfulness, discipline, and ambition are all concepts almost\nas complicated as determination.\n[3]Note too that determination and talent are not the whole story.\nThere's a third factor in achievement: how much you like the work.\nIf you really love working on something,\nyou don't need determination to drive you; it's what you'd do anyway.\nBut most types of work have aspects one doesn't like, because most\ntypes of work consist of doing things for other people, and it's\nvery unlikely that the tasks imposed by their needs will happen to\nalign exactly with what you want to do.Indeed, if you want to create the most wealth,\nthe way to do it is to focus more on their needs than your interests,\nand make up the difference with determination.Notes[1]\nLoosely speaking. What I'm claiming with the melon seed model\nis more like determination is proportionate to wd^m - k|w - d|^n,\nwhere w is will and d discipline.[2]\nWhich means one of the best ways to help a society generally\nis to create events and institutions that bring ambitious\npeople together. It's like pulling the control rods out of a\nreactor: the energy they emit encourages other ambitious people,\ninstead of being absorbed by the normal people they're usually\nsurrounded with.Conversely, it's probably a mistake to do as some European countries\nhave done and try to ensure none of your universities is significantly\nbetter than the others.[3]\nFor example, willfulness clearly has two subcomponents,\nstubbornness and energy. The first alone yields someone who's\nstubbornly inert. The second alone yields someone flighty.\nAs willful people get older or otherwise lose their energy, they\ntend to become merely stubborn.\nThanks to Sam Altman, Jessica Livingston, and Robert Morris\nfor reading drafts of this." }, { "path": "data/PaulGrahamEssays/die.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nAugust 2007(This is a talk I gave at the last \nY Combinator dinner of the summer. \nUsually we don't have a speaker at the last dinner; it's more of\na party. But it seemed worth spoiling the atmosphere if I could\nsave some of the startups from\npreventable deaths. So at the last minute I cooked up this rather\ngrim talk. I didn't mean this as an essay; I wrote it down\nbecause I only had two hours before dinner and think fastest while\nwriting.)\nA couple days ago I told a reporter that we expected about a third\nof the companies we funded to succeed. Actually I was being\nconservative. I'm hoping it might be as much as a half. Wouldn't\nit be amazing if we could achieve a 50% success rate?Another way of saying that is that half of you are going to die. Phrased\nthat way, it doesn't sound good at all. In fact, it's kind of weird\nwhen you think about it, because our definition of success is that\nthe founders get rich. If half the startups we fund succeed, then\nhalf of you are going to get rich and the other half are going to\nget nothing.If you can just avoid dying, you get rich. That sounds like a joke,\nbut it's actually a pretty good description of what happens in a\ntypical startup. It certainly describes what happened in Viaweb.\nWe avoided dying till we got rich.It was really close, too. When we were visiting Yahoo to talk about\nbeing acquired, we had to interrupt everything and borrow one of\ntheir conference rooms to talk down an investor who was about to\nback out of a new funding round we needed to stay alive. So even\nin the middle of getting rich we were fighting off the grim reaper.You may have heard that quote about luck consisting of opportunity\nmeeting preparation. You've now done the preparation. The work\nyou've done so far has, in effect, put you in a position to get\nlucky: you can now get rich by not letting your company die. That's\nmore than most people have. So let's talk about how not to die.We've done this five times now, and we've seen a bunch of startups\ndie. About 10 of them so far. We don't know exactly what happens\nwhen they die, because they generally don't die loudly and heroically.\nMostly they crawl off somewhere and die.For us the main indication of impending doom is when we don't hear\nfrom you. When we haven't heard from, or about, a startup for a\ncouple months, that's a bad sign. If we send them an email asking\nwhat's up, and they don't reply, that's a really bad sign. So far\nthat is a 100% accurate predictor of death.Whereas if a startup regularly does new deals and releases and\neither sends us mail or shows up at YC events, they're probably\ngoing to live.I realize this will sound naive, but maybe the linkage works in\nboth directions. Maybe if you can arrange that we keep hearing\nfrom you, you won't die.That may not be so naive as it sounds. You've probably noticed\nthat having dinners every Tuesday with us and the other founders\ncauses you to get more done than you would otherwise, because every\ndinner is a mini Demo Day. Every dinner is a kind of a deadline.\nSo the mere constraint of staying in regular contact with us will\npush you to make things happen, because otherwise you'll be embarrassed\nto tell us that you haven't done anything new since the last time\nwe talked.If this works, it would be an amazing hack. It would be pretty\ncool if merely by staying in regular contact with us you could get\nrich. It sounds crazy, but there's a good chance that would work.A variant is to stay in touch with other YC-funded startups. There\nis now a whole neighborhood of them in San Francisco. If you move\nthere, the peer pressure that made you work harder all summer will\ncontinue to operate.When startups die, the official cause of death is always either\nrunning out of money or a critical founder bailing. Often the two\noccur simultaneously. But I think the underlying cause is usually\nthat they've become demoralized. You rarely hear of a startup\nthat's working around the clock doing deals and pumping out new\nfeatures, and dies because they can't pay their bills and their ISP\nunplugs their server.Startups rarely die in mid keystroke. So keep typing!If so many startups get demoralized and fail when merely by hanging\non they could get rich, you have to assume that running a startup\ncan be demoralizing. That is certainly true. I've been there, and\nthat's why I've never done another startup. The low points in a\nstartup are just unbelievably low. I bet even Google had moments\nwhere things seemed hopeless.Knowing that should help. If you know it's going to feel terrible\nsometimes, then when it feels terrible you won't think \"ouch, this\nfeels terrible, I give up.\" It feels that way for everyone. And\nif you just hang on, things will probably get better. The metaphor\npeople use to describe the way a startup feels is at least a roller\ncoaster and not drowning. You don't just sink and sink; there are\nups after the downs.Another feeling that seems alarming but is in fact normal in a\nstartup is the feeling that what you're doing isn't working. The\nreason you can expect to feel this is that what you do probably\nwon't work. Startups almost never get it right the first time.\nMuch more commonly you launch something, and no one cares. Don't\nassume when this happens that you've failed. That's normal for\nstartups. But don't sit around doing nothing. Iterate.I like Paul Buchheit's suggestion of trying to make something that\nat least someone really loves. As long as you've made something\nthat a few users are ecstatic about, you're on the right track. It\nwill be good for your morale to have even a handful of users who\nreally love you, and startups run on morale. But also it\nwill tell you what to focus on. What is it about you that they\nlove? Can you do more of that? Where can you find more people who\nlove that sort of thing? As long as you have some core of users\nwho love you, all you have to do is expand it. It may take a while,\nbut as long as you keep plugging away, you'll win in the end. Both\nBlogger and Delicious did that. Both took years to succeed. But\nboth began with a core of fanatically devoted users, and all Evan\nand Joshua had to do was grow that core incrementally. \nWufoo is\non the same trajectory now.So when you release something and it seems like no one cares, look\nmore closely. Are there zero users who really love you, or is there\nat least some little group that does? It's quite possible there\nwill be zero. In that case, tweak your product and try again.\nEvery one of you is working on a space that contains at least one\nwinning permutation somewhere in it. If you just keep trying,\nyou'll find it.Let me mention some things not to do. The number one thing not to\ndo is other things. If you find yourself saying a sentence that\nends with \"but we're going to keep working on the startup,\" you are\nin big trouble. Bob's going to grad school, but we're going to\nkeep working on the startup. We're moving back to Minnesota, but\nwe're going to keep working on the startup. We're taking on some\nconsulting projects, but we're going to keep working on the startup.\nYou may as well just translate these to \"we're giving up on the\nstartup, but we're not willing to admit that to ourselves,\" because\nthat's what it means most of the time. A startup is so hard that\nworking on it can't be preceded by \"but.\"In particular, don't go to graduate school, and don't start other\nprojects. Distraction is fatal to startups. Going to (or back to)\nschool is a huge predictor of death because in addition to the\ndistraction it gives you something to say you're doing. If you're\nonly doing a startup, then if the startup fails, you fail. If\nyou're in grad school and your startup fails, you can say later \"Oh\nyeah, we had this startup on the side when I was in grad school,\nbut it didn't go anywhere.\"You can't use euphemisms like \"didn't go anywhere\" for something\nthat's your only occupation. People won't let you.One of the most interesting things we've discovered from working\non Y Combinator is that founders are more motivated by the fear of\nlooking bad than by the hope of getting millions of dollars. So\nif you want to get millions of dollars, put yourself in a position\nwhere failure will be public and humiliating.When we first met the founders of \nOctopart, they seemed very smart,\nbut not a great bet to succeed, because they didn't seem especially\ncommitted. One of the two founders was still in grad school. It\nwas the usual story: he'd drop out if it looked like the startup\nwas taking off. Since then he has not only dropped out of grad\nschool, but appeared full length in \nNewsweek \nwith the word \"Billionaire\"\nprinted across his chest. He just cannot fail now. Everyone he\nknows has seen that picture. Girls who dissed him in high school\nhave seen it. His mom probably has it on the fridge. It would be\nunthinkably humiliating to fail now. At this point he is committed\nto fight to the death.I wish every startup we funded could appear in a Newsweek article\ndescribing them as the next generation of billionaires, because\nthen none of them would be able to give up. The success rate would\nbe 90%. I'm not kidding.When we first knew the Octoparts they were lighthearted, cheery\nguys. Now when we talk to them they seem grimly determined. The\nelectronic parts distributors are trying to squash them to keep\ntheir monopoly pricing. (If it strikes you as odd that people still\norder electronic parts out of thick paper catalogs in 2007, there's\na reason for that. The distributors want to prevent the transparency\nthat comes from having prices online.) I feel kind of bad that\nwe've transformed these guys from lighthearted to grimly determined.\nBut that comes with the territory. If a startup succeeds, you get\nmillions of dollars, and you don't get that kind of money just by\nasking for it. You have to assume it takes some amount of pain.And however tough things get for the Octoparts, I predict they'll\nsucceed. They may have to morph themselves into something totally\ndifferent, but they won't just crawl off and die. They're smart;\nthey're working in a promising field; and they just cannot give up.All of you guys already have the first two. You're all smart and\nworking on promising ideas. Whether you end up among the living\nor the dead comes down to the third ingredient, not giving up.So I'll tell you now: bad shit is coming. It always is in a startup.\nThe odds of getting from launch to liquidity without some kind of\ndisaster happening are one in a thousand. So don't get demoralized.\nWhen the disaster strikes, just say to yourself, ok, this was what\nPaul was talking about. What did he say to do? Oh, yeah. Don't\ngive up." }, { "path": "data/PaulGrahamEssays/diff.txt", "content": "December 2001 (rev. May 2002)\n\n(This article came about in response to some questions on\nthe LL1 mailing list. It is now\nincorporated in Revenge of the Nerds.)When McCarthy designed Lisp in the late 1950s, it was\na radical departure from existing languages,\nthe most important of which was Fortran.Lisp embodied nine new ideas:\n1. Conditionals. A conditional is an if-then-else\nconstruct. We take these for granted now. They were \ninvented\nby McCarthy in the course of developing Lisp. \n(Fortran at that time only had a conditional\ngoto, closely based on the branch instruction in the \nunderlying hardware.) McCarthy, who was on the Algol committee, got\nconditionals into Algol, whence they spread to most other\nlanguages.2. A function type. In Lisp, functions are first class \nobjects-- they're a data type just like integers, strings,\netc, and have a literal representation, can be stored in variables,\ncan be passed as arguments, and so on.3. Recursion. Recursion existed as a mathematical concept\nbefore Lisp of course, but Lisp was the first programming language to support\nit. (It's arguably implicit in making functions first class\nobjects.)4. A new concept of variables. In Lisp, all variables\nare effectively pointers. Values are what\nhave types, not variables, and assigning or binding\nvariables means copying pointers, not what they point to.5. Garbage-collection.6. Programs composed of expressions. Lisp programs are \ntrees of expressions, each of which returns a value. \n(In some Lisps expressions\ncan return multiple values.) This is in contrast to Fortran\nand most succeeding languages, which distinguish between\nexpressions and statements.It was natural to have this\ndistinction in Fortran because (not surprisingly in a language\nwhere the input format was punched cards) the language was\nline-oriented. You could not nest statements. And\nso while you needed expressions for math to work, there was\nno point in making anything else return a value, because\nthere could not be anything waiting for it.This limitation\nwent away with the arrival of block-structured languages,\nbut by then it was too late. The distinction between\nexpressions and statements was entrenched. It spread from \nFortran into Algol and thence to both their descendants.When a language is made entirely of expressions, you can\ncompose expressions however you want. You can say either\n(using Arc syntax)(if foo (= x 1) (= x 2))or(= x (if foo 1 2))7. A symbol type. Symbols differ from strings in that\nyou can test equality by comparing a pointer.8. A notation for code using trees of symbols.9. The whole language always available. \nThere is\nno real distinction between read-time, compile-time, and runtime.\nYou can compile or run code while reading, read or run code\nwhile compiling, and read or compile code at runtime.Running code at read-time lets users reprogram Lisp's syntax;\nrunning code at compile-time is the basis of macros; compiling\nat runtime is the basis of Lisp's use as an extension\nlanguage in programs like Emacs; and reading at runtime\nenables programs to communicate using s-expressions, an\nidea recently reinvented as XML.\nWhen Lisp was first invented, all these ideas were far\nremoved from ordinary programming practice, which was\ndictated largely by the hardware available in the late 1950s.Over time, the default language, embodied\nin a succession of popular languages, has\ngradually evolved toward Lisp. 1-5 are now widespread.\n6 is starting to appear in the mainstream.\nPython has a form of 7, though there doesn't seem to be\nany syntax for it. \n8, which (with 9) is what makes Lisp macros\npossible, is so far still unique to Lisp,\nperhaps because (a) it requires those parens, or something \njust as bad, and (b) if you add that final increment of power, \nyou can no \nlonger claim to have invented a new language, but only\nto have designed a new dialect of Lisp ; -)Though useful to present-day programmers, it's\nstrange to describe Lisp in terms of its\nvariation from the random expedients other languages\nadopted. That was not, probably, how McCarthy\nthought of it. Lisp wasn't designed to fix the mistakes\nin Fortran; it came about more as the byproduct of an\nattempt to axiomatize computation." }, { "path": "data/PaulGrahamEssays/disagree.txt", "content": "March 2008The web is turning writing into a conversation. Twenty years ago,\nwriters wrote and readers read. The web lets readers respond, and\nincreasingly they do—in comment threads, on forums, and in their\nown blog posts.Many who respond to something disagree with it. That's to be\nexpected. Agreeing tends to motivate people less than disagreeing.\nAnd when you agree there's less to say. You could expand on something\nthe author said, but he has probably already explored the\nmost interesting implications. When you disagree you're entering\nterritory he may not have explored.The result is there's a lot more disagreeing going on, especially\nmeasured by the word. That doesn't mean people are getting angrier.\nThe structural change in the way we communicate is enough to account\nfor it. But though it's not anger that's driving the increase in\ndisagreement, there's a danger that the increase in disagreement\nwill make people angrier. Particularly online, where it's easy to\nsay things you'd never say face to face.If we're all going to be disagreeing more, we should be careful to\ndo it well. What does it mean to disagree well? Most readers can\ntell the difference between mere name-calling and a carefully\nreasoned refutation, but I think it would help to put names on the\nintermediate stages. So here's an attempt at a disagreement\nhierarchy:\nDH0. Name-calling.This is the lowest form of disagreement, and probably also the most\ncommon. We've all seen comments like this:\n\n u r a fag!!!!!!!!!!\n\nBut it's important to realize that more articulate name-calling has\njust as little weight. A comment like\n\n The author is a self-important dilettante.\n\nis really nothing more than a pretentious version of \"u r a fag.\"\nDH1. Ad Hominem.An ad hominem attack is not quite as weak as mere name-calling. It\nmight actually carry some weight. For example, if a senator wrote\nan article saying senators' salaries should be increased, one could\nrespond:\n\n Of course he would say that. He's a senator.\n\nThis wouldn't refute the author's argument, but it may at least be\nrelevant to the case. It's still a very weak form of disagreement,\nthough. If there's something wrong with the senator's argument,\nyou should say what it is; and if there isn't, what difference does\nit make that he's a senator?Saying that an author lacks the authority to write about a topic\nis a variant of ad hominem—and a particularly useless sort, because\ngood ideas often come from outsiders. The question is whether the\nauthor is correct or not. If his lack of authority caused him to\nmake mistakes, point those out. And if it didn't, it's not a\nproblem.\nDH2. Responding to Tone.The next level up we start to see responses to the writing, rather\nthan the writer. The lowest form of these is to disagree with the\nauthor's tone. E.g.\n\n I can't believe the author dismisses intelligent design in such\n a cavalier fashion.\n\nThough better than attacking the author, this is still a weak form\nof disagreement. It matters much more whether the author is wrong\nor right than what his tone is. Especially since tone is so hard\nto judge. Someone who has a chip on their shoulder about some topic\nmight be offended by a tone that to other readers seemed neutral.So if the worst thing you can say about something is to criticize\nits tone, you're not saying much. Is the author flippant, but\ncorrect? Better that than grave and wrong. And if the author is\nincorrect somewhere, say where.DH3. Contradiction.In this stage we finally get responses to what was said, rather\nthan how or by whom. The lowest form of response to an argument\nis simply to state the opposing case, with little or no supporting\nevidence.This is often combined with DH2 statements, as in:\n\n I can't believe the author dismisses intelligent design in such\n a cavalier fashion. Intelligent design is a legitimate scientific\n theory.\n\nContradiction can sometimes have some weight. Sometimes merely\nseeing the opposing case stated explicitly is enough to see that\nit's right. But usually evidence will help.DH4. Counterargument.At level 4 we reach the first form of convincing disagreement:\ncounterargument. Forms up to this point can usually be ignored as\nproving nothing. Counterargument might prove something. The problem\nis, it's hard to say exactly what.Counterargument is contradiction plus reasoning and/or evidence.\nWhen aimed squarely at the original argument, it can be convincing.\nBut unfortunately it's common for counterarguments to be aimed at\nsomething slightly different. More often than not, two people\narguing passionately about something are actually arguing about two\ndifferent things. Sometimes they even agree with one another, but\nare so caught up in their squabble they don't realize it.There could be a legitimate reason for arguing against something\nslightly different from what the original author said: when you\nfeel they missed the heart of the matter. But when you do that,\nyou should say explicitly you're doing it.DH5. Refutation.The most convincing form of disagreement is refutation. It's also\nthe rarest, because it's the most work. Indeed, the disagreement\nhierarchy forms a kind of pyramid, in the sense that the higher you\ngo the fewer instances you find.To refute someone you probably have to quote them. You have to\nfind a \"smoking gun,\" a passage in whatever you disagree with that\nyou feel is mistaken, and then explain why it's mistaken. If you\ncan't find an actual quote to disagree with, you may be arguing\nwith a straw man.While refutation generally entails quoting, quoting doesn't necessarily\nimply refutation. Some writers quote parts of things they disagree\nwith to give the appearance of legitimate refutation, then follow\nwith a response as low as DH3 or even DH0.DH6. Refuting the Central Point.The force of a refutation depends on what you refute. The most\npowerful form of disagreement is to refute someone's central point.Even as high as DH5 we still sometimes see deliberate dishonesty,\nas when someone picks out minor points of an argument and refutes\nthose. Sometimes the spirit in which this is done makes it more\nof a sophisticated form of ad hominem than actual refutation. For\nexample, correcting someone's grammar, or harping on minor mistakes\nin names or numbers. Unless the opposing argument actually depends\non such things, the only purpose of correcting them is to\ndiscredit one's opponent.Truly refuting something requires one to refute its central point,\nor at least one of them. And that means one has to commit explicitly\nto what the central point is. So a truly effective refutation would\nlook like:\n\n The author's main point seems to be x. As he says:\n\n \n\n But this is wrong for the following reasons...\n\nThe quotation you point out as mistaken need not be the actual\nstatement of the author's main point. It's enough to refute something\nit depends upon.\nWhat It MeansNow we have a way of classifying forms of disagreement. What good\nis it? One thing the disagreement hierarchy doesn't give us is\na way of picking a winner. DH levels merely describe the form of\na statement, not whether it's correct. A DH6 response could still\nbe completely mistaken.But while DH levels don't set a lower bound on the convincingness\nof a reply, they do set an upper bound. A DH6 response might be\nunconvincing, but a DH2 or lower response is always unconvincing.The most obvious advantage of classifying the forms of disagreement\nis that it will help people to evaluate what they read. In particular,\nit will help them to see through intellectually dishonest arguments.\nAn eloquent speaker or writer can give the impression of vanquishing\nan opponent merely by using forceful words. In fact that is probably\nthe defining quality of a demagogue. By giving names to the different\nforms of disagreement, we give critical readers a pin for popping\nsuch balloons.Such labels may help writers too. Most intellectual dishonesty is\nunintentional. Someone arguing against the tone of something he\ndisagrees with may believe he's really saying something. Zooming\nout and seeing his current position on the disagreement hierarchy\nmay inspire him to try moving up to counterargument or refutation.But the greatest benefit of disagreeing well is not just that it\nwill make conversations better, but that it will make the people\nwho have them happier. If you study conversations, you find there\nis a lot more meanness down in DH1 than up in DH6. You don't have\nto be mean when you have a real point to make. In fact, you don't\nwant to. If you have something real to say, being mean just gets\nin the way.If moving up the disagreement hierarchy makes people less mean,\nthat will make most of them happier. Most people don't really enjoy\nbeing mean; they do it because they can't help it.\nThanks to Trevor Blackwell and Jessica Livingston for reading\ndrafts of this.Related:" }, { "path": "data/PaulGrahamEssays/disc.txt", "content": "January 2017Because biographies of famous scientists tend to \nedit out their mistakes, we underestimate the \ndegree of risk they were willing to take.\nAnd because anything a famous scientist did that\nwasn't a mistake has probably now become the\nconventional wisdom, those choices don't\nseem risky either.Biographies of Newton, for example, understandably focus\nmore on physics than alchemy or theology.\nThe impression we get is that his unerring judgment\nled him straight to truths no one else had noticed.\nHow to explain all the time he spent on alchemy\nand theology? Well, smart people are often kind of\ncrazy.But maybe there is a simpler explanation. Maybe\nthe smartness and the craziness were not as separate\nas we think. Physics seems to us a promising thing\nto work on, and alchemy and theology obvious wastes\nof time. But that's because we know how things\nturned out. In Newton's day the three problems \nseemed roughly equally promising. No one knew yet\nwhat the payoff would be for inventing what we\nnow call physics; if they had, more people would \nhave been working on it. And alchemy and theology\nwere still then in the category Marc Andreessen would \ndescribe as \"huge, if true.\"Newton made three bets. One of them worked. But \nthey were all risky." }, { "path": "data/PaulGrahamEssays/discover.txt", "content": "September 2009When meeting people you don't know very well, the convention is\nto seem extra friendly. You smile and say \"pleased to meet you,\"\nwhether you are or not. There's nothing dishonest about this.\nEveryone knows that these little social lies aren't meant\nto be taken literally, just as everyone knows that \n\"Can you pass the salt?\" is only grammatically a question.I'm perfectly willing to smile and say \"pleased to meet you\"\nwhen meeting new people. But there is another set of \ncustoms for being ingratiating in print that are not so\nharmless.The reason there's a convention of being ingratiating in print\nis that most essays are written to persuade.\nAnd as any politician could tell\nyou, the way to persuade people is not just to baldly state the\nfacts. You have to add a spoonful of sugar to make the medicine\ngo down.For example, a politician announcing the cancellation of \na government program will not merely say \"The\nprogram is canceled.\" That would seem offensively\ncurt. Instead he'll spend most of his time talking about the\nnoble effort made by the people who worked on it.The reason these conventions are more dangerous is that they\ninteract with the ideas. Saying \"pleased to meet you\" is just\nsomething you prepend to a conversation, but the sort of spin \nadded by politicians is woven through it. We're starting to\nmove from social lies to real lies.Here's an example of a paragraph from an essay I wrote about\nlabor unions. As written,\nit tends to offend people who like unions.\n\n People who think the labor movement was the creation of heroic\n union organizers have a problem to explain: why are unions shrinking\n now? The best they can do is fall back on the default explanation\n of people living in fallen civilizations. Our ancestors were\n giants. The workers of the early twentieth century must have had\n a moral courage that's lacking today.\n\nNow here's the same paragraph rewritten to please instead of\noffending them:\n\n Early union organizers made heroic sacrifices to improve conditions\n for workers. But though\n labor unions are shrinking now, it's not because present union\n leaders are any less courageous. An employer couldn't get away\n with hiring thugs to beat up union leaders today, but if they\n did, I see no reason to believe today's union leaders would shrink\n from the challenge. So I think it would be a mistake to attribute\n the decline of unions to some kind of decline in the people who\n run them. Early union leaders were heroic, certainly, but we\n should not suppose that if unions have declined, it's because\n present union leaders are somehow inferior. The cause must be\n external.\n[1]\n\nIt makes the same point: that it can't have been the personal\nqualities of early union organizers that made unions successful,\nbut must have been some external factor, or otherwise present-day\nunion leaders would have to be inferior people. But written this\nway it seems like a defense of present-day union organizers rather\nthan an attack on early ones. That makes it more persuasive to\npeople who like unions, because it seems sympathetic to their cause.I believe everything I wrote in the second version. Early union\nleaders did make heroic sacrifices. And\npresent union leaders probably would rise to the occasion if\nnecessary. People tend to; I'm skeptical about the idea of \"the\ngreatest generation.\" \n[2]If I believe everything I said in the second version, why didn't I\nwrite it that way? Why offend people needlessly?Because I'd rather offend people than pander to them, \nand if you write about controversial topics you have to choose one or the other. The degree of\ncourage of past or present union leaders is beside the point; all\nthat matters for the argument is that they're the same.\nBut if you want to please\npeople who are mistaken, you can't simply tell the truth. You're\nalways going to have to add some sort of padding to protect their\nmisconceptions from bumping against reality.Most writers do. Most writers write to persuade, if only out of\nhabit or politeness. But I don't write to persuade; I write to\nfigure out. I write to persuade a hypothetical perfectly unbiased\nreader.Since the custom is to write to persuade the actual reader, someone\nwho doesn't will seem arrogant. In fact, worse than arrogant: since\nreaders are used to essays that try to please someone, an essay\nthat displeases one side in a dispute reads as an attempt to pander\nto the other. To a lot of pro-union readers, the first paragraph\nsounds like the sort of thing a right-wing radio talk show host\nwould say to stir up his followers. But it's not. Something that\ncurtly contradicts one's beliefs can be hard to distinguish from a\npartisan attack on them, but though they can end up in the same\nplace they come from different sources.Would it be so bad to add a few extra words, to make people feel\nbetter? Maybe not. Maybe I'm excessively attached to conciseness.\nI write code the same way I write essays, \nmaking pass after pass\nlooking for anything I can cut. But I have a legitimate reason for\ndoing this. You don't know what the ideas are until you get them\ndown to the fewest words. \n[3]The danger of the second paragraph\nis not merely that it's longer. It's that you start to lie to\nyourself. The ideas start to get mixed together with the spin\nyou've added to get them past the readers' misconceptions.I think the goal of an essay should be to discover \nsurprising things. That's my goal, at least.\nAnd most surprising means most different from what people currently\nbelieve. So writing to persuade and writing to discover are\ndiametrically opposed. The more your conclusions disagree with\nreaders' present beliefs, the more effort you'll have to expend on\nselling your ideas rather than having them. As you accelerate,\nthis drag increases, till eventually you reach a point where 100%\nof your energy is devoted to overcoming it and you can't go any\nfaster.It's hard enough to overcome one's own misconceptions without having\nto think about how to get the resulting ideas past other people's.\nI worry that if I wrote to persuade, I'd start to shy away unconsciously\nfrom ideas I knew would be hard to sell. When I notice something\nsurprising, it's usually very faint at first. There's nothing more\nthan a slight stirring of discomfort. I don't want anything to get\nin the way of noticing it consciously.\nNotes[1]\nI had a strange feeling of being back in high school writing\nthis. To get a good grade you had to both write the sort of pious\ncrap you were expected to, but also seem to be writing with conviction.\nThe solution was a kind of method acting. It was revoltingly\nfamiliar to slip back into it.[2]\nExercise for the reader:\nrephrase that thought to please the same people the first version\nwould offend.[3]\nCome to think of it, there is one way in which I deliberately\npander to readers, because it doesn't change the number of words:\nI switch person. This flattering distinction seems so natural to\nthe average reader that they probably don't notice even when I\nswitch in mid-sentence, though you tend to notice when it's done\nas conspicuously as this.Thanks to Jessica Livingston and Robert Morris\nfor reading drafts of this.Note: An earlier version of this essay began by talking\nabout why people dislike Michael Arrington. I now believe that\nwas mistaken, and that most people don't dislike him for the\nsame reason I did when I first met him, but simply because\nhe writes about controversial things." }, { "path": "data/PaulGrahamEssays/distraction.txt", "content": "Note: The strategy described at the end of this essay didn't work.\nIt would work for a while, and then I'd gradually find myself\nusing the Internet on my work computer. I'm trying other\nstrategies now, but I think this time I'll wait till I'm sure\nthey work before writing about them.May 2008Procrastination feeds on distractions. Most people find it\nuncomfortable just to sit and do nothing; you avoid work by doing\nsomething else.So one way to beat procrastination is to starve it of distractions.\nBut that's not as straightforward as it sounds, because there are\npeople working hard to distract you. Distraction is not a static\nobstacle that you avoid like you might avoid a rock in the road.\nDistraction seeks you out.Chesterfield described dirt as matter out of place. Distracting\nis, similarly, desirable at the wrong time. And technology is\ncontinually being refined to produce more and more desirable things.\nWhich means that as we learn to avoid one class of distractions,\nnew ones constantly appear, like drug-resistant bacteria.Television, for example, has after 50 years of refinement reached\nthe point where it's like visual crack. I realized when I was 13\nthat TV was addictive, so I stopped watching it. But I read recently\n that the average American watches \n4 hours \nof TV a day. A quarter\nof their life.TV is in decline now, but only because people have found even more\naddictive ways of wasting time. And what's especially dangerous\nis that many happen at your computer. This is no accident. An\never larger percentage of office workers sit in front of computers\nconnected to the Internet, and distractions always evolve toward\nthe procrastinators.I remember when computers were, for me at least, exclusively for\nwork. I might occasionally dial up a server to get mail or ftp\nfiles, but most of the time I was offline. All I could do was write\nand program. Now I feel as if someone snuck a television onto my\ndesk. Terribly addictive things are just a click away. Run into\nan obstacle in what you're working on? Hmm, I wonder what's new\nonline. Better check.After years of carefully avoiding classic time sinks like TV, games,\nand Usenet, I still managed to fall prey to distraction, because\nI didn't realize that it evolves. Something that used to be safe,\nusing the Internet, gradually became more and more dangerous. Some\ndays I'd wake up, get a cup of tea and check the news, then check\nemail, then check the news again, then answer a few emails, then\nsuddenly notice it was almost lunchtime and I hadn't gotten any real\nwork done. And this started to happen more and more often.It took me surprisingly long to realize how distracting the Internet\nhad become, because the problem was intermittent. I ignored it the\nway you let yourself ignore a bug that only appears intermittently. When\nI was in the middle of a project, distractions weren't really a\nproblem. It was when I'd finished one project and was deciding\nwhat to do next that they always bit me.Another reason it was hard to notice the danger of this new type\nof distraction was that social customs hadn't yet caught up with\nit. If I'd spent a whole morning sitting on a sofa watching TV,\nI'd have noticed very quickly. That's a known danger sign, like\ndrinking alone. But using the Internet still looked and felt a \nlot like work.Eventually, though, it became clear that the Internet had become so much\nmore distracting that I had to start treating it differently.\nBasically, I had to add a new application to my list of known time\nsinks: Firefox.* * *The problem is a hard one to solve because most people still need\nthe Internet for some things. If you drink too much, you can solve\nthat problem by stopping entirely. But you can't solve the problem\nof overeating by stopping eating. I couldn't simply avoid the \nInternet entirely, as I'd done with previous time sinks.At first I tried rules. For example, I'd tell myself I was only\ngoing to use the Internet twice a day. But these schemes never\nworked for long. Eventually something would come up that required\nme to use it more than that. And then I'd gradually slip back\ninto my old ways.Addictive things have to be treated as if they were sentient\nadversaries—as if there were a little man in your head always\ncooking up the most plausible arguments for doing whatever you're\ntrying to stop doing. If you leave a path to it, he'll find it.The key seems to be visibility. The biggest ingredient in most bad habits\nis denial. So you have to make it so that you can't merely slip\ninto doing the thing you're trying to avoid. It has to set off\nalarms.Maybe in the long term the right answer for dealing with Internet\ndistractions will be \nsoftware that watches and controls them. But\nin the meantime I've found a more drastic solution that definitely\nworks: to set up a separate computer for using the Internet.I now leave wifi turned off on my main computer except when I need\nto transfer a file or edit a web page, and I have a separate laptop \non the other side\nof the room that I use to check mail or browse the web. (Irony of\nironies, it's the computer Steve Huffman wrote Reddit on. When\nSteve and Alexis auctioned off their old laptops for charity, I\nbought them for the Y Combinator museum.)My rule is that I can spend as much time online as I want, as long\nas I do it on that computer. And this turns out to be enough. When\nI have to sit on the other side of the room to check email or browse\nthe web, I become much more aware of it. Sufficiently aware, in\nmy case at least, that it's hard to spend more than about an hour\na day online.And my main computer is now freed for work. If you try this trick,\nyou'll probably be struck by how different it feels when your\ncomputer is disconnected from the Internet. It was alarming to me\nhow foreign it felt to sit in front of a computer that could\nonly be used for work, because that showed how much time I must\nhave been wasting.Wow. All I can do at this computer is work. Ok, I better work\nthen.That's the good part. Your old bad habits now help you to work.\nYou're used to sitting in front of that computer for hours at a\ntime. But you can't browse the web or check email now. What are\nyou going to do? You can't just sit there. So you start working." }, { "path": "data/PaulGrahamEssays/divergence.txt", "content": "December 2008(I originally wrote this at the request of a company producing\na report about entrepreneurship. Unfortunately after reading it\nthey decided it was too controversial to include.)\nVC funding will probably dry up somewhat during the present recession,\nlike it usually does in bad times. But this time the result may\nbe different. This time the number of new startups may not decrease.\nAnd that could be dangerous for VCs.When VC funding dried up after the Internet Bubble, startups dried\nup too. There were not a lot of new startups being founded in\n2003. But startups aren't tied to VC the way they were 10 years\nago. It's now possible for VCs and startups to diverge. And if\nthey do, they may not reconverge once the economy gets better.The reason startups no longer depend so much on VCs is one that\neveryone in the startup business knows by now: it has gotten much\ncheaper to start a startup. There are four main reasons: Moore's\nlaw has made hardware cheap; open source has made software free;\nthe web has made marketing and distribution free; and more powerful\nprogramming languages mean development teams can be smaller. These\nchanges have pushed the cost of starting a startup down into the\nnoise. In a lot of startups—probaby most startups funded by\nY Combinator—the biggest expense is simply the founders'\nliving expenses. We've had startups that were profitable on revenues\nof $3000 a month.$3000 is insignificant as revenues go. Why should anyone care about\na startup making $3000 a month? Because, although insignificant\nas revenue, this amount of money can change a startup's\nfunding situation completely.Someone running a startup is always calculating in the back of their\nmind how much \"runway\" they have—how long they have till the\nmoney in the bank runs out and they either have to be profitable,\nraise more money, or go out of business. Once you cross the threshold\nof profitability, however low, your runway becomes infinite. It's\na qualitative change, like the stars turning into lines and\ndisappearing when the Enterprise accelerates to warp speed. Once\nyou're profitable you don't need investors' money. And because\nInternet startups have become so cheap to run, the threshold of\nprofitability can be trivially low. Which means many Internet\nstartups don't need VC-scale investments anymore. For many startups,\nVC funding has, in the language of VCs, gone from a must-have to a\nnice-to-have.This change happened while no one was looking, and its effects have\nbeen largely masked so far. It was during the trough after the\nInternet Bubble that it became trivially cheap to start a startup,\nbut few realized it because startups were so out of fashion. When\nstartups came back into fashion, around 2005, investors were starting\nto write checks again. And while founders may not have needed VC\nmoney the way they used to, they were willing to take it if\noffered—partly because there was a tradition of startups\ntaking VC money, and partly because startups, like dogs, tend to\neat when given the opportunity. As long as VCs were writing checks,\nfounders were never forced to explore the limits of how little they\nneeded them. There were a few startups who hit these limits\naccidentally because of their unusual circumstances—most\nfamously 37signals, which hit the limit because they crossed into\nstartup land from the other direction: they started as a consulting\nfirm, so they had revenue before they had a product.VCs and founders are like two components that used to be bolted\ntogether. Around 2000 the bolt was removed. Because the components\nhave so far been subjected to the same forces, they still seem to\nbe joined together, but really one is just resting on the other.\nA sharp impact would make them fly apart. And the present recession\ncould be that impact.Because of Y Combinator's position at the extreme end of the spectrum,\nwe'd be the first to see signs of a separation between founders and\ninvestors, and we are in fact seeing it. For example, though the\nstock market crash does seem to have made investors more cautious,\nit doesn't seem to have had any effect on the number of people who\nwant to start startups. We take applications for funding every 6\nmonths. Applications for the current funding cycle closed on October\n17, well after the markets tanked, and even so we got a record\nnumber, up 40% from the same cycle a year before.Maybe things will be different a year from now, if the economy\ncontinues to get worse, but so far there is zero slackening of\ninterest among potential founders. That's different from the way\nthings felt in 2001. Then there was a widespread feeling among\npotential founders that startups were over, and that one should\njust go to grad school. That isn't happening this time, and part\nof the reason is that even in a bad economy it's not that hard to\nbuild something that makes $3000 a month. If investors stop writing\nchecks, who cares?We also see signs of a divergence between founders and investors\nin the attitudes of existing startups we've funded. I was talking\nto one recently that had a round fall through at the last minute\nover the sort of trifle that breaks deals when investors feel they\nhave the upper hand—over an uncertainty about whether the\nfounders had correctly filed their 83(b) forms, if you can believe\nthat. And yet this startup is obviously going to succeed: their\ntraffic and revenue graphs look like a jet taking off. So I asked\nthem if they wanted me to introduce them to more investors. To my\nsurprise, they said no—that they'd just spent four months\ndealing with investors, and they were actually a lot happier now\nthat they didn't have to. There was a friend they wanted to hire\nwith the investor money, and now they'd have to postpone that. But\notherwise they felt they had enough in the bank to make it to\nprofitability. To make sure, they were moving to a cheaper apartment.\nAnd in this economy I bet they got a good deal on it.I've detected this \"investors aren't worth the trouble\" vibe from\nseveral YC founders I've talked to recently. At least one startup\nfrom the most recent (summer) cycle may not even raise angel money,\nlet alone VC. Ticketstumbler\nmade it to profitability on Y Combinator's $15,000 investment and\nthey hope not to need more. This surprised even us. Although YC\nis based on the idea of it being cheap to start a startup, we never\nanticipated that founders would grow successful startups on nothing\nmore than YC funding.If founders decide VCs aren't worth the trouble, that could be bad\nfor VCs. When the economy bounces back in a few years and they're\nready to write checks again, they may find that founders have moved\non.There is a founder community just as there's a VC community. They\nall know one another, and techniques spread rapidly between them.\nIf one tries a new programming language or a new hosting provider\nand gets good results, 6 months later half of them are using it.\nAnd the same is true for funding. The current generation of founders\nwant to raise money from VCs, and Sequoia specifically, because\nLarry and Sergey took money from VCs, and Sequoia specifically.\nImagine what it would do to the VC business if the next hot company\ndidn't take VC at all.VCs think they're playing a zero sum game. In fact, it's not even\nthat. If you lose a deal to Benchmark, you lose that deal, but VC\nas an industry still wins. If you lose a deal to None, all VCs\nlose.This recession may be different from the one after the Internet\nBubble. This time founders may keep starting startups. And if\nthey do, VCs will have to keep writing checks, or they could become\nirrelevant.Thanks to Sam Altman, Trevor Blackwell, David Hornik, Jessica\nLivingston, Robert Morris, and Fred Wilson for reading drafts of\nthis." }, { "path": "data/PaulGrahamEssays/donate.txt", "content": "March 2021The secret curse of the nonprofit world is restricted donations.\nIf you haven't been involved with nonprofits, you may never have\nheard this phrase before. But if you have been, it probably made\nyou wince.Restricted donations mean donations where the donor limits what can\nbe done with the money. This is common with big donations, perhaps\nthe default. And yet it's usually a bad idea. Usually the way the\ndonor wants the money spent is not the way the nonprofit would have\nchosen. Otherwise there would have been no need to restrict the\ndonation. But who has a better understanding of where money needs\nto be spent, the nonprofit or the donor?If a nonprofit doesn't understand better than its donors where money\nneeds to be spent, then it's incompetent and you shouldn't be\ndonating to it at all.Which means a restricted donation is inherently suboptimal. It's\neither a donation to a bad nonprofit, or a donation for the wrong\nthings.There are a couple exceptions to this principle. One is when the\nnonprofit is an umbrella organization. It's reasonable to make a\nrestricted donation to a university, for example, because a university\nis only nominally a single nonprofit. Another exception is when the\ndonor actually does know as much as the nonprofit about where money\nneeds to be spent. The Gates Foundation, for example, has specific\ngoals and often makes restricted donations to individual nonprofits\nto accomplish them. But unless you're a domain expert yourself or\ndonating to an umbrella organization, your donation would do more\ngood if it were unrestricted.If restricted donations do less good than unrestricted ones, why\ndo donors so often make them? Partly because doing good isn't donors'\nonly motive. They often have other motives as well — to make a mark,\nor to generate good publicity\n[1],\nor to comply with regulations\nor corporate policies. Many donors may simply never have considered\nthe distinction between restricted and unrestricted donations. They\nmay believe that donating money for some specific purpose is just\nhow donation works. And to be fair, nonprofits don't try very hard\nto discourage such illusions. They can't afford to. People running\nnonprofits are almost always anxious about money. They can't afford\nto talk back to big donors.You can't expect candor in a relationship so asymmetric. So I'll\ntell you what nonprofits wish they could tell you. If you want to\ndonate to a nonprofit, donate unrestricted. If you trust them to\nspend your money, trust them to decide how.\nNote[1]\nUnfortunately restricted donations tend to generate more\npublicity than unrestricted ones. \"X donates money to build a school\nin Africa\" is not only more interesting than \"X donates money to Y\nnonprofit to spend as Y chooses,\" but also focuses more attention\non X.\nThanks to Chase Adam, Ingrid Bassett, Trevor Blackwell, and Edith\nElliot for reading drafts of this." }, { "path": "data/PaulGrahamEssays/ds.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nJuly 2013One of the most common types of advice we give at Y Combinator is\nto do things that don't scale. A lot of would-be founders believe\nthat startups either take off or don't. You build something, make\nit available, and if you've made a better mousetrap, people beat a\npath to your door as promised. Or they don't, in which case the\nmarket must not exist.\n[1]Actually startups take off because the founders make them take off.\nThere may be a handful that just grew by themselves, but usually\nit takes some sort of push to get them going. A good metaphor would\nbe the cranks that car engines had before they got electric starters.\nOnce the engine was going, it would keep going, but there was a\nseparate and laborious process to get it going.RecruitThe most common unscalable thing founders have to do at the start\nis to recruit users manually. Nearly all startups have to. You\ncan't wait for users to come to you. You have to go out and get\nthem.Stripe is one of the most successful startups we've funded, and the\nproblem they solved was an urgent one. If anyone could have sat\nback and waited for users, it was Stripe. But in fact they're\nfamous within YC for aggressive early user acquisition.Startups building things for other startups have a big pool of\npotential users in the other companies we've funded, and none took\nbetter advantage of it than Stripe. At YC we use the term \"Collison\ninstallation\" for the technique they invented. More diffident\nfounders ask \"Will you try our beta?\" and if the answer is yes,\nthey say \"Great, we'll send you a link.\" But the Collison brothers\nweren't going to wait. When anyone agreed to try Stripe they'd say\n\"Right then, give me your laptop\" and set them up on the spot.There are two reasons founders resist going out and recruiting users\nindividually. One is a combination of shyness and laziness. They'd\nrather sit at home writing code than go out and talk to a bunch of\nstrangers and probably be rejected by most of them. But for a\nstartup to succeed, at least one founder (usually the CEO) will\nhave to spend a lot of time on sales and marketing.\n[2]The other reason founders ignore this path is that the absolute\nnumbers seem so small at first. This can't be how the big, famous\nstartups got started, they think. The mistake they make is to\nunderestimate the power of compound growth. We encourage every\nstartup to measure their progress by weekly growth\nrate. If you have 100 users, you need to get 10 more next week\nto grow 10% a week. And while 110 may not seem much better than\n100, if you keep growing at 10% a week you'll be surprised how big\nthe numbers get. After a year you'll have 14,000 users, and after\n2 years you'll have 2 million.You'll be doing different things when you're acquiring users a\nthousand at a time, and growth has to slow down eventually. But\nif the market exists you can usually start by recruiting users\nmanually and then gradually switch to less manual methods. \n[3]Airbnb is a classic example of this technique. Marketplaces are\nso hard to get rolling that you should expect to take heroic measures\nat first. In Airbnb's case, these consisted of going door to door\nin New York, recruiting new users and helping existing ones improve\ntheir listings. When I remember the Airbnbs during YC, I picture\nthem with rolly bags, because when they showed up for tuesday dinners\nthey'd always just flown back from somewhere.FragileAirbnb now seems like an unstoppable juggernaut, but early on it\nwas so fragile that about 30 days of going out and engaging in\nperson with users made the difference between success and failure.That initial fragility was not a unique feature of Airbnb. Almost\nall startups are fragile initially. And that's one of the biggest\nthings inexperienced founders and investors (and reporters and\nknow-it-alls on forums) get wrong about them. They unconsciously\njudge larval startups by the standards of established ones. They're\nlike someone looking at a newborn baby and concluding \"there's no\nway this tiny creature could ever accomplish anything.\"It's harmless if reporters and know-it-alls dismiss your startup.\nThey always get things wrong. It's even ok if investors dismiss\nyour startup; they'll change their minds when they see growth. The\nbig danger is that you'll dismiss your startup yourself. I've seen\nit happen. I often have to encourage founders who don't see the\nfull potential of what they're building. Even Bill Gates made that\nmistake. He returned to Harvard for the fall semester after starting\nMicrosoft. He didn't stay long, but he wouldn't have returned at\nall if he'd realized Microsoft was going to be even a fraction of\nthe size it turned out to be. \n[4]The question to ask about an early stage startup is not \"is this\ncompany taking over the world?\" but \"how big could this company\nget if the founders did the right things?\" And the right things\noften seem both laborious and inconsequential at the time. Microsoft\ncan't have seemed very impressive when it was just a couple guys\nin Albuquerque writing Basic interpreters for a market of a few\nthousand hobbyists (as they were then called), but in retrospect\nthat was the optimal path to dominating microcomputer software.\nAnd I know Brian Chesky and Joe Gebbia didn't feel like they were\nen route to the big time as they were taking \"professional\" photos\nof their first hosts' apartments. They were just trying to survive.\nBut in retrospect that too was the optimal path to dominating a big\nmarket.How do you find users to recruit manually? If you build something\nto solve your own problems, then\nyou only have to find your peers, which is usually straightforward.\nOtherwise you'll have to make a more deliberate effort to locate\nthe most promising vein of users. The usual way to do that is to\nget some initial set of users by doing a comparatively untargeted\nlaunch, and then to observe which kind seem most enthusiastic, and\nseek out more like them. For example, Ben Silbermann noticed that\na lot of the earliest Pinterest users were interested in design,\nso he went to a conference of design bloggers to recruit users, and\nthat worked well. \n[5]DelightYou should take extraordinary measures not just to acquire users,\nbut also to make them happy. For as long as they could (which\nturned out to be surprisingly long), Wufoo sent each new user a\nhand-written thank you note. Your first users should feel that\nsigning up with you was one of the best choices they ever made.\nAnd you in turn should be racking your brains to think of new ways\nto delight them.Why do we have to teach startups this? Why is it counterintuitive\nfor founders? Three reasons, I think.One is that a lot of startup founders are trained as engineers,\nand customer service is not part of the training of engineers.\nYou're supposed to build things that are robust and elegant, not\nbe slavishly attentive to individual users like some kind of\nsalesperson. Ironically, part of the reason engineering is\ntraditionally averse to handholding is that its traditions date\nfrom a time when engineers were less powerful — when they were\nonly in charge of their narrow domain of building things, rather\nthan running the whole show. You can be ornery when you're Scotty,\nbut not when you're Kirk.Another reason founders don't focus enough on individual customers\nis that they worry it won't scale. But when founders of larval\nstartups worry about this, I point out that in their current state\nthey have nothing to lose. Maybe if they go out of their way to\nmake existing users super happy, they'll one day have too many to\ndo so much for. That would be a great problem to have. See if you\ncan make it happen. And incidentally, when it does, you'll find\nthat delighting customers scales better than you expected. Partly\nbecause you can usually find ways to make anything scale more than\nyou would have predicted, and partly because delighting customers\nwill by then have permeated your culture.I have never once seen a startup lured down a blind alley by trying\ntoo hard to make their initial users happy.But perhaps the biggest thing preventing founders from realizing\nhow attentive they could be to their users is that they've never\nexperienced such attention themselves. Their standards for customer\nservice have been set by the companies they've been customers of,\nwhich are mostly big ones. Tim Cook doesn't send you a hand-written\nnote after you buy a laptop. He can't. But you can. That's one\nadvantage of being small: you can provide a level of service no big\ncompany can. \n[6]Once you realize that existing conventions are not the upper bound\non user experience, it's interesting in a very pleasant way to think\nabout how far you could go to delight your users.ExperienceI was trying to think of a phrase to convey how extreme your attention\nto users should be, and I realized Steve Jobs had already done it:\ninsanely great. Steve wasn't just using \"insanely\" as a synonym\nfor \"very.\" He meant it more literally — that one should focus\non quality of execution to a degree that in everyday life would be\nconsidered pathological.All the most successful startups we've funded have, and that probably\ndoesn't surprise would-be founders. What novice founders don't get\nis what insanely great translates to in a larval startup. When\nSteve Jobs started using that phrase, Apple was already an established\ncompany. He meant the Mac (and its documentation and even\npackaging — such is the nature of obsession) should be insanely\nwell designed and manufactured. That's not hard for engineers to\ngrasp. It's just a more extreme version of designing a robust and\nelegant product.What founders have a hard time grasping (and Steve himself might\nhave had a hard time grasping) is what insanely great morphs into\nas you roll the time slider back to the first couple months of a\nstartup's life. It's not the product that should be insanely great,\nbut the experience of being your user. The product is just one\ncomponent of that. For a big company it's necessarily the dominant\none. But you can and should give users an insanely great experience\nwith an early, incomplete, buggy product, if you make up the\ndifference with attentiveness.Can, perhaps, but should? Yes. Over-engaging with early users is\nnot just a permissible technique for getting growth rolling. For\nmost successful startups it's a necessary part of the feedback loop\nthat makes the product good. Making a better mousetrap is not an\natomic operation. Even if you start the way most successful startups\nhave, by building something you yourself need, the first thing you\nbuild is never quite right. And except in domains with big penalties\nfor making mistakes, it's often better not to aim for perfection\ninitially. In software, especially, it usually works best to get\nsomething in front of users as soon as it has a quantum of utility,\nand then see what they do with it. Perfectionism is often an excuse\nfor procrastination, and in any case your initial model of users\nis always inaccurate, even if you're one of them. \n[7]The feedback you get from engaging directly with your earliest users\nwill be the best you ever get. When you're so big you have to\nresort to focus groups, you'll wish you could go over to your users'\nhomes and offices and watch them use your stuff like you did when\nthere were only a handful of them.FireSometimes the right unscalable trick is to focus on a deliberately\nnarrow market. It's like keeping a fire contained at first to get\nit really hot before adding more logs.That's what Facebook did. At first it was just for Harvard students.\nIn that form it only had a potential market of a few thousand people,\nbut because they felt it was really for them, a critical mass of\nthem signed up. After Facebook stopped being for Harvard students,\nit remained for students at specific colleges for quite a while.\nWhen I interviewed Mark Zuckerberg at Startup School, he said that\nwhile it was a lot of work creating course lists for each school,\ndoing that made students feel the site was their natural home.Any startup that could be described as a marketplace usually has\nto start in a subset of the market, but this can work for other\nstartups as well. It's always worth asking if there's a subset of\nthe market in which you can get a critical mass of users quickly.\n[8]Most startups that use the contained fire strategy do it unconsciously.\nThey build something for themselves and their friends, who happen\nto be the early adopters, and only realize later that they could\noffer it to a broader market. The strategy works just as well if\nyou do it unconsciously. The biggest danger of not being consciously\naware of this pattern is for those who naively discard part of it.\nE.g. if you don't build something for yourself and your friends,\nor even if you do, but you come from the corporate world and your\nfriends are not early adopters, you'll no longer have a perfect\ninitial market handed to you on a platter.Among companies, the best early adopters are usually other startups.\nThey're more open to new things both by nature and because, having\njust been started, they haven't made all their choices yet. Plus\nwhen they succeed they grow fast, and you with them. It was one\nof many unforeseen advantages of the YC model (and specifically of\nmaking YC big) that B2B startups now have an instant market of\nhundreds of other startups ready at hand.MerakiFor hardware startups there's a variant of\ndoing things that don't scale that we call \"pulling a Meraki.\"\nAlthough we didn't fund Meraki, the founders were Robert Morris's\ngrad students, so we know their history. They got started by doing\nsomething that really doesn't scale: assembling their routers\nthemselves.Hardware startups face an obstacle that software startups don't.\nThe minimum order for a factory production run is usually several\nhundred thousand dollars. Which can put you in a catch-22: without\na product you can't generate the growth you need to raise the money\nto manufacture your product. Back when hardware startups had to\nrely on investors for money, you had to be pretty convincing to\novercome this. The arrival of crowdfunding (or more precisely,\npreorders) has helped a lot. But even so I'd advise startups to\npull a Meraki initially if they can. That's what Pebble did. The\nPebbles \nassembled\n the first several hundred watches themselves. If\nthey hadn't gone through that phase, they probably wouldn't have\nsold $10 million worth of watches when they did go on Kickstarter.Like paying excessive attention to early customers, fabricating\nthings yourself turns out to be valuable for hardware startups.\nYou can tweak the design faster when you're the factory, and you\nlearn things you'd never have known otherwise. Eric Migicovsky of\nPebble said one of the things he learned was \"how valuable it was to\nsource good screws.\" Who knew?ConsultSometimes we advise founders of B2B startups to take over-engagement\nto an extreme, and to pick a single user and act as if they were\nconsultants building something just for that one user. The initial\nuser serves as the form for your mold; keep tweaking till you fit\ntheir needs perfectly, and you'll usually find you've made something\nother users want too. Even if there aren't many of them, there are\nprobably adjacent territories that have more. As long as you can\nfind just one user who really needs something and can act on that\nneed, you've got a toehold in making something people want, and\nthat's as much as any startup needs initially. \n[9]Consulting is the canonical example of work that doesn't scale.\nBut (like other ways of bestowing one's favors liberally) it's safe\nto do it so long as you're not being paid to. That's where companies\ncross the line. So long as you're a product company that's merely\nbeing extra attentive to a customer, they're very grateful even if\nyou don't solve all their problems. But when they start paying you\nspecifically for that attentiveness — when they start paying\nyou by the hour — they expect you to do everything.Another consulting-like technique for recruiting initially lukewarm\nusers is to use your software yourselves on their behalf. We\ndid that at Viaweb. When we approached merchants asking if they\nwanted to use our software to make online stores, some said no, but\nthey'd let us make one for them. Since we would do anything to get\nusers, we did. We felt pretty lame at the time. Instead of\norganizing big strategic e-commerce partnerships, we were trying\nto sell luggage and pens and men's shirts. But in retrospect it\nwas exactly the right thing to do, because it taught us how it would\nfeel to merchants to use our software. Sometimes the feedback loop\nwas near instantaneous: in the middle of building some merchant's\nsite I'd find I needed a feature we didn't have, so I'd spend a\ncouple hours implementing it and then resume building the site.ManualThere's a more extreme variant where you don't just use your software,\nbut are your software. When you only have a small number of users,\nyou can sometimes get away with doing by hand things that you plan\nto automate later. This lets you launch faster, and when you do\nfinally automate yourself out of the loop, you'll know exactly what\nto build because you'll have muscle memory from doing it yourself.When manual components look to the user like software, this technique\nstarts to have aspects of a practical joke. For example, the way\nStripe delivered \"instant\" merchant accounts to its first users was\nthat the founders manually signed them up for traditional merchant\naccounts behind the scenes.Some startups could be entirely manual at first. If you can find\nsomeone with a problem that needs solving and you can solve it\nmanually, go ahead and do that for as long as you can, and then\ngradually automate the bottlenecks. It would be a little frightening\nto be solving users' problems in a way that wasn't yet automatic,\nbut less frightening than the far more common case of having something\nautomatic that doesn't yet solve anyone's problems.BigI should mention one sort of initial tactic that usually doesn't\nwork: the Big Launch. I occasionally meet founders who seem to\nbelieve startups are projectiles rather than powered aircraft, and\nthat they'll make it big if and only if they're launched with\nsufficient initial velocity. They want to launch simultaneously\nin 8 different publications, with embargoes. And on a tuesday, of\ncourse, since they read somewhere that's the optimum day to launch\nsomething.It's easy to see how little launches matter. Think of some successful\nstartups. How many of their launches do you remember?\nAll you need from a launch is some initial core of users. How well\nyou're doing a few months later will depend more on how happy you\nmade those users than how many there were of them.\n[10]So why do founders think launches matter? A combination of solipsism\nand laziness. They think what they're building is so great that\neveryone who hears about it will immediately sign up. Plus it would\nbe so much less work if you could get users merely by broadcasting\nyour existence, rather than recruiting them one at a time. But\neven if what you're building really is great, getting users will\nalways be a gradual process — partly because great things\nare usually also novel, but mainly because users have other things\nto think about.Partnerships too usually don't work. They don't work for startups\nin general, but they especially don't work as a way to get growth\nstarted. It's a common mistake among inexperienced founders to\nbelieve that a partnership with a big company will be their big\nbreak. Six months later they're all saying the same thing: that\nwas way more work than we expected, and we ended up getting practically\nnothing out of it. \n[11]It's not enough just to do something extraordinary initially. You\nhave to make an extraordinary effort initially. Any strategy\nthat omits the effort — whether it's expecting a big launch to\nget you users, or a big partner — is ipso facto suspect.VectorThe need to do something unscalably laborious to get started is so\nnearly universal that it might be a good idea to stop thinking of\nstartup ideas as scalars. Instead we should try thinking of them\nas pairs of what you're going to build, plus the unscalable thing(s)\nyou're going to do initially to get the company going.It could be interesting to start viewing startup ideas this way,\nbecause now that there are two components you can try to be imaginative\nabout the second as well as the first. But in most cases the second\ncomponent will be what it usually is — recruit users manually\nand give them an overwhelmingly good experience — and the main\nbenefit of treating startups as vectors will be to remind founders\nthey need to work hard in two dimensions.\n[12]In the best case, both components of the vector contribute to your\ncompany's DNA: the unscalable things you have to do to get started\nare not merely a necessary evil, but change the company permanently\nfor the better. If you have to be aggressive about user acquisition\nwhen you're small, you'll probably still be aggressive when you're\nbig. If you have to manufacture your own hardware, or use your\nsoftware on users's behalf, you'll learn things you couldn't have\nlearned otherwise. And most importantly, if you have to work hard\nto delight users when you only have a handful of them, you'll keep\ndoing it when you have a lot.Notes[1]\nActually Emerson never mentioned mousetraps specifically. He\nwrote \"If a man has good corn or wood, or boards, or pigs, to sell,\nor can make better chairs or knives, crucibles or church organs,\nthan anybody else, you will find a broad hard-beaten road to his\nhouse, though it be in the woods.\"[2]\nThanks to Sam Altman for suggesting I make this explicit.\nAnd no, you can't avoid doing sales by hiring someone to do it for\nyou. You have to do sales yourself initially. Later you can hire\na real salesperson to replace you.[3]\nThe reason this works is that as you get bigger, your size\nhelps you grow. Patrick Collison wrote \"At some point, there was\na very noticeable change in how Stripe felt. It tipped from being\nthis boulder we had to push to being a train car that in fact had\nits own momentum.\"[4]\nOne of the more subtle ways in which YC can help founders\nis by calibrating their ambitions, because we know exactly how a\nlot of successful startups looked when they were just getting\nstarted.[5]\nIf you're building something for which you can't easily get\na small set of users to observe — e.g. enterprise software — and\nin a domain where you have no connections, you'll have to rely on\ncold calls and introductions. But should you even be working on\nsuch an idea?[6]\nGarry Tan pointed out an interesting trap founders fall into\nin the beginning. They want so much to seem big that they imitate\neven the flaws of big companies, like indifference to individual\nusers. This seems to them more \"professional.\" Actually it's\nbetter to embrace the fact that you're small and use whatever\nadvantages that brings.[7]\nYour user model almost couldn't be perfectly accurate, because\nusers' needs often change in response to what you build for them.\nBuild them a microcomputer, and suddenly they need to run spreadsheets\non it, because the arrival of your new microcomputer causes someone\nto invent the spreadsheet.[8]\nIf you have to choose between the subset that will sign up\nquickest and those that will pay the most, it's usually best to\npick the former, because those are probably the early adopters.\nThey'll have a better influence on your product, and they won't\nmake you expend as much effort on sales. And though they have less\nmoney, you don't need that much to maintain your target growth rate\nearly on.[9]\nYes, I can imagine cases where you could end up making\nsomething that was really only useful for one user. But those are\nusually obvious, even to inexperienced founders. So if it's not\nobvious you'd be making something for a market of one, don't worry\nabout that danger.[10]\nThere may even be an inverse correlation between launch\nmagnitude and success. The only launches I remember are famous\nflops like the Segway and Google Wave. Wave is a particularly\nalarming example, because I think it was actually a great idea that\nwas killed partly by its overdone launch.[11]\nGoogle grew big on the back of Yahoo, but that wasn't a\npartnership. Yahoo was their customer.[12]\nIt will also remind founders that an idea where the second\ncomponent is empty — an idea where there is nothing you can do\nto get going, e.g. because you have no way to find users to recruit\nmanually — is probably a bad idea, at least for those founders.Thanks to Sam Altman, Paul Buchheit, Patrick Collison, Kevin\nHale, Steven Levy, Jessica Livingston, Geoff Ralston, and Garry Tan for reading\ndrafts of this." }, { "path": "data/PaulGrahamEssays/early.txt", "content": "October 2020One of the biggest things holding people back from doing great work\nis the fear of making something lame. And this fear is not an\nirrational one. Many great projects go through a stage early on\nwhere they don't seem very impressive, even to their creators. You\nhave to push through this stage to reach the great work that lies\nbeyond. But many people don't. Most people don't even reach the\nstage of making something they're embarrassed by, let alone continue\npast it. They're too frightened even to start.Imagine if we could turn off the fear of making something lame.\nImagine how much more we'd do.Is there any hope of turning it off? I think so. I think the habits\nat work here are not very deeply rooted.Making new things is itself a new thing for us as a species. It has\nalways happened, but till the last few centuries it happened so\nslowly as to be invisible to individual humans. And since we didn't\nneed customs for dealing with new ideas, we didn't develop any.We just don't have enough experience with early versions of ambitious\nprojects to know how to respond to them. We judge them as we would\njudge more finished work, or less ambitious projects. We don't\nrealize they're a special case.Or at least, most of us don't. One reason I'm confident we can do\nbetter is that it's already starting to happen. There are already\na few places that are living in the future in this respect. Silicon\nValley is one of them: an unknown person working on a strange-sounding\nidea won't automatically be dismissed the way they would back home.\nIn Silicon Valley, people have learned how dangerous that is.The right way to deal with new ideas is to treat them as a challenge\nto your imagination — not just to have lower standards, but to\nswitch polarity entirely, from listing \nthe reasons an idea won't\nwork to trying to think of ways it could. That's what I do when I\nmeet people with new ideas. I've become quite good at it, but I've\nhad a lot of practice. Being a partner at Y Combinator means being\npractically immersed in strange-sounding ideas proposed by unknown\npeople. Every six months you get thousands of new ones thrown at\nyou and have to sort through them, knowing that in a world with a\npower-law distribution of outcomes, it will be painfully obvious\nif you miss the needle in this haystack. Optimism becomes\nurgent.But I'm hopeful that, with time, this kind of optimism can become\nwidespread enough that it becomes a social custom, not just a trick\nused by a few specialists. It is after all an extremely lucrative\ntrick, and those tend to spread quickly.Of course, inexperience is not the only reason people are too harsh\non early versions of ambitious projects. They also do it to seem\nclever. And in a field where the new ideas are risky, like startups,\nthose who dismiss them are in fact more likely to be right. Just\nnot when their predictions are \nweighted by outcome.But there is another more sinister reason people dismiss new ideas.\nIf you try something ambitious, many of those around you will hope,\nconsciously or unconsciously, that you'll fail. They worry that if\nyou try something ambitious and succeed, it will put you above them.\nIn some countries this is not just an individual failing but part\nof the national culture.I wouldn't claim that people in Silicon Valley overcome these\nimpulses because they're morally better. \n[1]\nThe reason many hope\nyou'll succeed is that they hope to rise with you. For investors\nthis incentive is particularly explicit. They want you to succeed\nbecause they hope you'll make them rich in the process. But many\nother people you meet can hope to benefit in some way from your\nsuccess. At the very least they'll be able to say, when you're\nfamous, that they've known you since way back.But even if Silicon Valley's encouraging attitude\nis rooted in self-interest, it has over time actually grown into a\nsort of benevolence. Encouraging startups has been practiced for\nso long that it has become a custom. Now it just seems that that's\nwhat one does with startups.Maybe Silicon Valley is too optimistic. Maybe it's too easily fooled\nby impostors. Many less optimistic journalists want to believe that.\nBut the lists of impostors they cite are suspiciously short, and\nplagued with asterisks. \n[2] If you use revenue as the test, Silicon\nValley's optimism seems better tuned than the rest of the world's.\nAnd because it works, it will spread.There's a lot more to new ideas than new startup ideas, of course.\nThe fear of making something lame holds people back in every field.\nBut Silicon Valley shows how quickly customs can evolve to support\nnew ideas. And that in turn proves that dismissing new ideas is not\nso deeply rooted in human nature that it can't be unlearnt.\n___________\nUnfortunately, if you want to do new things, you'll face a force\nmore powerful than other people's skepticism: your own skepticism.\nYou too will judge your early work too harshly. How do you avoid\nthat?This is a difficult problem, because you don't want to completely\neliminate your horror of making something lame. That's what steers\nyou toward doing good work. You just want to turn it off temporarily,\nthe way a painkiller temporarily turns off pain.People have already discovered several techniques that work. Hardy\nmentions two in A Mathematician's Apology:\n\n Good work is not done by \"humble\" men. It is one of the first\n duties of a professor, for example, in any subject, to exaggerate\n a little both the importance of his subject and his importance\n in it.\n\nIf you overestimate the importance of what you're working on, that\nwill compensate for your mistakenly harsh judgment of your initial\nresults. If you look at something that's 20% of the way to a goal\nworth 100 and conclude that it's 10% of the way to a goal worth\n200, your estimate of its expected value is correct even though\nboth components are wrong.It also helps, as Hardy suggests, to be slightly overconfident.\nI've noticed in many fields that the most successful people are\nslightly overconfident. On the face of it this seems implausible.\nSurely it would be optimal to have exactly the right estimate of\none's abilities. How could it be an advantage to be mistaken?\nBecause this error compensates for other sources of error in the\nopposite direction: being slightly overconfident armors you against\nboth other people's skepticism and your own.Ignorance has a similar effect. It's safe to make the mistake of\njudging early work as finished work if you're a sufficiently lax\njudge of finished work. I doubt it's possible to cultivate this\nkind of ignorance, but empirically it's a real advantage, especially\nfor the young.Another way to get through the lame phase of ambitious projects is\nto surround yourself with the right people — to create an eddy in\nthe social headwind. But it's not enough to collect people who are\nalways encouraging. You'd learn to discount that. You need colleagues\nwho can actually tell an ugly duckling from a baby swan. The people\nbest able to do this are those working on similar projects of their\nown, which is why university departments and research labs work so\nwell. You don't need institutions to collect colleagues. They\nnaturally coalesce, given the chance. But it's very much worth\naccelerating this process by seeking out other people trying to do\nnew things.Teachers are in effect a special case of colleagues. It's a teacher's\njob both to see the promise of early work and to encourage you to\ncontinue. But teachers who are good at this are unfortunately quite\nrare, so if you have the opportunity to learn from one, take it.\n[3]For some it might work to rely on sheer discipline: to tell yourself\nthat you just have to press on through the initial crap phase and\nnot get discouraged. But like a lot of \"just tell yourself\" advice,\nthis is harder than it sounds. And it gets still harder as you get\nolder, because your standards rise. The old do have one compensating\nadvantage though: they've been through this before.It can help if you focus less on where you are and more on the rate\nof change. You won't worry so much about doing bad work if you can\nsee it improving. Obviously the faster it improves, the easier this\nis. So when you start something new, it's good if you can spend a\nlot of time on it. That's another advantage of being young: you\ntend to have bigger blocks of time.Another common trick is to start by considering new work to be of\na different, less exacting type. To start a painting saying that\nit's just a sketch, or a new piece of software saying that it's\njust a quick hack. Then you judge your initial results by a lower\nstandard. Once the project is rolling you can sneakily convert it\nto something more.\n[4]This will be easier if you use a medium that lets you work fast and\ndoesn't require too much commitment up front. It's easier to convince\nyourself that something is just a sketch when you're drawing in a\nnotebook than when you're carving stone. Plus you get initial results\nfaster. \n[5]\n[6]It will be easier to try out a risky project if you think of it as\na way to learn and not just as a way to make something. Then even\nif the project truly is a failure, you'll still have gained by it.\nIf the problem is sharply enough defined, failure itself is\nknowledge: if the theorem you're trying to prove turns out to\nbe false, or you use a structural member of a certain size and\nit fails under stress, you've learned something, even if it\nisn't what you wanted to learn.\n[7]One motivation that works particularly well for me is curiosity.\nI like to try new things just to see how they'll turn out. We started\nY Combinator in this spirit, and it was one of main things that\nkept me going while I was working on \nBel. Having worked for so long\nwith various dialects of Lisp, I was very curious to see what its\ninherent shape was: what you'd end up with if you followed the\naxiomatic approach all the way.But it's a bit strange that you have to play mind games with yourself\nto avoid being discouraged by lame-looking early efforts. The thing\nyou're trying to trick yourself into believing is in fact the truth.\nA lame-looking early version of an ambitious project truly is more\nvaluable than it seems. So the ultimate solution may be to teach\nyourself that.One way to do it is to study the histories of people who've\ndone great work. What were they thinking early on? What was the\nvery first thing they did? It can sometimes be hard to get an\naccurate answer to this question, because people are often embarrassed\nby their earliest work and make little effort to publish it. (They\ntoo misjudge it.) But when you can get an accurate picture of the\nfirst steps someone made on the path to some great work, they're\noften pretty feeble.\n[8]Perhaps if you study enough such cases, you can teach yourself to\nbe a better judge of early work. Then you'll be immune both to other\npeople's skepticism and your own fear of making something lame.\nYou'll see early work for what it is.Curiously enough, the solution to the problem of judging early work\ntoo harshly is to realize that our attitudes toward it are themselves\nearly work. Holding everything to the same standard is a crude\nversion 1. We're already evolving better customs, and we can already\nsee signs of how big the payoff will be.\nNotes[1]\nThis assumption may be too conservative. There is some evidence\nthat historically the Bay Area has attracted a \ndifferent sort of person than, \nsay, New York City.[2]\nOne of their great favorites is Theranos. But the most conspicuous\nfeature of Theranos's cap table is the absence of Silicon Valley\nfirms. Journalists were fooled by Theranos, but Silicon Valley\ninvestors weren't.[3]\nI made two mistakes about teachers when I was younger. I\ncared more about professors' research than their reputations as\nteachers, and I was also wrong about what it meant to be a good\nteacher. I thought it simply meant to be good at explaining things.[4]\nPatrick Collison points out that you can go past treating\nsomething as a hack in the sense of a prototype and onward to the\nsense of the word that means something closer to a practical joke:\n\n I think there may be something related to being a hack that can\n be powerful — the idea of making the tenuousness and implausibility\n a feature. \"Yes, it's a bit ridiculous, right? I'm just trying\n to see how far such a naive approach can get.\" YC seemed to me\n to have this characteristic.\n\n[5]\nMuch of the advantage of switching from physical to digital\nmedia is not the software per se but that it lets you start something\nnew with little upfront commitment.[6]\nJohn Carmack adds:\n\n The value of a medium without a vast gulf between the early work\n and the final work is exemplified in game mods. The original\n Quake game was a golden age for mods, because everything was very\n flexible, but so crude due to technical limitations, that quick\n hacks to try out a gameplay idea weren't all that far from the\n official game. Many careers were born from that, but as the\n commercial game quality improved over the years, it became almost\n a full time job to make a successful mod that would be appreciated\n by the community. This was dramatically reversed with Minecraft\n and later Roblox, where the entire esthetic of the experience was\n so explicitly crude that innovative gameplay concepts became the\n overriding value. These \"crude\" game mods by single authors are\n now often bigger deals than massive professional teams' work.\n\n[7]\nLisa Randall suggests that we\n\n treat new things as experiments. That way there's no such thing\n as failing, since you learn something no matter what. You treat\n it like an experiment in the sense that if it really rules something\n out, you give up and move on, but if there's some way to vary it\n to make it work better, go ahead and do that\n\n[8]\nMichael Nielsen points out that the internet has made this\neasier, because you can see programmers' first commits, musicians'\nfirst videos, and so on.Thanks to Trevor Blackwell, John Carmack, Patrick Collison, Jessica\nLivingston, Michael Nielsen, and Lisa Randall for reading drafts\nof this." }, { "path": "data/PaulGrahamEssays/earnest.txt", "content": "December 2020Jessica and I have certain words that have special significance\nwhen we're talking about startups. The highest compliment we can\npay to founders is to describe them as \"earnest.\" This is not by\nitself a guarantee of success. You could be earnest but incapable.\nBut when founders are both formidable (another of our words) and\nearnest, they're as close to unstoppable as you get.Earnestness sounds like a boring, even Victorian virtue. It seems\na bit of an anachronism that people in Silicon Valley would care\nabout it. Why does this matter so much?When you call someone earnest, you're making a statement about their\nmotives. It means both that they're doing something for the right\nreasons, and that they're trying as hard as they can. If we imagine\nmotives as vectors, it means both the direction and the magnitude\nare right. Though these are of course related: when people are doing\nsomething for the right reasons, they try harder.\n[1]The reason motives matter so much in Silicon Valley is that so many\npeople there have the wrong ones. Starting a successful startup\nmakes you rich and famous. So a lot of the people trying to start\nthem are doing it for those reasons. Instead of what? Instead of\ninterest in the problem for its own sake. That is the root of\nearnestness. \n[2]It's also the hallmark of a nerd. Indeed, when people describe\nthemselves as \"x nerds,\" what they mean is that they're interested\nin x for its own sake, and not because it's cool to be interested\nin x, or because of what they can get from it. They're saying they\ncare so much about x that they're willing to sacrifice seeming cool\nfor its sake.A genuine interest \nin something is a very powerful motivator — for\nsome people, the most powerful motivator of all.\n[3]\nWhich is why\nit's what Jessica and I look for in founders. But as well as being\na source of strength, it's also a source of vulnerability. Caring\nconstrains you. The earnest can't easily reply in kind to mocking\nbanter, or put on a cool facade of nihil admirari. They care too\nmuch. They are doomed to be the straight man. That's a real\ndisadvantage in your \nteenage years, \nwhen mocking banter and nihil\nadmirari often have the upper hand. But it becomes an advantage\nlater.It's a commonplace now that the kids who were \nnerds in high school\nbecome the cool kids' bosses later on. But people misunderstand why\nthis happens. It's not just because the nerds are smarter, but also\nbecause they're more earnest. When the problems get harder than the\nfake ones you're given in high school, caring about them starts to\nmatter.Does it always matter? Do the earnest always win? Not always. It\nprobably doesn't matter much in politics, or in crime, or in certain\ntypes of business that are similar to crime, like gambling, personal\ninjury law, patent trolling, and so on. Nor does it matter in\nacademic fields at the more \nbogus end of the spectrum. And though\nI don't know enough to say for sure, it may not matter in some kinds\nof humor: it may be possible to be completely cynical and still be\nvery funny.\n[4]Looking at the list of fields I mentioned, there's an obvious\npattern. Except possibly for humor, these are all types of work I'd\navoid like the plague. So that could be a useful heuristic for\ndeciding which fields to work in: how much does earnestness matter?\nWhich can in turn presumably be inferred from the prevalence of\nnerds at the top.Along with \"nerd,\" another word that tends to be associated with\nearnestness is \"naive.\" The earnest often seem naive. It's not\njust that they don't have the motives other people have. They often\ndon't fully grasp that such motives exist. Or they may know\nintellectually that they do, but because they don't feel them, they\nforget about them.\n[5]It works to be slightly naive not just about motives but also,\nbelieve it or not, about the problems you're working on. Naive\noptimism can compensate for the bit rot that \nrapid change causes\nin established beliefs. You plunge into some problem saying \"How\nhard can it be?\", and then after solving it you learn that it was\ntill recently insoluble.Naivete is an obstacle for anyone who wants to seem sophisticated,\nand this is one reason would-be intellectuals find it so difficult\nto understand Silicon Valley. It hasn't been safe for such people\nto use the word \"earnest\" outside scare quotes since Oscar Wilde\nwrote \"The Importance of Being Earnest\" in 1895. And yet when you\nzoom in on Silicon Valley, right into \nJessica Livingston's brain,\nthat's what her x-ray vision\nis seeking out in founders. Earnestness!\nWho'd have guessed? Reporters literally can't believe it when\nfounders making piles of money say that they started their companies\nto make the world better. The situation seems made for mockery.\nHow can these founders be so naive as not to realize how implausible\nthey sound?Though those asking this question don't realize it, that's not a\nrhetorical question.A lot of founders are faking it, of course, particularly the smaller\nfry, and the soon to be smaller fry. But not all of them. There are\na significant number of founders who really are interested in the\nproblem they're solving mainly for its own sake.Why shouldn't there be? We have no difficulty believing that people\nwould be interested in history or math or even old bus tickets for\ntheir own sake. Why can't there be people interested in self-driving\ncars or social networks for their own sake? When you look at the\nquestion from this side, it seems obvious there would be. And isn't\nit likely that having a deep interest in something would be a source\nof great energy and resilience? It is in every other field.The question really is why we have a blind spot about business.\nAnd the answer to that is obvious if you know enough history. For\nmost of history, making large amounts of money has not been very\nintellectually interesting. In preindustrial times it was never far\nfrom robbery, and some areas of business still retain that character,\nexcept using lawyers instead of soldiers.But there are other areas of business where the work is genuinely\ninteresting. Henry Ford got to spend much of his time working on\ninteresting technical problems, and for the last several decades\nthe trend in that direction has been accelerating. It's much easier\nnow to make a lot of money by working on something you're interested\nin than it was 50 years ago. \nAnd that, rather than how fast they\ngrow, may be the most important change that startups represent.\nThough indeed, the fact that the work is genuinely interesting is\na big part of why it gets done so fast.\n[6]Can you imagine a more important change than one in the relationship\nbetween intellectual curiosity and money? These are two of the most\npowerful forces in the world, and in my lifetime they've become\nsignificantly more aligned. How could you not be fascinated to watch\nsomething like this happening in real time?I meant this essay to be about earnestness generally, and now I've\ngone and talked about startups again. But I suppose at least it\nserves as an example of an x nerd in the wild.Notes[1]\nIt's interesting how many different ways there are not to\nbe earnest: to be cleverly cynical, to be superficially brilliant,\nto be conspicuously virtuous, to be cool, to be sophisticated, to\nbe orthodox, to be a snob, to bully, to pander, to be on the make.\nThis pattern suggests that earnestness is not one end of a continuum,\nbut a target one can fall short of in multiple dimensions.Another thing I notice about this list is that it sounds like a\nlist of the ways people behave on Twitter. Whatever else social\nmedia is, it's a vivid catalogue of ways not to be earnest.[2]\nPeople's motives are as mixed in Silicon Valley as anywhere\nelse. Even the founders motivated mostly by money tend to be at\nleast somewhat interested in the problem they're solving, and even\nthe founders most interested in the problem they're solving also\nlike the idea of getting rich. But there's great variation in the\nrelative proportions of different founders' motivations.And when I talk about \"wrong\" motives, I don't mean morally wrong.\nThere's nothing morally wrong with starting a startup to make money.\nI just mean that those startups don't do as well.[3]\nThe most powerful motivator for most people is probably family.\nBut there are some for whom intellectual curiosity comes first. In\nhis (wonderful) autobiography, Paul Halmos says explicitly that for\na mathematician, math must come before anything else, including\nfamily. Which at least implies that it did for him.[4]\nInterestingly, just as the word \"nerd\" implies earnestness even\nwhen used as a metaphor, the word \"politics\" implies the opposite.\nIt's not only in actual politics that earnestness seems to be a\nhandicap, but also in office politics and academic politics.[5]\nIt's a bigger social error to seem naive in most European\ncountries than it is in America, and this may be one of subtler\nreasons startups are less common there. Founder culture is completely\nat odds with sophisticated cynicism.The most earnest part of Europe is Scandinavia, and not surprisingly\nthis is also the region with the highest number of successful\nstartups per capita.[6]\nMuch of business is schleps, and probably always will be. But\neven being a professor is largely schleps. It would be interesting\nto collect statistics about the schlep ratios of different jobs,\nbut I suspect they'd rarely be less than 30%.Thanks to Trevor Blackwell, Patrick Collison, Suhail Doshi, Jessica\nLivingston, Mattias Ljungman, Harj Taggar, and Kyle Vogt for reading\ndrafts of this." }, { "path": "data/PaulGrahamEssays/ecw.txt", "content": "December 2014If the world were static, we could have monotonically increasing\nconfidence in our beliefs. The more (and more varied) experience\na belief survived, the less likely it would be false. Most people\nimplicitly believe something like this about their opinions. And\nthey're justified in doing so with opinions about things that don't\nchange much, like human nature. But you can't trust your opinions\nin the same way about things that change, which could include\npractically everything else.When experts are wrong, it's often because they're experts on an\nearlier version of the world.Is it possible to avoid that? Can you protect yourself against\nobsolete beliefs? To some extent, yes. I spent almost a decade\ninvesting in early stage startups, and curiously enough protecting\nyourself against obsolete beliefs is exactly what you have to do\nto succeed as a startup investor. Most really good startup ideas\nlook like bad ideas at first, and many of those look bad specifically\nbecause some change in the world just switched them from bad to\ngood. I spent a lot of time learning to recognize such ideas, and\nthe techniques I used may be applicable to ideas in general.The first step is to have an explicit belief in change. People who\nfall victim to a monotonically increasing confidence in their\nopinions are implicitly concluding the world is static. If you\nconsciously remind yourself it isn't, you start to look for change.Where should one look for it? Beyond the moderately useful\ngeneralization that human nature doesn't change much, the unfortunate\nfact is that change is hard to predict. This is largely a tautology\nbut worth remembering all the same: change that matters usually\ncomes from an unforeseen quarter.So I don't even try to predict it. When I get asked in interviews\nto predict the future, I always have to struggle to come up with\nsomething plausible-sounding on the fly, like a student who hasn't\nprepared for an exam.\n[1]\nBut it's not out of laziness that I haven't\nprepared. It seems to me that beliefs about the future are so\nrarely correct that they usually aren't worth the extra rigidity\nthey impose, and that the best strategy is simply to be aggressively\nopen-minded. Instead of trying to point yourself in the right\ndirection, admit you have no idea what the right direction is, and\ntry instead to be super sensitive to the winds of change.It's ok to have working hypotheses, even though they may constrain\nyou a bit, because they also motivate you. It's exciting to chase\nthings and exciting to try to guess answers. But you have to be\ndisciplined about not letting your hypotheses harden into anything\nmore.\n[2]I believe this passive m.o. works not just for evaluating new ideas\nbut also for having them. The way to come up with new ideas is not\nto try explicitly to, but to try to solve problems and simply not\ndiscount weird hunches you have in the process.The winds of change originate in the unconscious minds of domain\nexperts. If you're sufficiently expert in a field, any weird idea\nor apparently irrelevant question that occurs to you is ipso facto\nworth exploring. \n[3]\n Within Y Combinator, when an idea is described\nas crazy, it's a compliment—in fact, on average probably a\nhigher compliment than when an idea is described as good.Startup investors have extraordinary incentives for correcting\nobsolete beliefs. If they can realize before other investors that\nsome apparently unpromising startup isn't, they can make a huge\namount of money. But the incentives are more than just financial.\nInvestors' opinions are explicitly tested: startups come to them\nand they have to say yes or no, and then, fairly quickly, they learn\nwhether they guessed right. The investors who say no to a Google\n(and there were several) will remember it for the rest of their\nlives.Anyone who must in some sense bet on ideas rather than merely\ncommenting on them has similar incentives. Which means anyone who\nwants such incentives can have them, by turning their comments into\nbets: if you write about a topic in some fairly durable and public\nform, you'll find you worry much more about getting things right\nthan most people would in a casual conversation.\n[4]Another trick I've found to protect myself against obsolete beliefs\nis to focus initially on people rather than ideas. Though the nature\nof future discoveries is hard to predict, I've found I can predict\nquite well what sort of people will make them. Good new ideas come\nfrom earnest, energetic, independent-minded people.Betting on people over ideas saved me countless times as an investor.\nWe thought Airbnb was a bad idea, for example. But we could tell\nthe founders were earnest, energetic, and independent-minded.\n(Indeed, almost pathologically so.) So we suspended disbelief and\nfunded them.This too seems a technique that should be generally applicable.\nSurround yourself with the sort of people new ideas come from. If\nyou want to notice quickly when your beliefs become obsolete, you\ncan't do better than to be friends with the people whose discoveries\nwill make them so.It's hard enough already not to become the prisoner of your own\nexpertise, but it will only get harder, because change is accelerating.\nThat's not a recent trend; change has been accelerating since the\npaleolithic era. Ideas beget ideas. I don't expect that to change.\nBut I could be wrong.\nNotes[1]\nMy usual trick is to talk about aspects of the present that\nmost people haven't noticed yet.[2]\nEspecially if they become well enough known that people start\nto identify them with you. You have to be extra skeptical about\nthings you want to believe, and once a hypothesis starts to be\nidentified with you, it will almost certainly start to be in that\ncategory.[3]\nIn practice \"sufficiently expert\" doesn't require one to be\nrecognized as an expert—which is a trailing indicator in any\ncase. In many fields a year of focused work plus caring a lot would\nbe enough.[4]\nThough they are public and persist indefinitely, comments on\ne.g. forums and places like Twitter seem empirically to work like\ncasual conversation. The threshold may be whether what you write\nhas a title.\nThanks to Sam Altman, Patrick Collison, and Robert Morris\nfor reading drafts of this." }, { "path": "data/PaulGrahamEssays/equity.txt", "content": "July 2007An investor wants to give you money for a certain percentage of\nyour startup. Should you take it? You're about to hire your first\nemployee. How much stock should you give him?These are some of the hardest questions founders face. And yet\nboth have the same answer:1/(1 - n)Whenever you're trading stock in your company for anything, whether\nit's money or an employee or a deal with another company, the test\nfor whether to do it is the same. You should give up n% of your\ncompany if what you trade it for improves your average outcome\nenough that the (100 - n)% you have left is worth more than the\nwhole company was before.For example, if an investor wants to buy half your company, how\nmuch does that investment have to improve your average outcome for\nyou to break even? Obviously it has to double: if you trade half\nyour company for something that more than doubles the company's\naverage outcome, you're net ahead. You have half as big a share\nof something worth more than twice as much.In the general case, if n is the fraction of the company you're\ngiving up, the deal is a good one if it makes the company worth\nmore than 1/(1 - n).For example, suppose Y Combinator offers to fund you in return for\n7% of your company. In this case, n is .07 and 1/(1 - n) is 1.075.\nSo you should take the deal if you believe we can improve your\naverage outcome by more than 7.5%. If we improve your outcome by\n10%, you're net ahead, because the remaining .93 you hold is worth\n.93 x 1.1 = 1.023.\n[1]One of the things the equity equation shows us is that, financially\nat least, taking money from a top VC firm can be a really good deal.\nGreg Mcadoo from Sequoia recently said at a YC dinner that when\nSequoia invests alone they like to take about 30% of a company.\n1/.7 = 1.43, meaning that deal is worth taking if they can improve\nyour outcome by more than 43%. For the average startup, that would\nbe an extraordinary bargain. It would improve the average startup's\nprospects by more than 43% just to be able to say they were funded\nby Sequoia, even if they never actually got the money.The reason Sequoia is such a good deal is that the percentage of\nthe company they take is artificially low. They don't even try to\nget market price for their investment; they limit their holdings\nto leave the founders enough stock to feel the company is still\ntheirs.The catch is that Sequoia gets about 6000 business plans a year and\nfunds about 20 of them, so the odds of getting this great deal are\n1 in 300. The companies that make it through are not average startups.Of course, there are other factors to consider in a VC deal. It's\nnever just a straight trade of money for stock. But if it were,\ntaking money from a top firm would generally be a bargain.You can use the same formula when giving stock to employees, but\nit works in the other direction. If i is the average outcome for\nthe company with the addition of some new person, then they're worth\nn such that i = 1/(1 - n). Which means n = (i - 1)/i.For example, suppose you're just two founders and you want to hire\nan additional hacker who's so good you feel he'll increase the\naverage outcome of the whole company by 20%. n = (1.2 - 1)/1.2 =\n.167. So you'll break even if you trade 16.7% of the company\nfor him.That doesn't mean 16.7% is the right amount of stock to give him.\nStock is not the only cost of hiring someone: there's usually salary\nand overhead as well. And if the company merely breaks even on the\ndeal, there's no reason to do it.I think to translate salary and overhead into stock you should\nmultiply the annual rate by about 1.5. Most startups grow fast or\ndie; if you die you don't have to pay the guy, and if you grow fast\nyou'll be paying next year's salary out of next year's valuation,\nwhich should be 3x this year's. If your valuation grows 3x a year,\nthe total cost in stock of a new hire's salary and overhead is 1.5\nyears' cost at the present valuation. [2]How much of an additional margin should the company need as the\n\"activation energy\" for the deal? Since this is in effect the\ncompany's profit on a hire, the market will determine that: if\nyou're a hot opportunity, you can charge more.Let's run through an example. Suppose the company wants to make a\n\"profit\" of 50% on the new hire mentioned above. So subtract a\nthird from 16.7% and we have 11.1% as his \"retail\" price. Suppose\nfurther that he's going to cost $60k a year in salary and overhead,\nx 1.5 = $90k total. If the company's valuation is $2 million, $90k\nis 4.5%. 11.1% - 4.5% = an offer of 6.6%.Incidentally, notice how important it is for early employees to\ntake little salary. It comes right out of stock that could otherwise\nbe given to them.Obviously there is a great deal of play in these numbers. I'm not\nclaiming that stock grants can now be reduced to a formula. Ultimately\nyou always have to guess. But at least know what you're guessing.\nIf you choose a number based on your gut feel, or a table of typical\ngrant sizes supplied by a VC firm, understand what those are estimates\nof.And more generally, when you make any decision involving equity,\nrun it through 1/(1 - n) to see if it makes sense. You should\nalways feel richer after trading equity. If the trade didn't\nincrease the value of your remaining shares enough to put you net\nahead, you wouldn't have (or shouldn't have) done it.Notes[1] This is why we\ncan't believe anyone would think Y Combinator was a bad deal. Does\nanyone really think we're so useless that in three months we can't\nimprove a startup's prospects by 7.5%?\n[2] The obvious choice\nfor your present valuation is the post-money valuation of your last\nfunding round. This probably undervalues the company, though,\nbecause (a) unless your last round just happened, the company is\npresumably worth more, and (b) the valuation of an early funding\nround usually reflects some other contribution by the investors.Thanks to Sam Altman, Trevor Blackwell, Paul Buchheit, \nHutch Fishman, David Hornik, Paul Kedrosky, Jessica Livingston, Gary Sabot, and \nJoshua Schachter for reading drafts of this." }, { "path": "data/PaulGrahamEssays/essay.txt", "content": "September 2004Remember the essays you had to write in high school?\nTopic sentence, introductory paragraph,\nsupporting paragraphs, conclusion. The conclusion being,\nsay, that Ahab in Moby Dick was a Christ-like figure.Oy. So I'm going to try to give the other side of the\nstory: what an essay really is, and how you write one.\nOr at least, how I write one.ModsThe most obvious difference between real essays and\nthe things one has to write in school is that real\nessays are not exclusively about English literature.\nCertainly schools should teach students how to\nwrite. But due to a series of historical accidents\nthe teaching of\nwriting has gotten mixed together with the study\nof literature. And so all over the country students are\nwriting not about how a baseball team with a small budget\nmight compete with the Yankees, or the role of color in\nfashion, or what constitutes a good dessert, but about\nsymbolism in Dickens.With the result that writing is made to seem boring and\npointless. Who cares about symbolism in Dickens?\nDickens himself would be more interested in an essay\nabout color or baseball.How did things get this way? To answer that we have to go back\nalmost a thousand years. Around 1100, Europe at last began to\ncatch its breath after centuries of chaos, and once they\nhad the luxury of curiosity they rediscovered\nwhat we call \"the classics.\" The effect was rather as if\nwe were visited by beings from another solar system.\nThese earlier civilizations were so much more sophisticated\nthat for the next several centuries the main work of\nEuropean scholars, in almost every field, was to assimilate\nwhat they knew.During this period the study of ancient texts acquired great\nprestige. It seemed the essence of what scholars did. As\nEuropean scholarship gained momentum it became less and less important;\nby 1350\nsomeone who wanted to learn about science could find better\nteachers than Aristotle in his own era. [1]\nBut schools change slower than scholarship. In the\n19th century the study of ancient texts was still the backbone\nof the curriculum.The time was then ripe for the question: if the study of\nancient texts is a valid field for scholarship, why not modern\ntexts? The answer, of course, is that the original raison d'etre\nof classical scholarship was a kind of intellectual archaeology that\ndoes not need to be done in the case of contemporary authors.\nBut for obvious reasons no one wanted to give that answer.\nThe archaeological work being mostly done, it implied that\nthose studying the classics were, if not wasting their\ntime, at least working on problems of minor importance.And so began the study of modern literature. There was a good\ndeal of resistance at first.\nThe first courses in English literature\nseem to have been offered by the newer colleges, particularly\nAmerican ones. Dartmouth, the University of Vermont, Amherst,\nand University College, London\ntaught English literature in the 1820s.\n\nBut Harvard didn't have a professor of English literature until\n1876, and Oxford not till 1885. (Oxford had a chair of Chinese before\nit had one of English.) [2]What tipped the scales, at least in the US, seems to have\nbeen the idea that professors should do research as well\nas teach. This idea (along with the PhD, the department, and\nindeed the whole concept of the modern university) was imported\nfrom Germany in the late 19th century. Beginning at\nJohns Hopkins in 1876, the new model spread rapidly.Writing was one of the casualties. Colleges had long taught\nEnglish composition. But how do you do research on composition?\nThe professors who taught math could be required to do original\nmath, the professors who taught history could be required to\nwrite scholarly articles about history, but what about the \nprofessors who taught rhetoric or composition? What should they\ndo research on? The closest thing seemed to be English literature. [3]And so in the late 19th century the teaching of writing was inherited\nby English professors. This had two drawbacks:\n(a) an expert on literature need not himself be a good writer,\nany more than an art historian has to be a good painter, and (b)\nthe subject of writing now tends to be literature, since that's\nwhat the professor is interested in.High schools imitate universities. The seeds of our miserable\nhigh school experiences were sown in 1892, when\nthe National Education Association\n\"formally recommended that literature\nand composition be unified in the high school course.\" [4]\nThe 'riting component of the 3 Rs then morphed into English,\nwith the bizarre consequence that high school students now\nhad to write about English literature-- to write, without\neven realizing it, imitations of whatever\nEnglish professors had been publishing in their journals a \nfew decades before.It's no wonder if this seems to the\nstudent a pointless exercise, because we're now three steps\nremoved from real work: the students are imitating English\nprofessors, who are imitating classical scholars, who are\nmerely the inheritors of a tradition growing out of what\nwas, 700 years ago, fascinating and urgently needed work.No DefenseThe other big difference between a real essay and the things\nthey make you write in school is that a real essay doesn't\ntake a position and then defend it. That principle,\nlike the idea that we ought to be writing about literature,\nturns out to be another intellectual hangover of long\nforgotten origins.It's often mistakenly believed that\nmedieval universities were mostly seminaries. In fact they\nwere more law schools. And at least in our tradition\nlawyers are advocates, trained to take\neither side of an argument and make as good a case for it\nas they can.\nWhether cause or effect, this spirit pervaded\nearly universities. The study of rhetoric, the art of arguing\npersuasively, was a third of the undergraduate curriculum. [5]\nAnd after the lecture the most common form\nof discussion was the disputation. This is at least\nnominally preserved in our present-day thesis defense:\nmost people treat the words thesis\nand dissertation as interchangeable, but originally, at least,\na thesis was a position one took and the dissertation was\nthe argument by which one defended it.Defending a position may be a necessary evil in a\nlegal dispute, but it's not the best way to get at the truth,\nas I think lawyers would be the first to admit. It's not\njust that you miss subtleties this way.\nThe real problem is that you can't change the question.And yet this principle is built into the very structure of\nthe things they teach you to write in high school. The topic \nsentence is your thesis, chosen in advance, the supporting\nparagraphs the blows you strike in the conflict, and the\nconclusion-- uh, what is the conclusion? I was never sure\nabout that in high school. It seemed as if we were just\nsupposed to restate what we said in the first paragraph,\nbut in different enough words that no one could tell.\nWhy bother?\nBut when you understand the origins\nof this sort of \"essay,\" you can see where the\nconclusion comes from. It's the concluding remarks to the \njury.Good writing should be convincing, certainly, but it\nshould be convincing because you got the right answers,\nnot because you did a good job of arguing. When I give a \ndraft of an essay to friends, there are two things\nI want to know: which parts bore them, and which seem \nunconvincing. The boring bits can usually be fixed by \ncutting. But I don't try to fix the unconvincing bits by\narguing more cleverly. I need to talk the matter over.At the very least I must have explained something badly. In\nthat case, in the course of the conversation I'll be forced\nto come up a with a clearer explanation, which I can just\nincorporate in the essay. More often than not I have\nto change what I was saying as well.\nBut the aim is never to be convincing per se.\nAs the reader gets smarter, convincing and true become identical,\nso if I can convince smart readers I must be near the truth.The sort of writing that attempts to persuade may be\na valid (or at least inevitable) form, but it's historically\ninaccurate to call it an essay. An essay is \nsomething else.TryingTo understand what a real essay is, we have to\nreach back into history again, though this time not so far.\nTo Michel de Montaigne, who in 1580 published a book of\nwhat he called \"essais.\" He was\ndoing something quite different from what lawyers do, and\nthe difference is embodied in the name. Essayer is the French\nverb meaning \"to try\"\nand an essai is an attempt. An essay is something you\nwrite to try to figure something out.Figure out what? You don't know yet. And so you can't begin with a\nthesis, because you don't have one, and may never have\none. An essay doesn't begin with a statement, but with a\nquestion. In a real essay, you don't take a position and\ndefend it. You notice a door that's ajar, and you open it and\nwalk in to see what's inside.If all you want to do is figure things out, why do you need\nto write anything, though? Why not just sit and think? Well,\nthere precisely is Montaigne's great discovery. Expressing \nideas helps to form them. Indeed, helps is far too weak a\nword. Most of what ends up in my essays I only\nthought of when I sat down to write them. That's why I \nwrite them.In the things you write in school you are, in theory,\nmerely explaining yourself to the reader.\nIn a real essay you're writing for yourself.\nYou're thinking out loud.But not quite.\nJust as inviting people over forces you to\nclean up your apartment, writing something that\nother people will read forces you to think well. So it\ndoes matter to have an audience. The things I've written\njust for myself are no good.\nThey tend to peter out. When I run into\ndifficulties, I find I conclude with a few vague\nquestions and then drift off to get a cup of tea.Many published essays peter out in the same way.\nParticularly the sort written by the staff writers \nof newsmagazines. Outside writers tend to supply\neditorials of the defend-a-position variety, which\nmake a beeline toward a rousing (and\nforeordained) conclusion. But the staff writers feel\nobliged to write something \"balanced.\"\nSince they're writing for a popular magazine, they start with the\nmost radioactively controversial questions, from which-- because\nthey're writing for a popular magazine-- they\nthen proceed to recoil in terror.\nAbortion, for or against?\nThis group says one thing. That group says\nanother. One thing is certain: the question is a\ncomplex one. (But don't get mad at us. We didn't\ndraw any conclusions.)The RiverQuestions aren't enough. An essay has to come up with answers.\nThey don't always, of course. Sometimes you start with a\npromising question and get nowhere. But those you don't \npublish. Those are like experiments that get inconclusive\nresults. An essay you publish ought to tell the reader \nsomething he didn't already know.But what you tell him doesn't matter, so long as \nit's interesting. I'm sometimes accused of meandering.\nIn defend-a-position writing that would be a flaw.\nThere you're not concerned with truth. You already\nknow where you're going, and you want to go straight there,\nblustering through obstacles, and hand-waving\nyour way across swampy ground. But that's not what\nyou're trying to do in an essay. An essay is supposed to\nbe a search for truth. It would be suspicious if it didn't\nmeander.The Meander (aka Menderes) is a river in Turkey.\nAs you might expect, it winds all over the place.\nBut it doesn't do this out of frivolity.\nThe path it has discovered is the most\neconomical route to the sea. [6]The river's algorithm is simple. At each step, flow down.\nFor the essayist this translates to: flow interesting. \nOf all the places to go next, choose the most interesting.\nOne can't have quite as little foresight as a river. I always\nknow generally what I want to write about.\nBut not the\nspecific conclusions I want to reach; from paragraph to\nparagraph I let the ideas take their course.This doesn't always work. Sometimes, like a river,\none runs up against a wall. Then I do the same thing the river does:\nbacktrack. At one point in this essay\nI found that after following a certain thread I ran out\nof ideas. I had to go back seven paragraphs and start over\nin another direction.Fundamentally an essay is a train of thought-- but a cleaned-up\ntrain of thought, as dialogue is cleaned-up conversation.\nReal thought, like real conversation, is full of false starts.\nIt would be exhausting to read. You need to \ncut and fill to\nemphasize the central thread, like an\nillustrator inking over a pencil drawing. But don't\nchange so much that you lose the spontaneity of the original.Err on the side of the river. An essay is not a reference\nwork. It's not something you read looking for a specific\nanswer, and feel cheated if you don't find it. I'd much\nrather read an essay that went off in an unexpected but\ninteresting direction than one that plodded dutifully along\na prescribed course.SurpriseSo what's interesting? For me, interesting means surprise.\nInterfaces, as Geoffrey James has said, should follow the principle of\nleast astonishment. A button that looks like it will make a\nmachine stop should make it stop, not speed up. Essays \nshould do the opposite. Essays should aim for maximum\nsurprise.I was afraid of flying for a long time and could only travel\nvicariously. When friends came back from faraway places,\nit wasn't just out of politeness that I asked\nwhat they saw. I really wanted to know. And I found\nthe best way to get information out of them was to ask\nwhat surprised them. How was the place different from what\nthey expected? This is an extremely useful question.\nYou can ask it of the most unobservant people, and it will \nextract information they didn't even know they were\nrecording.Surprises are things that you not only didn't know, but that\ncontradict things you\nthought you knew. And so they're the most valuable sort of\nfact you can get. They're like a food that's not merely\nhealthy, but counteracts the unhealthy effects of things\nyou've already eaten.How do you find surprises? Well, therein lies half\nthe work of essay writing. (The other half is expressing\nyourself well.) The trick is to use yourself as a\nproxy for the reader. You should only write about things\nyou've thought about a lot. And anything you come across\nthat surprises you, who've thought about the topic a lot,\nwill probably surprise most readers.For example, in a recent \nessay I pointed out that because\nyou can only judge computer programmers by working with\nthem, no one knows who the best programmers are overall.\nI didn't realize this when I began\nthat essay, and even now I find it kind of weird. That's\nwhat you're looking for.So if you want to write essays, you need two ingredients:\na few topics you've thought about a lot, and\nsome ability to ferret out the unexpected.What should you think about? My guess is that it\ndoesn't matter-- that anything can be interesting if you get deeply\nenough into it. One possible exception might be things\nthat have deliberately had all the variation sucked out of them,\nlike working in fast food. In retrospect, was there\nanything interesting about working at Baskin-Robbins?\nWell, it was interesting how important color was\nto the customers. Kids a certain age would point into\nthe case and say that they wanted yellow. Did they want \nFrench Vanilla or Lemon? They would just look at you \nblankly. They wanted yellow. And then there was the \nmystery of why the perennial favorite Pralines 'n' Cream \nwas so appealing. (I think now it was the salt.)\n\nAnd the difference in the way fathers and\nmothers bought ice cream for their kids: the fathers\nlike benevolent kings bestowing largesse, the mothers\nharried, giving in to pressure.\nSo, yes, there does seem to be some material even in\nfast food.I didn't notice those things at the time, though. At sixteen\nI was about as observant as a lump of rock. I can see more now in\nthe fragments of memory I preserve of that age than I could see\nat the time from having it all happening live, right in front of me.ObservationSo the ability to ferret out the unexpected must not merely be an\ninborn one. It must be something you can learn.\nHow do you learn it?To some extent it's like learning history.\nWhen you first read\nhistory, it's just a whirl of names\nand dates. \nNothing seems to stick. But the more you learn, the more hooks you have\nfor new facts to stick onto-- which means\nyou accumulate knowledge at an exponential rate. Once you\nremember that Normans conquered\nEngland in 1066, it will catch your attention when you hear\nthat other Normans conquered southern Italy at about the same time.\nWhich will make you wonder about Normandy, and take note\nwhen a third book mentions that Normans\nwere not, like most of what is now\ncalled France, tribes that flowed in as the Roman empire collapsed,\nbut Vikings (norman = north man) who arrived\nfour centuries later in 911. Which makes\nit easier to remember that Dublin was also established by\nVikings in the 840s. Etc, etc squared.Collecting surprises is a similar process.\nThe more anomalies you've seen, the more easily you'll notice\nnew ones. Which means, oddly enough, that as you grow older,\nlife should become more and more surprising. When I was a\nkid, I used to think adults had it all figured out.\nI had it backwards. Kids are the ones who have it all figured \nout. They're just mistaken.When it comes to surprises, the rich get richer. But\n(as with wealth) there\nmay be habits of mind that will help the process along. It's\ngood to have a habit of asking questions, especially questions\nbeginning with Why.\nBut not in the random way that three year\nolds ask why. There are an infinite number of questions.\nHow do you find the fruitful ones?I find it especially\nuseful to ask why about things that seem wrong.\nFor example, why should there be a connection between\nhumor and misfortune? Why do we find it funny when a\ncharacter, even one we like, slips on a banana peel?\nThere's a whole essay's worth of surprises there for sure.If you want to notice things that seem wrong, you'll find a\ndegree of skepticism helpful. I take it as an axiom\nthat we're only achieving 1% of what we could.\nThis helps counteract the rule that gets beaten into our\nheads as children: that things are the way they are because\nthat is how things have to be.\nFor example, everyone I've talked to while writing this essay \nfelt the same about\nEnglish classes-- that the whole process seemed pointless.\nBut none of us had the balls at the time to hypothesize that\nit was, in fact, all a mistake.\nWe all thought there was just something we weren't getting.I have a hunch you want to pay attention not just to things\nthat seem wrong, but things that seem wrong in a humorous way. \nI'm always pleased when I see someone laugh as they\nread a draft of an essay. But why should I be? I'm aiming\nfor good ideas. Why should good ideas be funny?\nThe connection may be surprise.\nSurprises make us laugh, and surprises are what\none wants to deliver.I write down things that surprise me in notebooks. I never\nactually get around to reading them and using\nwhat I've written, but I do tend to\nreproduce the same thoughts later. So the main value\nof notebooks may be what writing things down leaves in your\nhead.People trying to be cool will find themselves at a disadvantage\nwhen collecting surprises. To be surprised is to be mistaken.\nAnd the essence of cool, as any fourteen year old could tell\nyou, is nil admirari. When you're mistaken, don't\ndwell on it; just act like nothing's wrong and maybe no one\nwill notice.One of the keys to coolness is to avoid situations where\ninexperience may make you look foolish. \nIf you want to find surprises you should do the opposite.\nStudy lots of different things,\nbecause some of the most interesting surprises are unexpected\nconnections between different fields. For example, \njam, bacon, pickles, and cheese, which are among the most pleasing\nof foods, were all originally intended as methods of preservation.\nAnd so were books and paintings.Whatever you study, include history-- but social and economic\nhistory, not political history. History seems to me so important\nthat it's misleading to treat it as a mere field of study.\nAnother way to describe it is all the data we have so far.Among other things, studying history gives one confidence that\nthere are good ideas waiting to be discovered right under our noses.\nSwords evolved during the Bronze Age out of daggers, which\n(like their flint predecessors) had a hilt separate from the\nblade. Because swords are longer\nthe hilts kept breaking off. But it took five hundred years\nbefore someone thought of casting hilt and blade as one\npiece.DisobedienceAbove all, make a habit of paying\nattention to things you're not supposed to, either because \nthey're \"inappropriate,\" \nor not important, or not what you're\nsupposed to be working on. If you're curious about something,\ntrust your instincts.\nFollow the threads that attract your\nattention. If there's something you're really interested\nin, you'll find they have an uncanny way of leading back to\nit anyway, just as the conversation of people who are especially\nproud of something always tends to lead back to it.For example, I've always been fascinated by comb-overs, especially\nthe extreme sort that\nmake a man look as if he's wearing a beret made of his own hair.\nSurely this is a lowly sort of thing to be interested in-- the\nsort of superficial quizzing\nbest left to teenage girls. And yet there is something underneath.\nThe key question, I realized, is how does the comber-over not\nsee how odd he looks?\nAnd the answer is that he got to look that way incrementally.\nWhat began as combing his hair a little carefully over a\nthin patch has gradually, over 20 years, grown into a monstrosity.\nGradualness is very powerful. And that power can be\nused for constructive purposes too: just as you can trick\nyourself into looking like a freak, you can trick yourself into\ncreating something so grand that you would never have dared to\nplan such a thing. Indeed, this is just how most good\nsoftware gets created. You start by writing a stripped-down\nkernel (how hard can it be?) and gradually it grows\ninto a complete operating system. Hence the next leap: could\nyou do the same thing in painting, or in a novel?See what you can extract from a frivolous question?\nIf there's one piece of advice I would give about writing essays,\nit would be: don't do as you're told.\nDon't believe what you're supposed to.\nDon't write the\nessay readers expect; one learns nothing from\nwhat one expects.\nAnd\ndon't write the way they taught you to in school.The most important sort of disobedience is to write\nessays at all. Fortunately, this sort of disobedience shows\nsigns of becoming \nrampant. \nIt used to be that only a tiny\nnumber of officially approved writers were allowed to\nwrite essays. Magazines published few of them, and judged\nthem less by what they said than who wrote them;\na magazine might publish a story by an\nunknown writer if it was good enough, but if they published\nan essay on x it had to be by someone who was at least\nforty and whose job title had x in it. Which is a problem,\nbecause there are a lot of things insiders can't say precisely\nbecause they're insiders.The Internet is changing that.\nAnyone can publish an essay on the Web, and it gets judged, as any\nwriting should, by what it says, not who wrote it.\nWho are you to write about x? You are whatever you wrote.Popular magazines made the period between the spread\nof literacy and the arrival of TV the golden age of the\nshort story.\nThe Web may well make this the golden age of the essay.\nAnd that's certainly not something I realized when\nI started writing this.Notes[1] I'm thinking of Oresme (c. 1323-82). But it's hard to pick\na date, because there was a sudden drop-off in scholarship\njust as Europeans finished assimilating classical science.\nThe cause may have been the plague of 1347; the trend in\nscientific progress matches the population curve.[2] Parker, William R. \"Where Do College English Departments\nCome From?\" College English 28 (1966-67), pp. 339-351.\nReprinted in Gray, Donald J. (ed). The Department of\nEnglish at Indiana University Bloomington 1868-1970. Indiana\nUniversity Publications.Daniels, Robert V. The University of Vermont: The First\nTwo Hundred Years. University of Vermont, 1991.Mueller, Friedrich M. Letter to the Pall Mall\nGazette. 1886/87. Reprinted in Bacon, Alan (ed).\nThe Nineteenth-Century\nHistory of English Studies. Ashgate, 1998.[3] I'm compressing the story a bit.\nAt first\nliterature took a back seat to philology, which (a) seemed more \nserious and (b) was popular in Germany, where many of the\nleading scholars of that generation had been trained.In some cases the writing teachers were transformed\nin situ into English professors.\nFrancis James Child, who had been Boylston Professor\nof Rhetoric at Harvard since 1851,\nbecame in 1876 the university's first professor of English.[4] Parker, op. cit., p. 25.[5] The undergraduate curriculum or trivium (whence\n\"trivial\") consisted of Latin grammar, rhetoric, and logic. \nCandidates for masters' degrees went on to study the\nquadrivium of arithmetic, geometry, music, and astronomy.\nTogether these were the seven liberal arts.The study of rhetoric was inherited directly from Rome, where\nit was considered the most important\nsubject. It would not be far from the truth to say that \neducation in the classical world\nmeant training landowners' sons\nto speak well enough to defend their interests\nin political and legal disputes.[6] Trevor Blackwell points out that this\nisn't strictly true, because the outside \nedges of curves erode faster.\nThanks to Ken Anderson, Trevor Blackwell, Sarah Harlin, Jessica\nLivingston, Jackie McDonough, and Robert Morris for reading drafts of\nthis." }, { "path": "data/PaulGrahamEssays/ffb.txt", "content": "August 2003\nWe may be able to improve the accuracy of Bayesian spam filters\nby having them follow links to see what's\nwaiting at the other end. Richard Jowsey of\ndeath2spam now does\nthis in borderline cases, and reports that it works well.Why only do it in borderline cases? And why only do it once?As I mentioned in Will Filters Kill Spam?,\nfollowing all the urls in\na spam would have an amusing side-effect. If popular email clients\ndid this in order to filter spam, the spammer's servers\nwould take a serious pounding. The more I think about this,\nthe better an idea it seems. This isn't just amusing; it\nwould be hard to imagine a more perfectly targeted counterattack\non spammers.So I'd like to suggest an additional feature to those\nworking on spam filters: a \"punish\" mode which,\nif turned on, would spider every url\nin a suspected spam n times, where n could be set by the user. [1]As many people have noted, one of the problems with the\ncurrent email system is that it's too passive. It does\nwhatever you tell it. So far all the suggestions for fixing\nthe problem seem to involve new protocols. This one \nwouldn't.If widely used, auto-retrieving spam filters would make\nthe email system rebound. The huge volume of the\nspam, which has so far worked in the spammer's favor,\nwould now work against him, like a branch snapping back in \nhis face. Auto-retrieving spam filters would drive the\nspammer's \ncosts up, \nand his sales down: his bandwidth usage\nwould go through the roof, and his servers would grind to a\nhalt under the load, which would make them unavailable\nto the people who would have responded to the spam.Pump out a million emails an hour, get a\nmillion hits an hour on your servers.\nWe would want to ensure that this is only done to\nsuspected spams. As a rule, any url sent to millions of\npeople is likely to be a spam url, so submitting every http\nrequest in every email would work fine nearly all the time.\nBut there are a few cases where this isn't true: the urls\nat the bottom of mails sent from free email services like\nYahoo Mail and Hotmail, for example.To protect such sites, and to prevent abuse, auto-retrieval\nshould be combined with blacklists of spamvertised sites.\nOnly sites on a blacklist would get crawled, and\nsites would be blacklisted\nonly after being inspected by humans. The lifetime of a spam\nmust be several hours at least, so\nit should be easy to update such a list in time to\ninterfere with a spam promoting a new site. [2]High-volume auto-retrieval would only be practical for users\non high-bandwidth\nconnections, but there are enough of those to cause spammers\nserious trouble. Indeed, this solution neatly\nmirrors the problem. The problem with spam is that in\norder to reach a few gullible people the spammer sends \nmail to everyone. The non-gullible recipients\nare merely collateral damage. But the non-gullible majority\nwon't stop getting spam until they can stop (or threaten to\nstop) the gullible\nfrom responding to it. Auto-retrieving spam filters offer\nthem a way to do this.Would that kill spam? Not quite. The biggest spammers\ncould probably protect their servers against auto-retrieving \nfilters. However, the easiest and cheapest way for them\nto do it would be to include working unsubscribe links in \ntheir mails. And this would be a necessity for smaller fry,\nand for \"legitimate\" sites that hired spammers to promote\nthem. So if auto-retrieving filters became widespread,\nthey'd become auto-unsubscribing filters.In this scenario, spam would, like OS crashes, viruses, and\npopups, become one of those plagues that only afflict people\nwho don't bother to use the right software.\nNotes[1] Auto-retrieving filters will have to follow redirects,\nand should in some cases (e.g. a page that just says\n\"click here\") follow more than one level of links.\nMake sure too that\nthe http requests are indistinguishable from those of\npopular Web browsers, including the order and referrer.If the response\ndoesn't come back within x amount of time, default to\nsome fairly high spam probability.Instead of making n constant, it might be a good idea to\nmake it a function of the number of spams that have been\nseen mentioning the site. This would add a further level of\nprotection against abuse and accidents.[2] The original version of this article used the term\n\"whitelist\" instead of \"blacklist\". Though they were\nto work like blacklists, I preferred to call them whitelists\nbecause it might make them less vulnerable to legal attack.\nThis just seems to have confused readers, though.There should probably be multiple blacklists. A single point\nof failure would be vulnerable both to attack and abuse.\nThanks to Brian Burton, Bill Yerazunis, Dan Giffin,\nEric Raymond, and Richard Jowsey for reading drafts of this." }, { "path": "data/PaulGrahamEssays/fh.txt", "content": "January 2020(I originally intended this for startup founders, who are often\nsurprised by the attention they get as their companies grow, but\nit applies equally to anyone who becomes famous.)If you become sufficiently famous, you'll acquire some fans who\nlike you too much. These people are sometimes called \"fanboys,\" and\nthough I dislike that term, I'm going to have to use it here. We\nneed some word for them, because this is a distinct phenomenon from\nsomeone simply liking your work.A fanboy is obsessive and uncritical. Liking you becomes part of\ntheir identity, and they create an image of you in their own head\nthat is much better than reality. Everything you do is good, because\nyou do it. If you do something bad, they find a way to see it as\ngood. And their love for you is not, usually, a quiet, private one.\nThey want everyone to know how great you are.Well, you may be thinking, I could do without this kind of obsessive\nfan, but I know there are all kinds of people in the world, and if\nthis is the worst consequence of fame, that's not so bad.Unfortunately this is not the worst consequence of fame. As well\nas fanboys, you'll have haters.A hater is obsessive and uncritical. Disliking you becomes part of\ntheir identity, and they create an image of you in their own head\nthat is much worse than reality. Everything you do is bad, because\nyou do it. If you do something good, they find a way to see it as\nbad. And their dislike for you is not, usually, a quiet, private\none. They want everyone to know how awful you are.If you're thinking of checking, I'll save you the trouble. The\nsecond and fifth paragraphs are identical except for \"good\" being\nswitched to \"bad\" and so on.I spent years puzzling about haters. What are they, and where do\nthey come from? Then one day it dawned on me. Haters are just fanboys\nwith the sign switched.Note that by haters, I don't simply mean trolls. I'm not talking about \npeople who say bad things about you and then move on. I'm talking\nabout the much smaller group of people for whom this becomes a \nkind of obsession and who do it repeatedly over a long period.Like fans, haters seem to be an automatic consequence of fame.\nAnyone sufficiently famous will have them. And like fans, haters\nare energized by the fame of whoever they hate. They hear a song\nby some pop singer. They don't like it much. If the singer were an\nobscure one, they'd just forget about it. But instead they keep\nhearing her name, and this seems to drive some people crazy.\nEveryone's always going on about this singer, but she's no good!\nShe's a fraud!That word \"fraud\" is an important one. It's the spectral signature\nof a hater to regard the object of their hatred as a \nfraud. They\ncan't deny their fame. Indeed, their fame is if anything exaggerated\nin the hater's mind. They notice every mention of the singer's name,\nbecause every mention makes them angrier. In their own minds they\nexaggerate both the singer's fame and her lack of talent, and the\nonly way to reconcile those two ideas is to conclude that she has\ntricked everyone.What sort of people become haters? Can anyone become one? I'm not\nsure about this, but I've noticed some patterns. Haters are generally\nlosers in a very specific sense: although they are occasionally\ntalented, they have never achieved much. And indeed, anyone\nsuccessful enough to have achieved significant fame would be unlikely\nto regard another famous person as a fraud on that account, because\nanyone famous knows how random fame is.But haters are not always complete losers. They are not always the\nproverbial guy living in his mom's basement. Many are, but some\nhave some amount of talent. In fact I suspect that a sense of\nfrustrated talent is what drives some people to become haters.\nThey're not just saying \"It's unfair that so-and-so is famous,\" but\n\"It's unfair that so-and-so is famous, and not me.\"Could a hater be cured if they achieved something impressive? My\nguess is that's a moot point, because they \nnever will. I've been\nable to observe for long enough that I'm fairly confident the pattern\nworks both ways: not only do people who do great work never become\nhaters, haters never do great work. Although I dislike the word\n\"fanboy,\" it's evocative of something important about both haters\nand fanboys. It implies that the fanboy is so slavishly predictable in his admiration\nthat he's diminished as a result, that he's less than a man.Haters seem even more diminished. I can imagine being a fanboy.\nI can think of people whose work I admire so much that I could abase\nmyself before them out of sheer gratitude. If P. G. Wodehouse were\nstill alive, I could see myself being a Wodehouse fanboy. But I\ncould not imagine being a hater.Knowing that haters are just fanboys with the sign bit flipped makes\nit much easier to deal with them. We don't need a separate theory\nof haters. We can just use existing techniques for dealing with\nobsessive fans.The most important of which is simply not to think much about them.\nIf you're like most people who become famous enough to acquire\nhaters, your initial reaction will be one of mystification. Why\ndoes this guy seem to have it in for me? Where does his obsessive\nenergy come from, and what makes him so appallingly nasty? What did\nI do to set him off? Is it something I can fix?The mistake here is to think of the hater as someone you have a\ndispute with. When you have a dispute with someone, it's usually a\ngood idea to try to understand why they're upset and then fix things\nif you can. Disputes are distracting. But it's a false analogy to\nthink of a hater as someone you have a dispute with. It's an\nunderstandable mistake, if you've never encountered haters before.\nBut when you realize that you're dealing with a hater, and what a\nhater is, it's clear that it's a waste of time even to think about\nthem. If you have obsessive fans, do you spend any time wondering\nwhat makes them love you so much? No, you just think \"some\npeople are kind of crazy,\" and that's the end of it.Since haters are equivalent to fanboys, that's the way to deal with\nthem too. There may have been something that set them off. But it's\nnot something that would have set off a normal person, so there's\nno reason to spend any time thinking about it. It's not you, it's\nthem.Notes[1] There are of course some people who are genuine frauds. How can\nyou distinguish between x calling y a fraud because x is a hater,\nand because y is a fraud? Look at neutral opinion. Actual frauds\nare usually pretty conspicuous. Thoughtful people are rarely taken\nin by them. So if there are some thoughtful people who like y, you\ncan usually assume y is not a fraud.[2] I would make an exception for teenagers, who sometimes act in\nsuch extreme ways that they are literally not themselves. I can\nimagine a teenage kid being a hater and then growing out of it. But\nnot anyone over 25.[3] I have a much worse memory for misdeeds than my wife Jessica,\nwho is a connoisseur of character, but I don't wish it were better.\nMost disputes are a waste of time even if you're in the right, and\nit's easy to bury the hatchet with someone if you can't remember\nwhy you were mad at them.[4] A competent hater will not merely attack you individually but\nwill try to get mobs after you. In some cases you may want to refute\nwhatever bogus claim they made in order to do so. But err on the\nside of not, because ultimately it probably won't matter.Thanks to Austen Allred, Trevor Blackwell, Patrick Collison,\nChristine Ford, Daniel Gackle, Jessica Livingston, Robert Morris, \nElon Musk, Harj Taggar, and Peter Thiel for reading drafts of this." }, { "path": "data/PaulGrahamEssays/fix.txt", "content": "\nKevin Kelleher suggested an interesting way to compare programming\nlanguages: to describe each in terms of the problem it\nfixes. The surprising thing is how many, and how well, languages can be\ndescribed this way.\n\nAlgol: Assembly language is too low-level.Pascal: Algol doesn't have enough data types.Modula: Pascal is too wimpy for systems programming.\nSimula: Algol isn't good enough at simulations.Smalltalk: Not everything in Simula is an object.Fortran: Assembly language is too low-level.Cobol: Fortran is scary.PL/1: Fortran doesn't have enough data types.Ada: Every existing language is missing something.Basic: Fortran is scary.APL: Fortran isn't good enough at manipulating arrays.J: APL requires its own character set.C: Assembly language is too low-level.C++: C is too low-level.Java: C++ is a kludge. And Microsoft is going to crush us.C#: Java is controlled by Sun.\nLisp: Turing Machines are an awkward way to describe computation.Scheme: MacLisp is a kludge.T: Scheme has no libraries.Common Lisp: There are too many dialects of Lisp.Dylan: Scheme has no libraries, and Lisp syntax is scary.\nPerl: Shell scripts/awk/sed are not enough like programming languages.Python: Perl is a kludge.Ruby: Perl is a kludge, and Lisp syntax is scary.Prolog: Programming is not enough like logic.\n" }, { "path": "data/PaulGrahamEssays/fn.txt", "content": "May 2021Most people think of nerds as quiet, diffident people. In ordinary\nsocial situations they are — as quiet and diffident as the star\nquarterback would be if he found himself in the middle of a physics\nsymposium. And for the same reason: they are fish out of water.\nBut the apparent diffidence of nerds is an illusion due to the fact\nthat when non-nerds observe them, it's usually in ordinary social\nsituations. In fact some nerds are quite fierce.The fierce nerds are a small but interesting group. They are as a\nrule extremely competitive — more competitive, I'd say, than highly\ncompetitive non-nerds. Competition is more personal for them. Partly\nperhaps because they're not emotionally mature enough to distance\nthemselves from it, but also because there's less randomness in the\nkinds of competition they engage in, and they are thus more justified\nin taking the results personally.Fierce nerds also tend to be somewhat overconfident, especially\nwhen young. It might seem like it would be a disadvantage to be\nmistaken about one's abilities, but empirically it isn't. Up to a\npoint, confidence is a self-fullfilling prophecy.Another quality you find in most fierce nerds is intelligence. Not\nall nerds are smart, but the fierce ones are always at least\nmoderately so. If they weren't, they wouldn't have the confidence\nto be fierce.\n[1]There's also a natural connection between nerdiness and\nindependent-mindedness. It's hard to be \nindependent-minded without\nbeing somewhat socially awkward, because conventional beliefs are\nso often mistaken, or at least arbitrary. No one who was both\nindependent-minded and ambitious would want to waste the effort it\ntakes to fit in. And the independent-mindedness of the fierce nerds\nwill obviously be of the aggressive \nrather than the passive type:\nthey'll be annoyed by rules, rather than dreamily unaware of them.I'm less sure why fierce nerds are impatient, but most seem to be.\nYou notice it first in conversation, where they tend to interrupt\nyou. This is merely annoying, but in the more promising fierce nerds\nit's connected to a deeper impatience about solving problems. Perhaps\nthe competitiveness and impatience of fierce nerds are not separate \nqualities, but two manifestations of a single underlying drivenness.When you combine all these qualities in sufficient quantities, the\nresult is quite formidable. The most vivid example of fierce nerds\nin action may be James Watson's The Double Helix. The first sentence\nof the book is \"I have never seen Francis Crick in a modest mood,\"\nand the portrait he goes on to paint of Crick is the quintessential\nfierce nerd: brilliant, socially awkward, competitive, independent-minded,\noverconfident. But so is the implicit portrait he paints of himself.\nIndeed, his lack of social awareness makes both portraits that much\nmore realistic, because he baldly states all sorts of opinions and\nmotivations that a smoother person would conceal. And moreover it's\nclear from the story that Crick and Watson's fierce nerdiness was\nintegral to their success. Their independent-mindedness caused them\nto consider approaches that most others ignored, their overconfidence\nallowed them to work on problems they only half understood (they\nwere literally described as \"clowns\" by one eminent insider), and\ntheir impatience and competitiveness got them to the answer ahead\nof two other groups that would otherwise have found it within the\nnext year, if not the next several months.\n[2]The idea that there could be fierce nerds is an unfamiliar one not\njust to many normal people but even to some young nerds. Especially\nearly on, nerds spend so much of their time in ordinary social\nsituations and so little doing real work that they get a lot more\nevidence of their awkwardness than their power. So there will be\nsome who read this description of the fierce nerd and realize \"Hmm,\nthat's me.\" And it is to you, young fierce nerd, that I now turn.I have some good news, and some bad news. The good news is that\nyour fierceness will be a great help in solving difficult problems.\nAnd not just the kind of scientific and technical problems that\nnerds have traditionally solved. As the world progresses, the number\nof things you can win at by getting the right answer increases.\nRecently getting rich became \none of them: 7 of the 8 richest people\nin America are now fierce nerds.Indeed, being a fierce nerd is probably even more helpful in business\nthan in nerds' original territory of scholarship. Fierceness seems\noptional there. Darwin for example doesn't seem to have been\nespecially fierce. Whereas it's impossible to be the CEO of a company\nover a certain size without being fierce, so now that nerds can win\nat business, fierce nerds will increasingly monopolize the really\nbig successes.The bad news is that if it's not exercised, your fierceness will\nturn to bitterness, and you will become an intellectual playground\nbully: the grumpy sysadmin, the forum troll, the \nhater, the shooter\ndown of new ideas.How do you avoid this fate? Work on ambitious projects. If you\nsucceed, it will bring you a kind of satisfaction that neutralizes\nbitterness. But you don't need to have succeeded to feel this;\nmerely working on hard projects gives most fierce nerds some\nfeeling of satisfaction. And those it doesn't, it at least keeps\nbusy.\n[3]Another solution may be to somehow turn off your fierceness, by\ndevoting yourself to meditation or psychotherapy or something like\nthat. Maybe that's the right answer for some people. I have no idea.\nBut it doesn't seem the optimal solution to me. If you're given a\nsharp knife, it seems to me better to use it than to blunt its edge\nto avoid cutting yourself.If you do choose the ambitious route, you'll have a tailwind behind\nyou. There has never been a better time to be a nerd. In the past\ncentury we've seen a continuous transfer of power from dealmakers\nto technicians — from the charismatic to the competent — and I\ndon't see anything on the horizon that will end it. At least not\ntill the nerds end it themselves by bringing about the singularity.Notes[1]\nTo be a nerd is to be socially awkward, and there are two\ndistinct ways to do that: to be playing the same game as everyone\nelse, but badly, and to be playing a different game. The smart nerds\nare the latter type.[2]\nThe same qualities that make fierce nerds so effective can\nalso make them very annoying. Fierce nerds would do well to remember\nthis, and (a) try to keep a lid on it, and (b) seek out organizations\nand types of work where getting the right answer matters more than\npreserving social harmony. In practice that means small groups\nworking on hard problems. Which fortunately is the most fun kind\nof environment anyway.[3]\nIf success neutralizes bitterness, why are there some people\nwho are at least moderately successful and yet still quite bitter?\nBecause people's potential bitterness varies depending on how\nnaturally bitter their personality is, and how ambitious they are:\nsomeone who's naturally very bitter will still have a lot left after\nsuccess neutralizes some of it, and someone who's very ambitious\nwill need proportionally more success to satisfy that ambition.So the worst-case scenario is someone who's both naturally bitter\nand extremely ambitious, and yet only moderately successful.\nThanks to Trevor Blackwell, Steve Blank, Patrick Collison, Jessica\nLivingston, Amjad Masad, and Robert Morris for reading drafts of this." }, { "path": "data/PaulGrahamEssays/founders.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nOctober 2010\n\n(I wrote this for Forbes, who asked me to write something\nabout the qualities we look for in founders. In print they had to cut\nthe last item because they didn't have room.)1. DeterminationThis has turned out to be the most important quality in startup\nfounders. We thought when we started Y Combinator that the most\nimportant quality would be intelligence. That's the myth in the\nValley. And certainly you don't want founders to be stupid. But\nas long as you're over a certain threshold of intelligence, what\nmatters most is determination. You're going to hit a lot of\nobstacles. You can't be the sort of person who gets demoralized\neasily.Bill Clerico and Rich Aberman of WePay \nare a good example. They're\ndoing a finance startup, which means endless negotiations with big,\nbureaucratic companies. When you're starting a startup that depends\non deals with big companies to exist, it often feels like they're\ntrying to ignore you out of existence. But when Bill Clerico starts\ncalling you, you may as well do what he asks, because he is not\ngoing away.\n2. FlexibilityYou do not however want the sort of determination implied by phrases\nlike \"don't give up on your dreams.\" The world of startups is so\nunpredictable that you need to be able to modify your dreams on the\nfly. The best metaphor I've found for the combination of determination\nand flexibility you need is a running back. \nHe's determined to get\ndownfield, but at any given moment he may need to go sideways or\neven backwards to get there.The current record holder for flexibility may be Daniel Gross of\nGreplin. He applied to YC with \nsome bad ecommerce idea. We told\nhim we'd fund him if he did something else. He thought for a second,\nand said ok. He then went through two more ideas before settling\non Greplin. He'd only been working on it for a couple days when\nhe presented to investors at Demo Day, but he got a lot of interest.\nHe always seems to land on his feet.\n3. ImaginationIntelligence does matter a lot of course. It seems like the type\nthat matters most is imagination. It's not so important to be able\nto solve predefined problems quickly as to be able to come up with\nsurprising new ideas. In the startup world, most good ideas \nseem\nbad initially. If they were obviously good, someone would already\nbe doing them. So you need the kind of intelligence that produces\nideas with just the right level of craziness.Airbnb is that kind of idea. \nIn fact, when we funded Airbnb, we\nthought it was too crazy. We couldn't believe large numbers of\npeople would want to stay in other people's places. We funded them\nbecause we liked the founders so much. As soon as we heard they'd\nbeen supporting themselves by selling Obama and McCain branded\nbreakfast cereal, they were in. And it turned out the idea was on\nthe right side of crazy after all.\n4. NaughtinessThough the most successful founders are usually good people, they\ntend to have a piratical gleam in their eye. They're not Goody\nTwo-Shoes type good. Morally, they care about getting the big\nquestions right, but not about observing proprieties. That's why\nI'd use the word naughty rather than evil. They delight in \nbreaking\nrules, but not rules that matter. This quality may be redundant\nthough; it may be implied by imagination.Sam Altman of Loopt \nis one of the most successful alumni, so we\nasked him what question we could put on the Y Combinator application\nthat would help us discover more people like him. He said to ask\nabout a time when they'd hacked something to their advantage—hacked in the sense of beating the system, not breaking into\ncomputers. It has become one of the questions we pay most attention\nto when judging applications.\n5. FriendshipEmpirically it seems to be hard to start a startup with just \none\nfounder. Most of the big successes have two or three. And the\nrelationship between the founders has to be strong. They must\ngenuinely like one another, and work well together. Startups do\nto the relationship between the founders what a dog does to a sock:\nif it can be pulled apart, it will be.Emmett Shear and Justin Kan of Justin.tv \nare a good example of close\nfriends who work well together. They've known each other since\nsecond grade. They can practically read one another's minds. I'm\nsure they argue, like all founders, but I have never once sensed\nany unresolved tension between them.Thanks to Jessica Livingston and Chris Steiner for reading drafts of this." }, { "path": "data/PaulGrahamEssays/foundersatwork.txt", "content": "January 2007(Foreword to Jessica Livingston's \nFounders at Work.)Apparently sprinters reach their highest speed right out of the\nblocks, and spend the rest of the race slowing down. The winners\nslow down the least. It's that way with most startups too. The\nearliest phase is usually the most productive. That's when they\nhave the really big ideas. Imagine what Apple was like when 100%\nof its employees were either Steve Jobs or Steve Wozniak.The striking thing about this phase is that it's completely different\nfrom most people's idea of what business is like. If you looked\nin people's heads (or stock photo collections) for images representing\n\"business,\" you'd get images of people dressed up in suits, groups\nsitting around conference tables looking serious, Powerpoint\npresentations, people producing thick reports for one another to\nread. Early stage startups are the exact opposite of this. And\nyet they're probably the most productive part of the whole economy.Why the disconnect? I think there's a general principle at work\nhere: the less energy people expend on performance, the more they\nexpend on appearances to compensate. More often than not the energy\nthey expend on seeming impressive makes their actual performance\nworse. A few years ago I read an article in which a car magazine\nmodified the \"sports\" model of some production car to get the fastest\npossible standing quarter mile. You know how they did it? They\ncut off all the crap the manufacturer had bolted onto the car to\nmake it look fast.Business is broken the same way that car was. The effort that goes\ninto looking productive is not merely wasted, but actually makes\norganizations less productive. Suits, for example. Suits do not\nhelp people to think better. I bet most executives at big companies\ndo their best thinking when they wake up on Sunday morning and go\ndownstairs in their bathrobe to make a cup of coffee. That's when\nyou have ideas. Just imagine what a company would be like if people\ncould think that well at work. People do in startups, at least\nsome of the time. (Half the time you're in a panic because your\nservers are on fire, but the other half you're thinking as deeply\nas most people only get to sitting alone on a Sunday morning.)Ditto for most of the other differences between startups and what\npasses for productivity in big companies. And yet conventional\nideas of professionalism have such an iron grip on our minds that\neven startup founders are affected by them. In our startup, when\noutsiders came to visit we tried hard to seem \"professional.\" We'd\nclean up our offices, wear better clothes, try to arrange that a\nlot of people were there during conventional office hours. In fact,\nprogramming didn't get done by well-dressed people at clean desks\nduring office hours. It got done by badly dressed people (I was\nnotorious for programmming wearing just a towel) in offices strewn\nwith junk at 2 in the morning. But no visitor would understand\nthat. Not even investors, who are supposed to be able to recognize\nreal productivity when they see it. Even we were affected by the\nconventional wisdom. We thought of ourselves as impostors, succeeding\ndespite being totally unprofessional. It was as if we'd created a\nFormula 1 car but felt sheepish because it didn't look like a car\nwas supposed to look.In the car world, there are at least some people who know that a\nhigh performance car looks like a Formula 1 racecar, not a sedan\nwith giant rims and a fake spoiler bolted to the trunk. Why not\nin business? Probably because startups are so small. The really\ndramatic growth happens when a startup only has three or four people,\nso only three or four people see that, whereas tens of thousands\nsee business as it's practiced by Boeing or Philip Morris.This book can help fix that problem, by showing everyone what, till\nnow, only a handful people got to see: what happens in the first\nyear of a startup. This is what real productivity looks like. This\nis the Formula 1 racecar. It looks weird, but it goes fast.Of course, big companies won't be able to do everything these\nstartups do. In big companies there's always going to be more\npolitics, and less scope for individual decisions. But seeing what\nstartups are really like will at least show other organizations\nwhat to aim for. The time may soon be coming when instead of\nstartups trying to seem more corporate, corporations will try to\nseem more like startups. That would be a good thing.\nJapanese\nTranslation\n" }, { "path": "data/PaulGrahamEssays/foundervisa.txt", "content": "\n\nApril 2009I usually avoid politics, but since we now seem to have an administration that's open to suggestions, I'm going to risk making one. The single biggest thing the government could do to increase the number of startups in this country is a policy that would cost nothing: establish a new class of visa for startup founders.The biggest constraint on the number of new startups that get created in the US is not tax policy or employment law or even Sarbanes-Oxley. It's that we won't let the people who want to start them into the country.Letting just 10,000 startup founders into the country each year could have a visible effect on the economy. If we assume 4 people per startup, which is probably an overestimate, that's 2500 new companies. Each year. They wouldn't all grow as big as Google, but out of 2500 some would come close.By definition these 10,000 founders wouldn't be taking jobs from Americans: it could be part of the terms of the visa that they couldn't work for existing companies, only new ones they'd founded. In fact they'd cause there to be \nmore jobs for Americans, because the companies they started would hire more employees as they grew.The tricky part might seem to be how one defined a startup. But that could be solved quite easily: let the market decide. Startup investors work hard to find the best startups. The government could not do better than to piggyback on their expertise, and use investment by recognized startup investors as the test of whether a company was a real startup.How would the government decide who's a startup investor? The same way they decide what counts as a university for student visas. We'll establish our own accreditation procedure. We know who one another are.10,000 people is a drop in the bucket by immigration standards, but would represent a huge increase in the pool of startup founders. I think this would have such a visible effect on the economy that it would make the legislator who introduced the bill famous. The only way to know for sure would be to try it, and that would cost practically nothing.\nThanks to Trevor Blackwell, Paul Buchheit, Jeff Clavier, David Hornik, Jessica Livingston, Greg Mcadoo, Aydin Senkut, and Fred Wilson for reading drafts of this.Related:" }, { "path": "data/PaulGrahamEssays/fp.txt", "content": "December 2019I've seen the same pattern in many different fields: even though\nlots of people have worked hard in the field, only a small fraction\nof the space of possibilities has been explored, because they've\nall worked on similar things.Even the smartest, most imaginative people are surprisingly\nconservative when deciding what to work on. People who would never\ndream of being fashionable in any other way get sucked into working\non fashionable problems.If you want to try working on unfashionable problems, one of the\nbest places to look is in fields that people think have already been\nfully explored: essays, Lisp, venture funding — you may notice a\npattern here. If you can find a new approach into a big but apparently\nplayed out field, the value of whatever you discover will be\nmultiplied by its enormous surface area.The best protection against getting drawn into working on the same\nthings as everyone else may be to genuinely \nlove what you're doing.\nThen you'll continue to work on it even if you make the same mistake\nas other people and think that it's too marginal to matter." }, { "path": "data/PaulGrahamEssays/fr.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nSeptember 2013Most startups that raise money do it more than once. A typical\ntrajectory might be (1) to get started with a few tens of thousands\nfrom something like Y Combinator or individual angels, then \n(2) raise a few hundred thousand to a few million to build the company,\nand then (3) once the company is clearly succeeding, raise one or\nmore later rounds to accelerate growth.Reality can be messier. Some companies raise money twice in phase\n2. Others skip phase 1 and go straight to phase 2. And at Y Combinator \nwe get an increasing number of companies that have already\nraised amounts in the hundreds of thousands. But the three phase\npath is at least the one about which individual startups' paths\noscillate.This essay focuses on phase 2 fundraising. That's the type the\nstartups we fund are doing on Demo Day, and this essay is the advice\nwe give them.\nForcesFundraising is hard in both senses: hard like lifting a heavy weight,\nand hard like solving a puzzle. It's hard like lifting a weight\nbecause it's intrinsically hard to convince people to part with\nlarge sums of money. That problem is irreducible; it should be\nhard. But much of the other kind of difficulty can be eliminated.\nFundraising only seems a puzzle because it's an alien world to most\nfounders, and I hope to fix that by supplying a map through it.To founders, the behavior of investors is often opaque — partly\nbecause their motivations are obscure, but partly because they\ndeliberately mislead you. And the misleading ways of investors\ncombine horribly with the wishful thinking of inexperienced founders.\nAt YC we're always warning founders about this danger, and investors\nare probably more circumspect with YC startups than with other\ncompanies they talk to, and even so we witness a constant series\nof explosions as these two volatile components combine.\n[1]If you're an inexperienced founder, the only way to survive is by\nimposing external constraints on yourself. You can't trust your\nintuitions. I'm going to give you a set of rules here that will\nget you through this process if anything will. At certain moments\nyou'll be tempted to ignore them. So rule number zero is: these\nrules exist for a reason. You wouldn't need a rule to keep you\ngoing in one direction if there weren't powerful forces pushing you\nin another.The ultimate source of the forces acting on you are the forces\nacting on investors. Investors are pinched between two kinds of\nfear: fear of investing in startups that fizzle, and fear of missing\nout on startups that take off. The cause of all this fear is the\nvery thing that makes startups such attractive investments: the\nsuccessful ones grow very fast. But that fast growth means investors\ncan't wait around. If you wait till a startup is obviously a\nsuccess, it's too late. To get the really high returns, you have\nto invest in startups when it's still unclear how they'll do. But\nthat in turn makes investors nervous they're about to invest in a\nflop. As indeed they often are.What investors would like to do, if they could, is wait. When a\nstartup is only a few months old, every week that passes gives you\nsignificantly more information about them. But if you wait too\nlong, other investors might take the deal away from you. And of\ncourse the other investors are all subject to the same forces. So\nwhat tends to happen is that they all wait as long as they can,\nthen when some act the rest have to.\nDon't raise money unless you want it and it wants you.Such a high proportion of successful startups raise money that it\nmight seem fundraising is one of the defining qualities of a startup.\nActually it isn't. Rapid growth is what\nmakes a company a startup. Most companies in a position to grow\nrapidly find that (a) taking outside money helps them grow faster,\nand (b) their growth potential makes it easy to attract such money.\nIt's so common for both (a) and (b) to be true of a successful\nstartup that practically all do raise outside money. But there may\nbe cases where a startup either wouldn't want to grow faster, or\noutside money wouldn't help them to, and if you're one of them,\ndon't raise money.The other time not to raise money is when you won't be able to. If\nyou try to raise money before you can convince\ninvestors, you'll not only waste your time, but also burn your\nreputation with those investors.\nBe in fundraising mode or not.One of the things that surprises founders most about fundraising\nis how distracting it is. When you start fundraising, everything\nelse grinds to a halt. The problem is not the time fundraising\nconsumes but that it becomes the top idea in\nyour mind. A startup can't endure that level of distraction\nfor long. An early stage startup grows mostly because the founders\nmake it grow, and if the founders look away,\ngrowth usually drops sharply.Because fundraising is so distracting, a startup should either be\nin fundraising mode or not. And when you do decide to raise money,\nyou should focus your whole attention on it so you can get it done\nquickly and get back to work.\n[2]You can take money from investors when you're not in fundraising\nmode. You just can't expend any attention on it. There are two\nthings that take attention: convincing investors, and negotiating\nwith them. So when you're not in fundraising mode, you should take\nmoney from investors only if they require no convincing, and are\nwilling to invest on terms you'll take without negotiation. For\nexample, if a reputable investor is willing to invest on a convertible\nnote, using standard paperwork, that is either uncapped or capped\nat a good valuation, you can take that without having to think.\n[3]\nThe terms will be whatever they turn out to be in your next\nequity round. And \"no convincing\" means just that: zero time spent\nmeeting with investors or preparing materials for them. If an\ninvestor says they're ready to invest, but they need you to come\nin for one meeting to meet some of the partners, tell them no, if\nyou're not in fundraising mode, because that's fundraising. \n[4]\nTell them politely; tell them you're focusing on the company right\nnow, and that you'll get back to them when you're fundraising; but\ndo not get sucked down the slippery slope.Investors will try to lure you into fundraising when you're not.\nIt's great for them if they can, because they can thereby get a\nshot at you before everyone else. They'll send you emails saying\nthey want to meet to learn more about you. If you get cold-emailed\nby an associate at a VC firm, you shouldn't meet even if you are\nin fundraising mode. Deals don't happen that way.\n[5]\nBut even\nif you get an email from a partner you should try to delay meeting\ntill you're in fundraising mode. They may say they just want to\nmeet and chat, but investors never just want to meet and chat. What\nif they like you? What if they start to talk about giving you\nmoney? Will you be able to resist having that conversation? Unless\nyou're experienced enough at fundraising to have a casual conversation\nwith investors that stays casual, it's safer to tell them that you'd\nbe happy to later, when you're fundraising, but that right now you\nneed to focus on the company.\n[6]Companies that are successful at raising money in phase 2 sometimes\ntack on a few investors after leaving fundraising mode. This is\nfine; if fundraising went well, you'll be able to do it without\nspending time convincing them or negotiating about terms.\nGet introductions to investors.Before you can talk to investors, you have to be introduced to them.\nIf you're presenting at a Demo Day, you'll be introduced to a whole\nbunch simultaneously. But even if you are, you should supplement\nthese with intros you collect yourself.Do you have to be introduced? In phase 2, yes. Some investors\nwill let you email them a business plan, but you can tell from the\nway their sites are organized that they don't really want startups\nto approach them directly.Intros vary greatly in effectiveness. The best type of intro is\nfrom a well-known investor who has just invested in you. So when\nyou get an investor to commit, ask them to introduce you to other\ninvestors they respect.\n[7]\nThe next best type of intro is from a\nfounder of a company they've funded. You can also get intros from\nother people in the startup community, like lawyers and reporters.There are now sites like AngelList, FundersClub, and WeFunder that\ncan introduce you to investors. We recommend startups treat them\nas auxiliary sources of money. Raise money first from leads you\nget yourself. Those will on average be better investors. Plus\nyou'll have an easier time raising money on these sites once you\ncan say you've already raised some from well-known investors.\nHear no till you hear yes.Treat investors as saying no till they unequivocally say yes, in\nthe form of a definite offer with no contingencies.I mentioned earlier that investors prefer to wait if they can.\nWhat's particularly dangerous for founders is the way they wait.\nEssentially, they lead you on. They seem like they're about to\ninvest right up till the moment they say no. If they even say no.\nSome of the worse ones never actually do say no; they just stop\nreplying to your emails. They hope that way to get a free option\non investing. If they decide later that they want to invest — usually\nbecause they've heard you're a hot deal — they can pretend they\njust got distracted and then restart the conversation as if they'd\nbeen about to.\n[8]That's not the worst thing investors will do. Some will use language\nthat makes it sound as if they're committing, but which doesn't\nactually commit them. And wishful thinking founders are happy to\nmeet them half way.\n[9]Fortunately, the next rule is a tactic for neutralizing this behavior.\nBut to work it depends on you not being tricked by the no that\nsounds like yes. It's so common for founders to be misled/mistaken\nabout this that we designed a protocol to fix the\nproblem. If you believe an investor has committed, get them to\nconfirm it. If you and they have different views of reality, whether\nthe source of the discrepancy is their sketchiness or your wishful\nthinking, the prospect of confirming a commitment in writing will\nflush it out. And till they confirm, regard them as saying no.\nDo breadth-first search weighted by expected value.When you talk to investors your m.o. should be breadth-first search,\nweighted by expected value. You should always talk to investors\nin parallel rather than serially. You can't afford the time it\ntakes to talk to investors serially, plus if you only talk to one\ninvestor at a time, they don't have the pressure of other investors\nto make them act. But you shouldn't pay the same attention to every\ninvestor, because some are more promising prospects than others.\nThe optimal solution is to talk to all potential investors in\nparallel, but give higher priority to the more promising ones. \n[10]Expected value = how likely an investor is to say yes, multiplied\nby how good it would be if they did. So for example, an eminent\ninvestor who would invest a lot, but will be hard to convince, might\nhave the same expected value as an obscure angel who won't invest\nmuch, but will be easy to convince. Whereas an obscure angel who\nwill only invest a small amount, and yet needs to meet multiple\ntimes before making up his mind, has very low expected value. Meet\nsuch investors last, if at all. \n[11]Doing breadth-first search weighted by expected value will save you\nfrom investors who never explicitly say no but merely drift away,\nbecause you'll drift away from them at the same rate. It protects\nyou from investors who flake in much the same way that a distributed\nalgorithm protects you from processors that fail. If some investor\nisn't returning your emails, or wants to have lots of meetings but\nisn't progressing toward making you an offer, you automatically\nfocus less on them. But you have to be disciplined about assigning\nprobabilities. You can't let how much you want an investor influence\nyour estimate of how much they want you.\nKnow where you stand.How do you judge how well you're doing with an investor, when\ninvestors habitually seem more positive than they are? By looking\nat their actions rather than their words. Every investor has some\ntrack they need to move along from the first conversation to wiring\nthe money, and you should always know what that track consists of,\nwhere you are on it, and how fast you're moving forward.Never leave a meeting with an investor without asking what happens\nnext. What more do they need in order to decide? Do they need\nanother meeting with you? To talk about what? And how soon? Do\nthey need to do something internally, like talk to their partners,\nor investigate some issue? How long do they expect it to take?\nDon't be too pushy, but know where you stand. If investors are\nvague or resist answering such questions, assume the worst; investors\nwho are seriously interested in you will usually be happy to talk\nabout what has to happen between now and wiring the money, because\nthey're already running through that in their heads. \n[12]If you're experienced at negotiations, you already know how to ask\nsuch questions.\n[13]\nIf you're not, there's a trick you can use\nin this situation. Investors know you're inexperienced at raising\nmoney. Inexperience there doesn't make you unattractive. Being a\nnoob at technology would, if you're starting a technology startup,\nbut not being a noob at fundraising. Larry and Sergey were noobs\nat fundraising. So you can just confess that you're inexperienced\nat this and ask how their process works and where you are in it.\n[14]\nGet the first commitment.The biggest factor in most investors' opinions of you is the opinion\nof other investors. Once you start getting\ninvestors to commit, it becomes increasingly easy to get more to.\nBut the other side of this coin is that it's often hard to get the\nfirst commitment.Getting the first substantial offer can be half the total difficulty\nof fundraising. What counts as a substantial offer depends on who\nit's from and how much it is. Money from friends and family doesn't\nusually count, no matter how much. But if you get $50k from a well\nknown VC firm or angel investor, that will usually be enough to set\nthings rolling.\n[15]\nClose committed money.It's not a deal till the money's in the bank. I often hear\ninexperienced founders say things like \"We've raised $800,000,\"\nonly to discover that zero of it is in the bank so far. Remember\nthe twin fears that torment investors? The fear of missing out\nthat makes them jump early, and the fear of jumping onto a turd\nthat results? This is a market where people are exceptionally prone\nto buyer's remorse. And it's also one that furnishes them plenty\nof excuses to gratify it. The public markets snap startup investing\naround like a whip. If the Chinese economy blows up tomorrow, all\nbets are off. But there are lots of surprises for individual\nstartups too, and they tend to be concentrated around fundraising.\nTomorrow a big competitor could appear, or you could get C&Ded, or\nyour cofounder could quit.\n[16]Even a day's delay can bring news that causes an investor to change\ntheir mind. So when someone commits, get the money. Knowing where\nyou stand doesn't end when they say they'll invest. After they say\nyes, know what the timetable is for getting the money, and then\nbabysit that process till it happens. Institutional investors have\npeople in charge of wiring money, but you may have to hunt angels\ndown in person to collect a check.Inexperienced investors are the ones most likely to get buyer's\nremorse. Established ones have learned to treat saying yes as like\ndiving off a diving board, and they also have more brand to preserve.\nBut I've heard of cases of even top-tier VC firms welching on deals.\nAvoid investors who don't \"lead.\"Since getting the first offer is most of the difficulty of fundraising,\nthat should be part of your calculation of expected value when you\nstart. You have to estimate not just the probability that an\ninvestor will say yes, but the probability that they'd be the first\nto say yes, and the latter is not simply a constant fraction of the\nformer. Some investors are known for deciding quickly, and those\nare extra valuable early on.Conversely, an investor who will only invest once other investors\nhave is worthless initially. And while most investors are influenced\nby how interested other investors are in you, there are some who\nhave an explicit policy of only investing after other investors\nhave. You can recognize this contemptible subspecies of investor\nbecause they often talk about \"leads.\" They say that they don't\nlead, or that they'll invest once you have a lead. Sometimes they\neven claim to be willing to lead themselves, by which they mean\nthey won't invest till you get $x from other investors. (It's great\nif by \"lead\" they mean they'll invest unilaterally, and in addition\nwill help you raise more. What's lame is when they use the term\nto mean they won't invest unless you can raise more elsewhere.)\n[17]Where does this term \"lead\" come from? Up till a few years ago,\nstartups raising money in phase 2 would usually raise equity rounds\nin which several investors invested at the same time using the same\npaperwork. You'd negotiate the terms with one \"lead\" investor, and\nthen all the others would sign the same documents and all the money\nchange hands at the closing.Series A rounds still work that way, but things now work differently\nfor most fundraising prior to the series A. Now there are rarely\nactual rounds before the A round, or leads for them. Now startups\nsimply raise money from investors one at a time till they feel they\nhave enough.Since there are no longer leads, why do investors use that term?\nBecause it's a more legitimate-sounding way of saying what they\nreally mean. All they really mean is that their interest in you\nis a function of other investors' interest in you. I.e. the spectral\nsignature of all mediocre investors. But when phrased in terms of\nleads, it sounds like there is something structural and therefore\nlegitimate about their behavior.When an investor tells you \"I want to invest in you, but I don't\nlead,\" translate that in your mind to \"No, except yes if you turn\nout to be a hot deal.\" And since that's the default opinion of any\ninvestor about any startup, they've essentially just told you\nnothing.When you first start fundraising, the expected value of an investor\nwho won't \"lead\" is zero, so talk to such investors last if at all.\nHave multiple plans.Many investors will ask how much you're planning to raise. This\nquestion makes founders feel they should be planning to raise a\nspecific amount. But in fact you shouldn't. It's a mistake to\nhave fixed plans in an undertaking as unpredictable as fundraising.So why do investors ask how much you plan to raise? For much the\nsame reasons a salesperson in a store will ask \"How much were you\nplanning to spend?\" if you walk in looking for a gift for a friend.\nYou probably didn't have a precise amount in mind; you just want\nto find something good, and if it's inexpensive, so much the better.\nThe salesperson asks you this not because you're supposed to have\na plan to spend a specific amount, but so they can show you only\nthings that cost the most you'll pay.Similarly, when investors ask how much you plan to raise, it's not\nbecause you're supposed to have a plan. It's to see whether you'd\nbe a suitable recipient for the size of investment they like to\nmake, and also to judge your ambition, reasonableness, and how far\nyou are along with fundraising.If you're a wizard at fundraising, you can say \"We plan to raise\na $7 million series A round, and we'll be accepting termsheets next\ntuesday.\" I've known a handful of founders who could pull that off\nwithout having VCs laugh in their faces. But if you're in the\ninexperienced but earnest majority, the solution is analogous to\nthe solution I recommend for pitching\nyour startup: do the right thing and then just tell investors what\nyou're doing.And the right strategy, in fundraising, is to have multiple plans\ndepending on how much you can raise. Ideally you should be able\nto tell investors something like: we can make it to profitability\nwithout raising any more money, but if we raise a few hundred\nthousand we can hire one or two smart friends, and if we raise a\ncouple million, we can hire a whole engineering team, etc.Different plans match different investors. If you're talking to a\nVC firm that only does series A rounds (though there are few of\nthose left), it would be a waste of time talking about any but your\nmost expensive plan. Whereas if you're talking to an angel who\ninvests $20k at a time and you haven't raised any money yet, you\nprobably want to focus on your least expensive plan.If you're so fortunate as to have to think about the upper limit\non what you should raise, a good rule of thumb is to multiply the\nnumber of people you want to hire times $15k times 18 months. In\nmost startups, nearly all the costs are a function of the number\nof people, and $15k per month is the conventional total cost\n(including benefits and even office space) per person. $15k per\nmonth is high, so don't actually spend that much. But it's ok to\nuse a high estimate when fundraising to add a margin for error. If\nyou have additional expenses, like manufacturing, add in those at\nthe end. Assuming you have none and you think you might hire 20\npeople, the most you'd want to raise is 20 x $15k x 18 = $5.4\nmillion.\n[18]\nUnderestimate how much you want.Though you can focus on different plans when talking to different\ntypes of investors, you should on the whole err on the side of\nunderestimating the amount you hope to raise.For example, if you'd like to raise $500k, it's better to say\ninitially that you're trying to raise $250k. Then when you reach\n$150k you're more than half done. That sends two useful signals\nto investors: that you're doing well, and that they have to decide\nquickly because you're running out of room. Whereas if you'd said\nyou were raising $500k, you'd be less than a third done at $150k.\nIf fundraising stalled there for an appreciable time, you'd start\nto read as a failure.Saying initially that you're raising $250k doesn't limit you to\nraising that much. When you reach your initial target and you still\nhave investor interest, you can just decide to raise more. Startups\ndo that all the time. In fact, most startups that are very successful\nat fundraising end up raising more than they originally intended.I'm not saying you should lie, but that you should lower your\nexpectations initially. There is almost no downside in starting\nwith a low number. It not only won't cap the amount you raise, but\nwill on the whole tend to increase it.A good metaphor here is angle of attack. If you try to fly at too\nsteep an angle of attack, you just stall. If you say right out of\nthe gate that you want to raise a $5 million series A round, unless\nyou're in a very strong position, you not only won't get that but\nwon't get anything. Better to start at a low angle of attack, build\nup speed, and then gradually increase the angle if you want.\nBe profitable if you can.You will be in a much stronger position if your collection of plans\nincludes one for raising zero dollars — i.e. if you can make\nit to profitability without raising any additional money. Ideally\nyou want to be able to say to investors \"We'll succeed no matter\nwhat, but raising money will help us do it faster.\"There are many analogies between fundraising and dating, and this\nis one of the strongest. No one wants you if you seem desperate.\nAnd the best way not to seem desperate is not to be desperate.\nThat's one reason we urge startups during YC to keep expenses low\nand to try to make it to ramen\nprofitability before Demo Day. Though it sounds slightly\nparadoxical, if you want to raise money, the best thing you can do\nis get yourself to the point where you don't need to.There are almost two distinct modes of fundraising: one in which\nfounders who need money knock on doors seeking it, knowing that\notherwise the company will die or at the very least people will\nhave to be fired, and one in which founders who don't need money\ntake some to grow faster than they could merely on their own revenues.\nTo emphasize the distinction I'm going to name them: type A fundraising\nis when you don't need money, and type B fundraising is when you\ndo.Inexperienced founders read about famous startups doing what was\ntype A fundraising, and decide they should raise money too, since\nthat seems to be how startups work. Except when they raise money\nthey don't have a clear path to profitability and are thus doing\ntype B fundraising. And they are then surprised how difficult and\nunpleasant it is.Of course not all startups can make it to ramen profitability in a\nfew months. And some that don't still manage to have the upper\nhand over investors, if they have some other advantage like\nextraordinary growth numbers or exceptionally formidable founders.\nBut as time passes it gets increasingly difficult to fundraise from\na position of strength without being profitable.\n[19]\nDon't optimize for valuation.When you raise money, what should your valuation be? The most\nimportant thing to understand about valuation is that it's not that\nimportant.Founders who raise money at high valuations tend to be unduly proud\nof it. Founders are often competitive people, and since valuation\nis usually the only visible number attached to a startup, they end\nup competing to raise money at the highest valuation. This is\nstupid, because fundraising is not the test that matters. The real\ntest is revenue. Fundraising is just a means to that end. Being\nproud of how well you did at fundraising is like being proud of\nyour college grades.Not only is fundraising not the test that matters, valuation is not\neven the thing to optimize about fundraising. The number one thing\nyou want from phase 2 fundraising is to get the money you need, so\nyou can get back to focusing on the real test, the success of your\ncompany. Number two is good investors. Valuation is at best third.The empirical evidence shows just how unimportant it is. Dropbox\nand Airbnb are the most successful companies we've funded so far,\nand they raised money after Y Combinator at premoney valuations of\n$4 million and $2.6 million respectively. Prices are so much higher\nnow that if you can raise money at all you'll probably raise it at\nhigher valuations than Dropbox and Airbnb. So let that satisfy\nyour competitiveness. You're doing better than Dropbox and Airbnb!\nAt a test that doesn't matter.When you start fundraising, your initial valuation (or valuation\ncap) will be set by the deal you make with the first investor who\ncommits. You can increase the price for later investors, if you\nget a lot of interest, but by default the valuation you got from\nthe first investor becomes your asking price.So if you're raising money from multiple investors, as most companies\ndo in phase 2, you have to be careful to avoid raising the first\nfrom an over-eager investor at a price you won't be able to\nsustain. You can of course lower your price if you need to (in\nwhich case you should give the same terms to investors who invested\nearlier at a higher price), but you may lose a bunch of leads in\nthe process of realizing you need to do this.What you can do if you have eager first investors is raise money\nfrom them on an uncapped convertible note with an MFN clause. This\nis essentially a way of saying that the valuation cap of the note\nwill be determined by the next investors you raise money from.It will be easier to raise money at a lower valuation. It shouldn't\nbe, but it is. Since phase 2 prices vary at most 10x and the big\nsuccesses generate returns of at least 100x, investors should pick\nstartups entirely based on their estimate of the probability that\nthe company will be a big success and hardly at all on price. But\nalthough it's a mistake for investors to care about price, a\nsignificant number do. A startup that investors seem to like but\nwon't invest in at a cap of $x will have an easier time at $x/2.\n[20]\nYes/no before valuation.Some investors want to know what your valuation is before they even\ntalk to you about investing. If your valuation has already been\nset by a prior investment at a specific valuation or cap, you can\ntell them that number. But if it isn't set because you haven't\nclosed anyone yet, and they try to push you to name a price, resist\ndoing so. If this would be the first investor you've closed, then\nthis could be the tipping point of fundraising. That means closing\nthis investor is the first priority, and you need to get the\nconversation onto that instead of being dragged sideways into a\ndiscussion of price.Fortunately there is a way to avoid naming a price in this situation.\nAnd it is not just a negotiating trick; it's how you (both) should\nbe operating. Tell them that valuation is not the most important\nthing to you and that you haven't thought much about it, that you\nare looking for investors you want to partner with and who want to\npartner with you, and that you should talk first about whether they\nwant to invest at all. Then if they decide they do want to invest,\nyou can figure out a price. But first things first.Since valuation isn't that important and getting fundraising rolling\nis, we usually tell founders to give the first investor who commits\nas low a price as they need to. This is a safe technique so long\nas you combine it with the next one. \n[21]\nBeware \"valuation sensitive\" investors.Occasionally you'll encounter investors who describe themselves as\n\"valuation sensitive.\" What this means in practice is that they\nare compulsive negotiators who will suck up a lot of your time\ntrying to push your price down. You should therefore never approach\nsuch investors first. While you shouldn't chase high valuations,\nyou also don't want your valuation to be set artificially low because\nthe first investor who committed happened to be a compulsive\nnegotiator. Some such investors have value, but the time to approach\nthem is near the end of fundraising, when you're in a position to\nsay \"this is the price everyone else has paid; take it or leave it\"\nand not mind if they leave it. This way, you'll not only get market\nprice, but it will also take less time.Ideally you know which investors have a reputation for being\n\"valuation sensitive\" and can postpone dealing with them till last,\nbut occasionally one you didn't know about will pop up early on.\nThe rule of doing breadth first search weighted by expected value\nalready tells you what to do in this case: slow down your interactions\nwith them.There are a handful of investors who will try to invest at a lower\nvaluation even when your price has already been set. Lowering your\nprice is a backup plan you resort to when you discover you've let\nthe price get set too high to close all the money you need. So\nyou'd only want to talk to this sort of investor if you were about\nto do that anyway. But since investor meetings have to be arranged\nat least a few days in advance and you can't predict when you'll\nneed to resort to lowering your price, this means in practice that\nyou should approach this type of investor last if at all.If you're surprised by a lowball offer, treat it as a backup offer\nand delay responding to it. When someone makes an offer in good\nfaith, you have a moral obligation to respond in a reasonable time.\nBut lowballing you is a dick move that should be met with the\ncorresponding countermove.\nAccept offers greedily.I'm a little leery of using the term \"greedily\" when writing about\nfundraising lest non-programmers misunderstand me, but a greedy\nalgorithm is simply one that doesn't try to look into the future.\nA greedy algorithm takes the best of the options in front of it\nright now. And that is how startups should approach fundraising\nin phases 2 and later. Don't try to look into the future because\n(a) the future is unpredictable, and indeed in this business you're\noften being deliberately misled about it and (b) your first priority\nin fundraising should be to get it finished and get back to work\nanyway.If someone makes you an acceptable offer, take it. If you have\nmultiple incompatible offers, take the best. Don't reject an\nacceptable offer in the hope of getting a better one in the future.These simple rules cover a wide variety of cases. If you're raising\nmoney from many investors, roll them up as they say yes. As you\nstart to feel you've raised enough, the threshold for acceptable\nwill start to get higher.In practice offers exist for stretches of time, not points. So\nwhen you get an acceptable offer that would be incompatible with\nothers (e.g. an offer to invest most of the money you need), you\ncan tell the other investors you're talking to that you have an\noffer good enough to accept, and give them a few days to make their\nown. This could lose you some that might have made an offer if\nthey had more time. But by definition you don't care; the initial\noffer was acceptable.Some investors will try to prevent others from having time to decide\nby giving you an \"exploding\" offer, meaning one that's only valid\nfor a few days. Offers from the very best investors explode less\nfrequently and less rapidly — Fred Wilson never gives exploding\noffers, for example — because they're confident you'll pick\nthem. But lower-tier investors sometimes give offers with very\nshort fuses, because they believe no one who had other options would\nchoose them. A deadline of three working days is acceptable. You\nshouldn't need more than that if you've been talking to investors\nin parallel. But a deadline any shorter is a sign you're dealing\nwith a sketchy investor. You can usually call their bluff, and you\nmay need to.\n[22]It might seem that instead of accepting offers greedily, your goal\nshould be to get the best investors as partners. That is certainly\na good goal, but in phase 2 \"get the best investors\" only rarely\nconflicts with \"accept offers greedily,\" because the best investors\ndon't usually take any longer to decide than the others. The only\ncase where the two strategies give conflicting advice is when you\nhave to forgo an offer from an acceptable investor to see if you'll\nget an offer from a better one. If you talk to investors in parallel\nand push back on exploding offers with excessively short deadlines,\nthat will almost never happen. But if it does, \"get the best\ninvestors\" is in the average case bad advice. The best investors\nare also the most selective, because they get their pick of all the\nstartups. They reject nearly everyone they talk to, which means\nin the average case it's a bad trade to exchange a definite offer\nfrom an acceptable investor for a potential offer from a better\none.(The situation is different in phase 1. You can't apply to all the\nincubators in parallel, because some offset their schedules to\nprevent this. In phase 1, \"accept offers greedily\" and \"get the\nbest investors\" do conflict, so if you want to apply to multiple\nincubators, you should do it in such a way that the ones you want\nmost decide first.)Sometimes when you're raising money from multiple investors, a\nseries A will emerge out of those conversations, and these rules\neven cover what to do in that case. When an investor starts to\ntalk to you about a series A, keep taking smaller investments till\nthey actually give you a termsheet. There's no practical difficulty.\nIf the smaller investments are on convertible notes, they'll just\nconvert into the series A round. The series A investor won't like\nhaving all these other random investors as bedfellows, but if it\nbothers them so much they should get on with giving you a termsheet.\nTill they do, you don't know for sure they will, and the greedy\nalgorithm tells you what to do.\n[23]\nDon't sell more than 25% in phase 2.If you do well, you will probably raise a series A round eventually.\nI say probably because things are changing with series A rounds.\nStartups may start to skip them. But only one company we've funded\nhas so far, so tentatively assume the path to huge passes through\nan A round.\n[24]Which means you should avoid doing things in earlier rounds that\nwill mess up raising an A round. For example, if you've sold more\nthan about 40% of your company total, it starts to get harder to\nraise an A round, because VCs worry there will not be enough stock\nleft to keep the founders motivated.Our rule of thumb is not to sell more than 25% in phase 2, on top\nof whatever you sold in phase 1, which should be less than 15%. If\nyou're raising money on uncapped notes, you'll have to guess what\nthe eventual equity round valuation might be. Guess conservatively.(Since the goal of this rule is to avoid messing up the series A,\nthere's obviously an exception if you end up raising a series A in\nphase 2, as a handful of startups do.)\nHave one person handle fundraising.If you have multiple founders, pick one to handle fundraising so\nthe other(s) can keep working on the company. And since the danger\nof fundraising is not the time taken up by the actual meetings but\nthat it becomes the top idea in your mind, the founder who handles\nfundraising should make a conscious effort to insulate the other\nfounder(s) from the details of the process.\n[25](If the founders mistrust one another, this could cause some friction.\nBut if the founders mistrust one another, you have worse problems\nto worry about than how to organize fundraising.)The founder who handles fundraising should be the CEO, who should\nin turn be the most formidable of the founders. Even if the CEO\nis a programmer and another founder is a salesperson? Yes. If you\nhappen to be that type of founding team, you're effectively a single\nfounder when it comes to fundraising.It's ok to bring all the founders to meet an investor who will\ninvest a lot, and who needs this meeting as the final step before\ndeciding. But wait till that point. Introducing an investor to\nyour cofounder(s) should be like introducing a girl/boyfriend to\nyour parents — something you do only when things reach a certain\nstage of seriousness.Even if there are still one or more founders focusing on the company\nduring fundraising, growth will slow. But try to get as much growth\nas you can, because fundraising is a segment of time, not a point,\nand what happens to the company during that time affects the outcome.\nIf your numbers grow significantly between two investor meetings,\ninvestors will be hot to close, and if your numbers are flat or\ndown they'll start to get cold feet.\nYou'll need an executive summary and (maybe) a deck.Traditionally phase 2 fundraising consists of presenting a slide\ndeck in person to investors. Sequoia describes what such a deck\nshould contain, and\nsince they're the customer you can take their word for it.I say \"traditionally\" because I'm ambivalent about decks, and (though\nperhaps this is wishful thinking) they seem to be on the way out.\nA lot of the most successful startups we fund never make decks in\nphase 2. They just talk to investors and explain what they plan\nto do. Fundraising usually takes off fast for the startups that\nare most successful at it, and they're thus able to excuse themselves\nby saying that they haven't had time to make a deck.You'll also want an executive summary, which should be no more than\na page long and describe in the most matter of fact language what\nyou plan to do, why it's a good idea, and what progress you've made\nso far. The point of the summary is to remind the investor (who\nmay have met many startups that day) what you talked about.Assume that if you give someone a copy of your deck or executive\nsummary, it will be passed on to whoever you'd least like to have\nit. But don't refuse on that account to give copies to investors\nyou meet. You just have to treat such leaks as a cost of doing\nbusiness. In practice it's not that high a cost. Though founders\nare rightly indignant when their plans get leaked to competitors,\nI can't think of a startup whose outcome has been affected by it.Sometimes an investor will ask you to send them your deck and/or\nexecutive summary before they decide whether to meet with you. I\nwouldn't do that. It's a sign they're not really interested.\nStop fundraising when it stops working.When do you stop fundraising? Ideally when you've raised enough.\nBut what if you haven't raised as much as you'd like? When do you\ngive up?It's hard to give general advice about this, because there have\nbeen cases of startups that kept trying to raise money even when\nit seemed hopeless, and miraculously succeeded. But what I usually\ntell founders is to stop fundraising when you start to get a lot\nof air in the straw. When you're drinking through a straw, you can\ntell when you get to the end of the liquid because you start to get\na lot of air in the straw. When your fundraising options run out,\nthey usually run out in the same way. Don't keep sucking on the\nstraw if you're just getting air. It's not going to get better.\nDon't get addicted to fundraising.Fundraising is a chore for most founders, but some find it more\ninteresting than working on their startup. The work at an early\nstage startup often consists of unglamorous schleps. Whereas fundraising, when it's\ngoing well, can be quite the opposite. Instead of sitting in your\ngrubby apartment listening to users complain about bugs in your\nsoftware, you're being offered millions of dollars by famous investors\nover lunch at a nice restaurant.\n[26]The danger of fundraising is particularly acute for people who are\ngood at it. It's always fun to work on something you're good at.\nIf you're one of these people, beware. Fundraising is not what\nwill make your company successful. Listening to users complain\nabout bugs in your software is what will make you successful. And\nthe big danger of getting addicted to fundraising is not merely\nthat you'll spend too long on it or raise too much money. It's\nthat you'll start to think of yourself as being already successful,\nand lose your taste for the schleps you need to undertake to actually\nbe successful. Startups can be destroyed by this.When I see a startup with young founders that is fabulously successful\nat fundraising, I mentally decrease my estimate of the probability\nthat they'll succeed. The press may be writing about them as if\nthey'd been anointed as the next Google, but I'm thinking \"this is\ngoing to end badly.\"\nDon't raise too much.Though only a handful of startups have to worry about this, it is\npossible to raise too much. The dangers of raising too much are\nsubtle but insidious. One is that it will set impossibly high\nexpectations. If you raise an excessive amount of money, it will\nbe at a high valuation, and the danger of raising money at too high\na valuation is that you won't be able to increase it sufficiently\nthe next time you raise money.A company's valuation is expected to rise each time it raises money.\nIf not it's a sign of a company in trouble, which makes you\nunattractive to investors. So if you raise money in phase 2 at a\npost-money valuation of $30 million, the pre-money valuation of\nyour next round, if you want to raise one, is going to have to be\nat least $50 million. And you have to be doing really, really well\nto raise money at $50 million.It's very dangerous to let the competitiveness of your current round\nset the performance threshold you have to meet to raise your next\none, because the two are only loosely coupled.But the money itself may be more dangerous than the valuation. The\nmore you raise, the more you spend, and spending a lot of money can\nbe disastrous for an early stage startup. Spending a lot makes it\nharder to become profitable, and perhaps even worse, it makes you\nmore rigid, because the main way to spend money is people, and the\nmore people you have, the harder it is to change directions. So\nif you do raise a huge amount of money, don't spend it. (You will\nfind that advice almost impossible to follow, so hot will be the\nmoney burning a hole in your pocket, but I feel obliged at least\nto try.)\nBe nice.Startups raising money occasionally alienate investors by seeming\narrogant. Sometimes because they are arrogant, and sometimes because\nthey're noobs clumsily attempting to mimic the toughness they've\nobserved in experienced founders.It's a mistake to behave arrogantly to investors. While there are\ncertain situations in which certain investors like certain kinds\nof arrogance, investors vary greatly in this respect, and a flick\nof the whip that will bring one to heel will make another roar with\nindignation. The only safe strategy is never to seem arrogant at\nall.That will require some diplomacy if you follow the advice I've given\nhere, because the advice I've given is essentially how to play\nhardball back. When you refuse to meet an investor because you're\nnot in fundraising mode, or slow down your interactions with an\ninvestor who moves too slow, or treat a contingent offer as the no\nit actually is and then, by accepting offers greedily, end up leaving\nthat investor out, you're going to be doing things investors don't\nlike. So you must cushion the blow with soft words. At YC we tell\nstartups they can blame us. And now that I've written this, everyone\nelse can blame me if they want. That plus the inexperience card\nshould work in most situations: sorry, we think you're great, but\nPG said startups shouldn't ___, and since we're new to fundraising,\nwe feel like we have to play it safe.The danger of behaving arrogantly is greatest when you're doing\nwell. When everyone wants you, it's hard not to let it go to your\nhead. Especially if till recently no one wanted you. But restrain\nyourself. The startup world is a small place, and startups have\nlots of ups and downs. This is a domain where it's more true than\nusual that pride goeth before a fall.\n[27]Be nice when investors reject you as well. The best investors are\nnot wedded to their initial opinion of you. If they reject you in\nphase 2 and you end up doing well, they'll often invest in phase\n3. In fact investors who reject you are some of your warmest leads\nfor future fundraising. Any investor who spent significant time\ndeciding probably came close to saying yes. Often you have some\ninternal champion who only needs a little more evidence to convince\nthe skeptics. So it's wise not merely to be nice to investors who\nreject you, but (unless they behaved badly) to treat it as the\nbeginning of a relationship.\nThe bar will be higher next time.Assume the money you raise in phase 2 will be the last you ever\nraise. You must make it to profitability on this money if you can.Over the past several years, the investment community has evolved\nfrom a strategy of anointing a small number of winners early and\nthen supporting them for years to a strategy of spraying money at\nearly stage startups and then ruthlessly culling them at the next\nstage. This is probably the optimal strategy for investors. It's\ntoo hard to pick winners early on. Better to let the market do it\nfor you. But it often comes as a surprise to startups how much\nharder it is to raise money in phase 3.When your company is only a couple months old, all it has to be is\na promising experiment that's worth funding to see how it turns\nout. The next time you raise money, the experiment has to have\nworked. You have to be on a trajectory that leads to going public.\nAnd while there are some ideas where the proof that the experiment\nworked might consist of e.g. query response times, usually the proof\nis profitability. Usually phase 3 fundraising has to be type A\nfundraising.In practice there are two ways startups hose themselves between\nphases 2 and 3. Some are just too slow to become profitable. They\nraise enough money to last for two years. There doesn't seem any\nparticular urgency to be profitable. So they don't make any effort\nto make money for a year. But by that time, not making money has\nbecome habitual. When they finally decide to try, they find they\ncan't.The other way companies hose themselves is by letting their expenses\ngrow too fast. Which almost always means hiring too many people.\nYou usually shouldn't go out and hire 8 people as soon as you raise\nmoney at phase 2. Usually you want to wait till you have growth\n(and thus usually revenues) to justify them. A lot of VCs will\nencourage you to hire aggressively. VCs generally tell you to spend\ntoo much, partly because as money people they err on the side of\nsolving problems by spending money, and partly because they want\nyou to sell them more of your company in subsequent rounds. Don't\nlisten to them.\nDon't make things complicated.I realize it may seem odd to sum up this huge treatise by saying\nthat my overall advice is not to make fundraising too complicated,\nbut if you go back and look at this list you'll see it's basically\na simple recipe with a lot of implications and edge cases. Avoid\ninvestors till you decide to raise money, and then when you do,\ntalk to them all in parallel, prioritized by expected value, and\naccept offers greedily. That's fundraising in one sentence. Don't\nintroduce complicated optimizations, and don't let investors introduce\ncomplications either.Fundraising is not what will make you successful. It's just a means\nto an end. Your primary goal should be to get it over with and get\nback to what will make you successful — making things and talking\nto users — and the path I've described will for most startups\nbe the surest way to that destination.Be good, take care of yourselves, and don't leave the path.\nNotes[1]\nThe worst explosions happen when unpromising-seeming startups\nencounter mediocre investors. Good investors don't lead startups\non; their reputations are too valuable. And startups that seem\npromising can usually get enough money from good investors that\nthey don't have to talk to mediocre ones. It is the unpromising-seeming\nstartups that have to resort to raising money from mediocre investors.\nAnd it's particularly damaging when these investors flake, because\nunpromising-seeming startups are usually more desperate for money.(Not all unpromising-seeming startups do badly. Some are merely\nugly ducklings in the sense that they violate current startup\nfashions.)[2]\nOne YC founder told me:\n\n I think in general we've done ok at fundraising, but I managed\n to screw up twice at the exact same thing — trying to focus\n on building the company and fundraising at the same time.\n\n[3]\nThere is one subtle danger you have to watch out for here, which\nI warn about later: beware of getting too high a valuation from an\neager investor, lest that set an impossibly high target when raising\nadditional money.[4]\nIf they really need a meeting, then they're not ready to invest,\nregardless of what they say. They're still deciding, which means\nyou're being asked to come in and convince them. Which is fundraising.[5]\nAssociates at VC firms regularly cold email startups. Naive\nfounders think \"Wow, a VC is interested in us!\" But an associate\nis not a VC. They have no decision-making power. And while they\nmay introduce startups they like to partners at their firm, the\npartners discriminate against deals that come to them this way. I\ndon't know of a single VC investment that began with an associate\ncold-emailing a startup. If you want to approach a specific firm,\nget an intro to a partner from someone they respect.It's ok to talk to an associate if you get an intro to a VC firm\nor they see you at a Demo Day and they begin by having an associate\nvet you. That's not a promising lead and should therefore get low\npriority, but it's not as completely worthless as a cold email.Because the title \"associate\" has gotten a bad reputation, a few\nVC firms have started to give their associates the title \"partner,\"\nwhich can make things very confusing. If you're a YC startup you\ncan ask us who's who; otherwise you may have to do some research\nonline. There may be a special title for actual partners. If\nsomeone speaks for the firm in the press or a blog on the firm's\nsite, they're probably a real partner. If they're on boards of\ndirectors they're probably a real partner.There are titles between \"associate\" and \"partner,\" including\n\"principal\" and \"venture partner.\" The meanings of these titles\nvary too much to generalize.[6]\nFor similar reasons, avoid casual conversations with potential\nacquirers. They can lead to distractions even more dangerous than\nfundraising. Don't even take a meeting with a potential acquirer\nunless you want to sell your company right now.[7]\nJoshua Reeves specifically suggests asking each investor to\nintro you to two more investors.Don't ask investors who say no for introductions to other investors.\nThat will in many cases be an anti-recommendation.[8]\nThis is not always as deliberate as its sounds. A lot of the\ndelays and disconnects between founders and investors are induced\nby the customs of the venture business, which have evolved the way\nthey have because they suit investors' interests.[9]\nOne YC founder who read a draft of this essay wrote:\n\n This is the most important section. I think it might bear stating\n even more clearly. \"Investors will deliberately affect more\n interest than they have to preserve optionality. If an investor\n seems very interested in you, they still probably won't invest.\n The solution for this is to assume the worst — that an investor\n is just feigning interest — until you get a definite commitment.\"\n\n[10]\nThough you should probably pack investor meetings as closely\nas you can, Jeff Byun mentions one reason not to: if you pack\ninvestor meetings too closely, you'll have less time for your pitch\nto evolve.Some founders deliberately schedule a handful of lame investors\nfirst, to get the bugs out of their pitch.[11]\nThere is not an efficient market in this respect. Some of the\nmost useless investors are also the highest maintenance.[12]\nIncidentally, this paragraph is sales 101. If you want to see\nit in action, go talk to a car dealer.[13]\nI know one very smooth founder who used to end investor meetings\nwith \"So, can I count you in?\" delivered as if it were \"Can you\npass the salt?\" Unless you're very smooth (if you're not sure...),\ndo not do this yourself. There is nothing more unconvincing, for\nan investor, than a nerdy founder trying to deliver the lines meant\nfor a smooth one.Investors are fine with funding nerds. So if you're a nerd, just\ntry to be a good nerd, rather than doing a bad imitation of a smooth\nsalesman.[14]\nIan Hogarth suggests a good way to tell how serious potential\ninvestors are: the resources they expend on you after the first\nmeeting. An investor who's seriously interested will already be\nworking to help you even before they've committed.[15]\nIn principle you might have to think about so-called \"signalling\nrisk.\" If a prestigious VC makes a small seed investment in you,\nwhat if they don't want to invest the next time you raise money?\nOther investors might assume that the VC knows you well, since\nthey're an existing investor, and if they don't want to invest in\nyour next round, that must mean you suck. The reason I say \"in\nprinciple\" is that in practice signalling hasn't been much of a\nproblem so far. It rarely arises, and in the few cases where it\ndoes, the startup in question usually is doing badly and is doomed\nanyway.If you have the luxury of choosing among seed investors, you can\nplay it safe by excluding VC firms. But it isn't critical to.[16]\nSometimes a competitor will deliberately threaten you with a\nlawsuit just as you start fundraising, because they know you'll\nhave to disclose the threat to potential investors and they hope\nthis will make it harder for you to raise money. If this happens\nit will probably frighten you more than investors. Experienced\ninvestors know about this trick, and know the actual lawsuits rarely\nhappen. So if you're attacked in this way, be forthright with\ninvestors. They'll be more alarmed if you seem evasive than if you\ntell them everything.[17]\nA related trick is to claim that they'll only invest contingently\non other investors doing so because otherwise you'd be \"undercapitalized.\"\nThis is almost always bullshit. They can't estimate your minimum\ncapital needs that precisely.[18]\nYou won't hire all those 20 people at once, and you'll probably\nhave some revenues before 18 months are out. But those too are\nacceptable or at least accepted additions to the margin for error.[19]\nType A fundraising is so much better that it might even be\nworth doing something different if it gets you there sooner. One\nYC founder told me that if he were a first-time founder again he'd\n\"leave ideas that are up-front capital intensive to founders with\nestablished reputations.\"[20]\nI don't know whether this happens because they're innumerate,\nor because they believe they have zero ability to predict startup\noutcomes (in which case this behavior at least wouldn't be irrational).\nIn either case the implications are similar.[21]\nIf you're a YC startup and you have an investor who for some\nreason insists that you decide the price, any YC partner can estimate\na market price for you.[22]\nYou should respond in kind when investors behave upstandingly\ntoo. When an investor makes you a clean offer with no deadline,\nyou have a moral obligation to respond promptly.[23]\nTell the investors talking to you about an A round about the\nsmaller investments you raise as you raise them. You owe them such\nupdates on your cap table, and this is also a good way to pressure\nthem to act. They won't like you raising other money and may\npressure you to stop, but they can't legitimately ask you to commit\nto them till they also commit to you. If they want you to stop\nraising money, the way to do it is to give you a series A termsheet\nwith a no-shop clause.You can relent a little if the potential series A investor has a\ngreat reputation and they're clearly working fast to get you a\ntermsheet, particularly if a third party like YC is involved to\nensure there are no misunderstandings. But be careful.[24]\nThe company is Weebly, which made it to profitability on a\nseed investment of $650k. They did try to raise a series A in the\nfall of 2008 but (no doubt partly because it was the fall of 2008)\nthe terms they were offered were so bad that they decided to skip\nraising an A round.[25]\nAnother advantage of having one founder take fundraising\nmeetings is that you never have to negotiate in real time, which\nis something inexperienced founders should avoid. One YC founder\ntold me:\n\n Investors are professional negotiators and can negotiate on the\n spot very easily. If only one founder is in the room, you can\n say \"I need to circle back with my co-founder\" before making any\n commitments. I used to do this all the time.\n\n[26]\nYou'll be lucky if fundraising feels pleasant enough to become\naddictive. More often you have to worry about the other\nextreme — becoming demoralized when investors reject you. As\none (very successful) YC founder wrote after reading a draft of\nthis:\n\n It's hard to mentally deal with the sheer scale of rejection in\n fundraising and if you are not in the right mindset you will fail.\n Users may love you but these supposedly smart investors may not\n understand you at all. At this point for me, rejection still\n rankles but I've come to accept that investors are just not super\n thoughtful for the most part and you need to play the game according\n to certain somewhat depressing rules (many of which you are\n listing) in order to win.\n\n[27]\nThe actual sentence in the King James Bible is \"Pride goeth\nbefore destruction, and an haughty spirit before a fall.\"Thanks to Slava Akhmechet, Sam Altman, Nate Blecharczyk,\nAdora Cheung, Bill Clerico, John Collison, Patrick Collison, Parker\nConrad, Ron Conway, Travis Deyle, Jason Freedman, Joe Gebbia, Mattan\nGriffel, Kevin Hale, Jacob Heller, Ian Hogarth, Justin Kan, Professor\nMoriarty, Nikhil Nirmel, David Petersen, Geoff Ralston, Joshua\nReeves, Yuri Sagalov, Emmett Shear, Rajat Suri, Garry Tan, and Nick\nTomarello for reading drafts of this." }, { "path": "data/PaulGrahamEssays/fundraising.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nAugust 2008Raising money is the second hardest part of starting a startup.\nThe hardest part is making something people want: most startups\nthat die, die because they didn't do that. But the second biggest\ncause of death is probably the difficulty of raising money.\nFundraising is brutal.One reason it's so brutal is simply the brutality of markets. People\nwho've spent most of their lives in schools or big companies may\nnot have been exposed to that. Professors and bosses usually feel\nsome sense of responsibility toward you; if you make a valiant\neffort and fail, they'll cut you a break. Markets are less forgiving.\nCustomers don't care how hard you worked, only whether you solved\ntheir problems.Investors evaluate startups the way customers evaluate products,\nnot the way bosses evaluate employees. If you're making a valiant\neffort and failing, maybe they'll invest in your next startup, but\nnot this one.But raising money from investors is harder than selling to\ncustomers, because there are so few of them. There's\nnothing like an efficient market. You're unlikely to have more\nthan 10 who are interested; it's difficult to talk to more. So the\nrandomness of any one investor's behavior can really affect you.Problem number 3: investors are very random. All investors, including\nus, are by ordinary standards incompetent. We constantly have to\nmake decisions about things we don't understand, and more often\nthan not we're wrong.And yet a lot is at stake. The amounts invested by different types\nof investors vary from five thousand dollars to fifty million, but\nthe amount usually seems large for whatever type of investor it is.\nInvestment decisions are big decisions.That combination—making big decisions about things they don't\nunderstand—tends to make investors very skittish. VCs are notorious\nfor leading founders on. Some of the more unscrupulous do it\ndeliberately. But even the most well-intentioned investors can\nbehave in a way that would seem crazy in everyday life. One day\nthey're full of enthusiasm and seem ready to write you a check on\nthe spot; the next they won't return your phone calls. They're not\nplaying games with you. They just can't make up their minds.\n[1]If that weren't bad enough, these wildly fluctuating nodes are all\nlinked together. Startup investors all know one another, and (though\nthey hate to admit it) the biggest factor in their opinion of you\nis the opinion of other investors. \n[2]\nTalk about a recipe for\nan unstable system. You get the opposite of the damping that the\nfear/greed balance usually produces in markets. No one is interested\nin a startup that's a \"bargain\" because everyone else hates it.So the inefficient market you get because there are so few players\nis exacerbated by the fact that they act less than independently.\nThe result is a system like some kind of primitive, multi-celled\nsea creature, where you irritate one extremity and the whole thing\ncontracts violently.Y Combinator is working to fix this. We're trying to increase the\nnumber of investors just as we're increasing the number of startups.\nWe hope that as the number of both increases we'll get something\nmore like an efficient market. As t approaches infinity, Demo Day\napproaches an auction.Unfortunately, t is still very far from infinity. What does a\nstartup do now, in the imperfect world we currently inhabit? The\nmost important thing is not to let fundraising get you down. Startups\nlive or die on morale. If you let the difficulty of raising money\ndestroy your morale, it will become a self-fulfilling prophecy.\nBootstrapping (= Consulting)Some would-be founders may by now be thinking, why deal with investors\nat all? If raising money is so painful, why do it?One answer to that is obvious: because you need money to live on.\nIt's a fine idea in principle to finance your startup with its own\nrevenues, but you can't create instant customers. Whatever you\nmake, you have to sell a certain amount to break even. It will\ntake time to grow your sales to that point, and it's hard to predict,\ntill you try, how long it will take.We could not have bootstrapped Viaweb, for example. We charged\nquite a lot for our software—about $140 per user per month—but\nit was at least a year before our revenues would have covered even\nour paltry costs. We didn't have enough saved to live on for a\nyear.If you factor out the \"bootstrapped\" companies that were actually\nfunded by their founders through savings or a day job, the remainder\neither (a) got really lucky, which is hard to do on demand, or (b)\nbegan life as consulting companies and gradually transformed\nthemselves into product companies.Consulting is the only option you can count on. But consulting is\nfar from free money. It's not as painful as raising money from\ninvestors, perhaps, but the pain is spread over a longer period.\nYears, probably. And for many types of startup, that delay could\nbe fatal. If you're working on something so unusual that no one\nelse is likely to think of it, you can take your time. Joshua\nSchachter gradually built Delicious on the side while working on\nWall Street. He got away with it because no one else realized it\nwas a good idea. But if you were building something as obviously\nnecessary as online store software at about the same time as Viaweb,\nand you were working on it on the side while spending most of your\ntime on client work, you were not in a good position.Bootstrapping sounds great in principle, but this apparently verdant\nterritory is one from which few startups emerge alive. The mere\nfact that bootstrapped startups tend to be famous on that account\nshould set off alarm bells. If it worked so well, it would be the\nnorm.\n[3]\nBootstrapping may get easier, because starting a company is getting\ncheaper. But I don't think we'll ever reach the point where most\nstartups can do without outside funding. Technology tends to\nget dramatically cheaper, but living expenses don't.The upshot is, you can choose your pain: either the short, sharp\npain of raising money, or the chronic ache of consulting. For a\ngiven total amount of pain, raising money is the better choice,\nbecause new technology is usually more valuable now than later.But although for most startups raising money will be the lesser\nevil, it's still a pretty big evil—so big that it can easily kill\nyou. Not merely in the obvious sense that if you fail to raise\nmoney you might have to shut the company down, but because the\nprocess of raising money itself can kill you.To survive it you need a set of techniques mostly\northogonal to the ones used in convincing investors, just as mountain\nclimbers need to know survival techniques that are mostly orthogonal\nto those used in physically getting up and down mountains.\n1. Have low expectations.The reason raising money destroys so many startups' morale is not\nsimply that it's hard, but that it's so much harder than they\nexpected. What kills you is the disappointment. And the lower\nyour expectations, the harder it is to be disappointed.Startup founders tend to be optimistic. This can work well in\ntechnology, at least some of the time, but it's the wrong way to\napproach raising money. Better to assume investors will always let\nyou down. Acquirers too, while we're at it. At YC one of our\nsecondary mantras is \"Deals fall through.\" No matter what deal\nyou have going on, assume it will fall through. The predictive\npower of this simple rule is amazing.There will be a tendency, as a deal progresses, to start to believe\nit will happen, and then to depend on it happening. You must resist\nthis. Tie yourself to the mast. This is what kills you. Deals\ndo not have a trajectory like most other human interactions, where\nshared plans solidify linearly over time. Deals often fall through\nat the last moment. Often the other party doesn't really think\nabout what they want till the last moment. So you can't use your\neveryday intuitions about shared plans as a guide. When it comes\nto deals, you have to consciously turn them off and become\npathologically cynical.This is harder to do than it sounds. It's very flattering when\neminent investors seem interested in funding you. It's easy to\nstart to believe that raising money will be quick and straightforward.\nBut it hardly ever is.\n2. Keep working on your startup.It sounds obvious to say that you should keep working on your startup\nwhile raising money. Actually this is hard to do. Most startups\ndon't manage to.Raising money has a mysterious capacity to suck up all your attention.\nEven if you only have one meeting a day with investors, somehow\nthat one meeting will burn up your whole day. It costs not just\nthe time of the actual meeting, but the time getting there and back,\nand the time preparing for it beforehand and thinking about it\nafterward.The best way to survive the distraction of meeting with investors\nis probably to partition the company: to pick one founder to deal\nwith investors while the others keep the company going. This works\nbetter when a startup has 3 founders than 2, and better when the\nleader of the company is not also the lead developer. In the best\ncase, the company keeps moving forward at about half speed.That's the best case, though. More often than not the company comes\nto a standstill while raising money. And that is dangerous for so\nmany reasons. Raising money always takes longer than you expect.\nWhat seems like it's going to be a 2 week interruption turns into\na 4 month interruption. That can be very demoralizing. And worse\nstill, it can make you less attractive to investors. They want to\ninvest in companies that are dynamic. A company that hasn't done\nanything new in 4 months doesn't seem dynamic, so they start to\nlose interest. Investors rarely grasp this, but much of what\nthey're responding to when they lose interest in a startup is the\ndamage done by their own indecision.The solution: put the startup first. Fit meetings with investors\ninto the spare moments in your development schedule, rather than\ndoing development in the spare moments between meetings with\ninvestors. If you keep the company moving forward—releasing new\nfeatures, increasing traffic, doing deals, getting written \nabout—those investor meetings are more likely to be productive. Not just\nbecause your startup will seem more alive, but also because it will\nbe better for your own morale, which is one of the main ways investors\njudge you.\n3. Be conservative.As conditions get worse, the optimal strategy becomes more conservative.\nWhen things go well you can take risks; when things are bad you\nwant to play it safe.I advise approaching fundraising as if it were always going badly.\nThe reason is that between your ability to delude yourself and the\nwildly unstable nature of the system you're dealing with, things\nprobably either already are or could easily become much worse than\nthey seem.What I tell most startups we fund is that if someone reputable\noffers you funding on reasonable terms, take it. There have been\nstartups that ignored this advice and got away with it—startups\nthat ignored a good offer in the hope of getting a better one, and\nactually did. But in the same position I'd give the same advice\nagain. Who knows how many bullets were in the gun they were playing\nRussian roulette with?Corollary: if an investor seems interested, don't just let them\nsit. You can't assume someone interested in investing will stay\ninterested. In fact, you can't even tell (they can't even tell)\nif they're really interested till you try to convert that interest\ninto money. So if you have hot prospect, either close them now or\nwrite them off. And unless you already have enough funding, that\nreduces to: close them now.Startups don't win by getting great funding rounds, but by making\ngreat products. So finish raising money and get\nback to work.\n4. Be flexible.There are two questions VCs ask that you shouldn't answer: \"Who\nelse are you talking to?\" and \"How much are you trying to raise?\"VCs don't expect you to answer the first question. They ask it just\nin case. \n[4]\nThey do seem to expect an answer to the second. But\nI don't think you should just tell them a number. Not as a way to\nplay games with them, but because you shouldn't have a fixed\namount you need to raise.The custom of a startup needing a fixed amount of funding is an\nobsolete one left over from the days when startups were more\nexpensive. A company that needed to build a factory or hire 50\npeople obviously needed to raise a certain minimum amount. But few\ntechnology startups are in that position today.We advise startups to tell investors there are several different\nroutes they could take depending on how much they raised. As little\nas $50k could pay for food and rent for the founders for a year.\nA couple hundred thousand would let them get office space and hire\nsome smart people they know from school. A couple million would\nlet them really blow this thing out. The message (and not just the\nmessage, but the fact) should be: we're going to succeed no matter\nwhat. Raising more money just lets us do it faster.If you're raising an angel round, the size of the round can even\nchange on the fly. In fact, it's just as well to make the round\nsmall initially, then expand as needed, rather than trying to raise\na large round and risk losing the investors you already have if you\ncan't raise the full amount. You may even want to do a \"rolling\nclose,\" where the round has no predetermined size, but instead you\nsell stock to investors one at a time as they say yes. That helps\nbreak deadlocks, because you can start as soon as the first one\nis ready to buy. \n[5]\n5. Be independent.A startup with a couple founders in their early twenties can have\nexpenses so low that they could be profitable on\nas little as $2000 per month. That's negligible as corporate\nrevenues go, but the effect on your morale and your bargaining\nposition is anything but. At YC we use the phrase \"ramen profitable\"\nto describe the situation where you're making just enough to pay\nyour living expenses. Once you cross into ramen profitable,\neverything changes. You may still need investment to make it big,\nbut you don't need it this month.You can't plan when you start a startup how long\nit will take to become profitable. But if you find yourself in a\nposition where a little more effort expended on sales would carry\nyou over the threshold of ramen profitable, do it.Investors like it when you're ramen profitable. It shows you've\nthought about making money, instead of just working on amusing\ntechnical problems; it shows you have the discipline to keep your\nexpenses low; but above all, it means you don't need them.There is nothing investors like more than a startup that seems like\nit's going to succeed even without them. Investors like it when\nthey can help a startup, but they don't like startups that would\ndie without that help.At YC we spend a lot of time trying to predict how the startups we've\nfunded will do, because we're trying to learn how to pick winners.\nWe've now watched the trajectories of so many startups that we're\ngetting better at predicting them. And when we're talking\nabout startups we think are likely to succeed, what we find ourselves\nsaying is things like \"Oh, those guys can take care of themselves.\nThey'll be fine.\" Not \"those guys are really smart\" or\n\"those guys are working on a great idea.\"\n[6]\nWhen we predict good outcomes for startups, the qualities\nthat come up in the supporting arguments are toughness, adaptability,\ndetermination. Which means to the extent we're correct, those are\nthe qualities you need to win.Investors know this, at least unconsciously. The reason they like\nit when you don't need them is not simply that they like what they\ncan't have, but because that quality is what makes founders succeed.Sam Altman \nhas it. You could parachute him into an island full of\ncannibals and come back in 5 years and he'd be the king. If you're\nSam Altman, you don't have to be profitable to convey to investors\nthat you'll succeed with or without them. (He wasn't, and he did.)\nNot everyone has Sam's deal-making ability. I myself don't. But\nif you don't, you can let the numbers speak for you.\n6. Don't take rejection personally.Getting rejected by investors can make you start to doubt yourself.\nAfter all, they're more experienced than you. If they think your\nstartup is lame, aren't they probably right?Maybe, maybe not. The way to handle rejection is with precision.\nYou shouldn't simply ignore rejection. It might mean something.\nBut you shouldn't automatically get demoralized either.To understand what rejection means, you have to understand first\nof all how common it is. Statistically, the average VC is a rejection\nmachine. David Hornik, a partner at August, told me:\n\n The numbers for me ended up being something like 500 to 800 plans\n received and read, somewhere between 50 and 100 initial 1 hour\n meetings held, about 20 companies that I got interested in, about\n 5 that I got serious about and did a bunch of work, 1 to 2 deals\n done in a year. So the odds are against you. You\n may be a great entrepreneur, working on interesting stuff, etc.\n but it is still incredibly unlikely that you get funded.\n\nThis is less true with angels, but VCs reject practically everyone.\nThe structure of their business means a partner does at most 2 new\ninvestments a year, no matter how many good startups approach him.In addition to the odds being terrible, the average investor is,\nas I mentioned, a pretty bad judge of startups. It's harder to\njudge startups than most other things, because great startup ideas\ntend to seem wrong. A good startup idea has to be not just good but\nnovel. And to be both good and novel, an idea probably has to seem\nbad to most people, or someone would already be doing it and it\nwouldn't be novel.That makes judging startups harder than most other things one judges.\nYou have to be an intellectual contrarian to be a good startup\ninvestor. That's a problem for VCs, most of whom are not particularly\nimaginative. VCs are mostly money guys, not people who make things.\n[7]\nAngels are better at appreciating novel ideas, because most\nwere founders themselves.So when you get a rejection, use the data that's in it, and not what's\nnot. If an investor gives you specific reasons for not investing,\nlook at your startup and ask if they're right. If they're real\nproblems, fix them. But don't just take their word for it. You're\nsupposed to be the domain expert; you have to decide.Though a rejection doesn't necessarily tell you anything about your\nstartup, it does suggest your pitch could be improved. Figure out\nwhat's not working and change it. Don't just think \"investors are\nstupid.\" Often they are, but figure out precisely where you lose\nthem.Don't let rejections pile up as a depressing, undifferentiated heap.\nSort them and analyze them, and then instead of thinking \"no one\nlikes us,\" you'll know precisely how big a problem you have, and\nwhat to do about it.\n7. Be able to downshift into consulting (if appropriate).Consulting, as I mentioned, is a dangerous way to finance a startup.\nBut it's better than dying. It's a bit like anaerobic respiration:\nnot the optimum solution for the long term, but it can save you\nfrom an immediate threat. If you're having trouble raising money\nfrom investors at all, it could save you to be able to shift\ntoward consulting.This works better for some startups than others. It wouldn't have\nbeen a natural fit for, say, Google, but if your company was making\nsoftware for building web sites, you could degrade fairly gracefully\ninto consulting by building sites for clients with it.So long as you were careful not to get sucked permanently into\nconsulting, this could even have advantages. You'd understand your\nusers well if you were using the software for them. Plus as a\nconsulting company you might be able to get big-name users using\nyour software that you wouldn't have gotten as a product company.At Viaweb we were forced to operate like a consulting company\ninitially, because we were so desperate for users that we'd offer\nto build merchants' sites for them if they'd sign up. \nBut we never charged for such work, because we didn't want them to\nstart treating us like actual consultants, and calling us every\ntime they wanted something changed on their site. We knew we had\nto stay a product company, because only\nthat scales.\n8. Avoid inexperienced investors.Though novice investors seem unthreatening they can be the most\ndangerous sort, because they're so nervous. Especially in\nproportion to the amount they invest. Raising $20,000 from a first-time\nangel investor can be as much work as raising $2 million from\na VC fund.Their lawyers are generally inexperienced too. But while the\ninvestors can admit they don't know what they're doing, their lawyers\ncan't. One YC startup negotiated terms for a tiny round with\nan angel, only to receive a 70-page agreement from his lawyer. And\nsince the lawyer could never admit, in front of his client, that\nhe'd screwed up, he instead had to insist on retaining all the\ndraconian terms in it, so the deal fell through.Of course, someone has to take money from novice investors, or there\nwould never be any experienced ones. But if you do, either (a)\ndrive the process yourself, including supplying the \npaperwork, or\n(b) use them only to fill up a larger round led by someone else.\n9. Know where you stand.The most dangerous thing about investors is their indecisiveness.\nThe worst case scenario is the long no, the no that comes after\nmonths of meetings. Rejections from investors are like design\nflaws: inevitable, but much less costly if you discover them early.So while you're talking to investors, constantly look for signs of\nwhere you stand. How likely are they to offer you a term sheet?\nWhat do they have to be convinced of first? You shouldn't necessarily\nalways be asking these questions outright—that could get \nannoying—but you should always be collecting data about them.Investors tend to resist committing except to the extent you push\nthem to. It's in their interest to collect the maximum amount of\ninformation while making the minimum number of decisions. The best\nway to force them to act is, of course, competing investors. But\nyou can also apply some force by focusing the discussion:\nby asking what specific questions they need answered to make\nup their minds, and then answering them. If you get through several\nobstacles and they keep raising new ones, assume that ultimately\nthey're going to flake.You have to be disciplined when collecting data about investors'\nintentions. Otherwise their desire to lead you on will combine\nwith your own desire to be led on to produce completely inaccurate\nimpressions.Use the data to weight your strategy.\nYou'll probably be talking to several investors. Focus on the ones\nthat are most likely to say yes. The value of a potential investor\nis a combination of how good it would be if they said yes, and how\nlikely they are to say it. Put the most weight on the second factor.\nPartly because the most important quality in an investor is simply\ninvesting. But also because, as I mentioned, the biggest factor\nin investors' opinion of you is other investors' opinion of you.\nIf you're talking to several investors and you manage to get one\nover the threshold of saying yes, it will make the others much more\ninterested. So you're not sacrificing the lukewarm investors if\nyou focus on the hot ones; convincing the hot investors is the best\nway to convince the lukewarm ones.\nFutureI'm hopeful things won't always be so awkward. I hope that as startups\nget cheaper and the number of investors increases, raising money\nwill become, if not easy, at least straightforward.In the meantime, the brokenness of the funding process offers a big\nopportunity. Most investors have no idea how dangerous they are.\nThey'd be surprised to hear that raising money from them is something\nthat has to be treated as a threat to a company's survival. They\njust think they need a little more information to make up their\nminds. They don't get that there are 10 other investors who also\nwant a little more information, and that the process of talking to\nthem all can bring a startup to a standstill for months.Because investors don't understand the cost of dealing with them,\nthey don't realize how much room there is for a potential competitor\nto undercut them. I know from my own experience how much faster\ninvestors could decide, because we've brought our own time down to\n20 minutes (5 minutes of reading an application plus a 10 minute\ninterview plus 5 minutes of discussion). If you were investing\nmore money you'd want to take longer, of course. But if we can\ndecide in 20 minutes, should it take anyone longer than a couple\ndays?Opportunities like this don't sit unexploited forever, even in an\nindustry as conservative as venture capital. So\neither existing investors will start to make up their minds faster,\nor new investors will emerge who do.In the meantime founders have to treat raising money as a dangerous\nprocess. Fortunately, I can fix the biggest danger right here.\nThe biggest danger is surprise. It's that startups will underestimate\nthe difficulty of raising money—that they'll cruise through all\nthe initial steps, but when they turn to raising money they'll find\nit surprisingly hard, get demoralized, and give up. So I'm telling\nyou in advance: raising money is hard.Notes[1]\nWhen investors can't make up their minds, they sometimes\ndescribe it as if it were a property of the startup. \"You're too\nearly for us,\" they sometimes say. But which of them, if they were\ntaken back in a time machine to the hour Google was founded, wouldn't\noffer to invest at any valuation the founders chose? An hour old\nis not too early if it's the right startup. What \"you're too early\"\nreally means is \"we can't figure out yet whether you'll succeed.\"\n[2]\nInvestors influence one another both directly and indirectly.\nThey influence one another directly through the \"buzz\" that surrounds\na hot startup. But they also influence one another indirectly\nthrough the founders. When a lot of investors are interested in\nyou, it increases your confidence in a way that makes you much more\nattractive to investors.No VC will admit they're influenced by buzz. Some genuinely aren't.\nBut there are few who can say they're not influenced by confidence.[3]\nOne VC who read this essay wrote:\"We try to avoid companies that got bootstrapped with consulting. \nIt creates very bad behaviors/instincts that are hard to erase \nfrom a company's culture.\"[4]\nThe optimal way to answer the first question is to say that\nit would be improper to name names, while simultaneously implying\nthat you're talking to a bunch of other VCs who are all about to\ngive you term sheets. If you're the sort of person who understands\nhow to do that, go ahead. If not, don't even try. Nothing annoys\nVCs more than clumsy efforts to manipulate them.[5]\nThe disadvantage of expanding a round on the fly is that the\nvaluation is fixed at the start, so if you get a sudden rush of\ninterest, you may have to decide between turning some investors\naway and selling more of the company than you meant to. That's a\ngood problem to have, however.[6]\nI wouldn't say that intelligence doesn't matter in startups.\nWe're only comparing YC startups, who've already made it over a\ncertain threshold.[7]\nBut not all are. Though most VCs are suits at heart,\nthe most successful ones tend not to be. Oddly enough,\nthe best VCs tend to be the least VC-like.\nThanks to Trevor Blackwell, David Hornik, Jessica Livingston,\nRobert Morris, and Fred Wilson for reading drafts of this." }, { "path": "data/PaulGrahamEssays/future.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nAugust 2010Two years ago I\nwrote about what I called \"a huge, unexploited\nopportunity in startup funding:\" the growing disconnect between\nVCs, whose current business model requires them to invest large\namounts, and a large class of startups that need less than they\nused to. Increasingly, startups want a couple hundred thousand\ndollars, not a couple million. \n[1]The opportunity is a lot less unexploited now. Investors have\npoured into this territory from both directions. VCs are much more\nlikely to make angel-sized investments than they were a year ago.\nAnd meanwhile the past year has seen a dramatic increase in a new\ntype of investor: the super-angel, who operates like an angel, but\nusing other people's money, like a VC.Though a lot of investors are entering this territory, there is\nstill room for more. The distribution of investors should mirror\nthe distribution of startups, which has the usual power law dropoff.\nSo there should be a lot more people investing tens or hundreds of\nthousands than millions. \n[2]In fact, it may be good for angels that there are more people doing\nangel-sized deals, because if angel rounds become more legitimate,\nthen startups may start to opt for angel rounds even when they\ncould, if they wanted, raise series A rounds from VCs. One reason\nstartups prefer series A rounds is that they're more prestigious.\nBut if angel investors become more active and better known, they'll\nincreasingly be able to compete with VCs in brand.Of course, prestige isn't the main reason to prefer a series A\nround. A startup will probably get more attention from investors\nin a series A round than an angel round. So if a startup is choosing\nbetween an angel round and an A round from a good VC fund, I usually\nadvise them to take the A round. \n[3]But while series A rounds aren't going away, I think VCs should be\nmore worried about super-angels than vice versa. Despite their\nname, the super-angels are really mini VC funds, and they clearly\nhave existing VCs in their sights.They would seem to have history on their side. \nThe pattern here seems the same\none we see when startups and established companies enter a new\nmarket. Online video becomes possible, and YouTube plunges right\nin, while existing media companies embrace it only half-willingly,\ndriven more by fear than hope, and aiming more to protect their\nturf than to do great things for users. Ditto for PayPal. This\npattern is repeated over and over, and it's usually the invaders\nwho win. In this case the super-angels are the invaders. Angel\nrounds are their whole business, as online video was for YouTube.\nWhereas VCs who make angel investments mostly do it as a way to\ngenerate deal flow for series A rounds.\n[4]On the other hand, startup investing is a very strange business.\nNearly all the returns are concentrated in a few big winners. If\nthe super-angels merely fail to invest in (and to some extent\nproduce) the big winners, they'll be out of business, even if they\ninvest in all the others.VCsWhy don't VCs start doing smaller series A rounds? The sticking\npoint is board seats. In a traditional series A round, the partner\nwhose deal it is takes a seat on the startup's board. If we assume\nthe average startup runs for 6 years and a partner can bear to be\non 12 boards at once, then a VC fund can do 2 series A deals per\npartner per year.It has always seemed to me the solution is to take fewer board\nseats. You don't have to be on the board to help a startup. Maybe\nVCs feel they need the power that comes with board membership to\nensure their money isn't wasted. But have they tested that theory?\nUnless they've tried not taking board seats and found their returns\nare lower, they're not bracketing the problem.I'm not saying VCs don't help startups. The good ones help them a\nlot. What I'm saying is that the kind of help that matters, you\nmay not have to be a board member to give.\n[5]How will this all play out? Some VCs will probably adapt, by doing\nmore, smaller deals. I wouldn't be surprised if by streamlining\ntheir selection process and taking fewer board seats, VC funds could\ndo 2 to 3 times as many series A rounds with no loss of quality.But other VCs will make no more than superficial changes. VCs are\nconservative, and the threat to them isn't mortal. The VC funds\nthat don't adapt won't be violently displaced. They'll edge gradually\ninto a different business without realizing it. They'll still do\nwhat they will call series A rounds, but these will increasingly\nbe de facto series B rounds.\n[6]In such rounds they won't get the 25 to 40% of the company they do\nnow. You don't give up as much of the company in later rounds\nunless something is seriously wrong. Since the VCs who don't adapt\nwill be investing later, their returns from winners may be smaller.\nBut investing later should also mean they have fewer losers. So\ntheir ratio of risk to return may be the same or even better.\nThey'll just have become a different, more conservative, type of\ninvestment.AngelsIn the big angel rounds that increasingly compete with series A\nrounds, the investors won't take as much equity as VCs do now. And\nVCs who try to compete with angels by doing more, smaller deals\nwill probably find they have to take less equity to do it. Which\nis good news for founders: they'll get to keep more of the company.The deal terms of angel rounds will become less restrictive\ntoo—not just less restrictive than series A terms, but less\nrestrictive than angel terms have traditionally been.In the future, angel rounds will less often be for specific amounts\nor have a lead investor. In the old days, the standard m.o. for\nstartups was to find one angel to act as the lead investor. You'd\nnegotiate a round size and valuation with the lead, who'd supply\nsome but not all of the money. Then the startup and the lead would\ncooperate to find the rest.The future of angel rounds looks more like this: instead of a fixed\nround size, startups will do a rolling close, where they take money\nfrom investors one at a time till they feel they have enough.\n[7]\nAnd though there's going to be one investor who gives them the first\ncheck, and his or her help in recruiting other investors will\ncertainly be welcome, this initial investor will no longer be the\nlead in the old sense of managing the round. The startup will now\ndo that themselves.There will continue to be lead investors in the sense of investors\nwho take the lead in advising a startup. They may also make\nthe biggest investment. But they won't always have to be the one\nterms are negotiated with, or be the first money in, as they have\nin the past. Standardized paperwork will do away with the need to\nnegotiate anything except the valuation, and that will get easier\ntoo.If multiple investors have to share a valuation, it will be whatever\nthe startup can get from the first one to write a check, limited\nby their guess at whether this will make later investors balk. But\nthere may not have to be just one valuation. Startups are increasingly\nraising money on convertible notes, and convertible notes have not\nvaluations but at most valuation caps: caps on what the\neffective valuation will be when the debt converts to equity (in a\nlater round, or upon acquisition if that happens first). That's\nan important difference because it means a startup could do multiple\nnotes at once with different caps. This is now starting to happen,\nand I predict it will become more common.SheepThe reason things are moving this way is that the old way sucked\nfor startups. Leads could (and did) use a fixed size round as a\nlegitimate-seeming way of saying what all founders hate to hear:\nI'll invest if other people will. Most investors, unable to judge\nstartups for themselves, rely instead on the opinions of other\ninvestors. If everyone wants in, they want in too; if not, not.\nFounders hate this because it's a recipe for deadlock, and delay\nis the thing a startup can least afford. Most investors know this\nm.o. is lame, and few say openly that they're doing it. But the\ncraftier ones achieve the same result by offering to lead rounds\nof fixed size and supplying only part of the money. If the startup\ncan't raise the rest, the lead is out too. How could they go ahead\nwith the deal? The startup would be underfunded!In the future, investors will increasingly be unable to offer\ninvestment subject to contingencies like other people investing.\nOr rather, investors who do that will get last place in line.\nStartups will go to them only to fill up rounds that are mostly\nsubscribed. And since hot startups tend to have rounds that are\noversubscribed, being last in line means they'll probably miss the\nhot deals. Hot deals and successful startups are not identical,\nbut there is a significant correlation. \n[8]\nSo investors who won't invest unilaterally will have lower returns.Investors will probably find they do better when deprived of this\ncrutch anyway. Chasing hot deals doesn't make investors choose\nbetter; it just makes them feel better about their choices. I've\nseen feeding frenzies both form and fall apart many times, and as\nfar as I can tell they're mostly random. \n[9]\nIf investors can\nno longer rely on their herd instincts, they'll have to think more\nabout each startup before investing. They may be surprised how\nwell this works.Deadlock wasn't the only disadvantage of letting a lead investor\nmanage an angel round. The investors would not infrequently collude\nto push down the valuation. And rounds took too long to close,\nbecause however motivated the lead was to get the round closed, he\nwas not a tenth as motivated as the startup.Increasingly, startups are taking charge of their own angel rounds.\nOnly a few do so far, but I think we can already declare the old\nway dead, because those few are the best startups. They're the\nones in a position to tell investors how the round is going to work.\nAnd if the startups you want to invest in do things a certain way,\nwhat difference does it make what the others do?TractionIn fact, it may be slightly misleading to say that angel rounds\nwill increasingly take the place of series A rounds. What's really\nhappening is that startup-controlled rounds are taking the place\nof investor-controlled rounds.This is an instance of a very important meta-trend, one that Y\nCombinator itself has been based on from the beginning: founders\nare becoming increasingly powerful relative to investors. So if\nyou want to predict what the future of venture funding will be like,\njust ask: how would founders like it to be? One by one, all the\nthings founders dislike about raising money are going to get\neliminated. \n[10]Using that heuristic, I'll predict a couple more things. One is\nthat investors will increasingly be unable to wait for startups to\nhave \"traction\" before they put in significant money. It's hard\nto predict in advance which startups will succeed. So most investors\nprefer, if they can, to wait till the startup is already succeeding,\nthen jump in quickly with an offer. Startups hate this as well,\npartly because it tends to create deadlock, and partly because it\nseems kind of slimy. If you're a promising startup but don't yet\nhave significant growth, all the investors are your friends in\nwords, but few are in actions. They all say they love you, but\nthey all wait to invest. Then when you start to see growth, they\nclaim they were your friend all along, and are aghast at the thought\nyou'd be so disloyal as to leave them out of your round. If founders\nbecome more powerful, they'll be able to make investors give them\nmore money upfront.(The worst variant of this behavior is the tranched deal, where the\ninvestor makes a small initial investment, with more to follow if\nthe startup does well. In effect, this structure gives the investor\na free option on the next round, which they'll only take if it's\nworse for the startup than they could get in the open market.\nTranched deals are an abuse. They're increasingly rare, and they're\ngoing to get rarer.) \n[11]Investors don't like trying to predict which startups will succeed,\nbut increasingly they'll have to. Though the way that happens won't\nnecessarily be that the behavior of existing investors will change;\nit may instead be that they'll be replaced by other investors with\ndifferent behavior—that investors who understand startups\nwell enough to take on the hard problem of predicting their trajectory\nwill tend to displace suits whose skills lie more in raising money\nfrom LPs.SpeedThe other thing founders hate most about fundraising is how long\nit takes. So as founders become more powerful, rounds should start\nto close faster.Fundraising is still terribly distracting for startups. If you're\na founder in the middle of raising a round, the round is the top idea in your mind, which means working on the\ncompany isn't. If a round takes 2 months to close, which is\nreasonably fast by present standards, that means 2 months during\nwhich the company is basically treading water. That's the worst\nthing a startup could do.So if investors want to get the best deals, the way to do it will\nbe to close faster. Investors don't need weeks to make up their\nminds anyway. We decide based on about 10 minutes of reading an\napplication plus 10 minutes of in person interview, and we only\nregret about 10% of our decisions. If we can decide in 20 minutes,\nsurely the next round of investors can decide in a couple days.\n[12]There are a lot of institutionalized delays in startup funding: the\nmulti-week mating dance with investors; the distinction between\ntermsheets and deals; the fact that each series A has enormously\nelaborate, custom paperwork. Both founders and investors tend to\ntake these for granted. It's the way things have always been. But\nultimately the reason these delays exist is that they're to the\nadvantage of investors. More time gives investors more information\nabout a startup's trajectory, and it also tends to make startups\nmore pliable in negotiations, since they're usually short of money.These conventions weren't designed to drag out the funding process,\nbut that's why they're allowed to persist. Slowness is to the\nadvantage of investors, who have in the past been the ones with the\nmost power. But there is no need for rounds to take months or even\nweeks to close, and once founders realize that, it's going to stop.\nNot just in angel rounds, but in series A rounds too. The future\nis simple deals with standard terms, done quickly.One minor abuse that will get corrected in the process is option\npools. In a traditional series A round, before the VCs invest they\nmake the company set aside a block of stock for future hires—usually\nbetween 10 and 30% of the company. The point is to ensure this\ndilution is borne by the existing shareholders. The practice isn't\ndishonest; founders know what's going on. But it makes deals\nunnecessarily complicated. In effect the valuation is 2 numbers.\nThere's no need to keep doing this.\n[13]The final thing founders want is to be able to sell some of\ntheir own stock in later rounds. This won't be a change, \nbecause the practice is now quite common. A lot of investors\nhated the idea, but the world hasn't exploded as a result,\nso it will happen more, and more openly.SurpriseI've talked here about a bunch of changes that will be forced on\ninvestors as founders become more powerful. Now the good news:\ninvestors may actually make more money as a result.A couple days ago an interviewer \nasked \nme if founders having more\npower would be better or worse for the world. I was surprised,\nbecause I'd never considered that question. Better or worse, it's\nhappening. But after a second's reflection, the answer seemed\nobvious. Founders understand their companies better than investors,\nand it has to be better if the people with more knowledge have more\npower.One of the mistakes novice pilots make is overcontrolling the\naircraft: applying corrections too vigorously, so the aircraft\noscillates about the desired configuration instead of approaching\nit asymptotically. It seems probable that investors have till now\non average been overcontrolling their portfolio companies. In a\nlot of startups, the biggest source of stress for the founders is\nnot competitors but investors. Certainly it was for us at Viaweb.\nAnd this is not a new phenomenon: investors were James Watt's biggest\nproblem too. If having less power prevents investors from\novercontrolling startups, it should be better not just for founders\nbut for investors too.Investors may end up with less stock per startup, but startups will\nprobably do better with founders more in control, and there will\nalmost certainly be more of them. Investors all compete with one\nanother for deals, but they aren't one another's main competitor.\nOur main competitor is employers. And so far that competitor is\ncrushing us. Only a tiny fraction of people who could start a\nstartup do. Nearly all customers choose the competing product, a\njob. Why? Well, let's look at the product we're offering. An\nunbiased review would go something like this:\n\n Starting a startup gives you more freedom and the opportunity to\n make a lot more money than a job, but it's also hard work and at\n times very stressful.\n\nMuch of the stress comes from dealing with investors. If reforming\nthe investment process removed that stress, we'd make our product\nmuch more attractive. The kind of people who make good startup\nfounders don't mind dealing with technical problems—they enjoy\ntechnical problems—but they hate the type of problems investors\ncause.Investors have no\nidea that when they maltreat one startup, they're preventing 10\nothers from happening, but they are. Indirectly, but they are. So\nwhen investors stop trying to squeeze a little more out of their\nexisting deals, they'll find they're net ahead, because so many\nmore new deals appear.One of our axioms at Y Combinator is not to think of deal flow as\na zero-sum game. Our main focus is to encourage more startups to happen,\nnot to win a larger share of the existing stream. We've found this\nprinciple very useful, and we think as it spreads outward it will\nhelp later stage investors as well.\"Make something people want\"\napplies to us too.Notes[1]\nIn this essay I'm talking mainly about software startups.\nThese points don't apply to types of startups that are still expensive\nto start, e.g. in energy or biotech.Even the cheap kinds of startups will generally raise large amounts\nat some point, when they want to hire a lot of people. What has\nchanged is how much they can get done before that.[2]\nIt's not the distribution of good startups that has a power\nlaw dropoff, but the distribution of potentially good startups,\nwhich is to say, good deals. There are lots of potential winners,\nfrom which a few actual winners emerge with superlinear certainty.[3]\nAs I was writing this, I asked some founders who'd taken\nseries A rounds from top VC funds whether it was worth it, and they\nunanimously said yes.The quality of investor is more important than the type of round,\nthough. I'd take an angel round from good angels over a series A\nfrom a mediocre VC.[4]\nFounders also worry that taking an angel investment from a\nVC means they'll look bad if the VC declines to participate in the\nnext round. The trend of VC angel investing is so new that it's\nhard to say how justified this worry is.Another danger, pointed out by Mitch Kapor, is that if VCs are only\ndoing angel deals to generate series A deal flow, then their\nincentives aren't aligned with the founders'. The founders want\nthe valuation of the next round to be high, and the VCs want it to\nbe low. Again, hard to say yet how much of a problem this will be.[5]\nJosh Kopelman pointed out that another way to be on fewer\nboards at once is to take board seats for shorter periods.[6]\nGoogle was in this respect as so many others the pattern for\nthe future. It would be great for VCs if the similarity extended\nto returns. That's probably too much to hope for, but the returns\nmay be somewhat higher, as I explain later.[7]\nDoing a rolling close doesn't mean the company is always\nraising money. That would be a distraction. The point of a rolling\nclose is to make fundraising take less time, not more. With a\nclassic fixed sized round, you don't get any money till all the\ninvestors agree, and that often creates a situation where they all\nsit waiting for the others to act. A rolling close usually prevents\nthis.\n[8]\nThere are two (non-exclusive) causes of hot deals: the quality\nof the company, and domino effects among investors. The former is\nobviously a better predictor of success.[9]\nSome of the randomness is concealed by the fact that investment\nis a self fulfilling prophecy.[10]\nThe shift in power to founders is exaggerated now because\nit's a seller's market. On the next downtick it will seem like I\noverstated the case. But on the next uptick after that, founders\nwill seem more powerful than ever.[11]\nMore generally, it will become less common for the same\ninvestor to invest in successive rounds, except when exercising an\noption to maintain their percentage. When the same investor invests\nin successive rounds, it often means the startup isn't getting\nmarket price. They may not care; they may prefer to work with an\ninvestor they already know; but as the investment market becomes\nmore efficient, it will become increasingly easy to get market price\nif they want it. Which in turn means the investment community will\ntend to become more stratified.[12]\nThe two 10 minuteses have 3 weeks between them so founders\ncan get cheap plane tickets, but except for that they could be\nadjacent.[13]\nI'm not saying option pools themselves will go away. They're\nan administrative convenience. What will go away is investors\nrequiring them.\nThanks to Sam Altman, John Bautista, Trevor Blackwell,\nPaul Buchheit, Jeff Clavier,\nPatrick Collison, Ron Conway, Matt Cohler, Chris Dixon, Mitch Kapor,\nJosh Kopelman, Pete Koomen, Carolynn Levy, Jessica Livingston, Ariel\nPoler, Geoff Ralston, Naval Ravikant, Dan Siroker, Harj Taggar, and \nFred Wilson\nfor reading drafts of this." }, { "path": "data/PaulGrahamEssays/gap.txt", "content": "May 2004When people care enough about something to do it well, those who\ndo it best tend to be far better than everyone else. There's a\nhuge gap between Leonardo and second-rate contemporaries like\nBorgognone. You see the same gap between Raymond Chandler and the\naverage writer of detective novels. A top-ranked professional chess\nplayer could play ten thousand games against an ordinary club player\nwithout losing once.Like chess or painting or writing novels, making money is a very\nspecialized skill. But for some reason we treat this skill\ndifferently. No one complains when a few people surpass all the\nrest at playing chess or writing novels, but when a few people make\nmore money than the rest, we get editorials saying this is wrong.Why? The pattern of variation seems no different than for any other\nskill. What causes people to react so strongly when the skill is\nmaking money?I think there are three reasons we treat making money as different:\nthe misleading model of wealth we learn as children; the disreputable\nway in which, till recently, most fortunes were accumulated; and\nthe worry that great variations in income are somehow bad for\nsociety. As far as I can tell, the first is mistaken, the second\noutdated, and the third empirically false. Could it be that, in a\nmodern democracy, variation in income is actually a sign of health?The Daddy Model of WealthWhen I was five I thought electricity was created by electric\nsockets. I didn't realize there were power plants out there\ngenerating it. Likewise, it doesn't occur to most kids that wealth\nis something that has to be generated. It seems to be something\nthat flows from parents.Because of the circumstances in which they encounter it, children\ntend to misunderstand wealth. They confuse it with money. They\nthink that there is a fixed amount of it. And they think of it as\nsomething that's distributed by authorities (and so should be\ndistributed equally), rather than something that has to be created\n(and might be created unequally).In fact, wealth is not money. Money is just a convenient way of\ntrading one form of wealth for another. Wealth is the underlying\nstuff—the goods and services we buy. When you travel to a\nrich or poor country, you don't have to look at people's bank\naccounts to tell which kind you're in. You can see\nwealth—in buildings and streets, in the clothes and the health\nof the people.Where does wealth come from? People make it. This was easier to\ngrasp when most people lived on farms, and made many of the things\nthey wanted with their own hands. Then you could see in the house,\nthe herds, and the granary the wealth that each family created. It\nwas obvious then too that the wealth of the world was not a fixed\nquantity that had to be shared out, like slices of a pie. If you\nwanted more wealth, you could make it.This is just as true today, though few of us create wealth directly\nfor ourselves (except for a few vestigial domestic tasks). Mostly\nwe create wealth for other people in exchange for money, which we\nthen trade for the forms of wealth we want. \n[1]Because kids are unable to create wealth, whatever they have has\nto be given to them. And when wealth is something you're given,\nthen of course it seems that it should be distributed equally.\n[2]\nAs in most families it is. The kids see to that. \"Unfair,\" they\ncry, when one sibling gets more than another.In the real world, you can't keep living off your parents. If you\nwant something, you either have to make it, or do something of\nequivalent value for someone else, in order to get them to give you\nenough money to buy it. In the real world, wealth is (except for\na few specialists like thieves and speculators) something you have\nto create, not something that's distributed by Daddy. And since\nthe ability and desire to create it vary from person to person,\nit's not made equally.You get paid by doing or making something people want, and those\nwho make more money are often simply better at doing what people\nwant. Top actors make a lot more money than B-list actors. The\nB-list actors might be almost as charismatic, but when people go\nto the theater and look at the list of movies playing, they want\nthat extra oomph that the big stars have.Doing what people want is not the only way to get money, of course.\nYou could also rob banks, or solicit bribes, or establish a monopoly.\nSuch tricks account for some variation in wealth, and indeed for\nsome of the biggest individual fortunes, but they are not the root\ncause of variation in income. The root cause of variation in income,\nas Occam's Razor implies, is the same as the root cause of variation\nin every other human skill.In the United States, the CEO of a large public company makes about\n100 times as much as the average person. \n[3]\nBasketball players\nmake about 128 times as much, and baseball players 72 times as much.\nEditorials quote this kind of statistic with horror. But I have\nno trouble imagining that one person could be 100 times as productive\nas another. In ancient Rome the price of slaves varied by\na factor of 50 depending on their skills. \n[4]\nAnd that's without\nconsidering motivation, or the extra leverage in productivity that\nyou can get from modern technology.Editorials about athletes' or CEOs' salaries remind me of early\nChristian writers, arguing from first principles about whether the\nEarth was round, when they could just walk outside and check.\n[5]\nHow much someone's work is worth is not a policy question. It's\nsomething the market already determines.\"Are they really worth 100 of us?\" editorialists ask. Depends on\nwhat you mean by worth. If you mean worth in the sense of what\npeople will pay for their skills, the answer is yes, apparently.A few CEOs' incomes reflect some kind of wrongdoing. But are there\nnot others whose incomes really do reflect the wealth they generate?\nSteve Jobs saved a company that was in a terminal decline. And not\nmerely in the way a turnaround specialist does, by cutting costs;\nhe had to decide what Apple's next products should be. Few others\ncould have done it. And regardless of the case with CEOs, it's\nhard to see how anyone could argue that the salaries of professional\nbasketball players don't reflect supply and demand.It may seem unlikely in principle that one individual could really\ngenerate so much more wealth than another. The key to this mystery\nis to revisit that question, are they really worth 100 of us?\nWould a basketball team trade one of their players for 100\nrandom people? What would Apple's next product look like if you\nreplaced Steve Jobs with a committee of 100 random people? \n[6]\nThese\nthings don't scale linearly. Perhaps the CEO or the professional\nathlete has only ten times (whatever that means) the skill and\ndetermination of an ordinary person. But it makes all the difference\nthat it's concentrated in one individual.When we say that one kind of work is overpaid and another underpaid,\nwhat are we really saying? In a free market, prices are determined\nby what buyers want. People like baseball more than poetry, so\nbaseball players make more than poets. To say that a certain kind\nof work is underpaid is thus identical with saying that people want\nthe wrong things.Well, of course people want the wrong things. It seems odd to be\nsurprised by that. And it seems even odder to say that it's\nunjust that certain kinds of work are underpaid. \n[7]\nThen\nyou're saying that it's unjust that people want the wrong things.\nIt's lamentable that people prefer reality TV and corndogs to\nShakespeare and steamed vegetables, but unjust? That seems like\nsaying that blue is heavy, or that up is circular.The appearance of the word \"unjust\" here is the unmistakable spectral\nsignature of the Daddy Model. Why else would this idea occur in\nthis odd context? Whereas if the speaker were still operating on\nthe Daddy Model, and saw wealth as something that flowed from a\ncommon source and had to be shared out, rather than something\ngenerated by doing what other people wanted, this is exactly what\nyou'd get on noticing that some people made much more than others.When we talk about \"unequal distribution of income,\" we should\nalso ask, where does that income come from?\n[8]\nWho made the wealth\nit represents? Because to the extent that income varies simply\naccording to how much wealth people create, the distribution may\nbe unequal, but it's hardly unjust.Stealing ItThe second reason we tend to find great disparities of wealth\nalarming is that for most of human history the usual way to accumulate\na fortune was to steal it: in pastoral societies by cattle raiding;\nin agricultural societies by appropriating others' estates in times\nof war, and taxing them in times of peace.In conflicts, those on the winning side would receive the estates\nconfiscated from the losers. In England in the 1060s, when William\nthe Conqueror distributed the estates of the defeated Anglo-Saxon\nnobles to his followers, the conflict was military. By the 1530s,\nwhen Henry VIII distributed the estates of the monasteries to his\nfollowers, it was mostly political. \n[9]\nBut the principle was the\nsame. Indeed, the same principle is at work now in Zimbabwe.In more organized societies, like China, the ruler and his officials\nused taxation instead of confiscation. But here too we see the\nsame principle: the way to get rich was not to create wealth, but\nto serve a ruler powerful enough to appropriate it.This started to change in Europe with the rise of the middle class.\nNow we think of the middle class as people who are neither rich nor\npoor, but originally they were a distinct group. In a feudal\nsociety, there are just two classes: a warrior aristocracy, and the\nserfs who work their estates. The middle class were a new, third\ngroup who lived in towns and supported themselves by manufacturing\nand trade.Starting in the tenth and eleventh centuries, petty nobles and\nformer serfs banded together in towns that gradually became powerful\nenough to ignore the local feudal lords. \n[10]\nLike serfs, the middle\nclass made a living largely by creating wealth. (In port cities\nlike Genoa and Pisa, they also engaged in piracy.) But unlike serfs\nthey had an incentive to create a lot of it. Any wealth a serf\ncreated belonged to his master. There was not much point in making\nmore than you could hide. Whereas the independence of the townsmen\nallowed them to keep whatever wealth they created.Once it became possible to get rich by creating wealth, society as\na whole started to get richer very rapidly. Nearly everything we\nhave was created by the middle class. Indeed, the other two classes\nhave effectively disappeared in industrial societies, and their\nnames been given to either end of the middle class. (In the original\nsense of the word, Bill Gates is middle class.)But it was not till the Industrial Revolution that wealth creation\ndefinitively replaced corruption as the best way to get rich. In\nEngland, at least, corruption only became unfashionable (and in\nfact only started to be called \"corruption\") when there started to\nbe other, faster ways to get rich.Seventeenth-century England was much like the third world today,\nin that government office was a recognized route to wealth. The\ngreat fortunes of that time still derived more from what we would\nnow call corruption than from commerce. \n[11]\nBy the nineteenth\ncentury that had changed. There continued to be bribes, as there\nstill are everywhere, but politics had by then been left to men who\nwere driven more by vanity than greed. Technology had made it\npossible to create wealth faster than you could steal it. The\nprototypical rich man of the nineteenth century was not a courtier\nbut an industrialist.With the rise of the middle class, wealth stopped being a zero-sum\ngame. Jobs and Wozniak didn't have to make us poor to make themselves\nrich. Quite the opposite: they created things that made our lives\nmaterially richer. They had to, or we wouldn't have paid for them.But since for most of the world's history the main route to wealth\nwas to steal it, we tend to be suspicious of rich people. Idealistic\nundergraduates find their unconsciously preserved child's model of\nwealth confirmed by eminent writers of the past. It is a case of\nthe mistaken meeting the outdated.\"Behind every great fortune, there is a crime,\" Balzac wrote. Except\nhe didn't. What he actually said was that a great fortune with no\napparent cause was probably due to a crime well enough executed\nthat it had been forgotten. If we were talking about Europe in\n1000, or most of the third world today, the standard misquotation\nwould be spot on. But Balzac lived in nineteenth-century France,\nwhere the Industrial Revolution was well advanced. He knew you\ncould make a fortune without stealing it. After all, he did himself,\nas a popular novelist.\n[12]Only a few countries (by no coincidence, the richest ones) have\nreached this stage. In most, corruption still has the upper hand.\nIn most, the fastest way to get wealth is by stealing it. And so\nwhen we see increasing differences in income in a rich country,\nthere is a tendency to worry that it's sliding back toward becoming\nanother Venezuela. I think the opposite is happening. I think\nyou're seeing a country a full step ahead of Venezuela.The Lever of TechnologyWill technology increase the gap between rich and poor? It will\ncertainly increase the gap between the productive and the unproductive.\nThat's the whole point of technology. With a tractor an energetic\nfarmer could plow six times as much land in a day as he could with\na team of horses. But only if he mastered a new kind of farming.I've seen the lever of technology grow visibly in my own time. In\nhigh school I made money by mowing lawns and scooping ice cream at\nBaskin-Robbins. This was the only kind of work available at the\ntime. Now high school kids could write software or design web\nsites. But only some of them will; the rest will still be scooping\nice cream.I remember very vividly when in 1985 improved technology made it\npossible for me to buy a computer of my own. Within months I was\nusing it to make money as a freelance programmer. A few years\nbefore, I couldn't have done this. A few years before, there was\nno such thing as a freelance programmer. But Apple created\nwealth, in the form of powerful, inexpensive computers, and programmers\nimmediately set to work using it to create more.As this example suggests, the rate at which technology increases\nour productive capacity is probably exponential, rather than linear.\nSo we should expect to see ever-increasing variation in individual\nproductivity as time goes on. Will that increase the gap between\nrich and the poor? Depends which gap you mean.Technology should increase the gap in income, but it seems to\ndecrease other gaps. A hundred years ago, the rich led a different\nkind of life from ordinary people. They lived in houses\nfull of servants, wore elaborately uncomfortable clothes, and\ntravelled about in carriages drawn by teams of horses which themselves\nrequired their own houses and servants. Now, thanks to technology,\nthe rich live more like the average person.Cars are a good example of why. It's possible to buy expensive,\nhandmade cars that cost hundreds of thousands of dollars. But there\nis not much point. Companies make more money by building a large\nnumber of ordinary cars than a small number of expensive ones. So\na company making a mass-produced car can afford to spend a lot more\non its design. If you buy a custom-made car, something will always\nbe breaking. The only point of buying one now is to advertise that\nyou can.Or consider watches. Fifty years ago, by spending a lot of money\non a watch you could get better performance. When watches had\nmechanical movements, expensive watches kept better time. Not any\nmore. Since the invention of the quartz movement, an ordinary Timex\nis more accurate than a Patek Philippe costing hundreds of thousands\nof dollars.\n[13]\nIndeed, as with expensive cars, if you're determined\nto spend a lot of money on a watch, you have to put up with some\ninconvenience to do it: as well as keeping worse time, mechanical\nwatches have to be wound.The only thing technology can't cheapen is brand. Which is precisely\nwhy we hear ever more about it. Brand is the residue left as the\nsubstantive differences between rich and poor evaporate. But what\nlabel you have on your stuff is a much smaller matter than having\nit versus not having it. In 1900, if you kept a carriage, no one\nasked what year or brand it was. If you had one, you were rich.\nAnd if you weren't rich, you took the omnibus or walked. Now even\nthe poorest Americans drive cars, and it is only because we're so\nwell trained by advertising that we can even recognize the especially\nexpensive ones.\n[14]The same pattern has played out in industry after industry. If\nthere is enough demand for something, technology will make it cheap\nenough to sell in large volumes, and the mass-produced versions\nwill be, if not better, at least more convenient.\n[15]\nAnd there\nis nothing the rich like more than convenience. The rich people I\nknow drive the same cars, wear the same clothes, have the same kind\nof furniture, and eat the same foods as my other friends. Their\nhouses are in different neighborhoods, or if in the same neighborhood\nare different sizes, but within them life is similar. The houses\nare made using the same construction techniques and contain much\nthe same objects. It's inconvenient to do something expensive and\ncustom.The rich spend their time more like everyone else too. Bertie\nWooster seems long gone. Now, most people who are rich enough not\nto work do anyway. It's not just social pressure that makes them;\nidleness is lonely and demoralizing.Nor do we have the social distinctions there were a hundred years\nago. The novels and etiquette manuals of that period read now\nlike descriptions of some strange tribal society. \"With respect\nto the continuance of friendships...\" hints Mrs. Beeton's Book\nof Household Management (1880), \"it may be found necessary, in\nsome cases, for a mistress to relinquish, on assuming the responsibility\nof a household, many of those commenced in the earlier part of her\nlife.\" A woman who married a rich man was expected to drop friends\nwho didn't. You'd seem a barbarian if you behaved that way today.\nYou'd also have a very boring life. People still tend to segregate\nthemselves somewhat, but much more on the basis of education than\nwealth.\n[16]Materially and socially, technology seems to be decreasing the gap\nbetween the rich and the poor, not increasing it. If Lenin walked\naround the offices of a company like Yahoo or Intel or Cisco, he'd\nthink communism had won. Everyone would be wearing the same clothes,\nhave the same kind of office (or rather, cubicle) with the same\nfurnishings, and address one another by their first names instead\nof by honorifics. Everything would seem exactly as he'd predicted,\nuntil he looked at their bank accounts. Oops.Is it a problem if technology increases that gap? It doesn't seem\nto be so far. As it increases the gap in income, it seems to\ndecrease most other gaps.Alternative to an AxiomOne often hears a policy criticized on the grounds that it would\nincrease the income gap between rich and poor. As if it were an\naxiom that this would be bad. It might be true that increased\nvariation in income would be bad, but I don't see how we can say\nit's axiomatic.Indeed, it may even be false, in industrial democracies. In a\nsociety of serfs and warlords, certainly, variation in income is a\nsign of an underlying problem. But serfdom is not the only cause\nof variation in income. A 747 pilot doesn't make 40 times as much\nas a checkout clerk because he is a warlord who somehow holds her\nin thrall. His skills are simply much more valuable.I'd like to propose an alternative idea: that in a modern society,\nincreasing variation in income is a sign of health. Technology\nseems to increase the variation in productivity at faster than\nlinear rates. If we don't see corresponding variation in income,\nthere are three possible explanations: (a) that technical innovation\nhas stopped, (b) that the people who would create the most wealth\naren't doing it, or (c) that they aren't getting paid for it.I think we can safely say that (a) and (b) would be bad. If you\ndisagree, try living for a year using only the resources available\nto the average Frankish nobleman in 800, and report back to us.\n(I'll be generous and not send you back to the stone age.)The only option, if you're going to have an increasingly prosperous\nsociety without increasing variation in income, seems to be (c),\nthat people will create a lot of wealth without being paid for it.\nThat Jobs and Wozniak, for example, will cheerfully work 20-hour\ndays to produce the Apple computer for a society that allows them,\nafter taxes, to keep just enough of their income to match what they\nwould have made working 9 to 5 at a big company.Will people create wealth if they can't get paid for it? Only if\nit's fun. People will write operating systems for free. But they\nwon't install them, or take support calls, or train customers to\nuse them. And at least 90% of the work that even the highest tech\ncompanies do is of this second, unedifying kind.All the unfun kinds of wealth creation slow dramatically in a society\nthat confiscates private fortunes. We can confirm this empirically.\nSuppose you hear a strange noise that you think may be due to a\nnearby fan. You turn the fan off, and the noise stops. You turn\nthe fan back on, and the noise starts again. Off, quiet. On,\nnoise. In the absence of other information, it would seem the noise\nis caused by the fan.At various times and places in history, whether you could accumulate\na fortune by creating wealth has been turned on and off. Northern\nItaly in 800, off (warlords would steal it). Northern Italy in\n1100, on. Central France in 1100, off (still feudal). England in\n1800, on. England in 1974, off (98% tax on investment income).\nUnited States in 1974, on. We've even had a twin study: West\nGermany, on; East Germany, off. In every case, the creation of\nwealth seems to appear and disappear like the noise of a fan as you\nswitch on and off the prospect of keeping it.There is some momentum involved. It probably takes at least a\ngeneration to turn people into East Germans (luckily for England).\nBut if it were merely a fan we were studying, without all the extra\nbaggage that comes from the controversial topic of wealth, no one\nwould have any doubt that the fan was causing the noise.If you suppress variations in income, whether by stealing private\nfortunes, as feudal rulers used to do, or by taxing them away, as\nsome modern governments have done, the result always seems to be\nthe same. Society as a whole ends up poorer.If I had a choice of living in a society where I was materially\nmuch better off than I am now, but was among the poorest, or in one\nwhere I was the richest, but much worse off than I am now, I'd take\nthe first option. If I had children, it would arguably be immoral\nnot to. It's absolute poverty you want to avoid, not relative\npoverty. If, as the evidence so far implies, you have to have one\nor the other in your society, take relative poverty.You need rich people in your society not so much because in spending\ntheir money they create jobs, but because of what they have to do\nto get rich. I'm not talking about the trickle-down effect\nhere. I'm not saying that if you let Henry Ford get rich, he'll\nhire you as a waiter at his next party. I'm saying that he'll make\nyou a tractor to replace your horse.Notes[1]\nPart of the reason this subject is so contentious is that some\nof those most vocal on the subject of wealth—university\nstudents, heirs, professors, politicians, and journalists—have\nthe least experience creating it. (This phenomenon will be familiar\nto anyone who has overheard conversations about sports in a bar.)Students are mostly still on the parental dole, and have not stopped\nto think about where that money comes from. Heirs will be on the\nparental dole for life. Professors and politicians live within\nsocialist eddies of the economy, at one remove from the creation\nof wealth, and are paid a flat rate regardless of how hard they\nwork. And journalists as part of their professional code segregate\nthemselves from the revenue-collecting half of the businesses they\nwork for (the ad sales department). Many of these people never\ncome face to face with the fact that the money they receive represents\nwealth—wealth that, except in the case of journalists, someone\nelse created earlier. They live in a world in which income is\ndoled out by a central authority according to some abstract notion\nof fairness (or randomly, in the case of heirs), rather than given\nby other people in return for something they wanted, so it may seem\nto them unfair that things don't work the same in the rest of the\neconomy.(Some professors do create a great deal of wealth for\nsociety. But the money they're paid isn't a quid pro quo.\nIt's more in the nature of an investment.)[2]\nWhen one reads about the origins of the Fabian Society, it\nsounds like something cooked up by the high-minded Edwardian\nchild-heroes of Edith Nesbit's The Wouldbegoods.[3]\nAccording to a study by the Corporate Library, the median total\ncompensation, including salary, bonus, stock grants, and the exercise\nof stock options, of S&P 500 CEOs in 2002 was $3.65 million.\nAccording to Sports Illustrated, the average NBA player's\nsalary during the 2002-03 season was $4.54 million, and the average\nmajor league baseball player's salary at the start of the 2003\nseason was $2.56 million. According to the Bureau of Labor\nStatistics, the mean annual wage in the US in 2002 was $35,560.[4]\nIn the early empire the price of an ordinary adult slave seems\nto have been about 2,000 sestertii (e.g. Horace, Sat. ii.7.43).\nA servant girl cost 600 (Martial vi.66), while Columella (iii.3.8)\nsays that a skilled vine-dresser was worth 8,000. A doctor, P.\nDecimus Eros Merula, paid 50,000 sestertii for his freedom (Dessau,\nInscriptiones 7812). Seneca (Ep. xxvii.7) reports\nthat one Calvisius Sabinus paid 100,000 sestertii apiece for slaves\nlearned in the Greek classics. Pliny (Hist. Nat. vii.39)\nsays that the highest price paid for a slave up to his time was\n700,000 sestertii, for the linguist (and presumably teacher) Daphnis,\nbut that this had since been exceeded by actors buying their own\nfreedom.Classical Athens saw a similar variation in prices. An ordinary\nlaborer was worth about 125 to 150 drachmae. Xenophon (Mem.\nii.5) mentions prices ranging from 50 to 6,000 drachmae (for the\nmanager of a silver mine).For more on the economics of ancient slavery see:Jones, A. H. M., \"Slavery in the Ancient World,\" Economic History\nReview, 2:9 (1956), 185-199, reprinted in Finley, M. I. (ed.),\nSlavery in Classical Antiquity, Heffer, 1964.[5]\nEratosthenes (276—195 BC) used shadow lengths in different\ncities to estimate the Earth's circumference. He was off by only\nabout 2%.[6]\nNo, and Windows, respectively.[7]\nOne of the biggest divergences between the Daddy Model and\nreality is the valuation of hard work. In the Daddy Model, hard\nwork is in itself deserving. In reality, wealth is measured by\nwhat one delivers, not how much effort it costs. If I paint someone's\nhouse, the owner shouldn't pay me extra for doing it with a toothbrush.It will seem to someone still implicitly operating on the Daddy\nModel that it is unfair when someone works hard and doesn't get\npaid much. To help clarify the matter, get rid of everyone else\nand put our worker on a desert island, hunting and gathering fruit.\nIf he's bad at it he'll work very hard and not end up with much\nfood. Is this unfair? Who is being unfair to him?[8]\nPart of the reason for the tenacity of the Daddy Model may be\nthe dual meaning of \"distribution.\" When economists talk about\n\"distribution of income,\" they mean statistical distribution. But\nwhen you use the phrase frequently, you can't help associating it\nwith the other sense of the word (as in e.g. \"distribution of alms\"),\nand thereby subconsciously seeing wealth as something that flows\nfrom some central tap. The word \"regressive\" as applied to tax\nrates has a similar effect, at least on me; how can anything\nregressive be good?[9]\n\"From the beginning of the reign Thomas Lord Roos was an assiduous\ncourtier of the young Henry VIII and was soon to reap the rewards.\nIn 1525 he was made a Knight of the Garter and given the Earldom\nof Rutland. In the thirties his support of the breach with Rome,\nhis zeal in crushing the Pilgrimage of Grace, and his readiness to\nvote the death-penalty in the succession of spectacular treason\ntrials that punctuated Henry's erratic matrimonial progress made\nhim an obvious candidate for grants of monastic property.\"Stone, Lawrence, Family and Fortune: Studies in Aristocratic\nFinance in the Sixteenth and Seventeenth Centuries, Oxford\nUniversity Press, 1973, p. 166.[10]\nThere is archaeological evidence for large settlements earlier,\nbut it's hard to say what was happening in them.Hodges, Richard and David Whitehouse, Mohammed, Charlemagne and\nthe Origins of Europe, Cornell University Press, 1983.[11]\nWilliam Cecil and his son Robert were each in turn the most\npowerful minister of the crown, and both used their position to\namass fortunes among the largest of their times. Robert in particular\ntook bribery to the point of treason. \"As Secretary of State and\nthe leading advisor to King James on foreign policy, [he] was a\nspecial recipient of favour, being offered large bribes by the Dutch\nnot to make peace with Spain, and large bribes by Spain to make\npeace.\" (Stone, op. cit., p. 17.)[12]\nThough Balzac made a lot of money from writing, he was notoriously\nimprovident and was troubled by debts all his life.[13]\nA Timex will gain or lose about .5 seconds per day. The most\naccurate mechanical watch, the Patek Philippe 10 Day Tourbillon,\nis rated at -1.5 to +2 seconds. Its retail price is about $220,000.[14]\nIf asked to choose which was more expensive, a well-preserved\n1989 Lincoln Town Car ten-passenger limousine ($5,000) or a 2004\nMercedes S600 sedan ($122,000), the average Edwardian might well\nguess wrong.[15]\nTo say anything meaningful about income trends, you have to\ntalk about real income, or income as measured in what it can buy.\nBut the usual way of calculating real income ignores much of the\ngrowth in wealth over time, because it depends on a consumer price\nindex created by bolting end to end a series of numbers that are\nonly locally accurate, and that don't include the prices of new\ninventions until they become so common that their prices stabilize.So while we might think it was very much better to live in a world\nwith antibiotics or air travel or an electric power grid than\nwithout, real income statistics calculated in the usual way will\nprove to us that we are only slightly richer for having these things.Another approach would be to ask, if you were going back to the\nyear x in a time machine, how much would you have to spend on trade\ngoods to make your fortune? For example, if you were going back\nto 1970 it would certainly be less than $500, because the processing\npower you can get for $500 today would have been worth at least\n$150 million in 1970. The function goes asymptotic fairly quickly,\nbecause for times over a hundred years or so you could get all you\nneeded in present-day trash. In 1800 an empty plastic drink bottle\nwith a screw top would have seemed a miracle of workmanship.[16]\nSome will say this amounts to the same thing, because the rich\nhave better opportunities for education. That's a valid point. It\nis still possible, to a degree, to buy your kids' way into top\ncolleges by sending them to private schools that in effect hack the\ncollege admissions process.According to a 2002 report by the National Center for Education\nStatistics, about 1.7% of American kids attend private, non-sectarian\nschools. At Princeton, 36% of the class of 2007 came from such\nschools. (Interestingly, the number at Harvard is significantly\nlower, about 28%.) Obviously this is a huge loophole. It does at\nleast seem to be closing, not widening.Perhaps the designers of admissions processes should take a lesson\nfrom the example of computer security, and instead of just assuming\nthat their system can't be hacked, measure the degree to which it\nis." }, { "path": "data/PaulGrahamEssays/gba.txt", "content": "April 2004To the popular press, \"hacker\" means someone who breaks\ninto computers. Among programmers it means a good programmer.\nBut the two meanings are connected. To programmers,\n\"hacker\" connotes mastery in the most literal sense: someone\nwho can make a computer do what he wants—whether the computer\nwants to or not.To add to the confusion, the noun \"hack\" also has two senses. It can\nbe either a compliment or an insult. It's called a hack when\nyou do something in an ugly way. But when you do something\nso clever that you somehow beat the system, that's also\ncalled a hack. The word is used more often in the former than\nthe latter sense, probably because ugly solutions are more\ncommon than brilliant ones.Believe it or not, the two senses of \"hack\" are also\nconnected. Ugly and imaginative solutions have something in\ncommon: they both break the rules. And there is a gradual\ncontinuum between rule breaking that's merely ugly (using\nduct tape to attach something to your bike) and rule breaking\nthat is brilliantly imaginative (discarding Euclidean space).Hacking predates computers. When he\nwas working on the Manhattan Project, Richard Feynman used to\namuse himself by breaking into safes containing secret documents.\nThis tradition continues today.\nWhen we were in grad school, a hacker friend of mine who spent too much\ntime around MIT had\nhis own lock picking kit.\n(He now runs a hedge fund, a not unrelated enterprise.)It is sometimes hard to explain to authorities why one would\nwant to do such things.\nAnother friend of mine once got in trouble with the government for\nbreaking into computers. This had only recently been declared\na crime, and the FBI found that their usual investigative\ntechnique didn't work. Police investigation apparently begins with\na motive. The usual motives are few: drugs, money, sex,\nrevenge. Intellectual curiosity was not one of the motives on\nthe FBI's list. Indeed, the whole concept seemed foreign to\nthem.Those in authority tend to be annoyed by hackers'\ngeneral attitude of disobedience. But that disobedience is\na byproduct of the qualities that make them good programmers.\nThey may laugh at the CEO when he talks in generic corporate\nnewspeech, but they also laugh at someone who tells them\na certain problem can't be solved.\nSuppress one, and you suppress the other.This attitude is sometimes affected. Sometimes young programmers\nnotice the eccentricities of eminent hackers and decide to\nadopt some of their own in order to seem smarter.\nThe fake version is not merely\nannoying; the prickly attitude of these posers\ncan actually slow the process of innovation.But even factoring in their annoying eccentricities,\nthe disobedient attitude of hackers is a net win. I wish its\nadvantages were better understood.For example, I suspect people in Hollywood are\nsimply mystified by\nhackers' attitudes toward copyrights. They are a perennial\ntopic of heated discussion on Slashdot.\nBut why should people who program computers\nbe so concerned about copyrights, of all things?Partly because some companies use mechanisms to prevent\ncopying. Show any hacker a lock and his first thought is\nhow to pick it. But there is a deeper reason that\nhackers are alarmed by measures like copyrights and patents.\nThey see increasingly aggressive measures to protect\n\"intellectual property\"\nas a threat to the intellectual\nfreedom they need to do their job.\nAnd they are right.It is by poking about inside current technology that\nhackers get ideas for the next generation. No thanks,\nintellectual homeowners may say, we don't need any\noutside help. But they're wrong.\nThe next generation of computer technology has\noften—perhaps more often than not—been developed by outsiders.In 1977 there was no doubt some group within IBM developing\nwhat they expected to be\nthe next generation of business computer. They were mistaken.\nThe next generation of business computer was\nbeing developed on entirely different lines by two long-haired\nguys called Steve in a garage in Los Altos. At about the\nsame time, the powers that be\nwere cooperating to develop the\nofficial next generation operating system, Multics.\nBut two guys who thought Multics excessively complex went off\nand wrote their own. They gave it a name that\nwas a joking reference to Multics: Unix.The latest intellectual property laws impose\nunprecedented restrictions on the sort of poking around that\nleads to new ideas. In the past, a competitor might use patents\nto prevent you from selling a copy of something they\nmade, but they couldn't prevent you from\ntaking one apart to see how it worked. The latest\nlaws make this a crime. How are we\nto develop new technology if we can't study current\ntechnology to figure out how to improve it?Ironically, hackers have brought this on themselves.\nComputers are responsible for the problem. The control systems\ninside machines used to be physical: gears and levers and cams.\nIncreasingly, the brains (and thus the value) of products is\nin software. And by this I mean software in the general sense:\ni.e. data. A song on an LP is physically stamped into the\nplastic. A song on an iPod's disk is merely stored on it.Data is by definition easy to copy. And the Internet\nmakes copies easy to distribute. So it is no wonder\ncompanies are afraid. But, as so often happens, fear has\nclouded their judgement. The government has responded\nwith draconian laws to protect intellectual property.\nThey probably mean well. But\nthey may not realize that such laws will do more harm\nthan good.Why are programmers so violently opposed to these laws?\nIf I were a legislator, I'd be interested in this\nmystery—for the same reason that, if I were a farmer and suddenly\nheard a lot of squawking coming from my hen house one night,\nI'd want to go out and investigate. Hackers are not stupid,\nand unanimity is very rare in this world.\nSo if they're all squawking, \nperhaps there is something amiss.Could it be that such laws, though intended to protect America,\nwill actually harm it? Think about it. There is something\nvery American about Feynman breaking into safes during\nthe Manhattan Project. It's hard to imagine the authorities\nhaving a sense of humor about such things over\nin Germany at that time. Maybe it's not a coincidence.Hackers are unruly. That is the essence of hacking. And it\nis also the essence of Americanness. It is no accident\nthat Silicon Valley\nis in America, and not France, or Germany,\nor England, or Japan. In those countries, people color inside\nthe lines.I lived for a while in Florence. But after I'd been there\na few months I realized that what I'd been unconsciously hoping\nto find there was back in the place I'd just left.\nThe reason Florence is famous is that in 1450, it was New York.\nIn 1450 it was filled with the kind of turbulent and ambitious\npeople you find now in America. (So I went back to America.)It is greatly to America's advantage that it is\na congenial atmosphere for the right sort of unruliness—that\nit is a home not just for the smart, but for smart-alecks.\nAnd hackers are invariably smart-alecks. If we had a national\nholiday, it would be April 1st. It says a great deal about\nour work that we use the same word for a brilliant or a\nhorribly cheesy solution. When we cook one up we're not\nalways 100% sure which kind it is. But as long as it has\nthe right sort of wrongness, that's a promising sign.\nIt's odd that people\nthink of programming as precise and methodical. Computers\nare precise and methodical. Hacking is something you do\nwith a gleeful laugh.In our world some of the most characteristic solutions\nare not far removed from practical\njokes. IBM was no doubt rather surprised by the consequences\nof the licensing deal for DOS, just as the hypothetical\n\"adversary\" must be when Michael Rabin solves a problem by\nredefining it as one that's easier to solve.Smart-alecks have to develop a keen sense of how much they\ncan get away with. And lately hackers \nhave sensed a change\nin the atmosphere.\nLately hackerliness seems rather frowned upon.To hackers the recent contraction in civil liberties seems\nespecially ominous. That must also mystify outsiders. \nWhy should we care especially about civil\nliberties? Why programmers, more than\ndentists or salesmen or landscapers?Let me put the case in terms a government official would appreciate.\nCivil liberties are not just an ornament, or a quaint\nAmerican tradition. Civil liberties make countries rich.\nIf you made a graph of\nGNP per capita vs. civil liberties, you'd notice a definite\ntrend. Could civil liberties really be a cause, rather\nthan just an effect? I think so. I think a society in which\npeople can do and say what they want will also tend to\nbe one in which the most efficient solutions win, rather than\nthose sponsored by the most influential people.\nAuthoritarian countries become corrupt;\ncorrupt countries become poor; and poor countries are weak. \nIt seems to me there is\na Laffer curve for government power, just as for\ntax revenues. At least, it seems likely enough that it\nwould be stupid to try the experiment and find out. Unlike\nhigh tax rates, you can't repeal totalitarianism if it\nturns out to be a mistake.This is why hackers worry. The government spying on people doesn't\nliterally make programmers write worse code. It just leads\neventually to a world in which bad ideas win. And because\nthis is so important to hackers, they're especially sensitive\nto it. They can sense totalitarianism approaching from a\ndistance, as animals can sense an approaching \nthunderstorm.It would be ironic if, as hackers fear, recent measures\nintended to protect national security and intellectual property\nturned out to be a missile aimed right at what makes \nAmerica successful. But it would not be the first time that\nmeasures taken in an atmosphere of panic had\nthe opposite of the intended effect.There is such a thing as Americanness.\nThere's nothing like living abroad to teach you that. \nAnd if you want to know whether something will nurture or squash\nthis quality, it would be hard to find a better focus\ngroup than hackers, because they come closest of any group\nI know to embodying it. Closer, probably, than\nthe men running our government,\nwho for all their talk of patriotism\nremind me more of Richelieu or Mazarin\nthan Thomas Jefferson or George Washington.When you read what the founding fathers had to say for\nthemselves, they sound more like hackers.\n\"The spirit of resistance to government,\"\nJefferson wrote, \"is so valuable on certain occasions, that I wish\nit always to be kept alive.\"Imagine an American president saying that today.\nLike the remarks of an outspoken old grandmother, the sayings of\nthe founding fathers have embarrassed generations of\ntheir less confident successors. They remind us where we come from.\nThey remind us that it is the people who break rules that are\nthe source of America's wealth and power.Those in a position to impose rules naturally want them to be\nobeyed. But be careful what you ask for. You might get it.Thanks to Ken Anderson, Trevor Blackwell, Daniel Giffin, \nSarah Harlin, Shiro Kawai, Jessica Livingston, Matz, \nJackie McDonough, Robert Morris, Eric Raymond, Guido van Rossum,\nDavid Weinberger, and\nSteven Wolfram for reading drafts of this essay.\n(The image shows Steves Jobs and Wozniak \nwith a \"blue box.\"\nPhoto by Margret Wozniak. Reproduced by permission of Steve\nWozniak.)" }, { "path": "data/PaulGrahamEssays/genius.txt", "content": "November 2019Everyone knows that to do great work you need both natural ability\nand determination. But there's a third ingredient that's not as\nwell understood: an obsessive interest in a particular topic.To explain this point I need to burn my reputation with some group\nof people, and I'm going to choose bus ticket collectors. There\nare people who collect old bus tickets. Like many collectors, they\nhave an obsessive interest in the minutiae of what they collect.\nThey can keep track of distinctions between different types of bus\ntickets that would be hard for the rest of us to remember. Because\nwe don't care enough. What's the point of spending so much time\nthinking about old bus tickets?Which leads us to the second feature of this kind of obsession:\nthere is no point. A bus ticket collector's love is disinterested.\nThey're not doing it to impress us or to make themselves rich, but\nfor its own sake.When you look at the lives of people who've done great work, you\nsee a consistent pattern. They often begin with a bus ticket\ncollector's obsessive interest in something that would have seemed\npointless to most of their contemporaries. One of the most striking\nfeatures of Darwin's book about his voyage on the Beagle is the\nsheer depth of his interest in natural history. His curiosity seems\ninfinite. Ditto for Ramanujan, sitting by the hour working out on\nhis slate what happens to series.It's a mistake to think they were \"laying the groundwork\" for the\ndiscoveries they made later. There's too much intention in that\nmetaphor. Like bus ticket collectors, they were doing it\nbecause they liked it.But there is a difference between Ramanujan and a bus ticket\ncollector. Series matter, and bus tickets don't.If I had to put the recipe for genius into one sentence, that might\nbe it: to have a disinterested obsession with something that matters.Aren't I forgetting about the other two ingredients? Less than you\nmight think. An obsessive interest in a topic is both a proxy for\nability and a substitute for determination. Unless you have\nsufficient mathematical aptitude, you won't find series interesting.\nAnd when you're obsessively interested in something, you don't need\nas much determination: you don't need to push yourself as hard when\ncuriosity is pulling you.An obsessive interest will even bring you luck, to the extent\nanything can. Chance, as Pasteur said, favors the prepared mind,\nand if there's one thing an obsessed mind is, it's prepared.The disinterestedness of this kind of obsession is its most important\nfeature. Not just because it's a filter for earnestness, but because\nit helps you discover new ideas.The paths that lead to new ideas tend to look unpromising. If they\nlooked promising, other people would already have explored them.\nHow do the people who do great work discover these paths that others\noverlook? The popular story is that they simply have better vision:\nbecause they're so talented, they see paths that others miss. But\nif you look at the way great discoveries are made, that's not what\nhappens. Darwin didn't pay closer attention to individual species\nthan other people because he saw that this would lead to great\ndiscoveries, and they didn't. He was just really, really interested\nin such things.Darwin couldn't turn it off. Neither could Ramanujan. They didn't\ndiscover the hidden paths that they did because they seemed promising,\nbut because they couldn't help it. That's what allowed them to\nfollow paths that someone who was merely ambitious would have\nignored.What rational person would decide that the way to write great novels\nwas to begin by spending several years creating an imaginary elvish\nlanguage, like Tolkien, or visiting every household in southwestern\nBritain, like Trollope? No one, including Tolkien and Trollope.The bus ticket theory is similar to Carlyle's famous definition of\ngenius as an infinite capacity for taking pains. But there are two\ndifferences. The bus ticket theory makes it clear that the source\nof this infinite capacity for taking pains is not infinite diligence,\nas Carlyle seems to have meant, but the sort of infinite interest\nthat collectors have. It also adds an important qualification: an\ninfinite capacity for taking pains about something that matters.So what matters? You can never be sure. It's precisely because no\none can tell in advance which paths are promising that you can\ndiscover new ideas by working on what you're interested in.But there are some heuristics you can use to guess whether an\nobsession might be one that matters. For example, it's more promising\nif you're creating something, rather than just consuming something\nsomeone else creates. It's more promising if something you're\ninterested in is difficult, especially if it's more difficult for\nother people than it is for you. And the obsessions of talented\npeople are more likely to be promising. When talented people become\ninterested in random things, they're not truly random.But you can never be sure. In fact, here's an interesting idea\nthat's also rather alarming if it's true: it may be that to do great\nwork, you also have to waste a lot of time.In many different areas, reward is proportionate to risk. If that\nrule holds here, then the way to find paths that lead to truly great\nwork is to be willing to expend a lot of effort on things that turn\nout to be every bit as unpromising as they seem.I'm not sure if this is true. On one hand, it seems surprisingly\ndifficult to waste your time so long as you're working hard on\nsomething interesting. So much of what you do ends up being useful.\nBut on the other hand, the rule about the relationship between risk\nand reward is so powerful that it seems to hold wherever risk occurs.\nNewton's case, at least, suggests that the risk/reward rule holds\nhere. He's famous for one particular obsession of his that turned\nout to be unprecedentedly fruitful: using math to describe the\nworld. But he had two other obsessions, alchemy and theology, that\nseem to have been complete wastes of time. He ended up net ahead.\nHis bet on what we now call physics paid off so well that it more\nthan compensated for the other two. But were the other two necessary,\nin the sense that he had to take big risks to make such big\ndiscoveries? I don't know.Here's an even more alarming idea: might one make all bad bets? It\nprobably happens quite often. But we don't know how often, because\nthese people don't become famous.It's not merely that the returns from following a path are hard to\npredict. They change dramatically over time. 1830 was a really good\ntime to be obsessively interested in natural history. If Darwin had\nbeen born in 1709 instead of 1809, we might never have heard of\nhim.What can one do in the face of such uncertainty? One solution is\nto hedge your bets, which in this case means to follow the obviously\npromising paths instead of your own private obsessions. But as with\nany hedge, you're decreasing reward when you decrease risk. If you\nforgo working on what you like in order to follow some more\nconventionally ambitious path, you might miss something wonderful\nthat you'd otherwise have discovered. That too must happen all the\ntime, perhaps even more often than the genius whose bets all fail.The other solution is to let yourself be interested in lots of\ndifferent things. You don't decrease your upside if you switch\nbetween equally genuine interests based on which seems to be working\nso far. But there is a danger here too: if you work on too many\ndifferent projects, you might not get deeply enough into any of\nthem.One interesting thing about the bus ticket theory is that it may\nhelp explain why different types of people excel at different kinds\nof work. Interest is much more unevenly distributed than ability.\nIf natural ability is all you need to do great work, and natural\nability is evenly distributed, you have to invent elaborate theories\nto explain the skewed distributions we see among those who actually\ndo great work in various fields. But it may be that much of the\nskew has a simpler explanation: different people are interested in\ndifferent things.The bus ticket theory also explains why people are less likely to\ndo great work after they have children. Here interest has to compete\nnot just with external obstacles, but with another interest, and\none that for most people is extremely powerful. It's harder to find\ntime for work after you have kids, but that's the easy part. The\nreal change is that you don't want to.But the most exciting implication of the bus ticket theory is that\nit suggests ways to encourage great work. If the recipe for genius\nis simply natural ability plus hard work, all we can do is hope we\nhave a lot of ability, and work as hard as we can. But if interest\nis a critical ingredient in genius, we may be able, by cultivating\ninterest, to cultivate genius.For example, for the very ambitious, the bus ticket theory suggests\nthat the way to do great work is to relax a little. Instead of\ngritting your teeth and diligently pursuing what all your peers\nagree is the most promising line of research, maybe you should try\ndoing something just for fun. And if you're stuck, that may be the\nvector along which to break out.I've always liked Hamming's famous double-barrelled question: what\nare the most important problems in your field, and why aren't you\nworking on one of them? It's a great way to shake yourself up. But\nit may be overfitting a bit. It might be at least as useful to ask\nyourself: if you could take a year off to work on something that\nprobably wouldn't be important but would be really interesting,\nwhat would it be?The bus ticket theory also suggests a way to avoid slowing down as\nyou get older. Perhaps the reason people have fewer new ideas as\nthey get older is not simply that they're losing their edge. It may\nalso be because once you become established, you can no longer mess\nabout with irresponsible side projects the way you could when you\nwere young and no one cared what you did.The solution to that is obvious: remain irresponsible. It will be\nhard, though, because the apparently random projects you take up\nto stave off decline will read to outsiders as evidence of it. And\nyou yourself won't know for sure that they're wrong. But it will\nat least be more fun to work on what you want.It may even be that we can cultivate a habit of intellectual bus\nticket collecting in kids. The usual plan in education is to start\nwith a broad, shallow focus, then gradually become more specialized.\nBut I've done the opposite with my kids. I know I can count on their\nschool to handle the broad, shallow part, so I take them deep.When they get interested in something, however random, I encourage\nthem to go preposterously, bus ticket collectorly, deep. I don't\ndo this because of the bus ticket theory. I do it because I want\nthem to feel the joy of learning, and they're never going to feel\nthat about something I'm making them learn. It has to be something\nthey're interested in. I'm just following the path of least resistance;\ndepth is a byproduct. But if in trying to show them the joy of\nlearning I also end up training them to go deep, so much the better.Will it have any effect? I have no idea. But that uncertainty may\nbe the most interesting point of all. There is so much more to learn\nabout how to do great work. As old as human civilization feels,\nit's really still very young if we haven't nailed something so\nbasic. It's exciting to think there are still discoveries to make\nabout discovery. If that's the sort of thing you're interested in.\nNotes[1] There are other types of collecting that illustrate this point\nbetter than bus tickets, but they're also more popular. It seemed\njust as well to use an inferior example rather than offend more\npeople by telling them their hobby doesn't matter.[2] I worried a little about using the word \"disinterested,\" since\nsome people mistakenly believe it means not interested. But anyone\nwho expects to be a genius will have to know the meaning of such a\nbasic word, so I figure they may as well start now.[3] Think how often genius must have been nipped in the bud by\npeople being told, or telling themselves, to stop messing about and\nbe responsible. Ramanujan's mother was a huge enabler. Imagine if\nshe hadn't been. Imagine if his parents had made him go out and get\na job instead of sitting around at home doing math.On the other hand, anyone quoting the preceding paragraph to justify\nnot getting a job is probably mistaken.[4] 1709 Darwin is to time what the Milanese Leonardo is to space.[5] \"An infinite capacity for taking pains\" is a paraphrase of what\nCarlyle wrote. What he wrote, in his History of Frederick the Great,\nwas \"... it is the fruit of 'genius' (which means transcendent\ncapacity of taking trouble, first of all)....\" Since the paraphrase\nseems the name of the idea at this point, I kept it.Carlyle's History was published in 1858. In 1785 Hérault de Séchelles\nquoted Buffon as saying \"Le génie n'est qu'une plus grande aptitude\nà la patience.\" (Genius is only a greater aptitude for patience.)[6] Trollope was establishing the system of postal routes. He himself\nsensed the obsessiveness with which he pursued this goal.\n\n It is amusing to watch how a passion will grow upon a man. During\n those two years it was the ambition of my life to cover the\n country with rural letter-carriers.\n\nEven Newton occasionally sensed the degree of his obsessiveness.\nAfter computing pi to 15 digits, he wrote in a letter to a friend:\n\n I am ashamed to tell you to how many figures I carried these\n computations, having no other business at the time.\n\nIncidentally, Ramanujan was also a compulsive calculator. As Kanigel\nwrites in his excellent biography:\n\n One Ramanujan scholar, B. M. Wilson, later told how Ramanujan's\n research into number theory was often \"preceded by a table of\n numerical results, carried usually to a length from which most\n of us would shrink.\"\n\n[7] Working to understand the natural world counts as creating\nrather than consuming.Newton tripped over this distinction when he chose\nto work on theology. His beliefs did not allow him to see it, but\nchasing down paradoxes in nature is fruitful in a way that chasing\ndown paradoxes in sacred texts is not.[8] How much of people's propensity to become interested in a topic\nis inborn? My experience so far suggests the answer is: most of\nit. Different kids get interested in different things, and it's\nhard to make a child interested in something they wouldn't otherwise\nbe. Not in a way that sticks. The most you can do on behalf of a\ntopic is to make sure it gets a fair showing — to make it clear to\nthem, for example, that there's more to math than the dull drills\nthey do in school. After that it's up to the child.Thanks to Marc Andreessen, Trevor Blackwell, Patrick Collison, Kevin\nLacker, Jessica Livingston, Jackie McDonough, Robert Morris, Lisa\nRandall, Zak Stone, and my 7 year old for reading drafts of this." }, { "path": "data/PaulGrahamEssays/getideas.txt", "content": "January 2023(Someone fed my essays into GPT to make something that could answer\nquestions based on them, then asked it where good ideas come from. The\nanswer was ok, but not what I would have said. This is what I would have said.)The way to get new ideas is to notice anomalies: what seems strange,\nor missing, or broken? You can see anomalies in everyday life (much\nof standup comedy is based on this), but the best place to look for\nthem is at the frontiers of knowledge.Knowledge grows fractally.\nFrom a distance its edges look smooth, but when you learn enough\nto get close to one, you'll notice it's full of gaps. These gaps\nwill seem obvious; it will seem inexplicable that no one has tried\nx or wondered about y. In the best case, exploring such gaps yields\nwhole new fractal buds." }, { "path": "data/PaulGrahamEssays/gh.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nJuly 2004(This essay is derived from a talk at Oscon 2004.)\nA few months ago I finished a new \nbook, \nand in reviews I keep\nnoticing words like \"provocative'' and \"controversial.'' To say\nnothing of \"idiotic.''I didn't mean to make the book controversial. I was trying to make\nit efficient. I didn't want to waste people's time telling them\nthings they already knew. It's more efficient just to give them\nthe diffs. But I suppose that's bound to yield an alarming book.EdisonsThere's no controversy about which idea is most controversial:\nthe suggestion that variation in wealth might not be as big a\nproblem as we think.I didn't say in the book that variation in wealth was in itself a\ngood thing. I said in some situations it might be a sign of good\nthings. A throbbing headache is not a good thing, but it can be\na sign of a good thing-- for example, that you're recovering\nconsciousness after being hit on the head.Variation in wealth can be a sign of variation in productivity.\n(In a society of one, they're identical.) And that\nis almost certainly a good thing: if your society has no variation\nin productivity, it's probably not because everyone is Thomas\nEdison. It's probably because you have no Thomas Edisons.In a low-tech society you don't see much variation in productivity.\nIf you have a tribe of nomads collecting sticks for a fire, how\nmuch more productive is the best stick gatherer going to be than\nthe worst? A factor of two? Whereas when you hand people a complex tool\nlike a computer, the variation in what they can do with\nit is enormous.That's not a new idea. Fred Brooks wrote about it in 1974, and\nthe study he quoted was published in 1968. But I think he\nunderestimated the variation between programmers. He wrote about productivity in lines\nof code: the best programmers can solve a given problem in a tenth\nthe time. But what if the problem isn't given? In programming, as\nin many fields, the hard part isn't solving problems, but deciding\nwhat problems to solve. Imagination is hard to measure, but\nin practice it dominates the kind of productivity that's measured\nin lines of code.Productivity varies in any field, but there are few in which it\nvaries so much. The variation between programmers\nis so great that it becomes a difference in kind. I don't\nthink this is something intrinsic to programming, though. In every field,\ntechnology magnifies differences in productivity. I think what's\nhappening in programming is just that we have a lot of technological\nleverage. But in every field the lever is getting longer, so the\nvariation we see is something that more and more fields will see\nas time goes on. And the success of companies, and countries, will\ndepend increasingly on how they deal with it.If variation in productivity increases with technology, then the\ncontribution of the most productive individuals will not only be\ndisproportionately large, but will actually grow with time. When\nyou reach the point where 90% of a group's output is created by 1%\nof its members, you lose big if something (whether Viking raids,\nor central planning) drags their productivity down to the average.If we want to get the most out of them, we need to understand these\nespecially productive people. What motivates them? What do they\nneed to do their jobs? How do you recognize them? How do you\nget them to come and work for you? And then of course there's the\nquestion, how do you become one?More than MoneyI know a handful of super-hackers, so I sat down and thought about\nwhat they have in common. Their defining quality is probably that\nthey really love to program. Ordinary programmers write code to pay\nthe bills. Great hackers think of it as something they do for fun,\nand which they're delighted to find people will pay them for.Great programmers are sometimes said to be indifferent to money.\nThis isn't quite true. It is true that all they really care about\nis doing interesting work. But if you make enough money, you get\nto work on whatever you want, and for that reason hackers are\nattracted by the idea of making really large amounts of money.\nBut as long as they still have to show up for work every day, they\ncare more about what they do there than how much they get paid for\nit.Economically, this is a fact of the greatest importance, because\nit means you don't have to pay great hackers anything like what\nthey're worth. A great programmer might be ten or a hundred times\nas productive as an ordinary one, but he'll consider himself lucky\nto get paid three times as much. As I'll explain later, this is\npartly because great hackers don't know how good they are. But\nit's also because money is not the main thing they want.What do hackers want? Like all craftsmen, hackers like good tools.\nIn fact, that's an understatement. Good hackers find it unbearable\nto use bad tools. They'll simply refuse to work on projects with\nthe wrong infrastructure.At a startup I once worked for, one of the things pinned up on our\nbulletin board was an ad from IBM. It was a picture of an AS400,\nand the headline read, I think, \"hackers despise\nit.'' [1]When you decide what infrastructure to use for a project, you're\nnot just making a technical decision. You're also making a social\ndecision, and this may be the more important of the two. For\nexample, if your company wants to write some software, it might\nseem a prudent choice to write it in Java. But when you choose a\nlanguage, you're also choosing a community. The programmers you'll\nbe able to hire to work on a Java project won't be as\nsmart as the\nones you could get to work on a project written in Python.\nAnd the quality of your hackers probably matters more than the\nlanguage you choose. Though, frankly, the fact that good hackers\nprefer Python to Java should tell you something about the relative\nmerits of those languages.Business types prefer the most popular languages because they view\nlanguages as standards. They don't want to bet the company on\nBetamax. The thing about languages, though, is that they're not\njust standards. If you have to move bits over a network, by all\nmeans use TCP/IP. But a programming language isn't just a format.\nA programming language is a medium of expression.I've read that Java has just overtaken Cobol as the most popular\nlanguage. As a standard, you couldn't wish for more. But as a\nmedium of expression, you could do a lot better. Of all the great\nprogrammers I can think of, I know of only one who would voluntarily\nprogram in Java. And of all the great programmers I can think of\nwho don't work for Sun, on Java, I know of zero.Great hackers also generally insist on using open source software.\nNot just because it's better, but because it gives them more control.\nGood hackers insist on control. This is part of what makes them\ngood hackers: when something's broken, they need to fix it. You\nwant them to feel this way about the software they're writing for\nyou. You shouldn't be surprised when they feel the same way about\nthe operating system.A couple years ago a venture capitalist friend told me about a new\nstartup he was involved with. It sounded promising. But the next\ntime I talked to him, he said they'd decided to build their software\non Windows NT, and had just hired a very experienced NT developer\nto be their chief technical officer. When I heard this, I thought,\nthese guys are doomed. One, the CTO couldn't be a first rate\nhacker, because to become an eminent NT developer he would have\nhad to use NT voluntarily, multiple times, and I couldn't imagine\na great hacker doing that; and two, even if he was good, he'd have\na hard time hiring anyone good to work for him if the project had\nto be built on NT. [2]The Final FrontierAfter software, the most important tool to a hacker is probably\nhis office. Big companies think the function of office space is to express\nrank. But hackers use their offices for more than that: they\nuse their office as a place to think in. And if you're a technology\ncompany, their thoughts are your product. So making hackers work\nin a noisy, distracting environment is like having a paint factory\nwhere the air is full of soot.The cartoon strip Dilbert has a lot to say about cubicles, and with\ngood reason. All the hackers I know despise them. The mere prospect\nof being interrupted is enough to prevent hackers from working on\nhard problems. If you want to get real work done in an office with\ncubicles, you have two options: work at home, or come in early or\nlate or on a weekend, when no one else is there. Don't companies\nrealize this is a sign that something is broken? An office\nenvironment is supposed to be something that helps\nyou work, not something you work despite.Companies like Cisco are proud that everyone there has a cubicle,\neven the CEO. But they're not so advanced as they think; obviously\nthey still view office space as a badge of rank. Note too that\nCisco is famous for doing very little product development in house.\nThey get new technology by buying the startups that created it-- where\npresumably the hackers did have somewhere quiet to work.One big company that understands what hackers need is Microsoft.\nI once saw a recruiting ad for Microsoft with a big picture of a\ndoor. Work for us, the premise was, and we'll give you a place to\nwork where you can actually get work done. And you know, Microsoft\nis remarkable among big companies in that they are able to develop\nsoftware in house. Not well, perhaps, but well enough.If companies want hackers to be productive, they should look at\nwhat they do at home. At home, hackers can arrange things themselves\nso they can get the most done. And when they work at home, hackers\ndon't work in noisy, open spaces; they work in rooms with doors. They\nwork in cosy, neighborhoody places with people around and somewhere\nto walk when they need to mull something over, instead of in glass\nboxes set in acres of parking lots. They have a sofa they can take\na nap on when they feel tired, instead of sitting in a coma at\ntheir desk, pretending to work. There's no crew of people with\nvacuum cleaners that roars through every evening during the prime\nhacking hours. There are no meetings or, God forbid, corporate\nretreats or team-building exercises. And when you look at what\nthey're doing on that computer, you'll find it reinforces what I\nsaid earlier about tools. They may have to use Java and Windows\nat work, but at home, where they can choose for themselves, you're\nmore likely to find them using Perl and Linux.Indeed, these statistics about Cobol or Java being the most popular\nlanguage can be misleading. What we ought to look at, if we want\nto know what tools are best, is what hackers choose when they can\nchoose freely-- that is, in projects of their own. When you ask\nthat question, you find that open source operating systems already\nhave a dominant market share, and the number one language is probably\nPerl.InterestingAlong with good tools, hackers want interesting projects. What\nmakes a project interesting? Well, obviously overtly sexy\napplications like stealth planes or special effects software would\nbe interesting to work on. But any application can be interesting\nif it poses novel technical challenges. So it's hard to predict\nwhich problems hackers will like, because some become\ninteresting only when the people working on them discover a new\nkind of solution. Before ITA\n(who wrote the software inside Orbitz),\nthe people working on airline fare searches probably thought it\nwas one of the most boring applications imaginable. But ITA made\nit interesting by \nredefining the problem in a more ambitious way.I think the same thing happened at Google. When Google was founded,\nthe conventional wisdom among the so-called portals was that search\nwas boring and unimportant. But the guys at Google didn't think\nsearch was boring, and that's why they do it so well.This is an area where managers can make a difference. Like a parent\nsaying to a child, I bet you can't clean up your whole room in\nten minutes, a good manager can sometimes redefine a problem as a\nmore interesting one. Steve Jobs seems to be particularly good at\nthis, in part simply by having high standards. There were a lot\nof small, inexpensive computers before the Mac. He redefined the\nproblem as: make one that's beautiful. And that probably drove\nthe developers harder than any carrot or stick could.They certainly delivered. When the Mac first appeared, you didn't\neven have to turn it on to know it would be good; you could tell\nfrom the case. A few weeks ago I was walking along the street in\nCambridge, and in someone's trash I saw what appeared to be a Mac\ncarrying case. I looked inside, and there was a Mac SE. I carried\nit home and plugged it in, and it booted. The happy Macintosh\nface, and then the finder. My God, it was so simple. It was just\nlike ... Google.Hackers like to work for people with high standards. But it's not\nenough just to be exacting. You have to insist on the right things.\nWhich usually means that you have to be a hacker yourself. I've\nseen occasional articles about how to manage programmers. Really\nthere should be two articles: one about what to do if\nyou are yourself a programmer, and one about what to do if you're not. And the \nsecond could probably be condensed into two words: give up.The problem is not so much the day to day management. Really good\nhackers are practically self-managing. The problem is, if you're\nnot a hacker, you can't tell who the good hackers are. A similar\nproblem explains why American cars are so ugly. I call it the\ndesign paradox. You might think that you could make your products\nbeautiful just by hiring a great designer to design them. But if\nyou yourself don't have good taste, \nhow are you going to recognize\na good designer? By definition you can't tell from his portfolio.\nAnd you can't go by the awards he's won or the jobs he's had,\nbecause in design, as in most fields, those tend to be driven by\nfashion and schmoozing, with actual ability a distant third.\nThere's no way around it: you can't manage a process intended to\nproduce beautiful things without knowing what beautiful is. American\ncars are ugly because American car companies are run by people with\nbad taste.Many people in this country think of taste as something elusive,\nor even frivolous. It is neither. To drive design, a manager must\nbe the most demanding user of a company's products. And if you\nhave really good taste, you can, as Steve Jobs does, make satisfying\nyou the kind of problem that good people like to work on.Nasty Little ProblemsIt's pretty easy to say what kinds of problems are not interesting:\nthose where instead of solving a few big, clear, problems, you have\nto solve a lot of nasty little ones. One of the worst kinds of\nprojects is writing an interface to a piece of software that's\nfull of bugs. Another is when you have to customize\nsomething for an individual client's complex and ill-defined needs.\nTo hackers these kinds of projects are the death of a thousand\ncuts.The distinguishing feature of nasty little problems is that you\ndon't learn anything from them. Writing a compiler is interesting\nbecause it teaches you what a compiler is. But writing an interface\nto a buggy piece of software doesn't teach you anything, because the\nbugs are random. [3] So it's not just fastidiousness that makes good\nhackers avoid nasty little problems. It's more a question of\nself-preservation. Working on nasty little problems makes you\nstupid. Good hackers avoid it for the same reason models avoid\ncheeseburgers.Of course some problems inherently have this character. And because\nof supply and demand, they pay especially well. So a company that\nfound a way to get great hackers to work on tedious problems would\nbe very successful. How would you do it?One place this happens is in startups. At our startup we had \nRobert Morris working as a system administrator. That's like having the\nRolling Stones play at a bar mitzvah. You can't hire that kind of\ntalent. But people will do any amount of drudgery for companies\nof which they're the founders. [4]Bigger companies solve the problem by partitioning the company.\nThey get smart people to work for them by establishing a separate\nR&D department where employees don't have to work directly on\ncustomers' nasty little problems. [5] In this model, the research\ndepartment functions like a mine. They produce new ideas; maybe\nthe rest of the company will be able to use them.You may not have to go to this extreme. \nBottom-up programming\nsuggests another way to partition the company: have the smart people\nwork as toolmakers. If your company makes software to do x, have\none group that builds tools for writing software of that type, and\nanother that uses these tools to write the applications. This way\nyou might be able to get smart people to write 99% of your code,\nbut still keep them almost as insulated from users as they would\nbe in a traditional research department. The toolmakers would have\nusers, but they'd only be the company's own developers. [6]If Microsoft used this approach, their software wouldn't be so full\nof security holes, because the less smart people writing the actual\napplications wouldn't be doing low-level stuff like allocating\nmemory. Instead of writing Word directly in C, they'd be plugging\ntogether big Lego blocks of Word-language. (Duplo, I believe, is\nthe technical term.)ClumpingAlong with interesting problems, what good hackers like is other\ngood hackers. Great hackers tend to clump together-- sometimes\nspectacularly so, as at Xerox Parc. So you won't attract good\nhackers in linear proportion to how good an environment you create\nfor them. The tendency to clump means it's more like the square\nof the environment. So it's winner take all. At any given time,\nthere are only about ten or twenty places where hackers most want to\nwork, and if you aren't one of them, you won't just have fewer\ngreat hackers, you'll have zero.Having great hackers is not, by itself, enough to make a company\nsuccessful. It works well for Google and ITA, which are two of\nthe hot spots right now, but it didn't help Thinking Machines or\nXerox. Sun had a good run for a while, but their business model\nis a down elevator. In that situation, even the best hackers can't\nsave you.I think, though, that all other things being equal, a company that\ncan attract great hackers will have a huge advantage. There are\npeople who would disagree with this. When we were making the rounds\nof venture capital firms in the 1990s, several told us that software\ncompanies didn't win by writing great software, but through brand,\nand dominating channels, and doing the right deals.They really seemed to believe this, and I think I know why. I\nthink what a lot of VCs are looking for, at least unconsciously,\nis the next Microsoft. And of course if Microsoft is your model,\nyou shouldn't be looking for companies that hope to win by writing\ngreat software. But VCs are mistaken to look for the next Microsoft,\nbecause no startup can be the next Microsoft unless some other\ncompany is prepared to bend over at just the right moment and be\nthe next IBM.It's a mistake to use Microsoft as a model, because their whole\nculture derives from that one lucky break. Microsoft is a bad data\npoint. If you throw them out, you find that good products do tend\nto win in the market. What VCs should be looking for is the next\nApple, or the next Google.I think Bill Gates knows this. What worries him about Google is\nnot the power of their brand, but the fact that they have\nbetter hackers. [7]\nRecognitionSo who are the great hackers? How do you know when you meet one?\nThat turns out to be very hard. Even hackers can't tell. I'm\npretty sure now that my friend Trevor Blackwell is a great hacker.\nYou may have read on Slashdot how he made his \nown Segway. The\nremarkable thing about this project was that he wrote all the\nsoftware in one day (in Python, incidentally).For Trevor, that's\npar for the course. But when I first met him, I thought he was a\ncomplete idiot. He was standing in Robert Morris's office babbling\nat him about something or other, and I remember standing behind\nhim making frantic gestures at Robert to shoo this nut out of his\noffice so we could go to lunch. Robert says he misjudged Trevor\nat first too. Apparently when Robert first met him, Trevor had\njust begun a new scheme that involved writing down everything about\nevery aspect of his life on a stack of index cards, which he carried\nwith him everywhere. He'd also just arrived from Canada, and had\na strong Canadian accent and a mullet.The problem is compounded by the fact that hackers, despite their\nreputation for social obliviousness, sometimes put a good deal of\neffort into seeming smart. When I was in grad school I used to\nhang around the MIT AI Lab occasionally. It was kind of intimidating\nat first. Everyone there spoke so fast. But after a while I\nlearned the trick of speaking fast. You don't have to think any\nfaster; just use twice as many words to say everything. With this amount of noise in the signal, it's hard to tell good\nhackers when you meet them. I can't tell, even now. You also\ncan't tell from their resumes. It seems like the only way to judge\na hacker is to work with him on something.And this is the reason that high-tech areas \nonly happen around universities. The active ingredient\nhere is not so much the professors as the students. Startups grow up\naround universities because universities bring together promising young\npeople and make them work on the same projects. The\nsmart ones learn who the other smart ones are, and together\nthey cook up new projects of their own.Because you can't tell a great hacker except by working with him,\nhackers themselves can't tell how good they are. This is true to\na degree in most fields. I've found that people who\nare great at something are not so much convinced of their own\ngreatness as mystified at why everyone else seems so incompetent.\nBut it's particularly hard for hackers to know how good they are,\nbecause it's hard to compare their work. This is easier in most\nother fields. In the hundred meters, you know in 10 seconds who's\nfastest. Even in math there seems to be a general consensus about\nwhich problems are hard to solve, and what constitutes a good\nsolution. But hacking is like writing. Who can say which of two\nnovels is better? Certainly not the authors.With hackers, at least, other hackers can tell. That's because,\nunlike novelists, hackers collaborate on projects. When you get\nto hit a few difficult problems over the net at someone, you learn\npretty quickly how hard they hit them back. But hackers can't\nwatch themselves at work. So if you ask a great hacker how good\nhe is, he's almost certain to reply, I don't know. He's not just\nbeing modest. He really doesn't know.And none of us know, except about people we've actually worked\nwith. Which puts us in a weird situation: we don't know who our\nheroes should be. The hackers who become famous tend to become\nfamous by random accidents of PR. Occasionally I need to give an\nexample of a great hacker, and I never know who to use. The first\nnames that come to mind always tend to be people I know personally,\nbut it seems lame to use them. So, I think, maybe I should say\nRichard Stallman, or Linus Torvalds, or Alan Kay, or someone famous\nlike that. But I have no idea if these guys are great hackers.\nI've never worked with them on anything.If there is a Michael Jordan of hacking, no one knows, including\nhim.CultivationFinally, the question the hackers have all been wondering about:\nhow do you become a great hacker? I don't know if it's possible\nto make yourself into one. But it's certainly possible to do things\nthat make you stupid, and if you can make yourself stupid, you\ncan probably make yourself smart too.The key to being a good hacker may be to work on what you like.\nWhen I think about the great hackers I know, one thing they have\nin common is the extreme \ndifficulty of making them work \non anything they\ndon't want to. I don't know if this is cause or effect; it may be\nboth.To do something well you have to love it. \nSo to the extent you\ncan preserve hacking as something you love, you're likely to do it\nwell. Try to keep the sense of wonder you had about programming at\nage 14. If you're worried that your current job is rotting your\nbrain, it probably is.The best hackers tend to be smart, of course, but that's true in\na lot of fields. Is there some quality that's unique to hackers?\nI asked some friends, and the number one thing they mentioned was\ncuriosity. \nI'd always supposed that all smart people were curious--\nthat curiosity was simply the first derivative of knowledge. But\napparently hackers are particularly curious, especially about how\nthings work. That makes sense, because programs are in effect\ngiant descriptions of how things work.Several friends mentioned hackers' ability to concentrate-- their\nability, as one put it, to \"tune out everything outside their own\nheads.'' I've certainly noticed this. And I've heard several \nhackers say that after drinking even half a beer they can't program at\nall. So maybe hacking does require some special ability to focus.\nPerhaps great hackers can load a large amount of context into their\nhead, so that when they look at a line of code, they see not just\nthat line but the whole program around it. John McPhee\nwrote that Bill Bradley's success as a basketball player was due\npartly to his extraordinary peripheral vision. \"Perfect'' eyesight\nmeans about 47 degrees of vertical peripheral vision. Bill Bradley\nhad 70; he could see the basket when he was looking at the floor.\nMaybe great hackers have some similar inborn ability. (I cheat by\nusing a very dense language, \nwhich shrinks the court.)This could explain the disconnect over cubicles. Maybe the people\nin charge of facilities, not having any concentration to shatter,\nhave no idea that working in a cubicle feels to a hacker like having\none's brain in a blender. (Whereas Bill, if the rumors of autism\nare true, knows all too well.)One difference I've noticed between great hackers and smart people\nin general is that hackers are more \npolitically incorrect. To the\nextent there is a secret handshake among good hackers, it's when they\nknow one another well enough to express opinions that would get\nthem stoned to death by the general public. And I can see why\npolitical incorrectness would be a useful quality in programming.\nPrograms are very complex and, at least in the hands of good\nprogrammers, very fluid. In such situations it's helpful to have\na habit of questioning assumptions.Can you cultivate these qualities? I don't know. But you can at\nleast not repress them. So here is my best shot at a recipe. If\nit is possible to make yourself into a great hacker, the way to do\nit may be to make the following deal with yourself: you never have\nto work on boring projects (unless your family will starve otherwise),\nand in return, you'll never allow yourself to do a half-assed job.\nAll the great hackers I know seem to have made that deal, though\nperhaps none of them had any choice in the matter.Notes\n[1] In fairness, I have to say that IBM makes decent hardware. I\nwrote this on an IBM laptop.[2] They did turn out to be doomed. They shut down a few months\nlater.[3] I think this is what people mean when they talk\nabout the \"meaning of life.\" On the face of it, this seems an \nodd idea. Life isn't an expression; how could it have meaning?\nBut it can have a quality that feels a lot like meaning. In a project\nlike a compiler, you have to solve a lot of problems, but the problems\nall fall into a pattern, as in a signal. Whereas when the problems\nyou have to solve are random, they seem like noise.\n[4] Einstein at one point worked designing refrigerators. (He had equity.)[5] It's hard to say exactly what constitutes research in the\ncomputer world, but as a first approximation, it's software that\ndoesn't have users.I don't think it's publication that makes the best hackers want to work\nin research departments. I think it's mainly not having to have a\nthree hour meeting with a product manager about problems integrating\nthe Korean version of Word 13.27 with the talking paperclip.[6] Something similar has been happening for a long time in the\nconstruction industry. When you had a house built a couple hundred\nyears ago, the local builders built everything in it. But increasingly\nwhat builders do is assemble components designed and manufactured\nby someone else. This has, like the arrival of desktop publishing,\ngiven people the freedom to experiment in disastrous ways, but it\nis certainly more efficient.[7] Google is much more dangerous to Microsoft than Netscape was.\nProbably more dangerous than any other company has ever been. Not\nleast because they're determined to fight. On their job listing\npage, they say that one of their \"core values'' is \"Don't be evil.''\nFrom a company selling soybean oil or mining equipment, such a\nstatement would merely be eccentric. But I think all of us in the\ncomputer world recognize who that is a declaration of war on.Thanks to Jessica Livingston, Robert Morris, and Sarah Harlin\nfor reading earlier versions of this talk." }, { "path": "data/PaulGrahamEssays/good.txt", "content": "April 2008(This essay is derived from a talk at the 2008 Startup School.)About a month after we started Y Combinator we came up with the\nphrase that became our motto: Make something people want. We've\nlearned a lot since then, but if I were choosing now that's still\nthe one I'd pick.Another thing we tell founders is not to worry too much about the\nbusiness model, at least at first. Not because making money is\nunimportant, but because it's so much easier than building something\ngreat.A couple weeks ago I realized that if you put those two ideas\ntogether, you get something surprising. Make something people want.\nDon't worry too much about making money. What you've got is a\ndescription of a charity.When you get an unexpected result like this, it could either be a\nbug or a new discovery. Either businesses aren't supposed to be\nlike charities, and we've proven by reductio ad absurdum that one\nor both of the principles we began with is false. Or we have a new\nidea.I suspect it's the latter, because as soon as this thought occurred\nto me, a whole bunch of other things fell into place.ExamplesFor example, Craigslist. It's not a charity, but they run it like\none. And they're astoundingly successful. When you scan down the\nlist of most popular web sites, the number of employees at Craigslist\nlooks like a misprint. Their revenues aren't as high as they could\nbe, but most startups would be happy to trade places with them.In Patrick O'Brian's novels, his captains always try to get upwind\nof their opponents. If you're upwind, you decide when and if to\nengage the other ship. Craigslist is effectively upwind of enormous\nrevenues. They'd face some challenges if they wanted to make more,\nbut not the sort you face when you're tacking upwind, trying to\nforce a crappy product on ambivalent users by spending ten times\nas much on sales as on development. [1]I'm not saying startups should aim to end up like Craigslist.\nThey're a product of unusual circumstances. But they're a good\nmodel for the early phases.Google looked a lot like a charity in the beginning. They didn't\nhave ads for over a year. At year 1, Google was indistinguishable\nfrom a nonprofit. If a nonprofit or government organization had\nstarted a project to index the web, Google at year 1 is the limit\nof what they'd have produced.Back when I was working on spam filters I thought it would be a\ngood idea to have a web-based email service with good spam filtering.\nI wasn't thinking of it as a company. I just wanted to keep people\nfrom getting spammed. But as I thought more about this project, I\nrealized it would probably have to be a company. It would cost\nsomething to run, and it would be a pain to fund with grants and\ndonations.That was a surprising realization. Companies often claim to be\nbenevolent, but it was surprising to realize there were purely\nbenevolent projects that had to be embodied as companies to work.I didn't want to start another company, so I didn't do it. But if\nsomeone had, they'd probably be quite rich now. There was a window\nof about two years when spam was increasing rapidly but all the big\nemail services had terrible filters. If someone had launched a\nnew, spam-free mail service, users would have flocked to it.Notice the pattern here? From either direction we get to the same\nspot. If you start from successful startups, you find they often\nbehaved like nonprofits. And if you start from ideas for nonprofits,\nyou find they'd often make good startups.PowerHow wide is this territory? Would all good nonprofits be good\ncompanies? Possibly not. What makes Google so valuable is that\ntheir users have money. If you make people with money love you,\nyou can probably get some of it. But could you also base a successful\nstartup on behaving like a nonprofit to people who don't have money?\nCould you, for example, grow a successful startup out of curing an\nunfashionable but deadly disease like malaria?I'm not sure, but I suspect that if you pushed this idea, you'd be\nsurprised how far it would go. For example, people who apply to Y\nCombinator don't generally have much money, and yet we can profit\nby helping them, because with our help they could make money. Maybe\nthe situation is similar with malaria. Maybe an organization that\nhelped lift its weight off a country could benefit from the resulting\ngrowth.I'm not proposing this is a serious idea. I don't know anything\nabout malaria. But I've been kicking ideas around long enough to\nknow when I come across a powerful one.One way to guess how far an idea extends is to ask yourself at what\npoint you'd bet against it. The thought of betting against benevolence\nis alarming in the same way as saying that something is technically\nimpossible. You're just asking to be made a fool of, because these\nare such powerful forces. [2]For example, initially I thought maybe this principle only applied\nto Internet startups. Obviously it worked for Google, but what\nabout Microsoft? Surely Microsoft isn't benevolent? But when I\nthink back to the beginning, they were. Compared to IBM they were\nlike Robin Hood. When IBM introduced the PC, they thought they\nwere going to make money selling hardware at high prices. But by\ngaining control of the PC standard, Microsoft opened up the market\nto any manufacturer. Hardware prices plummeted, and lots of people\ngot to have computers who couldn't otherwise have afforded them.\nIt's the sort of thing you'd expect Google to do.Microsoft isn't so benevolent now. Now when one thinks of what\nMicrosoft does to users, all the verbs that come to mind begin with\nF. [3] And yet it doesn't seem to pay.\nTheir stock price has been flat for years. Back when they were\nRobin Hood, their stock price rose like Google's. Could there be\na connection?You can see how there would be. When you're small, you can't bully\ncustomers, so you have to charm them. Whereas when you're big you\ncan maltreat them at will, and you tend to, because it's easier\nthan satisfying them. You grow big by being nice, but you can stay\nbig by being mean.You get away with it till the underlying conditions change, and\nthen all your victims escape. So \"Don't be evil\" may be the most\nvaluable thing Paul Buchheit made for Google, because it may turn\nout to be an elixir of corporate youth. I'm sure they find it\nconstraining, but think how valuable it will be if it saves them\nfrom lapsing into the fatal laziness that afflicted Microsoft and\nIBM.The curious thing is, this elixir is freely available to any other\ncompany. Anyone can adopt \"Don't be evil.\" The catch is that\npeople will hold you to it. So I don't think you're going to see\nrecord labels or tobacco companies using this discovery.MoraleThere's a lot of external evidence that benevolence works. But how\ndoes it work? One advantage of investing in a large number of\nstartups is that you get a lot of data about how they work. From\nwhat we've seen, being good seems to help startups in three ways:\nit improves their morale, it makes other people want to help them,\nand above all, it helps them be decisive.Morale is tremendously important to a startup—so important\nthat morale alone is almost enough to determine success. Startups\nare often described as emotional roller-coasters. One minute you're\ngoing to take over the world, and the next you're doomed. The\nproblem with feeling you're doomed is not just that it makes you\nunhappy, but that it makes you stop working. So the downhills\nof the roller-coaster are more of a self fulfilling prophecy than\nthe uphills. If feeling you're going to succeed makes you work\nharder, that probably improves your chances of succeeding, but if\nfeeling you're going to fail makes you stop working, that practically\nguarantees you'll fail.Here's where benevolence comes in. If you feel you're really helping\npeople, you'll keep working even when it seems like your startup\nis doomed. Most of us have some amount of natural benevolence.\nThe mere fact that someone needs you makes you want to help them.\nSo if you start the kind of startup where users come back each day,\nyou've basically built yourself a giant tamagotchi. You've made\nsomething you need to take care of.Blogger is a famous example of a startup that went through really\nlow lows and survived. At one point they ran out of money and\neveryone left. Evan Williams came in to work the next day, and there\nwas no one but him. What kept him going? Partly that users needed\nhim. He was hosting thousands of people's blogs. He couldn't just\nlet the site die.There are many advantages of launching quickly, but the most important\nmay be that once you have users, the tamagotchi effect kicks in.\nOnce you have users to take care of, you're forced to figure out\nwhat will make them happy, and that's actually very valuable\ninformation.The added confidence that comes from trying to help people can\nalso help you with investors. One of the founders of \nChatterous told \nme recently that he and his cofounder had decided that this service\nwas something the world needed, so they were going to keep working\non it no matter what, even if they had to move back to Canada and live\nin their parents' basements.Once they realized this, they stopped caring so much what investors thought\nabout them. They still met with them, but they weren't going to\ndie if they didn't get their money. And you know what? The investors\ngot a lot more interested. They could sense that the Chatterouses\nwere going to do this startup with or without them.If you're really committed and your startup is cheap to run, you\nbecome very hard to kill. And practically all startups, even the\nmost successful, come close to death at some point. So if doing\ngood for people gives you a sense of mission that makes you harder\nto kill, that alone more than compensates for whatever you lose by\nnot choosing a more selfish project.HelpAnother advantage of being good is that it makes other people want\nto help you. This too seems to be an inborn trait in humans.One of the startups we've funded, Octopart, is currently locked in\na classic battle of good versus evil. They're a search site for\nindustrial components. A lot of people need to search for components,\nand before Octopart there was no good way to do it. That, it turned\nout, was no coincidence.Octopart built the right way to search for components. Users like\nit and they've been growing rapidly. And yet for most of Octopart's\nlife, the biggest distributor, Digi-Key, has been trying to force\nthem take their prices off the site. Octopart is sending them\ncustomers for free, and yet Digi-Key is trying to make that traffic\nstop. Why? Because their current business model depends on\novercharging people who have incomplete information about prices.\nThey don't want search to work.The Octoparts are the nicest guys in the world. They dropped out\nof the PhD program in physics at Berkeley to do this. They just\nwanted to fix a problem they encountered in their research. Imagine\nhow much time you could save the world's engineers if they could\ndo searches online. So when I hear that a big, evil company is\ntrying to stop them in order to keep search broken, it makes me\nreally want to help them. It makes me spend more time on the Octoparts\nthan I do with most of the other startups we've funded. It just\nmade me spend several minutes telling you how great they are. Why?\nBecause they're good guys and they're trying to help the world.If you're benevolent, people will rally around you: investors,\ncustomers, other companies, and potential employees. In the long\nterm the most important may be the potential employees. I think\neveryone knows now that \ngood hackers are much better than mediocre\nones. If you can attract the best hackers to work for you, as\nGoogle has, you have a big advantage. And the very best hackers\ntend to be idealistic. They're not desperate for a job. They can\nwork wherever they want. So most want to work on things that will\nmake the world better.CompassBut the most important advantage of being good is that it acts as\na compass. One of the hardest parts of doing a startup is that you\nhave so many choices. There are just two or three of you, and a\nthousand things you could do. How do you decide?Here's the answer: Do whatever's best for your users. You can hold\nonto this like a rope in a hurricane, and it will save you if\nanything can. Follow it and it will take you through everything\nyou need to do.It's even the answer to questions that seem unrelated, like how to\nconvince investors to give you money. If you're a good salesman,\nyou could try to just talk them into it. But the more reliable\nroute is to convince them through your users: if you make something\nusers love enough to tell their friends, you grow exponentially,\nand that will convince any investor.Being good is a particularly useful strategy for making decisions\nin complex situations because it's stateless. It's like telling\nthe truth. The trouble with lying is that you have to remember\neverything you've said in the past to make sure you don't contradict\nyourself. If you tell the truth you don't have to remember anything,\nand that's a really useful property in domains where things happen\nfast.For example, Y Combinator has now invested in 80 startups, 57 of\nwhich are still alive. (The rest have died or merged or been\nacquired.) When you're trying to advise 57 startups, it turns out\nyou have to have a stateless algorithm. You can't have ulterior\nmotives when you have 57 things going on at once, because you can't\nremember them. So our rule is just to do whatever's best for the\nfounders. Not because we're particularly benevolent, but because\nit's the only algorithm that works on that scale.When you write something telling people to be good, you seem to be\nclaiming to be good yourself. So I want to say explicitly that I\nam not a particularly good person. When I was a kid I was firmly\nin the camp of bad. The way adults used the word good, it seemed\nto be synonymous with quiet, so I grew up very suspicious of it.You know how there are some people whose names come up in conversation\nand everyone says \"He's such a great guy?\" People never say\nthat about me. The best I get is \"he means well.\" I am not claiming\nto be good. At best I speak good as a second language.So I'm not suggesting you be good in the usual sanctimonious way.\nI'm suggesting it because it works. It will work not just as a\nstatement of \"values,\" but as a guide to strategy,\nand even a design spec for software. Don't just not be evil. Be\ngood.Notes[1] Fifty years ago\nit would have seemed shocking for a public company not to pay\ndividends. Now many tech companies don't. The markets seem to\nhave figured out how to value potential dividends. Maybe that isn't\nthe last step in this evolution. Maybe markets will eventually get\ncomfortable with potential earnings. (VCs already are, and at least\nsome of them consistently make money.)I realize this sounds like the stuff one used to hear about the\n\"new economy\" during the Bubble. Believe me, I was not drinking\nthat kool-aid at the time. But I'm convinced there were some \ngood\nideas buried in Bubble thinking. For example, it's ok to focus on\ngrowth instead of profits—but only if the growth is genuine.\nYou can't be buying users; that's a pyramid scheme. But a company\nwith rapid, genuine growth is valuable, and eventually markets learn\nhow to value valuable things.[2] The idea of starting\na company with benevolent aims is currently undervalued, because\nthe kind of people who currently make that their explicit goal don't\nusually do a very good job.It's one of the standard career paths of trustafarians to start\nsome vaguely benevolent business. The problem with most of them\nis that they either have a bogus political agenda or are feebly\nexecuted. The trustafarians' ancestors didn't get rich by preserving\ntheir traditional culture; maybe people in Bolivia don't want to\neither. And starting an organic farm, though it's at least\nstraightforwardly benevolent, doesn't help people on the scale that\nGoogle does.Most explicitly benevolent projects don't hold themselves sufficiently\naccountable. They act as if having good intentions were enough to\nguarantee good effects.[3] Users dislike their\nnew operating system so much that they're starting petitions to\nsave the old one. And the old one was nothing special. The hackers\nwithin Microsoft must know in their hearts that if the company\nreally cared about users they'd just advise them to switch to OSX.Thanks to Trevor Blackwell, Paul Buchheit, Jessica Livingston,\nand Robert Morris for reading drafts of this." }, { "path": "data/PaulGrahamEssays/goodart.txt", "content": "December 2006I grew up believing that taste is just a matter of personal preference.\nEach person has things they like, but no one's preferences are any\nbetter than anyone else's. There is no such thing as good taste.Like a lot of things I grew up believing, this turns out to be\nfalse, and I'm going to try to explain why.One problem with saying there's no such thing as good taste is that\nit also means there's no such thing as good art. If there were\ngood art, then people who liked it would have better taste than\npeople who didn't. So if you discard taste, you also have to discard\nthe idea of art being good, and artists being good at making it.It was pulling on that thread that unravelled my childhood faith\nin relativism. When you're trying to make things, taste becomes a\npractical matter. You have to decide what to do next. Would it\nmake the painting better if I changed that part? If there's no\nsuch thing as better, it doesn't matter what you do. In fact, it\ndoesn't matter if you paint at all. You could just go out and buy\na ready-made blank canvas. If there's no such thing as good, that\nwould be just as great an achievement as the ceiling of the Sistine\nChapel. Less laborious, certainly, but if you can achieve the same\nlevel of performance with less effort, surely that's more impressive,\nnot less.Yet that doesn't seem quite right, does it?AudienceI think the key to this puzzle is to remember that art has an\naudience. Art has a purpose, which is to interest its audience.\nGood art (like good anything) is art that achieves its purpose\nparticularly well. The meaning of \"interest\" can vary. Some works\nof art are meant to shock, and others to please; some are meant to\njump out at you, and others to sit quietly in the background. But\nall art has to work on an audience, and—here's the critical \npoint—members of the audience share things in common.For example, nearly all humans find human faces engaging. It seems\nto be wired into us. Babies can recognize faces practically from\nbirth. In fact, faces seem to have co-evolved with our interest\nin them; the face is the body's billboard. So all other things\nbeing equal, a painting with faces in it will interest people more\nthan one without. \n[1]One reason it's easy to believe that taste is merely personal\npreference is that, if it isn't, how do you pick out the people\nwith better taste? There are billions of people, each with their\nown opinion; on what grounds can you prefer one to another?\n[2]But if audiences have a lot in common, you're not in a position of\nhaving to choose one out of a random set of individual biases,\nbecause the set isn't random. All humans find faces \nengaging—practically by definition: face recognition is \nin our DNA. And so\nhaving a notion of good art, in the sense of art that does its job\nwell, doesn't require you to pick out a few individuals and label\ntheir opinions as correct. No matter who you pick, they'll find\nfaces engaging.Of course, space aliens probably wouldn't find human faces engaging.\nBut there might be other things they shared in common with us. The\nmost likely source of examples is math. I expect space aliens would\nagree with us most of the time about which of two proofs was better.\nErdos thought so. He called a maximally elegant proof one out of\nGod's book, and presumably God's book is universal.\n[3]Once you start talking about audiences, you don't have to argue\nsimply that there are or aren't standards of taste. Instead tastes\nare a series of concentric rings, like ripples in a pond. There\nare some things that will appeal to you and your friends, others\nthat will appeal to most people your age, others that will appeal\nto most humans, and perhaps others that would appeal to most sentient\nbeings (whatever that means).The picture is slightly more complicated than that, because in the\nmiddle of the pond there are overlapping sets of ripples. For\nexample, there might be things that appealed particularly to men,\nor to people from a certain culture.If good art is art that interests its audience, then when you talk\nabout art being good, you also have to say for what audience. So\nis it meaningless to talk about art simply being good or bad? No,\nbecause one audience is the set of all possible humans. I think\nthat's the audience people are implicitly talking about when they\nsay a work of art is good: they mean it would engage any human.\n[4]And that is a meaningful test, because although, like any everyday\nconcept, \"human\" is fuzzy around the edges, there are a lot of\nthings practically all humans have in common. In addition to our\ninterest in faces, there's something special about primary colors\nfor nearly all of us, because it's an artifact of the way our eyes\nwork. Most humans will also find images of 3D objects engaging,\nbecause that also seems to be built into our visual perception.\n[5]\nAnd beneath that there's edge-finding, which makes images\nwith definite shapes more engaging than mere blur.Humans have a lot more in common than this, of course. My goal is\nnot to compile a complete list, just to show that there's some solid\nground here. People's preferences aren't random. So an artist\nworking on a painting and trying to decide whether to change some\npart of it doesn't have to think \"Why bother? I might as well flip\na coin.\" Instead he can ask \"What would make the painting more\ninteresting to people?\" And the reason you can't equal Michelangelo\nby going out and buying a blank canvas is that the ceiling of the\nSistine Chapel is more interesting to people.A lot of philosophers have had a hard time believing it was possible\nfor there to be objective standards for art. It seemed obvious that\nbeauty, for example, was something that happened in the head of the observer,\nnot something that was a property of objects. It was thus \n\"subjective\" rather than \"objective.\" But in fact if you narrow the\ndefinition of beauty to something that works a certain way on\nhumans, and you observe how much humans have in common, it turns out\nto be a property of objects after all. You don't\nhave to choose between something being a property of the \nsubject or the object if subjects all react similarly.\nBeing good art is thus a property of objects as much as, say, being\ntoxic to humans is: it's good art if it consistently affects humans \nin a certain way.\nErrorSo could we figure out what the best art is by taking a vote? After\nall, if appealing to humans is the test, we should be able to just\nask them, right?Well, not quite. For products of nature that might work. I'd be\nwilling to eat the apple the world's population had voted most\ndelicious, and I'd probably be willing to visit the beach they voted\nmost beautiful, but having to look at the painting they voted the\nbest would be a crapshoot.Man-made stuff is different. For one thing, artists, unlike apple\ntrees, often deliberately try to trick us. Some tricks are quite\nsubtle. For example, any work of art sets expectations by its level\nof finish. You don't expect photographic accuracy in something\nthat looks like a quick sketch. So one widely used trick, especially\namong illustrators, is to intentionally make a painting or drawing\nlook like it was done faster than it was. The average person looks\nat it and thinks: how amazingly skillful. It's like saying something\nclever in a conversation as if you'd thought of it on the spur of\nthe moment, when in fact you'd worked it out the day before.Another much less subtle influence is brand. If you go to see the\nMona Lisa, you'll probably be disappointed, because it's hidden\nbehind a thick glass wall and surrounded by a frenzied crowd taking\npictures of themselves in front of it. At best you can see it the\nway you see a friend across the room at a crowded party. The Louvre\nmight as well replace it with copy; no one would be able to tell.\nAnd yet the Mona Lisa is a small, dark painting. If you found\npeople who'd never seen an image of it and sent them to a museum\nin which it was hanging among other paintings with a tag labelling\nit as a portrait by an unknown fifteenth century artist, most would\nwalk by without giving it a second look.For the average person, brand dominates all other factors in the\njudgement of art. Seeing a painting they recognize from reproductions\nis so overwhelming that their response to it as a painting is drowned\nout.And then of course there are the tricks people play on themselves.\nMost adults looking at art worry that if they don't like what they're\nsupposed to, they'll be thought uncultured. This doesn't just\naffect what they claim to like; they actually make themselves like\nthings they're supposed to.That's why you can't just take a vote. Though appeal to people is\na meaningful test, in practice you can't measure it, just as you\ncan't find north using a compass with a magnet sitting next to it.\nThere are sources of error so powerful that if you take a vote, all\nyou're measuring is the error.We can, however, approach our goal from another direction, by using\nourselves as guinea pigs. You're human. If you want to know what\nthe basic human reaction to a piece of art would be, you can at\nleast approach that by getting rid of the sources of error in your\nown judgements.For example, while anyone's reaction to a famous painting will be\nwarped at first by its fame, there are ways to decrease its effects.\nOne is to come back to the painting over and over. After a few\ndays the fame wears off, and you can start to see it as a painting.\nAnother is to stand close. A painting familiar from reproductions\nlooks more familiar from ten feet away; close in you see details\nthat get lost in reproductions, and which you're therefore seeing\nfor the first time.There are two main kinds of error that get in the way of seeing a\nwork of art: biases you bring from your own circumstances, and\ntricks played by the artist. Tricks are straightforward to correct\nfor. Merely being aware of them usually prevents them from working.\nFor example, when I was ten I used to be very impressed by airbrushed\nlettering that looked like shiny metal. But once you study how\nit's done, you see that it's a pretty cheesy trick—one of the\nsort that relies on pushing a few visual buttons really hard to\ntemporarily overwhelm the viewer. It's like trying to convince\nsomeone by shouting at them.The way not to be vulnerable to tricks is to explicitly seek out\nand catalog them. When you notice a whiff of dishonesty coming\nfrom some kind of art, stop and figure out what's going on. When\nsomeone is obviously pandering to an audience that's easily fooled,\nwhether it's someone making shiny stuff to impress ten year olds,\nor someone making conspicuously avant-garde stuff to impress would-be\nintellectuals, learn how they do it. Once you've seen enough\nexamples of specific types of tricks, you start to become a connoisseur\nof trickery in general, just as professional magicians are.What counts as a trick? Roughly, it's something done with contempt\nfor the audience. For example, the guys designing Ferraris in the\n1950s were probably designing cars that they themselves admired.\nWhereas I suspect over at General Motors the marketing people are\ntelling the designers, \"Most people who buy SUVs do it to seem\nmanly, not to drive off-road. So don't worry about the suspension;\njust make that sucker as big and tough-looking as you can.\" \n[6]I think with some effort you can make yourself nearly immune to\ntricks. It's harder to escape the influence of your own circumstances,\nbut you can at least move in that direction. The way to do it is\nto travel widely, in both time and space. If you go and see all\nthe different kinds of things people like in other cultures, and\nlearn about all the different things people have liked in the past,\nyou'll probably find it changes what you like. I doubt you could\never make yourself into a completely universal person, if only\nbecause you can only travel in one direction in time. But if you\nfind a work of art that would appeal equally to your friends, to\npeople in Nepal, and to the ancient Greeks, you're probably onto\nsomething.My main point here is not how to have good taste, but that there\ncan even be such a thing. And I think I've shown that. There is\nsuch a thing as good art. It's art that interests its human audience,\nand since humans have a lot in common, what interests them is not\nrandom. Since there's such a thing as good art, there's\nalso such a thing as good taste, which is the ability to recognize\nit.If we were talking about the taste of apples, I'd agree that taste\nis just personal preference. Some people like certain kinds of\napples and others like other kinds, but how can you say that one\nis right and the other wrong? \n[7]The thing is, art isn't apples. Art is man-made. It comes with a\nlot of cultural baggage, and in addition the people who make it\noften try to trick us. Most people's judgement of art is dominated\nby these extraneous factors; they're like someone trying to judge\nthe taste of apples in a dish made of equal parts apples and jalapeno\npeppers. All they're tasting is the peppers. So it turns out you\ncan pick out some people and say that they have better taste than\nothers: they're the ones who actually taste art like apples.Or to put it more prosaically, they're the people who (a) are hard\nto trick, and (b) don't just like whatever they grew up with. If\nyou could find people who'd eliminated all such influences on their\njudgement, you'd probably still see variation in what they liked.\nBut because humans have so much in common, you'd also find they\nagreed on a lot. They'd nearly all prefer the ceiling of the Sistine\nChapel to a blank canvas.Making ItI wrote this essay because I was tired of hearing \"taste is subjective\"\nand wanted to kill it once and for all. Anyone who makes things\nknows intuitively that's not true. When you're trying to make art,\nthe temptation to be lazy is as great as in any other kind of work.\nOf course it matters to do a good job. And yet you can see how\ngreat a hold \"taste is subjective\" has even in the art world by how\nnervous it makes people to talk about art being good or bad. Those\nwhose jobs require them to judge art, like curators, mostly resort\nto euphemisms like \"significant\" or \"important\" or (getting dangerously\nclose) \"realized.\" \n[8]I don't have any illusions that being able to talk about art being\ngood or bad will cause the people who talk about it to have anything\nmore useful to say. Indeed, one of the reasons \"taste is subjective\"\nfound such a receptive audience is that, historically, the things\npeople have said about good taste have generally been such nonsense.It's not for the people who talk about art that I want to free the\nidea of good art, but for those who \nmake it. Right now, ambitious\nkids going to art school run smack into a brick wall. They arrive\nhoping one day to be as good as the famous artists they've seen in\nbooks, and the first thing they learn is that the concept of good\nhas been retired. Instead everyone is just supposed to explore\ntheir own personal vision. \n[9]When I was in art school, we were looking one day at a slide of\nsome great fifteenth century painting, and one of the students asked\n\"Why don't artists paint like that now?\" The room suddenly got\nquiet. Though rarely asked out loud, this question lurks uncomfortably\nin the back of every art student's mind. It was as if someone had\nbrought up the topic of lung cancer in a meeting within Philip\nMorris.\"Well,\" the professor replied, \"we're interested in different\nquestions now.\" He was a pretty nice guy, but at the time I couldn't\nhelp wishing I could send him back to fifteenth century Florence\nto explain in person to Leonardo & Co. how we had moved beyond their\nearly, limited concept of art. Just imagine that conversation.In fact, one of the reasons artists in fifteenth century Florence made\nsuch great things was that they believed you could make great things.\n[10]\nThey were intensely competitive and were always trying to outdo\none another, like mathematicians or physicists today—maybe like\nanyone who has ever done anything really well.The idea that you could make great things was not just a useful\nillusion. They were actually right. So the most important consequence\nof realizing there can be good art is that it frees artists to try\nto make it. To the ambitious kids arriving at art school this year\nhoping one day to make great things, I say: don't believe it when\nthey tell you this is a naive and outdated ambition. There is such\na thing as good art, and if you try to make it, there are people\nwho will notice.Notes[1]\nThis is not to say, of course, that good paintings must\nhave faces in them, just that everyone's visual piano has that key\non it. There are situations in which you want to avoid faces,\nprecisely because they attract so much attention. But you can see\nhow universally faces work by their prevalence in\nadvertising.[2]\nThe other reason it's easy to believe is that it makes people\nfeel good. To a kid, this idea is crack. In every other respect\nthey're constantly being told that they have a lot to learn. But\nin this they're perfect. Their opinion carries the same weight as\nany adult's. You should probably question anything you believed\nas a kid that you'd want to believe this much.[3]\nIt's conceivable that the elegance of proofs is quantifiable,\nin the sense that there may be some formal measure that turns out\nto coincide with mathematicians' judgements. Perhaps it would be\nworth trying to make a formal language for proofs in which those\nconsidered more elegant consistently came out shorter (perhaps after\nbeing macroexpanded or compiled).[4]\nMaybe it would be possible to make art that would appeal to\nspace aliens, but I'm not going to get into that because (a) it's\ntoo hard to answer, and (b) I'm satisfied if I can establish that\ngood art is a meaningful idea for human audiences.[5]\nIf early abstract paintings seem more interesting than later\nones, it may be because the first abstract painters were trained\nto paint from life, and their hands thus tended to make the kind\nof gestures you use in representing physical things. In effect\nthey were saying \"scaramara\" instead of \"uebfgbsb.\"[6]\nIt's a bit more complicated, because sometimes artists\nunconsciously use tricks by imitating art that does.[7]\nI phrased this in terms of the taste of apples because if\npeople can see the apples, they can be fooled. When I was a kid\nmost apples were a variety called Red Delicious that had been bred\nto look appealing in stores, but which didn't taste very good.[8]\nTo be fair, curators are in a difficult position. If they're\ndealing with recent art, they have to include things in shows that\nthey think are bad. That's because the test for what gets included\nin shows is basically the market price, and for recent art that is\nlargely determined by successful businessmen and their wives. So\nit's not always intellectual dishonesty that makes curators and\ndealers use neutral-sounding language.[9]\nWhat happens in practice is that everyone gets really good at\ntalking about art. As the art itself gets more random, the effort\nthat would have gone into the work goes instead into the intellectual\nsounding theory behind it. \"My work represents an exploration of\ngender and sexuality in an urban context,\" etc. Different people\nwin at that game.[10]\nThere were several other reasons, including that Florence was\nthen the richest and most sophisticated city in the world, and that\nthey lived in a time before photography had (a) killed portraiture\nas a source of income and (b) made brand the dominant factor in the\nsale of art.Incidentally, I'm not saying that good art = fifteenth century\nEuropean art. I'm not saying we should make what they made, but\nthat we should work like they worked. There are fields now in which\nmany people work with the same energy and honesty that fifteenth\ncentury artists did, but art is not one of them.Thanks to Trevor Blackwell, Jessica Livingston, and Robert Morris \nfor reading drafts of this, and to Paul Watson for permission to \nuse the image at the top." }, { "path": "data/PaulGrahamEssays/goodtaste.txt", "content": "November 2021(This essay is derived from a talk at the Cambridge Union.)When I was a kid, I'd have said there wasn't. My father told me so.\nSome people like some things, and other people like other things,\nand who's to say who's right?It seemed so obvious that there was no such thing as good taste\nthat it was only through indirect evidence that I realized my father\nwas wrong. And that's what I'm going to give you here: a proof by\nreductio ad absurdum. If we start from the premise that there's no\nsuch thing as good taste, we end up with conclusions that are\nobviously false, and therefore the premise must be wrong.We'd better start by saying what good taste is. There's a narrow\nsense in which it refers to aesthetic judgements and a broader one\nin which it refers to preferences of any kind. The strongest proof\nwould be to show that taste exists in the narrowest sense, so I'm\ngoing to talk about taste in art. You have better taste than me if\nthe art you like is better than the art I like.If there's no such thing as good taste, then there's no such thing\nas good art. Because if there is such a\nthing as good art, it's\neasy to tell which of two people has better taste. Show them a lot\nof works by artists they've never seen before and ask them to\nchoose the best, and whoever chooses the better art has better\ntaste.So if you want to discard the concept of good taste, you also have\nto discard the concept of good art. And that means you have to\ndiscard the possibility of people being good at making it. Which\nmeans there's no way for artists to be good at their jobs. And not\njust visual artists, but anyone who is in any sense an artist. You\ncan't have good actors, or novelists, or composers, or dancers\neither. You can have popular novelists, but not good ones.We don't realize how far we'd have to go if we discarded the concept\nof good taste, because we don't even debate the most obvious cases.\nBut it doesn't just mean we can't say which of two famous painters\nis better. It means we can't say that any painter is better than a\nrandomly chosen eight year old.That was how I realized my father was wrong. I started studying\npainting. And it was just like other kinds of work I'd done: you\ncould do it well, or badly, and if you tried hard, you could get\nbetter at it. And it was obvious that Leonardo and Bellini were\nmuch better at it than me. That gap between us was not imaginary.\nThey were so good. And if they could be good, then art could be\ngood, and there was such a thing as good taste after all.Now that I've explained how to show there is such a thing as good\ntaste, I should also explain why people think there isn't. There\nare two reasons. One is that there's always so much disagreement\nabout taste. Most people's response to art is a tangle of unexamined\nimpulses. Is the artist famous? Is the subject attractive? Is this\nthe sort of art they're supposed to like? Is it hanging in a famous\nmuseum, or reproduced in a big, expensive book? In practice most\npeople's response to art is dominated by such extraneous factors.And the people who do claim to have good taste are so often mistaken.\nThe paintings admired by the so-called experts in one generation\nare often so different from those admired a few generations later.\nIt's easy to conclude there's nothing real there at all. It's only\nwhen you isolate this force, for example by trying to paint and\ncomparing your work to Bellini's, that you can see that it does in\nfact exist.The other reason people doubt that art can be good is that there\ndoesn't seem to be any room in the art for this goodness. The\nargument goes like this. Imagine several people looking at a work\nof art and judging how good it is. If being good art really is a\nproperty of objects, it should be in the object somehow. But it\ndoesn't seem to be; it seems to be something happening in the heads\nof each of the observers. And if they disagree, how do you choose\nbetween them?The solution to this puzzle is to realize that the purpose of art\nis to work on its human audience, and humans have a lot in common.\nAnd to the extent the things an object acts upon respond in the\nsame way, that's arguably what it means for the object to have the\ncorresponding property. If everything a particle interacts with\nbehaves as if the particle had a mass of m, then it has a mass of\nm. So the distinction between \"objective\" and \"subjective\" is not\nbinary, but a matter of degree, depending on how much the subjects\nhave in common. Particles interacting with one another are at one\npole, but people interacting with art are not all the way at the\nother; their reactions aren't random.Because people's responses to art aren't random, art can be designed\nto operate on people, and be good or bad depending on how effectively\nit does so. Much as a vaccine can be. If someone were talking about\nthe ability of a vaccine to confer immunity, it would seem very\nfrivolous to object that conferring immunity wasn't really a property\nof vaccines, because acquiring immunity is something that happens\nin the immune system of each individual person. Sure, people's\nimmune systems vary, and a vaccine that worked on one might not\nwork on another, but that doesn't make it meaningless to talk about\nthe effectiveness of a vaccine.The situation with art is messier, of course. You can't measure\neffectiveness by simply taking a vote, as you do with vaccines.\nYou have to imagine the responses of subjects with a deep knowledge\nof art, and enough clarity of mind to be able to ignore extraneous\ninfluences like the fame of the artist. And even then you'd still\nsee some disagreement. People do vary, and judging art is hard,\nespecially recent art. There is definitely not a total order either\nof works or of people's ability to judge them. But there is equally\ndefinitely a partial order of both. So while it's not possible to\nhave perfect taste, it is possible to have good taste.\nThanks to the Cambridge Union for inviting me, and to Trevor\nBlackwell, Jessica Livingston, and Robert Morris for reading drafts\nof this.\n" }, { "path": "data/PaulGrahamEssays/googles.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nApril 2008Umair Haque \nwrote recently that the reason there aren't more Googles is\nthat most startups get bought before they can change the world.\n\n Google, despite serious interest from Microsoft and Yahoo—what\n must have seemed like lucrative interest at the time—didn't\n sell out. Google might simply have been nothing but Yahoo's or\n MSN's search box.Why isn't it? Because Google had a deeply felt sense of purpose:\n a conviction to change the world for the better.\n\nThis has a nice sound to it, but it isn't true. \nGoogle's founders were willing to sell early on.\nThey just wanted more than acquirers were willing to pay.It was the same with Facebook. They would have sold, but Yahoo blew it \nby offering too little.Tip for acquirers: when a startup turns you down, consider raising\nyour offer, because there's a good chance the outrageous price they \nwant will later seem a bargain. \n[1]From the evidence I've seen so far,\nstartups that turn down acquisition offers usually end up doing better. \nNot always, but usually there's a bigger offer coming, or\nperhaps even an IPO.Of course, the reason startups do better when they turn down\nacquisition offers is not necessarily that all such offers undervalue\nstartups. More likely the reason is that the kind of founders who\nhave the balls to turn down a big offer also tend to be very\nsuccessful. That spirit is exactly what you want in a startup.While I'm sure Larry and Sergey do want to change the world, at\nleast now, the reason Google survived to become a big, independent\ncompany is the same reason Facebook has so far remained independent:\nacquirers underestimated them.Corporate M&A is a strange business in that respect. They consistently\nlose the best deals, because turning down reasonable offers is the\nmost reliable test you could invent for whether a startup will make\nit big.VCsSo what's the real reason there aren't more Googles? Curiously\nenough, it's the same reason Google and Facebook have remained\nindependent: money guys undervalue the most innovative startups.The reason there aren't more Googles is not that investors encourage\ninnovative startups to sell out, but that they won't even fund them.\nI've learned a lot about VCs during the 3 years we've been doing Y\nCombinator, because we often have to work quite closely with them.\nThe most surprising thing I've learned is how conservative they\nare. VC firms present an image of boldly encouraging innovation.\nOnly a handful actually do, and even they are more conservative in\nreality than you'd guess from reading their sites.I used to think of VCs as piratical: bold but unscrupulous. On\ncloser acquaintance they turn out to be more like bureaucrats.\nThey're more upstanding than I used to think (the good ones, at\nleast), but less bold. Maybe the VC industry has changed. Maybe\nthey used to be bolder. \nBut I suspect it's the startup world that has\nchanged, not them. The low cost of starting a startup means the\naverage good bet is a riskier one, but most existing VC firms still\noperate as if they were investing in hardware startups in 1985.Howard Aiken said \"Don't worry about people stealing your ideas.\nIf your ideas are any good, you'll have to ram them down people's\nthroats.\" I have a similar feeling when I'm trying to convince VCs\nto invest in startups Y Combinator has funded. They're terrified\nof really novel ideas, unless the founders are good enough salesmen\nto compensate.But it's the bold ideas that generate the biggest returns. Any\nreally good new idea will seem bad to most people; otherwise someone\nwould already be doing it. And\nyet most VCs are driven by consensus, not just within their firms,\nbut within the VC community. The biggest factor determining how a\nVC will feel about your startup is how other VCs feel about it. I\ndoubt they realize it, but this algorithm guarantees they'll miss\nall the very best ideas. The more people who have to like a new\nidea, the more outliers you lose.Whoever the next Google is, they're probably being told right now\nby VCs to come back when they have more \"traction.\"Why are VCs so conservative? It's probably a combination of factors.\nThe large size of their investments makes them conservative.\nPlus they're investing other people's money, which makes\nthem worry they'll get in trouble if they do something risky and\nit fails. Plus most of them are money guys rather than technical\nguys, so they don't understand what the startups they're investing\nin do.What's NextThe exciting thing about market economies is that stupidity equals\nopportunity. And so it is in this case. There is a huge, unexploited\nopportunity in startup investing. Y Combinator funds startups at\nthe very beginning. VCs will fund them once they're already starting\nto succeed. But between the two there is a substantial gap.There are companies that will give $20k to a startup that has nothing\nmore than the founders, and there are companies that will give $2\nmillion to a startup that's already taking off,\nbut there aren't enough investors who will give $200k to a startup\nthat seems very promising but still has some things to figure out.\nThis territory is occupied mostly by\nindividual angel investors—people like Andy Bechtolsheim, who\ngave Google $100k when they seemed promising but still had some\nthings to figure out. I like angels, but there just aren't enough\nof them, and investing is for most of them a part time job.And yet as it gets cheaper to start startups, this sparsely occupied\nterritory is becoming more and more valuable. Nowadays a lot of\nstartups don't want to raise multi-million dollar series A rounds.\nThey don't need that much money, and they don't want the hassles\nthat come with it. The median startup coming out of Y Combinator\nwants to raise $250-500k. When they go to VC firms they have to\nask for more because they know VCs aren't interested in such small\ndeals.VCs are money managers. They're looking for ways to put large sums\nto work. But the startup world is evolving away from their current\nmodel.Startups have gotten cheaper. That means they want less money, but\nalso that there are more of them. So you can still get large returns\non large amounts of money; you just have to spread it more broadly.I've tried to explain this to VC firms. Instead of making one $2\nmillion investment, make five $400k investments. Would that mean\nsitting on too many boards? Don't sit on their boards. Would that\nmean too much due diligence? Do less. If you're investing at a\ntenth the valuation, you only have to be a tenth as sure.It seems obvious. But I've proposed to several VC firms that they\nset aside some money and designate one partner to make more, smaller\nbets, and they react as if I'd proposed the partners all get nose\nrings. It's remarkable how wedded they are to their standard m.o.But there is a big opportunity here, and one way or the other it's\ngoing to get filled. Either VCs will evolve down into this gap or,\nmore likely, new investors will appear to fill it. That will be a\ngood thing when it happens, because these new investors will be\ncompelled by the structure of the investments they make to be ten\ntimes bolder than present day VCs. And that will get us a lot more\nGoogles. At least, as long as acquirers remain stupid.\nNotes[1]\nAnother tip: If you want to get all that value, don't destroy the\nstartup after you buy it. Give the founders enough autonomy that\nthey can grow the acquisition into what it would have become.Thanks to Sam Altman, Paul Buchheit, David Hornik, Jessica \nLivingston, Robert Morris, and Fred Wilson for reading drafts of this." }, { "path": "data/PaulGrahamEssays/growth.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nSeptember 2012A startup is a company designed to grow fast. Being newly founded\ndoes not in itself make a company a startup. Nor is it necessary\nfor a startup to work on technology, or take venture funding, or\nhave some sort of \"exit.\" The only essential thing is growth.\nEverything else we associate with startups follows from growth.If you want to start one it's important to understand that. Startups\nare so hard that you can't be pointed off to the side and hope to\nsucceed. You have to know that growth is what you're after. The\ngood news is, if you get growth, everything else tends to fall into\nplace. Which means you can use growth like a compass to make almost\nevery decision you face.\nRedwoodsLet's start with a distinction that should be obvious but is often\noverlooked: not every newly founded company is a startup. Millions\nof companies are started every year in the US. Only a tiny fraction\nare startups. Most are service businesses — restaurants, barbershops,\nplumbers, and so on. These are not startups, except in a few unusual\ncases. A barbershop isn't designed to grow fast. Whereas a search\nengine, for example, is.When I say startups are designed to grow fast, I mean it in two\nsenses. Partly I mean designed in the sense of intended, because\nmost startups fail. But I also mean startups are different by\nnature, in the same way a redwood seedling has a different destiny\nfrom a bean sprout.That difference is why there's a distinct word, \"startup,\" for\ncompanies designed to grow fast. If all companies were essentially\nsimilar, but some through luck or the efforts of their founders\nended up growing very fast, we wouldn't need a separate word. We\ncould just talk about super-successful companies and less successful\nones. But in fact startups do have a different sort of DNA from\nother businesses. Google is not just a barbershop whose founders\nwere unusually lucky and hard-working. Google was different from\nthe beginning.To grow rapidly, you need to make something you can sell to a big\nmarket. That's the difference between Google and a barbershop. A\nbarbershop doesn't scale.For a company to grow really big, it must (a) make something lots\nof people want, and (b) reach and serve all those people. Barbershops\nare doing fine in the (a) department. Almost everyone needs their\nhair cut. The problem for a barbershop, as for any retail\nestablishment, is (b). A barbershop serves customers in person,\nand few will travel far for a haircut. And even if they did, the\nbarbershop couldn't accomodate them. \n[1]Writing software is a great way to solve (b), but you can still end\nup constrained in (a). If you write software to teach Tibetan to\nHungarian speakers, you'll be able to reach most of the people who\nwant it, but there won't be many of them. If you make software\nto teach English to Chinese speakers, however, you're in startup\nterritory.Most businesses are tightly constrained in (a) or (b). The distinctive\nfeature of successful startups is that they're not.\nIdeasIt might seem that it would always be better to start a startup\nthan an ordinary business. If you're going to start a company, why\nnot start the type with the most potential? The catch is that this\nis a (fairly) efficient market. If you write software to teach\nTibetan to Hungarians, you won't have much competition. If you\nwrite software to teach English to Chinese speakers, you'll face\nferocious competition, precisely because that's such a larger prize.\n[2]The constraints that limit ordinary companies also protect them.\nThat's the tradeoff. If you start a barbershop, you only have to\ncompete with other local barbers. If you start a search engine you\nhave to compete with the whole world.The most important thing that the constraints on a normal business\nprotect it from is not competition, however, but the difficulty of\ncoming up with new ideas. If you open a bar in a particular\nneighborhood, as well as limiting your potential and protecting you\nfrom competitors, that geographic constraint also helps define your\ncompany. Bar + neighborhood is a sufficient idea for a small\nbusiness. Similarly for companies constrained in (a). Your niche\nboth protects and defines you.Whereas if you want to start a startup, you're probably going to\nhave to think of something fairly novel. A startup has to make\nsomething it can deliver to a large market, and ideas of that type\nare so valuable that all the obvious ones are already taken.That space of ideas has been so thoroughly picked over that a startup\ngenerally has to work on something everyone else has overlooked.\nI was going to write that one has to make a conscious effort to\nfind ideas everyone else has overlooked. But that's not how most\nstartups get started. Usually successful startups happen because\nthe founders are sufficiently different from other people that ideas\nfew others can see seem obvious to them. Perhaps later they step\nback and notice they've found an idea in everyone else's blind spot,\nand from that point make a deliberate effort to stay there. \n[3]\nBut at the moment when successful startups get started, much of the\ninnovation is unconscious.What's different about successful founders is that they can see\ndifferent problems. It's a particularly good combination both to\nbe good at technology and to face problems that can be solved by\nit, because technology changes so rapidly that formerly bad ideas\noften become good without anyone noticing. Steve Wozniak's problem\nwas that he wanted his own computer. That was an unusual problem\nto have in 1975. But technological change was about to make it a\nmuch more common one. Because he not only wanted a computer but\nknew how to build them, Wozniak was able to make himself one. And\nthe problem he solved for himself became one that Apple solved for\nmillions of people in the coming years. But by the time it was\nobvious to ordinary people that this was a big market, Apple was\nalready established.Google has similar origins. Larry Page and Sergey Brin wanted to\nsearch the web. But unlike most people they had the technical\nexpertise both to notice that existing search engines were not as\ngood as they could be, and to know how to improve them. Over the\nnext few years their problem became everyone's problem, as the web\ngrew to a size where you didn't have to be a picky search expert\nto notice the old algorithms weren't good enough. But as happened\nwith Apple, by the time everyone else realized how important search\nwas, Google was entrenched.That's one connection between startup ideas and technology. Rapid\nchange in one area uncovers big, soluble problems in other areas.\nSometimes the changes are advances, and what they change is solubility.\nThat was the kind of change that yielded Apple; advances in chip\ntechnology finally let Steve Wozniak design a computer he could\nafford. But in Google's case the most important change was the\ngrowth of the web. What changed there was not solubility but bigness.The other connection between startups and technology is that startups\ncreate new ways of doing things, and new ways of doing things are,\nin the broader sense of the word, new technology. \nWhen a startup both begins with an\nidea exposed by technological change and makes a product consisting\nof technology in the narrower sense (what used to be called \"high\ntechnology\"), it's easy to conflate the two. But the two connections\nare distinct and in principle one could start a startup that was\nneither driven by technological change, nor whose product consisted\nof technology except in the broader sense. \n[4]RateHow fast does a company have to grow to be considered a startup?\nThere's no precise answer to that. \"Startup\" is a pole, not a\nthreshold. Starting one is at first no more than a declaration of\none's ambitions. You're committing not just to starting a company,\nbut to starting a fast growing one, and you're thus committing to\nsearch for one of the rare ideas of that type. But at first you\nhave no more than commitment. Starting a startup is like being an\nactor in that respect. \"Actor\" too is a pole rather than a threshold.\nAt the beginning of his career, an actor is a waiter who goes to\nauditions. Getting work makes him a successful actor, but he doesn't\nonly become an actor when he's successful.So the real question is not what growth rate makes a company a\nstartup, but what growth rate successful startups tend to have.\nFor founders that's more than a theoretical question, because it's\nequivalent to asking if they're on the right path.The growth of a successful startup usually has three phases:\n\n There's an initial period of slow or no growth while the startup\n tries to figure out what it's doing. As the startup figures out how to make something lots of people\n want and how to reach those people, there's a period of rapid\n growth. Eventually a successful startup will grow into a big company.\n Growth will slow, partly due to internal limits and partly because\n the company is starting to bump up against the limits of the\n markets it serves. \n [5]\n\nTogether these three phases produce an S-curve. The phase whose\ngrowth defines the startup is the second one, the ascent. Its\nlength and slope determine how big the company will be.The slope is the company's growth rate. If there's one number every\nfounder should always know, it's the company's growth rate. That's\nthe measure of a startup. If you don't know that number, you don't\neven know if you're doing well or badly.When I first meet founders and ask what their growth rate is,\nsometimes they tell me \"we get about a hundred new customers a\nmonth.\" That's not a rate. What matters is not the absolute number\nof new customers, but the ratio of new customers to existing ones.\nIf you're really getting a constant number of new customers every\nmonth, you're in trouble, because that means your growth rate is\ndecreasing.During Y Combinator we measure growth rate per week, partly because\nthere is so little time before Demo Day, and partly because startups\nearly on need frequent feedback from their users to tweak what\nthey're doing. \n[6]A good growth rate during YC is 5-7% a week. If you can hit 10% a\nweek you're doing exceptionally well. If you can only manage 1%,\nit's a sign you haven't yet figured out what you're doing.The best thing to measure the growth rate of is revenue. The next\nbest, for startups that aren't charging initially, is active users.\nThat's a reasonable proxy for revenue growth because whenever the\nstartup does start trying to make money, their revenues will probably\nbe a constant multiple of active users. \n[7]\nCompassWe usually advise startups to pick a growth rate they think they\ncan hit, and then just try to hit it every week. The key word here\nis \"just.\" If they decide to grow at 7% a week and they hit that\nnumber, they're successful for that week. There's nothing more\nthey need to do. But if they don't hit it, they've failed in the\nonly thing that mattered, and should be correspondingly alarmed.Programmers will recognize what we're doing here. We're turning\nstarting a startup into an optimization problem. And anyone who\nhas tried optimizing code knows how wonderfully effective that sort\nof narrow focus can be. Optimizing code means taking an existing\nprogram and changing it to use less of something, usually time or\nmemory. You don't have to think about what the program should do,\njust make it faster. For most programmers this is very satisfying\nwork. The narrow focus makes it a sort of puzzle, and you're\ngenerally surprised how fast you can solve it.Focusing on hitting a growth rate reduces the otherwise bewilderingly\nmultifarious problem of starting a startup to a single problem.\nYou can use that target growth rate to make all your decisions for\nyou; anything that gets you the growth you need is ipso facto right.\nShould you spend two days at a conference? Should you hire another\nprogrammer? Should you focus more on marketing? Should you spend\ntime courting some big customer? Should you add x feature? Whatever\ngets you your target growth rate. \n[8]Judging yourself by weekly growth doesn't mean you can look no more\nthan a week ahead. Once you experience the pain of missing your\ntarget one week (it was the only thing that mattered, and you failed\nat it), you become interested in anything that could spare you such\npain in the future. So you'll be willing for example to hire another\nprogrammer, who won't contribute to this week's growth but perhaps\nin a month will have implemented some new feature that will get you\nmore users. But only if (a) the distraction of hiring someone\nwon't make you miss your numbers in the short term, and (b) you're\nsufficiently worried about whether you can keep hitting your numbers\nwithout hiring someone new.It's not that you don't think about the future, just that you think\nabout it no more than necessary.In theory this sort of hill-climbing could get a startup into\ntrouble. They could end up on a local maximum. But in practice\nthat never happens. Having to hit a growth number every week forces\nfounders to act, and acting versus not acting is the high bit of\nsucceeding. Nine times out of ten, sitting around strategizing is\njust a form of procrastination. Whereas founders' intuitions about\nwhich hill to climb are usually better than they realize. Plus the\nmaxima in the space of startup ideas are not spiky and isolated.\nMost fairly good ideas are adjacent to even better ones.The fascinating thing about optimizing for growth is that it can\nactually discover startup ideas. You can use the need for growth\nas a form of evolutionary pressure. If you start out with some\ninitial plan and modify it as necessary to keep hitting, say, 10%\nweekly growth, you may end up with a quite different company than\nyou meant to start. But anything that grows consistently at 10% a\nweek is almost certainly a better idea than you started with.There's a parallel here to small businesses. Just as the constraint\nof being located in a particular neighborhood helps define a bar,\nthe constraint of growing at a certain rate can help define a\nstartup.You'll generally do best to follow that constraint wherever it leads\nrather than being influenced by some initial vision, just as a\nscientist is better off following the truth wherever it leads rather\nthan being influenced by what he wishes were the case. When Richard\nFeynman said that the imagination of nature was greater than the\nimagination of man, he meant that if you just keep following the\ntruth you'll discover cooler things than you could ever have made\nup. For startups, growth is a constraint much like truth. Every\nsuccessful startup is at least partly a product of the imagination\nof growth. \n[9]\nValueIt's hard to find something that grows consistently at several\npercent a week, but if you do you may have found something surprisingly\nvaluable. If we project forward we see why.\n\nweeklyyearly\n1%1.7x\n2%2.8x\n5%12.6x\n7%33.7x\n10%142.0x\n\n\n\nA company that grows at 1% a week will grow 1.7x a year, whereas a\ncompany that grows at 5% a week will grow 12.6x. A company making\n$1000 a month (a typical number early in YC) and growing at 1% a\nweek will 4 years later be making $7900 a month, which is less than\na good programmer makes in salary in Silicon Valley. A startup\nthat grows at 5% a week will in 4 years be making $25 million a\nmonth. \n[10]Our ancestors must rarely have encountered cases of exponential\ngrowth, because our intuitions are no guide here. What happens\nto fast growing startups tends to surprise even the founders.Small variations in growth rate produce qualitatively different\noutcomes. That's why there's a separate word for startups, and why\nstartups do things that ordinary companies don't, like raising money\nand getting acquired. And, strangely enough, it's also why they\nfail so frequently.Considering how valuable a successful startup can become, anyone\nfamiliar with the concept of expected value would be surprised if\nthe failure rate weren't high. If a successful startup could make\na founder $100 million, then even if the chance of succeeding were\nonly 1%, the expected value of starting one would be $1 million.\nAnd the probability of a group of sufficiently smart and determined\nfounders succeeding on that scale might be significantly over 1%.\nFor the right people — e.g. the young Bill Gates — the probability\nmight be 20% or even 50%. So it's not surprising that so many want\nto take a shot at it. In an efficient market, the number of failed\nstartups should be proportionate to the size of the successes. And\nsince the latter is huge the former should be too. \n[11]What this means is that at any given time, the great majority of\nstartups will be working on something that's never going to go\nanywhere, and yet glorifying their doomed efforts with the grandiose\ntitle of \"startup.\"This doesn't bother me. It's the same with other high-beta vocations,\nlike being an actor or a novelist. I've long since gotten used to\nit. But it seems to bother a lot of people, particularly those\nwho've started ordinary businesses. Many are annoyed that these\nso-called startups get all the attention, when hardly any of them\nwill amount to anything.If they stepped back and looked at the whole picture they might be\nless indignant. The mistake they're making is that by basing their\nopinions on anecdotal evidence they're implicitly judging by the\nmedian rather than the average. If you judge by the median startup,\nthe whole concept of a startup seems like a fraud. You have to\ninvent a bubble to explain why founders want to start them or\ninvestors want to fund them. But it's a mistake to use the median\nin a domain with so much variation. If you look at the average\noutcome rather than the median, you can understand why investors\nlike them, and why, if they aren't median people, it's a rational\nchoice for founders to start them.\nDealsWhy do investors like startups so much? Why are they so hot to\ninvest in photo-sharing apps, rather than solid money-making\nbusinesses? Not only for the obvious reason.The test of any investment is the ratio of return to risk. Startups\npass that test because although they're appallingly risky, the\nreturns when they do succeed are so high. But that's not the only\nreason investors like startups. An ordinary slower-growing business\nmight have just as good a ratio of return to risk, if both were\nlower. So why are VCs interested only in high-growth companies?\nThe reason is that they get paid by getting their capital back,\nideally after the startup IPOs, or failing that when it's acquired.The other way to get returns from an investment is in the form of\ndividends. Why isn't there a parallel VC industry that invests in\nordinary companies in return for a percentage of their profits?\nBecause it's too easy for people who control a private company to\nfunnel its revenues to themselves (e.g. by buying overpriced\ncomponents from a supplier they control) while making it look like\nthe company is making little profit. Anyone who invested in private\ncompanies in return for dividends would have to pay close attention\nto their books.The reason VCs like to invest in startups is not simply the returns,\nbut also because such investments are so easy to oversee. The\nfounders can't enrich themselves without also enriching the investors.\n[12]Why do founders want to take the VCs' money? Growth, again. The\nconstraint between good ideas and growth operates in both directions.\nIt's not merely that you need a scalable idea to grow. If you have\nsuch an idea and don't grow fast enough, competitors will. Growing\ntoo slowly is particularly dangerous in a business with network\neffects, which the best startups usually have to some degree.Almost every company needs some amount of funding to get started.\nBut startups often raise money even when they are or could be\nprofitable. It might seem foolish to sell stock in a profitable\ncompany for less than you think it will later be worth, but it's\nno more foolish than buying insurance. Fundamentally that's how\nthe most successful startups view fundraising. They could grow the\ncompany on its own revenues, but the extra money and help supplied\nby VCs will let them grow even faster. Raising money lets you\nchoose your growth rate.Money to grow faster is always at the command of the most successful\nstartups, because the VCs need them more than they need the VCs.\nA profitable startup could if it wanted just grow on its own revenues.\nGrowing slower might be slightly dangerous, but chances are it\nwouldn't kill them. Whereas VCs need to invest in startups, and\nin particular the most successful startups, or they'll be out of\nbusiness. Which means that any sufficiently promising startup will\nbe offered money on terms they'd be crazy to refuse. And yet because\nof the scale of the successes in the startup business, VCs can still\nmake money from such investments. You'd have to be crazy to believe\nyour company was going to become as valuable as a high growth rate\ncan make it, but some do.Pretty much every successful startup will get acquisition offers\ntoo. Why? What is it about startups that makes other companies\nwant to buy them? \n[13]Fundamentally the same thing that makes everyone else want the stock\nof successful startups: a rapidly growing company is valuable. It's\na good thing eBay bought Paypal, for example, because Paypal is now\nresponsible for 43% of their sales and probably more of their growth.But acquirers have an additional reason to want startups. A rapidly\ngrowing company is not merely valuable, but dangerous. If it keeps\nexpanding, it might expand into the acquirer's own territory. Most\nproduct acquisitions have some component of fear. Even if an\nacquirer isn't threatened by the startup itself, they might be\nalarmed at the thought of what a competitor could do with it. And\nbecause startups are in this sense doubly valuable to acquirers,\nacquirers will often pay more than an ordinary investor would. \n[14]\nUnderstandThe combination of founders, investors, and acquirers forms a natural\necosystem. It works so well that those who don't understand it are\ndriven to invent conspiracy theories to explain how neatly things\nsometimes turn out. Just as our ancestors did to explain the\napparently too neat workings of the natural world. But there is\nno secret cabal making it all work.If you start from the mistaken assumption that Instagram was\nworthless, you have to invent a secret boss to force Mark Zuckerberg\nto buy it. To anyone who knows Mark Zuckerberg, that is the reductio\nad absurdum of the initial assumption. The reason he bought Instagram\nwas that it was valuable and dangerous, and what made it so was\ngrowth.If you want to understand startups, understand growth. Growth\ndrives everything in this world. Growth is why startups usually\nwork on technology — because ideas for fast growing companies are\nso rare that the best way to find new ones is to discover those\nrecently made viable by change, and technology is the best source\nof rapid change. Growth is why it's a rational choice economically\nfor so many founders to try starting a startup: growth makes the\nsuccessful companies so valuable that the expected value is high\neven though the risk is too. Growth is why VCs want to invest in\nstartups: not just because the returns are high but also because\ngenerating returns from capital gains is easier to manage than\ngenerating returns from dividends. Growth explains why the most\nsuccessful startups take VC money even if they don't need to: it\nlets them choose their growth rate. And growth explains why\nsuccessful startups almost invariably get acquisition offers. To\nacquirers a fast-growing company is not merely valuable but dangerous\ntoo.It's not just that if you want to succeed in some domain, you have\nto understand the forces driving it. Understanding growth is what\nstarting a startup consists of. What you're really doing (and\nto the dismay of some observers, all you're really doing) when you\nstart a startup is committing to solve a harder type of problem\nthan ordinary businesses do. You're committing to search for one\nof the rare ideas that generates rapid growth. Because these ideas\nare so valuable, finding one is hard. The startup is the embodiment\nof your discoveries so far. Starting a startup is thus very much\nlike deciding to be a research scientist: you're not committing to\nsolve any specific problem; you don't know for sure which problems\nare soluble; but you're committing to try to discover something no\none knew before. A startup founder is in effect an economic research\nscientist. Most don't discover anything that remarkable, but some\ndiscover relativity.\nNotes[1]\nStrictly speaking it's not lots of customers you need but a big\nmarket, meaning a high product of number of customers times how\nmuch they'll pay. But it's dangerous to have too few customers\neven if they pay a lot, or the power that individual customers have\nover you could turn you into a de facto consulting firm. So whatever\nmarket you're in, you'll usually do best to err on the side of\nmaking the broadest type of product for it.[2]\nOne year at Startup School David Heinemeier Hansson encouraged\nprogrammers who wanted to start businesses to use a restaurant as\na model. What he meant, I believe, is that it's fine to start\nsoftware companies constrained in (a) in the same way a restaurant\nis constrained in (b). I agree. Most people should not try to\nstart startups.[3]\nThat sort of stepping back is one of the things we focus on at\nY Combinator. It's common for founders to have discovered something\nintuitively without understanding all its implications. That's\nprobably true of the biggest discoveries in any field.[4]\nI got it wrong in \"How to Make Wealth\" when I said that a\nstartup was a small company that takes on a hard technical\nproblem. That is the most common recipe but not the only one.[5]\nIn principle companies aren't limited by the size of the markets\nthey serve, because they could just expand into new markets. But\nthere seem to be limits on the ability of big companies to do that.\nWhich means the slowdown that comes from bumping up against the\nlimits of one's markets is ultimately just another way in which\ninternal limits are expressed.It may be that some of these limits could be overcome by changing\nthe shape of the organization — specifically by sharding it.[6]\nThis is, obviously, only for startups that have already launched\nor can launch during YC. A startup building a new database will\nprobably not do that. On the other hand, launching something small\nand then using growth rate as evolutionary pressure is such a\nvaluable technique that any company that could start this way\nprobably should.[7]\nIf the startup is taking the Facebook/Twitter route and building\nsomething they hope will be very popular but from which they don't\nyet have a definite plan to make money, the growth rate has to be\nhigher, even though it's a proxy for revenue growth, because such\ncompanies need huge numbers of users to succeed at all.Beware too of the edge case where something spreads rapidly but the\nchurn is high as well, so that you have good net growth till you run\nthrough all the potential users, at which point it suddenly stops.[8]\nWithin YC when we say it's ipso facto right to do whatever gets\nyou growth, it's implicit that this excludes trickery like buying\nusers for more than their lifetime value, counting users as active\nwhen they're really not, bleeding out invites at a regularly\nincreasing rate to manufacture a perfect growth curve, etc. Even\nif you were able to fool investors with such tricks, you'd ultimately\nbe hurting yourself, because you're throwing off your own compass.[9]\nWhich is why it's such a dangerous mistake to believe that\nsuccessful startups are simply the embodiment of some brilliant\ninitial idea. What you're looking for initially is not so much a\ngreat idea as an idea that could evolve into a great one. The\ndanger is that promising ideas are not merely blurry versions of\ngreat ones. They're often different in kind, because the early\nadopters you evolve the idea upon have different needs from the\nrest of the market. For example, the idea that evolves into Facebook\nisn't merely a subset of Facebook; the idea that evolves into\nFacebook is a site for Harvard undergrads.[10]\nWhat if a company grew at 1.7x a year for a really long time?\nCould it not grow just as big as any successful startup? In principle\nyes, of course. If our hypothetical company making $1000 a month\ngrew at 1% a week for 19 years, it would grow as big as a company\ngrowing at 5% a week for 4 years. But while such trajectories may\nbe common in, say, real estate development, you don't see them much\nin the technology business. In technology, companies that grow\nslowly tend not to grow as big.[11]\nAny expected value calculation varies from person to person\ndepending on their utility function for money. I.e. the first\nmillion is worth more to most people than subsequent millions. How\nmuch more depends on the person. For founders who are younger or\nmore ambitious the utility function is flatter. Which is probably\npart of the reason the founders of the most successful startups of\nall tend to be on the young side.[12]\nMore precisely, this is the case in the biggest winners, which\nis where all the returns come from. A startup founder could pull\nthe same trick of enriching himself at the company's expense by\nselling them overpriced components. But it wouldn't be worth it\nfor the founders of Google to do that. Only founders of failing\nstartups would even be tempted, but those are writeoffs from the\nVCs' point of view anyway.[13]\nAcquisitions fall into two categories: those where the acquirer\nwants the business, and those where the acquirer just wants the\nemployees. The latter type is sometimes called an HR acquisition.\nThough nominally acquisitions and sometimes on a scale that has a\nsignificant effect on the expected value calculation for potential\nfounders, HR acquisitions are viewed by acquirers as more akin to\nhiring bonuses.[14]\nI once explained this to some founders who had recently arrived\nfrom Russia. They found it novel that if you threatened a company\nthey'd pay a premium for you. \"In Russia they just kill you,\" they\nsaid, and they were only partly joking. Economically, the fact\nthat established companies can't simply eliminate new competitors\nmay be one of the most valuable aspects of the rule of law. And\nso to the extent we see incumbents suppressing competitors via\nregulations or patent suits, we should worry, not because it's a\ndeparture from the rule of law per se but from what the rule of law\nis aiming at.\nThanks to Sam Altman, Marc Andreessen, Paul Buchheit, Patrick\nCollison, Jessica Livingston, Geoff Ralston, and Harj Taggar for\nreading drafts of this." }, { "path": "data/PaulGrahamEssays/guidetoinvestors.txt", "content": "April 2007(This essay is derived from a keynote talk at the 2007 ASES Summit\nat Stanford.)The world of investors is a foreign one to most hackers—partly\nbecause investors are so unlike hackers, and partly because they\ntend to operate in secret. I've been dealing with this world for\nmany years, both as a founder and an investor, and I still don't\nfully understand it.In this essay I'm going to list some of the more surprising things\nI've learned about investors. Some I only learned in the past year.Teaching hackers how to deal with investors is probably the second\nmost important thing we do at Y Combinator. The most important\nthing for a startup is to make something good. But everyone knows\nthat's important. The dangerous thing about investors is that\nhackers don't know how little they know about this strange world.1. The investors are what make a startup hub.About a year ago I tried to figure out what you'd need to reproduce\nSilicon Valley. I decided the \ncritical ingredients were rich people\nand nerds—investors and founders. People are all you need to\nmake technology, and all the other people will move.If I had to narrow that down, I'd say investors are the limiting\nfactor. Not because they contribute more to the startup, but simply\nbecause they're least willing to move. They're rich. They're not\ngoing to move to Albuquerque just because there are some smart\nhackers there they could invest in. Whereas hackers will move to\nthe Bay Area to find investors.2. Angel investors are the most critical.There are several types of investors. The two main categories are\nangels and VCs: VCs invest other people's money, and angels invest\ntheir own.Though they're less well known, the angel investors are probably\nthe more critical ingredient in creating a silicon valley. Most\ncompanies that VCs invest in would never have made it that far if angels\nhadn't invested first. VCs say between half and three quarters of\ncompanies that raise series A rounds have taken some outside\ninvestment already.\n[1]Angels are willing to fund riskier projects than VCs. They also\ngive valuable advice, because (unlike VCs) many have been startup\nfounders themselves.Google's story shows the key role angels play. A lot of people know\nGoogle raised money from Kleiner and Sequoia. What most don't realize\nis how late. That VC round was a series B round; the premoney\nvaluation was $75 million. Google was already a successful company\nat that point. Really, Google was funded with angel money.It may seem odd that the canonical Silicon Valley startup was funded\nby angels, but this is not so surprising. Risk is always proportionate\nto reward. So the most successful startup of all is likely to have\nseemed an extremely risky bet at first, and that is exactly the\nkind VCs won't touch.Where do angel investors come from? From other startups. So startup\nhubs like Silicon Valley benefit from something like the marketplace\neffect, but shifted in time: startups are there because startups\nwere there.3. Angels don't like publicity.If angels are so important, why do we hear more about VCs? Because\nVCs like publicity. They need to market themselves to the investors\nwho are their \"customers\"—the endowments and pension funds and\nrich families whose money they invest—and also to founders who\nmight come to them for funding.Angels don't need to market themselves to investors because they\ninvest their own money. Nor do they want to market themselves to\nfounders: they don't want random people pestering them with business\nplans. Actually, neither do VCs. Both angels and VCs get deals\nalmost exclusively through personal introductions. \n[2]The reason VCs want a strong brand is not to draw in more business\nplans over the transom, but so they win deals when competing\nagainst other VCs. Whereas angels are rarely in direct competition,\nbecause (a) they do fewer deals, (b) they're happy to split them,\nand (c) they invest at a point where the stream is broader.4. Most investors, especially VCs, are not like founders.Some angels are, or were, hackers. But most VCs are a different\ntype of people: they're dealmakers.If you're a hacker, here's a thought experiment you can run to\nunderstand why there are basically no hacker VCs: How would you\nlike a job where you never got to make anything, but instead spent\nall your time listening to other people pitch (mostly terrible)\nprojects, deciding whether to fund them, and sitting on their boards\nif you did? That would not be fun for most hackers. Hackers like\nto make things. This would be like being an administrator.Because most VCs are a different species of people from\nfounders, it's hard to know what they're thinking. If you're a\nhacker, the last time you had to deal with these guys was in high\nschool. Maybe in college you walked past their fraternity on your\nway to the lab. But don't underestimate them. They're as expert\nin their world as you are in yours. What they're good at is reading\npeople, and making deals work to their advantage. Think twice\nbefore you try to beat them at that.5. Most investors are momentum investors.Because most investors are dealmakers rather than technology people,\nthey generally don't understand what you're doing. I knew as a\nfounder that most VCs didn't get technology. I also knew some made\na lot of money. And yet it never occurred to me till recently to\nput those two ideas together and ask \"How can VCs make money by\ninvesting in stuff they don't understand?\"The answer is that they're like momentum investors. You can (or\ncould once) make a lot of money by noticing sudden changes in stock\nprices. When a stock jumps upward, you buy, and when it suddenly\ndrops, you sell. In effect you're insider trading, without knowing\nwhat you know. You just know someone knows something, and that's\nmaking the stock move.This is how most venture investors operate. They don't try to look\nat something and predict whether it will take off. They win by\nnoticing that something is taking off a little sooner than everyone\nelse. That generates almost as good returns as actually being able\nto pick winners. They may have to pay a little more than they would\nif they got in at the very beginning, but only a little.Investors always say what they really care about is the team.\nActually what they care most about is your traffic, then what other\ninvestors think, then the team. If you don't yet have any traffic,\nthey fall back on number 2, what other investors think. And this,\nas you can imagine, produces wild oscillations in the \"stock price\"\nof a startup. One week everyone wants you, and they're begging not\nto be cut out of the deal. But all it takes is for one big investor\nto cool on you, and the next week no one will return your phone\ncalls. We regularly have startups go from hot to cold or cold to\nhot in a matter of days, and literally nothing has changed.There are two ways to deal with this phenomenon. If you're feeling\nreally confident, you can try to ride it. You can start by asking\na comparatively lowly VC for a small amount of money, and then after\ngenerating interest there, ask more prestigious VCs for larger\namounts, stirring up a crescendo of buzz, and then \"sell\" at the\ntop. This is extremely risky, and takes months even if you succeed.\nI wouldn't try it myself. My advice is to err on the side of safety:\nwhen someone offers you a decent deal, just take it and get on with\nbuilding the company. Startups win or lose based on the quality\nof their product, not the quality of their funding deals.6. Most investors are looking for big hits.Venture investors like companies that could go public. That's where\nthe big returns are. They know the odds of any individual startup\ngoing public are small, but they want to invest in those that at\nleast have a chance of going public.Currently the way VCs seem to operate is to invest in a bunch of\ncompanies, most of which fail, and one of which is Google. Those\nfew big wins compensate for losses on their other investments. What this\nmeans is that most VCs will only invest in you if you're a potential\nGoogle. They don't care about companies that are a safe bet to be\nacquired for $20 million. There needs to be a chance, however\nsmall, of the company becoming really big.Angels are different in this respect. They're happy to invest in\na company where the most likely outcome is a $20 million acquisition\nif they can do it at a low enough valuation. But of course they\nlike companies that could go public too. So having an ambitious\nlong-term plan pleases everyone.If you take VC money, you have to mean it, because the structure\nof VC deals prevents early acquisitions. If you take VC money,\nthey won't let you sell early.7. VCs want to invest large amounts.The fact that they're running investment funds makes VCs want to\ninvest large amounts. A typical VC fund is now hundreds of millions\nof dollars. If $400 million has to be invested by 10 partners,\nthey have to invest $40 million each. VCs usually sit on the boards\nof companies they fund. If the average deal size was $1 million,\neach partner would have to sit on 40 boards, which would not be\nfun. So they prefer bigger deals, where they can put a lot of money\nto work at once.VCs don't regard you as a bargain if you don't need a lot of money.\nThat may even make you less attractive, because it means their\ninvestment creates less of a barrier to entry for competitors.Angels are in a different position because they're investing their\nown money. They're happy to invest small amounts—sometimes as\nlittle as $20,000—as long as the potential returns look good\nenough. So if you're doing something inexpensive, go to angels.8. Valuations are fiction.VCs admit that valuations are an artifact. They decide how much\nmoney you need and how much of the company they want, and those two\nconstraints yield a valuation.Valuations increase as the size of the investment does. A company\nthat an angel is willing to put $50,000 into at a valuation of a\nmillion can't take $6 million from VCs at that valuation. That\nwould leave the founders less than a seventh of the company between\nthem (since the option pool would also come out of that seventh).\nMost VCs wouldn't want that, which is why you never hear of deals\nwhere a VC invests $6 million at a premoney valuation of $1 million.If valuations change depending on the amount invested, that shows\nhow far they are from reflecting any kind of value of the company.Since valuations are made up, founders shouldn't care too much about\nthem. That's not the part to focus on. In fact, a high valuation\ncan be a bad thing. If you take funding at a premoney valuation\nof $10 million, you won't be selling the company for 20. You'll\nhave to sell for over 50 for the VCs to get even a 5x return, which\nis low to them. More likely they'll want you to hold out for 100.\nBut needing to get a high price decreases the chance of getting\nbought at all; many companies can buy you for $10 million, but only\na handful for 100. And since a startup is like a pass/fail course\nfor the founders, what you want to optimize is your chance of a\ngood outcome, not the percentage of the company you keep.So why do founders chase high valuations? They're tricked by\nmisplaced ambition. They feel they've achieved more if they get a\nhigher valuation. They usually know other founders, and if they\nget a higher valuation they can say \"mine is bigger than yours.\"\nBut funding is not the real test. The real test is the final outcome\nfor the founder, and getting too high a valuation may just make a\ngood outcome less likely.The one advantage of a high valuation is that you get less dilution.\nBut there is another less sexy way to achieve that: just take less\nmoney.9. Investors look for founders like the current stars.Ten years ago investors were looking for the next Bill Gates. This\nwas a mistake, because Microsoft was a very anomalous startup. They\nstarted almost as a contract programming operation, and the reason\nthey became huge was that IBM happened to drop the PC standard in\ntheir lap.Now all the VCs are looking for the next Larry and Sergey. This\nis a good trend, because Larry and Sergey are closer to the ideal\nstartup founders.Historically investors thought it was important for a founder to\nbe an expert in business. So they were willing to fund teams of\nMBAs who planned to use the money to pay programmers to build their\nproduct for them. This is like funding Steve Ballmer in the hope\nthat the programmer he'll hire is Bill Gates—kind of backward,\nas the events of the Bubble showed. Now most VCs know they should\nbe funding technical guys. This is more pronounced among the very\ntop funds; the lamer ones still want to fund MBAs.If you're a hacker, it's good news that investors are looking for\nLarry and Sergey. The bad news is, the only investors who can do\nit right are the ones who knew them when they were a\ncouple of CS grad students, not the confident media stars they are\ntoday. What investors still don't get is how clueless and tentative\ngreat founders can seem at the very beginning.10. The contribution of investors tends to be underestimated.Investors do more for startups than give them money. They're helpful\nin doing deals and arranging introductions, and some of the smarter\nones, particularly angels, can give good advice about the product.In fact, I'd say what separates the great investors from the mediocre\nones is the quality of their advice. Most investors give advice,\nbut the top ones give good advice.Whatever help investors give a startup tends to be underestimated.\nIt's to everyone's advantage to let the world think the founders\nthought of everything. The goal of the investors is for the company\nto become valuable, and the company seems more valuable if it seems\nlike all the good ideas came from within.This trend is compounded by the obsession that the press has with\nfounders. In a company founded by two people, 10% of the ideas\nmight come from the first guy they hire. Arguably they've done a\nbad job of hiring otherwise. And yet this guy will be almost\nentirely overlooked by the press.I say this as a founder: the contribution of founders is always\noverestimated. The danger here is that new founders, looking at\nexisting founders, will think that they're supermen that one couldn't\npossibly equal oneself. Actually they have a hundred different\ntypes of support people just offscreen making the whole show possible.\n[3]11. VCs are afraid of looking bad.I've been very surprised to discover how timid most VCs are. They\nseem to be afraid of looking bad to their partners, and perhaps\nalso to the limited partners—the people whose money they invest.You can measure this fear in how much less risk VCs are willing to\ntake. You can tell they won't make investments for their fund that\nthey might be willing to make themselves as angels. Though it's\nnot quite accurate to say that VCs are less willing to take risks.\nThey're less willing to do things that might look bad. That's not\nthe same thing.For example, most VCs would be very reluctant to invest in a startup\nfounded by a pair of 18 year old hackers, no matter how brilliant,\nbecause if the startup failed their partners could turn on them and\nsay \"What, you invested $x million of our money in a pair of 18\nyear olds?\" Whereas if a VC invested in a startup founded by\nthree former banking executives in their 40s who planned to outsource\ntheir product development—which to my mind is actually a lot\nriskier than investing in a pair of really smart 18 year olds—he\ncouldn't be faulted, if it failed, for making such an apparently\nprudent investment.As a friend of mine said, \"Most VCs can't do anything that would\nsound bad to the kind of doofuses who run pension funds.\" Angels\ncan take greater risks because they don't have to answer to anyone.12. Being turned down by investors doesn't mean much.Some founders are quite dejected when they get turned down by\ninvestors. They shouldn't take it so much to heart. To start with,\ninvestors are often wrong. It's hard to think of a successful\nstartup that wasn't turned down by investors at some point. Lots\nof VCs rejected Google. So obviously the reaction of investors is\nnot a very meaningful test.Investors will often reject you for what seem to be superficial\nreasons. I read of one VC who \nturned\ndown a startup simply because\nthey'd given away so many little bits of stock that the deal required\ntoo many signatures to close. \n[4]\nThe reason investors can get away\nwith this is that they see so many deals. It doesn't matter if\nthey underestimate you because of some surface imperfection, because\nthe next best deal will be almost as good. \nImagine picking out\napples at a grocery store. You grab one with a little bruise.\nMaybe it's just a surface bruise, but why even bother checking when\nthere are so many other unbruised apples to choose from?Investors would be the first to admit they're often wrong. So when\nyou get rejected by investors, don't think \"we suck,\" but instead\nask \"do we suck?\" Rejection is a question, not an answer.13. Investors are emotional.I've been surprised to discover how emotional investors can be.\nYou'd expect them to be cold and calculating, or at least businesslike,\nbut often they're not. I'm not sure if it's their position of power\nthat makes them this way, or the large sums of money involved, but\ninvestment negotiations can easily turn personal. If you offend\ninvestors, they'll leave in a huff.A while ago an eminent VC firm offered a series A round to a startup\nwe'd seed funded. Then they heard a rival VC firm was also interested.\nThey were so afraid that they'd be rejected in favor of this other\nfirm that they gave the startup what's known as an \"exploding\ntermsheet.\" They had, I think, 24 hours to say yes or no, or the\ndeal was off. Exploding termsheets are a somewhat dubious device,\nbut not uncommon. What surprised me was their reaction when I\ncalled to talk about it. I asked if they'd still be interested in\nthe startup if the rival VC didn't end up making an offer, and they\nsaid no. What rational basis could they have had for saying that?\nIf they thought the startup was worth investing in, what difference\nshould it make what some other VC thought? Surely it was their\nduty to their limited partners simply to invest in the best\nopportunities they found; they should be delighted if the other VC\nsaid no, because it would mean they'd overlooked a good opportunity.\nBut of course there was no rational basis for their decision. They\njust couldn't stand the idea of taking this rival firm's rejects.In this case the exploding termsheet was not (or not only) a tactic\nto pressure the startup. It was more like the high school trick\nof breaking up with someone before they can break up with you. In\nan earlier essay I said that VCs were a lot like high school girls.\nA few VCs have joked about that characterization, but none have\ndisputed it.14. The negotiation never stops till the closing.Most deals, for investment or acquisition, happen in two phases.\nThere's an initial phase of negotiation about the big questions.\nIf this succeeds you get a termsheet, so called because it outlines\nthe key terms of a deal. A termsheet is not legally binding,\nbut it is a definite step. It's supposed to mean that a\ndeal is going to happen, once the lawyers work out all the details.\nIn theory these details are minor ones; by definition all the\nimportant points are supposed to be covered in the termsheet.Inexperience and wishful thinking combine to make founders feel\nthat when they have a termsheet, they have a deal. They want there\nto be a deal; everyone acts like they have a deal; so there must\nbe a deal. But there isn't and may not be for several months. A\nlot can change for a startup in several months. It's not uncommon\nfor investors and acquirers to get buyer's remorse. So you have\nto keep pushing, keep selling, all the way to the close. Otherwise\nall the \"minor\" details left unspecified in the termsheet will be\ninterpreted to your disadvantage. The other side may even break\nthe deal; if they do that, they'll usually seize on some technicality\nor claim you misled them, rather than admitting they changed their\nminds.It can be hard to keep the pressure on an investor or acquirer all\nthe way to the closing, because the most effective pressure is\ncompetition from other investors or acquirers, and these tend to\ndrop away when you get a termsheet. You should try to stay as close\nfriends as you can with these rivals, but the most important thing\nis just to keep up the momentum in your startup. The investors or\nacquirers chose you because you seemed hot. Keep doing whatever\nmade you seem hot. Keep releasing new features; keep getting new\nusers; keep getting mentioned in the press and in blogs.15. Investors like to co-invest.I've been surprised how willing investors are to split deals. You\nmight think that if they found a good deal they'd want it all to\nthemselves, but they seem positively eager to syndicate. This is\nunderstandable with angels; they invest on a smaller scale and don't\nlike to have too much money tied up in any one deal. But VCs also\nshare deals a lot. Why?Partly I think this is an artifact of the rule I quoted earlier:\nafter traffic, VCs care most what other VCs think. A deal that has\nmultiple VCs interested in it is more likely to close, so of deals\nthat close, more will have multiple investors.There is one rational reason to want multiple VCs in a deal: Any\ninvestor who co-invests with you is one less investor who could\nfund a competitor. Apparently Kleiner and Sequoia didn't like\nsplitting the Google deal, but it did at least have the advantage,\nfrom each one's point of view, that there probably wouldn't be a\ncompetitor funded by the other. Splitting deals thus has similar\nadvantages to confusing paternity.But I think the main reason VCs like splitting deals is the fear\nof looking bad. If another firm shares the deal, then in the event\nof failure it will seem to have been a prudent choice—a consensus\ndecision, rather than just the whim of an individual partner.16. Investors collude.Investing is not covered by antitrust law. At least, it better not\nbe, because investors regularly do things that would be illegal\notherwise. I know personally of cases where one investor has talked\nanother out of making a competitive offer, using the promise of\nsharing future deals.In principle investors are all competing for the same deals, but\nthe spirit of cooperation is stronger than the spirit of competition.\nThe reason, again, is that there are so many deals. Though a\nprofessional investor may have a closer relationship with a founder\nhe invests in than with other investors, his relationship with the\nfounder is only going to last a couple years, whereas his relationship\nwith other firms will last his whole career. There isn't so much\nat stake in his interactions with other investors, but there will\nbe a lot of them. Professional investors are constantly trading\nlittle favors.Another reason investors stick together is to preserve the power\nof investors as a whole. So you will not, as of this writing, be\nable to get investors into an auction for your series A round.\nThey'd rather lose the deal than establish a precedent of VCs\ncompetitively bidding against one another. An efficient startup\nfunding market may be coming in the distant future; things tend to\nmove in that direction; but it's certainly not here now.\n17. Large-scale investors care about their portfolio, not any\nindividual company.The reason startups work so well is that everyone with power also\nhas equity. The only way any of them can succeed is if they all\ndo. This makes everyone naturally pull in the same direction,\nsubject to differences of opinion about tactics.The problem is, larger scale investors don't have exactly the same\nmotivation. Close, but not identical. They don't need any given\nstartup to succeed, like founders do, just their portfolio as a\nwhole to. So in borderline cases the rational thing for them to\ndo is to sacrifice unpromising startups.Large-scale investors tend to put startups in three categories:\nsuccesses, failures, and the \"living dead\"—companies that are\nplugging along but don't seem likely in the immediate future to get\nbought or go public. To the founders, \"living dead\" sounds harsh.\nThese companies may be far from failures by ordinary standards. But\nthey might as well be from a venture investor's point of view, and\nthey suck up just as much time and attention as the successes. So\nif such a company has two possible strategies, a conservative one\nthat's slightly more likely to work in the end, or a risky one that\nwithin a short time will either yield a giant success or kill the\ncompany, VCs will push for the kill-or-cure option. To them the\ncompany is already a write-off. Better to have resolution, one way\nor the other, as soon as possible.If a startup gets into real trouble, instead of trying to save it\nVCs may just sell it at a low price to another of their portfolio\ncompanies. Philip Greenspun said in Founders at Work that Ars Digita's VCs did this to them.18. Investors have different risk profiles from founders.Most people would rather a 100% chance of $1 million than a 20%\nchance of $10 million. Investors are rich enough to be rational\nand prefer the latter. So they'll always tend to encourage founders\nto keep rolling the dice. If a company is doing well, investors\nwill want founders to turn down most acquisition offers. And indeed,\nmost startups that turn down acquisition offers ultimately do better.\nBut it's still hair-raising for the founders, because they might\nend up with nothing. When someone's offering to buy you for a price\nat which your stock is worth $5 million, saying no is equivalent\nto having $5 million and betting it all on one spin of the roulette\nwheel.Investors will tell you the company is worth more. And they may\nbe right. But that doesn't mean it's wrong to sell. Any financial\nadvisor who put all his client's assets in the stock of a single,\nprivate company would probably lose his license for it.More and more, investors are letting founders cash out partially.\nThat should correct the problem. Most founders have such low standards\nthat they'll feel rich with a sum that doesn't seem huge to investors.\nBut this custom is spreading too slowly, because VCs are afraid of\nseeming irresponsible. No one wants to be the first VC to give\nsomeone fuck-you money and then actually get told \"fuck you.\" But\nuntil this does start to happen, we know VCs are being too conservative.19. Investors vary greatly.Back when I was a founder I used to think all VCs were the same.\nAnd in fact they do all look \nthe same. They're all what hackers\ncall \"suits.\" But since I've been dealing with VCs more I've learned\nthat some suits are smarter than others.They're also in a business where winners tend to keep winning and\nlosers to keep losing. When a VC firm has been successful in the\npast, everyone wants funding from them, so they get the pick of all\nthe new deals. The self-reinforcing nature of the venture funding\nmarket means that the top ten firms live in a completely different\nworld from, say, the hundredth. As well as being smarter, they\ntend to be calmer and more upstanding; they don't need to do iffy\nthings to get an edge, and don't want to because they have more\nbrand to protect.There are only two kinds of VCs you want to take money from, if you\nhave the luxury of choosing: the \"top tier\" VCs, meaning about the\ntop 20 or so firms, plus a few new ones that are not among the top\n20 only because they haven't been around long enough.It's particularly important to raise money from a top firm if you're\na hacker, because they're more confident. That means they're less\nlikely to stick you with a business guy as CEO, like VCs used to\ndo in the 90s. If you seem smart and want to do it, they'll let\nyou run the company.20. Investors don't realize how much it costs to raise money from\nthem.Raising money is a huge time suck at just the point where startups\ncan least afford it. It's not unusual for it to take five or six\nmonths to close a funding round. Six weeks is fast. And raising\nmoney is not just something you can leave running as a background\nprocess. When you're raising money, it's inevitably the main focus\nof the company. Which means building the product isn't.Suppose a Y Combinator company starts talking to VCs after demo\nday, and is successful in raising money from them, closing the deal\nafter a comparatively short 8 weeks. Since demo day occurs after\n10 weeks, the company is now 18 weeks old. Raising money, rather\nthan working on the product, has been the company's main focus for\n44% of its existence. And mind you, this an example where things\nturned out well.When a startup does return to working on the product after a funding\nround finally closes, it's as if they were returning to work after\na months-long illness. They've lost most of their momentum.Investors have no idea how much they damage the companies they\ninvest in by taking so long to do it. But companies do. So there\nis a big opportunity here for a new kind of venture fund that invests\nsmaller amounts at lower valuations, but promises to either close\nor say no very quickly. If there were such a firm, I'd recommend\nit to startups in preference to any other, no matter how prestigious.\nStartups live on speed and momentum.21. Investors don't like to say no.The reason funding deals take so long to close is mainly that\ninvestors can't make up their minds. VCs are not big companies;\nthey can do a deal in 24 hours if they need to. But they usually\nlet the initial meetings stretch out over a couple weeks. The\nreason is the selection algorithm I mentioned earlier. Most don't\ntry to predict whether a startup will win, but to notice quickly\nthat it already is winning. They care what the market thinks of\nyou and what other VCs think of you, and they can't judge those\njust from meeting you.Because they're investing in things that (a) change fast and (b)\nthey don't understand, a lot of investors will reject you in a way\nthat can later be claimed not to have been a rejection. Unless you\nknow this world, you may not even realize you've been rejected.\nHere's a VC saying no:\n\n We're really excited about your project, and we want to keep in\n close touch as you develop it further.\n\nTranslated into more straightforward language, this means: We're\nnot investing in you, but we may change our minds if it looks like\nyou're taking off. Sometimes they're more candid and say explicitly\nthat they need to \"see some traction.\" They'll invest in you if\nyou start to get lots of users. But so would any VC. So all they're\nsaying is that you're still at square 1.Here's a test for deciding whether a VC's response was yes or no.\nLook down at your hands. Are you holding a termsheet?22. You need investors.Some founders say \"Who needs investors?\" Empirically the answer\nseems to be: everyone who wants to succeed. Practically every\nsuccessful startup takes outside investment at some point.Why? What the people who think they don't need investors forget is\nthat they will have competitors. The question is not whether you\nneed outside investment, but whether it could help you at all.\nIf the answer is yes, and you don't take investment, then competitors\nwho do will have an advantage over you. And in the startup world\na little advantage can expand into a lot.Mike Moritz famously said that he invested in Yahoo because he\nthought they had a few weeks' lead over their competitors. That\nmay not have mattered quite so much as he thought, because Google\ncame along three years later and kicked Yahoo's ass. But there is\nsomething in what he said. Sometimes a small lead can grow into\nthe yes half of a binary choice.Maybe as it gets cheaper to start a startup, it will start to be\npossible to succeed in a competitive market without outside funding. \nThere are certainly\ncosts to raising money. But as of this writing the empirical\nevidence says it's a net win.23. Investors like it when you don't need them.A lot of founders approach investors as if they needed their\npermission to start a company—as if it were like getting into\ncollege. But you don't need investors to start most companies;\nthey just make it easier.And in fact, investors greatly prefer it if you don't need them.\nWhat excites them, both consciously and unconsciously, is the sort\nof startup that approaches them saying \"the train's leaving the\nstation; are you in or out?\" not the one saying \"please can we have\nsome money to start a company?\"Most investors are \"bottoms\" in the sense that the startups they\nlike most are those that are rough with them. When Google stuck\nKleiner and Sequoia with a $75 million premoney valuation, their\nreaction was probably \"Ouch! That feels so good.\" And they were\nright, weren't they? That deal probably made them more than any\nother they've done.The thing is, VCs are pretty good at reading people. So don't try\nto act tough with them unless you really are the next Google, or\nthey'll see through you in a second. Instead of acting tough, what\nmost startups should do is simply always have a backup plan. Always\nhave some alternative plan for getting started if any given investor\nsays no. Having one is the best insurance against needing one.So you shouldn't start a startup that's expensive to start, because\nthen you'll be at the mercy of investors. If you ultimately want\nto do something that will cost a lot, start by doing a cheaper\nsubset of it, and expand your ambitions when and if you raise more\nmoney.Apparently the most likely animals to be left alive after a nuclear\nwar are cockroaches, because they're so hard to kill. That's what\nyou want to be as a startup, initially. Instead of a beautiful\nbut fragile flower that needs to have its stem in a plastic tube\nto support itself, better to be small, ugly, and indestructible.Notes[1]\nI may be underestimating VCs. They may play some behind the scenes \nrole in IPOs, which you ultimately need if you want to create a silicon \nvalley.[2]\nA few VCs have an email address you can send your business\nplan to, but the number of startups that get funded this way is\nbasically zero. You should always get a personal introduction—and \nto a partner, not an associate.[3]\nSeveral people have told us that the most valuable thing about \nstartup school \nwas that they got to see famous startup founders and realized\nthey were just ordinary guys. Though we're happy to provide this\nservice, this is not generally the way we pitch startup school to\npotential speakers.[4]\nActually this sounds to me like a VC who got buyer's remorse,\nthen used a technicality to get out of the deal. But it's telling\nthat it even seemed a plausible excuse.Thanks to Sam Altman, Paul Buchheit, Hutch Fishman, and Robert \nMorris for reading drafts of\nthis, and to Kenneth King of ASES for inviting me to speak.\nComment on this essay." }, { "path": "data/PaulGrahamEssays/hackernews.txt", "content": "February 2009Hacker News was two years\nold last week. Initially it was supposed to be a side project—an\napplication to sharpen Arc on, and a place for current and future\nY Combinator founders to exchange news. It's grown bigger and taken\nup more time than I expected, but I don't regret that because I've\nlearned so much from working on it.GrowthWhen we launched in February 2007, weekday traffic was around 1600\ndaily uniques. It's since grown to around 22,000. This growth\nrate is a bit higher than I'd like. I'd like the site to grow,\nsince a site that isn't growing at least slowly is probably dead.\nBut I wouldn't want it to grow as large as Digg or Reddit—mainly\nbecause that would dilute the character of the site, but also because\nI don't want to spend all my time dealing with scaling.I already have problems enough with that. Remember, the original\nmotivation for HN was to test a new programming language, and\nmoreover one that's focused on experimenting with language design,\nnot performance. Every time the site gets slow, I fortify myself\nby recalling McIlroy and Bentley's famous quote\n\n The key to performance is elegance, not battalions of special\n cases.\n\nand look for the bottleneck I can remove with least code. So far\nI've been able to keep up, in the sense that performance has remained\nconsistently mediocre despite 14x growth. I don't know what I'll\ndo next, but I'll probably think of something.This is my attitude to the site generally. Hacker News is an\nexperiment, and an experiment in a very young field. Sites of this\ntype are only a few years old. Internet conversation generally is\nonly a few decades old. So we've probably only discovered a fraction\nof what we eventually will.That's why I'm so optimistic about HN. When a technology is this\nyoung, the existing solutions are usually terrible; which means it\nmust be possible to do much better; which means many problems that\nseem insoluble aren't. Including, I hope, the problem that has\nafflicted so many previous communities: being ruined by growth.DilutionUsers have worried about that since the site was a few months old.\nSo far these alarms have been false, but they may not always be.\nDilution is a hard problem. But probably soluble; it doesn't mean\nmuch that open conversations have \"always\" been destroyed by growth\nwhen \"always\" equals 20 instances.But it's important to remember we're trying to solve a new problem,\nbecause that means we're going to have to try new things, most of\nwhich probably won't work. A couple weeks ago I tried displaying\nthe names of users with the highest average comment scores in orange.\n[1]\nThat was a mistake. Suddenly a culture that had been more\nor less united was divided into haves and have-nots. I didn't\nrealize how united the culture had been till I saw it divided. It\nwas painful to watch.\n[2]So orange usernames won't be back. (Sorry about that.) But there\nwill be other equally broken-seeming ideas in the future, and the\nones that turn out to work will probably seem just as broken as\nthose that don't.Probably the most important thing I've learned about dilution is\nthat it's measured more in behavior than users. It's bad behavior\nyou want to keep out more than bad people. User behavior turns out\nto be surprisingly malleable. If people are \nexpected to behave\nwell, they tend to; and vice versa.Though of course forbidding bad behavior does tend to keep away bad\npeople, because they feel uncomfortably constrained in a place where\nthey have to behave well. But this way of keeping them out is\ngentler and probably also more effective than overt barriers.It's pretty clear now that the broken windows theory applies to\ncommunity sites as well. The theory is that minor forms of bad\nbehavior encourage worse ones: that a neighborhood with lots of\ngraffiti and broken windows becomes one where robberies occur. I\nwas living in New York when Giuliani introduced the reforms that\nmade the broken windows theory famous, and the transformation was\nmiraculous. And I was a Reddit user when the opposite happened\nthere, and the transformation was equally dramatic.I'm not criticizing Steve and Alexis. What happened to Reddit\ndidn't happen out of neglect. From the start they had a policy of\ncensoring nothing except spam. Plus Reddit had different goals\nfrom Hacker News. Reddit was a startup, not a side project; its\ngoal was to grow as fast as possible. Combine rapid growth and\nzero censorship, and the result is a free for all. But I don't\nthink they'd do much differently if they were doing it again.\nMeasured by traffic, Reddit is much more successful than Hacker\nNews.But what happened to Reddit won't inevitably happen to HN. There\nare several local maxima. There can be places that are free for\nalls and places that are more thoughtful, just as there are in the\nreal world; and people will behave differently depending on which\nthey're in, just as they do in the real world.I've observed this in the wild. I've seen people cross-posting on\nReddit and Hacker News who actually took the trouble to write two\nversions, a flame for Reddit and a more subdued version for HN.SubmissionsThere are two major types of problems a site like Hacker News needs\nto avoid: bad stories and bad comments. So far the danger of bad\nstories seems smaller. The stories on the frontpage now are still\nroughly the ones that would have been there when HN started.I once thought I'd have to weight votes to keep crap off the\nfrontpage, but I haven't had to yet. I wouldn't have predicted the\nfrontpage would hold up so well, and I'm not sure why it has.\nPerhaps only the more thoughtful users care enough to submit and\nupvote links, so the marginal cost of one random new user approaches\nzero. Or perhaps the frontpage protects itself, by advertising what type of submission is expected.The most dangerous thing for the frontpage is stuff that's too easy\nto upvote. If someone proves a new theorem, it takes some work by\nthe reader to decide whether or not to upvote it. An amusing cartoon\ntakes less. A rant with a rallying cry as the title takes zero,\nbecause people vote it up without even reading it.Hence what I call the Fluff Principle: on a user-voted news site,\nthe links that are easiest to judge will take over unless you take\nspecific measures to prevent it.Hacker News has two kinds of protections against fluff. The most\ncommon types of fluff links are banned as off-topic. Pictures of\nkittens, political diatribes, and so on are explicitly banned. This\nkeeps out most fluff, but not all of it. Some links are both fluff,\nin the sense of being very short, and also on topic.There's no single solution to that. If a link is just an empty\nrant, editors will sometimes kill it even if it's on topic in the\nsense of being about hacking, because it's not on topic by the real\nstandard, which is to engage one's intellectual curiosity. If the\nposts on a site are characteristically of this type I sometimes ban\nit, which means new stuff at that url is auto-killed. If a post\nhas a linkbait title, editors sometimes rephrase it to be more\nmatter-of-fact. This is especially necessary with links whose\ntitles are rallying cries, because otherwise they become implicit\n\"vote up if you believe such-and-such\" posts, which are the most\nextreme form of fluff.The techniques for dealing with links have to evolve, because the\nlinks do. The existence of aggregators has already affected what\nthey aggregate. Writers now deliberately write things to draw traffic\nfrom aggregators—sometimes even specific ones. (No, the irony\nof this statement is not lost on me.) Then there are the more\nsinister mutations, like linkjacking—posting a paraphrase of\nsomeone else's article and submitting that instead of the original.\nThese can get a lot of upvotes, because a lot of what's good in an\narticle often survives; indeed, the closer the paraphrase is to\nplagiarism, the more survives.\n[3]I think it's important that a site that kills submissions provide\na way for users to see what got killed if they want to. That keeps\neditors honest, and just as importantly, makes users confident\nthey'd know if the editors stopped being honest. HN users can do\nthis by flipping a switch called showdead in their profile.\n[4]CommentsBad comments seem to be a harder problem than bad submissions.\nWhile the quality of links on the frontpage of HN hasn't changed\nmuch, the quality of the median comment may have decreased somewhat.There are two main kinds of badness in comments: meanness and\nstupidity. There is a lot of overlap between the two—mean\ncomments are disproportionately likely also to be dumb—but\nthe strategies for dealing with them are different. Meanness is\neasier to control. You can have rules saying one shouldn't be mean,\nand if you enforce them it seems possible to keep a lid on meanness.Keeping a lid on stupidity is harder, perhaps because stupidity is\nnot so easily distinguishable. Mean people are more likely to know\nthey're being mean than stupid people are to know they're being\nstupid.The most dangerous form of stupid comment is not the long but\nmistaken argument, but the dumb joke. Long but mistaken arguments\nare actually quite rare. There is a strong correlation between\ncomment quality and length; if you wanted to compare the quality\nof comments on community sites, average length would be a good\npredictor. Probably the cause is human nature rather than anything\nspecific to comment threads. Probably it's simply that stupidity\nmore often takes the form of having few ideas than wrong ones.Whatever the cause, stupid comments tend to be short. And since\nit's hard to write a short comment that's distinguished for the\namount of information it conveys, people try to distinguish them\ninstead by being funny. The most tempting format for stupid comments\nis the supposedly witty put-down, probably because put-downs are\nthe easiest form of humor. \n[5]\nSo one advantage of forbidding\nmeanness is that it also cuts down on these.Bad comments are like kudzu: they take over rapidly. Comments have\nmuch more effect on new comments than submissions have on new\nsubmissions. If someone submits a lame article, the other submissions\ndon't all become lame. But if someone posts a stupid comment on a\nthread, that sets the tone for the region around it. People reply\nto dumb jokes with dumb jokes.Maybe the solution is to add a delay before people can respond to\na comment, and make the length of the delay inversely proportional\nto some prediction of its quality. Then dumb threads would grow\nslower.\n[6]\nPeopleI notice most of the techniques I've described are conservative:\nthey're aimed at preserving the character of the site rather than\nenhancing it. I don't think that's a bias of mine. It's due to\nthe shape of the problem. Hacker News had the good fortune to start\nout good, so in this case it's literally a matter of preservation.\nBut I think this principle would also apply to sites with different\norigins.The good things in a community site come from people more than\ntechnology; it's mainly in the prevention of bad things that\ntechnology comes into play. Technology certainly can enhance\ndiscussion. Nested comments do, for example. But I'd rather use\na site with primitive features and smart, nice users than a more\nadvanced one whose users were idiots or trolls.So the most important thing a community site can do is attract the\nkind of people it wants. A site trying to be as big as possible\nwants to attract everyone. But a site aiming at a particular subset\nof users has to attract just those—and just as importantly,\nrepel everyone else. I've made a conscious effort to do this on\nHN. The graphic design is as plain as possible, and the site rules\ndiscourage dramatic link titles. The goal is that the only thing\nto interest someone arriving at HN for the first time should be the\nideas expressed there.The downside of tuning a site to attract certain people is that,\nto those people, it can be too attractive. I'm all too aware how\naddictive Hacker News can be. For me, as for many users, it's a\nkind of virtual town square. When I want to take a break from\nworking, I walk into the square, just as I might into Harvard Square\nor University Ave in the physical world.\n[7]\nBut an online square is\nmore dangerous than a physical one. If I spent half the day loitering\non University Ave, I'd notice. I have to walk a mile to get there,\nand sitting in a cafe feels different from working. But visiting\nan online forum takes just a click, and feels superficially very\nmuch like working. You may be wasting your time, but you're not\nidle. Someone is wrong on the Internet, and you're fixing the\nproblem.Hacker News is definitely useful. I've learned a lot from things\nI've read on HN. I've written several essays that began as comments\nthere. So I wouldn't want the site to go away. But I would like\nto be sure it's not a net drag on productivity. What a disaster\nthat would be, to attract thousands of smart people to a site that\ncaused them to waste lots of time. I wish I could be 100% sure\nthat's not a description of HN.I feel like the addictiveness of games and social applications is\nstill a mostly unsolved problem. The situation now is like it was\nwith crack in the 1980s: we've invented terribly addictive new\nthings, and we haven't yet evolved ways to protect ourselves from\nthem. We will eventually, and that's one of the problems I hope\nto focus on next.\nNotes[1]\nI tried ranking users by both average and median comment\nscore, and average (with the high score thrown out) seemed the more\naccurate predictor of high quality. Median may be the more accurate\npredictor of low quality though.[2]\nAnother thing I learned from this experiment is that if you're\ngoing to distinguish between people, you better be sure you do it\nright. This is one problem where rapid prototyping doesn't work.Indeed, that's the intellectually honest argument for not discriminating\nbetween various types of people. The reason not to do it is not\nthat everyone's the same, but that it's bad to do wrong and hard\nto do right.[3]\nWhen I catch egregiously linkjacked posts I replace the url\nwith that of whatever they copied. Sites that habitually linkjack\nget banned.[4]\nDigg is notorious for its lack of transparency. The root of\nthe problem is not that the guys running Digg are especially sneaky,\nbut that they use the wrong algorithm for generating their frontpage.\nInstead of bubbling up from the bottom as they get more votes, as\non Reddit, stories start at the top and get pushed down by new\narrivals.The reason for the difference is that Digg is derived from Slashdot,\nwhile Reddit is derived from Delicious/popular. Digg is Slashdot\nwith voting instead of editors, and Reddit is Delicious/popular\nwith voting instead of bookmarking. (You can still see fossils of\ntheir origins in their graphic design.)Digg's algorithm is very vulnerable to gaming, because any story\nthat makes it onto the frontpage is the new top story. Which in\nturn forces Digg to respond with extreme countermeasures. A lot\nof startups have some kind of secret about the subterfuges they had\nto resort to in the early days, and I suspect Digg's is the extent\nto which the top stories were de facto chosen by human editors.[5]\nThe dialog on Beavis and Butthead was composed largely of\nthese, and when I read comments on really bad sites I can hear them\nin their voices.[6]\nI suspect most of the techniques for discouraging stupid\ncomments have yet to be discovered. Xkcd implemented a particularly\nclever one in its IRC channel: don't allow the same thing twice.\nOnce someone has said \"fail,\" no one can ever say it again. This\nwould penalize short comments especially, because they have less\nroom to avoid collisions in.Another promising idea is the stupid \nfilter, which is just like a\nprobabilistic spam filter, but trained on corpora of stupid and\nnon-stupid comments instead.You may not have to kill bad comments to solve the problem. Comments\nat the bottom of a long thread are rarely seen, so it may be enough\nto incorporate a prediction of quality in the comment sorting\nalgorithm.[7]\nWhat makes most suburbs so demoralizing is that there's no\ncenter to walk to.\nThanks to Justin Kan, Jessica Livingston, Robert Morris,\nAlexis Ohanian, Emmet Shear, and Fred Wilson for reading drafts of\nthis.\nComment on this essay." }, { "path": "data/PaulGrahamEssays/head.txt", "content": "August 2007A good programmer working intensively on his own code can hold it\nin his mind the way a mathematician holds a problem he's working\non. Mathematicians don't answer questions by working them out on\npaper the way schoolchildren are taught to. They do more in their\nheads: they try to understand a problem space well enough that they\ncan walk around it the way you can walk around the memory of the\nhouse you grew up in. At its best programming is the same. You\nhold the whole program in your head, and you can manipulate it at\nwill.That's particularly valuable at the start of a project, because\ninitially the most important thing is to be able to change what\nyou're doing. Not just to solve the problem in a different way,\nbut to change the problem you're solving.Your code is your understanding of the problem you're exploring.\nSo it's only when you have your code in your head that you really\nunderstand the problem.It's not easy to get a program into your head. If you leave a\nproject for a few months, it can take days to really understand it\nagain when you return to it. Even when you're actively working on\na program it can take half an hour to load into your head when you\nstart work each day. And that's in the best case. Ordinary\nprogrammers working in typical office conditions never enter this\nmode. Or to put it more dramatically, ordinary programmers working\nin typical office conditions never really understand the problems\nthey're solving.Even the best programmers don't always have the whole program they're\nworking on loaded into their heads. But there are things you can\ndo to help:\n Avoid distractions. Distractions are bad for many types of work,\n but especially bad for programming, because programmers tend to\n operate at the limit of the detail they can handle.The danger of a distraction depends not on how long it is, but\n on how much it scrambles your brain. A programmer can leave the\n office and go and get a sandwich without losing the code in his\n head. But the wrong kind of interruption can wipe your brain\n in 30 seconds.Oddly enough, scheduled distractions may be worse than unscheduled\n ones. If you know you have a meeting in an hour, you don't even\n start working on something hard. Work in long stretches. Since there's a fixed cost each time\n you start working on a program, it's more efficient to work in\n a few long sessions than many short ones. There will of course\n come a point where you get stupid because you're tired. This\n varies from person to person. I've heard of people hacking for\n 36 hours straight, but the most I've ever been able to manage\n is about 18, and I work best in chunks of no more than 12.The optimum is not the limit you can physically endure. There's\n an advantage as well as a cost of breaking up a project. Sometimes\n when you return to a problem after a rest, you find your unconscious\n mind has left an answer waiting for you. Use succinct languages. More \n powerful programming languages\n make programs shorter. And programmers seem to think of programs\n at least partially in the language they're using to write them.\n The more succinct the language, the shorter the program, and the\n easier it is to load and keep in your head.You can magnify the effect of a powerful language by using a\n style called bottom-up programming, where you write programs in\n multiple layers, the lower ones acting as programming languages\n for those above. If you do this right, you only have to keep\n the topmost layer in your head. Keep rewriting your program. Rewriting a program often yields\n a cleaner design. But it would have advantages even if it didn't:\n you have to understand a program completely to rewrite it, so\n there is no better way to get one loaded into your head. Write rereadable code. All programmers know it's good to write\n readable code. But you yourself are the most important reader.\n Especially in the beginning; a prototype is a conversation with\n yourself. And when writing for yourself you have different\n priorities. If you're writing for other people, you may not\n want to make code too dense. Some parts of a program may be\n easiest to read if you spread things out, like an introductory \n textbook. Whereas if you're writing code to make it easy to reload \n into your head, it may be best to go for brevity. Work in small groups. When you manipulate a program in your\n head, your vision tends to stop at the edge of the code you own.\n Other parts you don't understand as well, and more importantly,\n can't take liberties with. So the smaller the number of\n programmers, the more completely a project can mutate. If there's\n just one programmer, as there often is at first, you can do\n all-encompassing redesigns. Don't have multiple people editing the same piece of code. You\n never understand other people's code as well as your own. No\n matter how thoroughly you've read it, you've only read it, not\n written it. So if a piece of code is written by multiple authors,\n none of them understand it as well as a single author would.And of course you can't safely redesign something other people\n are working on. It's not just that you'd have to ask permission.\n You don't even let yourself think of such things. Redesigning\n code with several authors is like changing laws; redesigning\n code you alone control is like seeing the other interpretation\n of an ambiguous image.If you want to put several people to work on a project, divide\n it into components and give each to one person. Start small. A program gets easier to hold in your head as you\n become familiar with it. You can start to treat parts as black\n boxes once you feel confident you've fully explored them. But\n when you first start working on a project, you're forced to see\n everything. If you start with too big a problem, you may never\n quite be able to encompass it. So if you need to write a big,\n complex program, the best way to begin may not be to write a\n spec for it, but to write a prototype that solves a subset of\n the problem. Whatever the advantages of planning, they're often\n outweighed by the advantages of being able to keep a program in\n your head.\n\nIt's striking how often programmers manage to hit all eight points\nby accident. Someone has an idea for a new project, but because\nit's not officially sanctioned, he has to do it in off hours—which\nturn out to be more productive because there are no distractions.\nDriven by his enthusiasm for the new project he works on it for\nmany hours at a stretch. Because it's initially just an\nexperiment, instead of a \"production\" language he uses a mere\n\"scripting\" language—which is in fact far more powerful. He\ncompletely rewrites the program several times; that wouldn't be\njustifiable for an official project, but this is a labor of love\nand he wants it to be perfect. And since no one is going to see\nit except him, he omits any comments except the note-to-self variety.\nHe works in a small group perforce, because he either hasn't told\nanyone else about the idea yet, or it seems so unpromising that no\none else is allowed to work on it. Even if there is a group, they\ncouldn't have multiple people editing the same code, because it\nchanges too fast for that to be possible. And the project starts\nsmall because the idea is small at first; he just has some cool\nhack he wants to try out.Even more striking are the number of officially sanctioned projects\nthat manage to do all eight things wrong. In fact, if you look at\nthe way software gets written in most organizations, it's almost\nas if they were deliberately trying to do things wrong. In a sense,\nthey are. One of the defining qualities of organizations since\nthere have been such a thing is to treat individuals as interchangeable\nparts. This works well for more parallelizable tasks, like fighting\nwars. For most of history a well-drilled army of professional\nsoldiers could be counted on to beat an army of individual warriors,\nno matter how valorous. But having ideas is not very parallelizable.\nAnd that's what programs are: ideas.It's not merely true that organizations dislike the idea of depending\non individual genius, it's a tautology. It's part of the definition\nof an organization not to. Of our current concept of an organization,\nat least.Maybe we could define a new kind of organization that combined the\nefforts of individuals without requiring them to be interchangeable.\nArguably a market is such a form of organization, though it may be\nmore accurate to describe a market as a degenerate case—as what\nyou get by default when organization isn't possible.Probably the best we'll do is some kind of hack, like making the\nprogramming parts of an organization work differently from the rest.\nPerhaps the optimal solution is for big companies not even to try\nto develop ideas in house, but simply to \nbuy them. But regardless\nof what the solution turns out to be, the first step is to realize\nthere's a problem. There is a contradiction in the very phrase\n\"software company.\" The two words are pulling in opposite directions.\nAny good programmer in a large organization is going to be at odds\nwith it, because organizations are designed to prevent what\nprogrammers strive for.Good programmers manage to get a lot done anyway. \nBut often it\nrequires practically an act of rebellion against the organizations\nthat employ them. Perhaps it will help if more people understand that the way\nprogrammers behave is driven by the demands of the work they do.\nIt's not because they're irresponsible that they work in long binges\nduring which they blow off all other obligations, plunge straight into\nprogramming instead of writing specs first, and rewrite code that\nalready works. It's not because they're unfriendly that they prefer\nto work alone, or growl at people who pop their head in the door\nto say hello. This apparently random collection of annoying habits\nhas a single explanation: the power of holding a program in one's\nhead.Whether or not understanding this can help large organizations, it\ncan certainly help their competitors. The weakest point in big\ncompanies is that they don't let individual programmers do great\nwork. So if you're a little startup, this is the place to attack\nthem. Take on the kind of problems that have to be solved in one\nbig brain.\nThanks to Sam Altman, David Greenspan, Aaron Iba, Jessica Livingston,\nRobert Morris, Peter Norvig, Lisa Randall, Emmett Shear, Sergei Tsarev,\nand Stephen Wolfram for reading drafts of this." }, { "path": "data/PaulGrahamEssays/herd.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nAugust 2013The biggest component in most investors' opinion of you is the\nopinion of other investors. Which is of course a recipe for\nexponential growth. When one investor wants to invest in you, that\nmakes other investors want to, which makes others want to, and so\non.Sometimes inexperienced founders mistakenly conclude that manipulating\nthese forces is the essence of fundraising. They hear stories about\nstampedes to invest in successful startups, and think it's therefore\nthe mark of a successful startup to have this happen. But actually\nthe two are not that highly correlated. Lots of startups that cause\nstampedes end up flaming out (in extreme cases, partly as a result\nof the stampede), and lots of very successful startups were only\nmoderately popular with investors the first time they raised money.So the point of this essay is not to explain how to create a stampede,\nbut merely to explain the forces that generate them. These forces\nare always at work to some degree in fundraising, and they can cause\nsurprising situations. If you understand them, you can at least\navoid being surprised.One reason investors like you more when other investors like you\nis that you actually become a better investment. Raising money\ndecreases the risk of failure. Indeed, although investors hate it,\nyou are for this reason justified in raising your valuation for\nlater investors. The investors who invested when you had no money\nwere taking more risk, and are entitled to higher returns. Plus a\ncompany that has raised money is literally more valuable. After\nyou raise the first million dollars, the company is at least a\nmillion dollars more valuable, because it's the same company as\nbefore, plus it has a million dollars in the bank.\n[1]Beware, though, because later investors so hate to have the price\nraised on them that they resist even this self-evident reasoning.\nOnly raise the price on an investor you're comfortable with losing,\nbecause some will angrily refuse.\n[2]The second reason investors like you more when you've had some\nsuccess at fundraising is that it makes you more confident, and an\ninvestors' opinion of you is the foundation\nof their opinion of your company. Founders are often surprised how\nquickly investors seem to know when they start to succeed at raising\nmoney. And while there are in fact lots of ways for such information\nto spread among investors, the main vector is probably the founders\nthemselves. Though they're often clueless about technology, most\ninvestors are pretty good at reading people. When fundraising is\ngoing well, investors are quick to sense it in your increased\nconfidence. (This is one case where the average founder's inability\nto remain poker-faced works to your advantage.)But frankly the most important reason investors like you more when\nyou've started to raise money is that they're bad at judging startups.\nJudging startups is hard even for the best investors. The mediocre\nones might as well be flipping coins. So when mediocre investors\nsee that lots of other people want to invest in you, they assume\nthere must be a reason. This leads to the phenomenon known in the\nValley as the \"hot deal,\" where you have more interest from investors\nthan you can handle.The best investors aren't influenced much by the opinion of other\ninvestors. It would only dilute their own judgment to average it\ntogether with other people's. But they are indirectly influenced\nin the practical sense that interest from other investors imposes\na deadline. This is the fourth way in which offers beget offers.\nIf you start to get far along the track toward an offer with one\nfirm, it will sometimes provoke other firms, even good ones, to\nmake up their minds, lest they lose the deal.Unless you're a wizard at negotiation (and if you're not sure,\nyou're not) be very careful about exaggerating this to push a good\ninvestor to decide. Founders try this sort of thing all the time,\nand investors are very sensitive to it. If anything oversensitive.\nBut you're safe so long as you're telling the truth. If you're\ngetting far along with investor B, but you'd rather raise money\nfrom investor A, you can tell investor A that this is happening.\nThere's no manipulation in that. You're genuinely in a bind, because\nyou really would rather raise money from A, but you can't safely\nreject an offer from B when it's still uncertain what A will decide.Do not, however, tell A who B is. VCs will sometimes ask which\nother VCs you're talking to, but you should never tell them. Angels\nyou can sometimes tell about other angels, because angels cooperate\nmore with one another. But if VCs ask, just point out that they\nwouldn't want you telling other firms about your conversations, and\nyou feel obliged to do the same for any firm you talk to. If they\npush you, point out that you're inexperienced at fundraising — which\nis always a safe card to play — and you feel you have to be\nextra cautious. \n[3]While few startups will experience a stampede of interest, almost\nall will at least initially experience the other side of this\nphenomenon, where the herd remains clumped together at a distance.\nThe fact that investors are so much influenced by other investors'\nopinions means you always start out in something of a hole. So\ndon't be demoralized by how hard it is to get the first commitment,\nbecause much of the difficulty comes from this external force. The\nsecond will be easier.Notes[1]\nAn accountant might say that a company that has raised a million\ndollars is no richer if it's convertible debt, but in practice money\nraised as convertible debt is little different from money raised\nin an equity round.[2]\nFounders are often surprised by this, but investors can get\nvery emotional. Or rather indignant; that's the main emotion I've\nobserved; but it is very common, to the point where it sometimes\ncauses investors to act against their own interests. I know of one\ninvestor who invested in a startup at a $15 million valuation cap.\nEarlier he'd had an opportunity to invest at a $5 million cap, but\nhe refused because a friend who invested earlier had been able to\ninvest at a $3 million cap.[3]\nIf an investor pushes you hard to tell them about your conversations\nwith other investors, is this someone you want as an investor?\nThanks to Paul Buchheit, Jessica Livingston, Geoff Ralston, and Garry Tan\nfor reading drafts of this." }, { "path": "data/PaulGrahamEssays/heresy.txt", "content": "April 2022One of the most surprising things I've witnessed in my lifetime is\nthe rebirth of the concept of heresy.In his excellent biography of Newton, Richard Westfall writes about the\nmoment when he was elected a fellow of Trinity College:\n\n Supported comfortably, Newton was free to devote himself wholly\n to whatever he chose. To remain on, he had only to avoid the three\n unforgivable sins: crime, heresy, and marriage.\n [1]\n\nThe first time I read that, in the 1990s, it sounded amusingly\nmedieval. How strange, to have to avoid committing heresy. But when\nI reread it 20 years later it sounded like a description of\ncontemporary employment.There are an ever-increasing number of opinions you can be fired\nfor. Those doing the firing don't use the word \"heresy\" to describe\nthem, but structurally they're equivalent. Structurally there are\ntwo distinctive things about heresy: (1) that it takes priority\nover the question of truth or falsity, and (2) that it outweighs\neverything else the speaker has done.For example, when someone calls a statement \"x-ist,\" they're also\nimplicitly saying that this is the end of the discussion. They do\nnot, having said this, go on to consider whether the statement is\ntrue or not. Using such labels is the conversational equivalent of\nsignalling an exception. That's one of the reasons they're used:\nto end a discussion.If you find yourself talking to someone who uses these labels a\nlot, it might be worthwhile to ask them explicitly if they believe\nany babies are being thrown out with the bathwater. Can a statement\nbe x-ist, for whatever value of x, and also true? If the answer is\nyes, then they're admitting to banning the truth. That's obvious\nenough that I'd guess most would answer no. But if they answer no,\nit's easy to show that they're mistaken, and that in practice such\nlabels are applied to statements regardless of their truth or\nfalsity.The clearest evidence of this is that whether a statement is\nconsidered x-ist often depends on who said it. Truth doesn't work\nthat way. The same statement can't be true when one person says it,\nbut x-ist, and therefore false, when another person does.\n[2]The other distinctive thing about heresies, compared to ordinary\nopinions, is that the public expression of them outweighs everything\nelse the speaker has done. In ordinary matters, like knowledge of\nhistory, or taste in music, you're judged by the average of your\nopinions. A heresy is qualitatively different. It's like dropping\na chunk of uranium onto the scale.Back in the day (and still, in some places) the punishment for\nheresy was death. You could have led a life of exemplary goodness,\nbut if you publicly doubted, say, the divinity of Christ, you were\ngoing to burn. Nowadays, in civilized countries, heretics only get\nfired in the metaphorical sense, by losing their jobs. But the\nstructure of the situation is the same: the heresy\noutweighs everything else. You could have spent the last ten years\nsaving children's lives, but if you express certain opinions, you're\nautomatically fired.It's much the same as if you committed a crime. No matter how\nvirtuously you've lived, if you commit a crime, you must still\nsuffer the penalty of the law. Having lived a previously blameless\nlife might mitigate the punishment, but it doesn't affect whether\nyou're guilty or not.A heresy is an opinion whose expression is treated like a crime —\none that makes some people feel not merely that you're mistaken,\nbut that you should be punished. Indeed, their desire to see you\npunished is often stronger than it would be if you'd committed an\nactual crime. There are many on the far left who believe\nstrongly in the reintegration of felons (as I do myself), and yet\nseem to feel that anyone guilty of certain heresies should never\nwork again.There are always some heresies — some opinions you'd be punished\nfor expressing. But there are a lot more now than there were a few\ndecades ago, and even those who are happy about this would have to\nagree that it's so.Why? Why has this antiquated-sounding religious concept come back\nin a secular form? And why now?You need two ingredients for a wave of intolerance: intolerant\npeople, and an ideology to guide them. The intolerant people are\nalways there. They exist in every sufficiently large society. That's\nwhy waves of intolerance can arise so suddenly; all they need is\nsomething to set them off.I've already written an essay \ndescribing the aggressively\nconventional-minded. The short version is that people can be\nclassified in two dimensions according to (1) how independent- or\nconventional-minded they are, and (2) how aggressive they are about\nit. The aggressively conventional-minded are the enforcers of\northodoxy.Normally they're only locally visible. They're the grumpy, censorious\npeople in a group — the ones who are always first to complain when\nsomething violates the current rules of propriety. But occasionally,\nlike a vector field whose elements become aligned, a large number\nof aggressively conventional-minded people unite behind some ideology\nall at once. Then they become much more of a problem, because a mob\ndynamic takes over, where the enthusiasm of each participant is\nincreased by the enthusiasm of the others.The most notorious 20th century case may have been the Cultural\nRevolution. Though initiated by Mao to undermine his rivals, the\nCultural Revolution was otherwise mostly a grass-roots phenomenon.\nMao said in essence: There are heretics among us. Seek them out and\npunish them. And that's all the aggressively conventional-minded\never need to hear. They went at it with the delight of dogs chasing\nsquirrels.To unite the conventional-minded, an ideology must have many of the\nfeatures of a religion. In particular it must have strict and\narbitrary rules that adherents can demonstrate their \npurity \nby obeying, and its adherents must believe that anyone who obeys these\nrules is ipso facto morally superior to anyone who doesn't.\n[3]In the late 1980s a new ideology of this type appeared in US\nuniversities. It had a very strong component of moral purity, and\nthe aggressively conventional-minded seized upon it with their usual\neagerness — all the more because the relaxation of social norms\nin the preceding decades meant there had been less and less to\nforbid. The resulting wave of intolerance has been eerily similar\nin form to the Cultural Revolution, though fortunately much smaller\nin magnitude.\n[4]I've deliberately avoided mentioning any specific heresies here.\nPartly because one of the universal tactics of heretic hunters, now\nas in the past, is to accuse those who disapprove of the way in\nwhich they suppress ideas of being heretics themselves. Indeed,\nthis tactic is so consistent that you could use it as a way of\ndetecting witch hunts in any era.And that's the second reason I've avoided mentioning any specific\nheresies. I want this essay to work in the future, not just now.\nAnd unfortunately it probably will. The aggressively conventional-minded\nwill always be among us, looking for things to forbid. All they\nneed is an ideology to tell them what. And it's unlikely the current\none will be the last.There are aggressively conventional-minded people on both the right\nand the left. The reason the current wave of intolerance comes from\nthe left is simply because the new unifying ideology happened to\ncome from the left. The next one might come from the right. Imagine\nwhat that would be like.Fortunately in western countries the suppression of heresies is\nnothing like as bad as it used to be. Though the window of opinions\nyou can express publicly has narrowed in the last decade, it's still\nmuch wider than it was a few hundred years ago. The problem is the\nderivative. Up till about 1985 the window had been growing ever\nwider. Anyone looking into the future in 1985 would have expected\nfreedom of expression to continue to increase. Instead it has\ndecreased.\n[5]The situation is similar to what's happened with infectious diseases\nlike measles. Anyone looking into the future in 2010 would have\nexpected the number of measles cases in the US to continue to\ndecrease. Instead, thanks to anti-vaxxers, it has increased. The\nabsolute number is still not that high. The problem is the derivative.\n[6]In both cases it's hard to know how much to worry. Is it really\ndangerous to society as a whole if a handful of extremists refuse\nto get their kids vaccinated, or shout down speakers at universities?\nThe point to start worrying is presumably when their efforts start\nto spill over into everyone else's lives. And in both cases that\ndoes seem to be happening.So it's probably worth spending some amount of effort on pushing\nback to keep open the window of free expression. My hope is that\nthis essay will help form social antibodies not just against current\nefforts to suppress ideas, but against the concept of heresy in\ngeneral. That's the real prize. How do you disable the concept of\nheresy? Since the Enlightenment, western societies have discovered\nmany techniques for doing that, but there are surely more to be\ndiscovered.Overall I'm optimistic. Though the trend in freedom of expression\nhas been bad over the last decade, it's been good over the longer\nterm. And there are signs that the current wave of intolerance is\npeaking. Independent-minded people I talk to seem more confident\nthan they did a few years ago. On the other side, even some of the\nleaders are starting to wonder if things have \ngone too far. And popular culture among the young has already moved on. \nAll we have\nto do is keep pushing back, and the wave collapses. And then we'll\nbe net ahead, because as well as having defeated this wave, we'll\nalso have developed new tactics for resisting the next one.Notes[1] \nOr more accurately, biographies of Newton, since Westfall wrote\ntwo: a long version called Never at Rest, and a shorter one called\nThe Life of Isaac Newton. Both are great. The short version moves\nfaster, but the long one is full of interesting and often very funny\ndetails. This passage is the same in both.[2]\nAnother more subtle but equally damning bit of evidence is\nthat claims of x-ism are never qualified. You never hear anyone say\nthat a statement is \"probably x-ist\" or \"almost certainly y-ist.\"\nIf claims of x-ism were actually claims about truth, you'd expect\nto see \"probably\" in front of \"x-ist\" as often as you see it in\nfront of \"fallacious.\"[3] \nThe rules must be strict, but they need not be demanding. So\nthe most effective type of rules are those about superficial matters,\nlike doctrinal minutiae, or the precise words adherents must use.\nSuch rules can be made extremely complicated, and yet don't repel\npotential converts by requiring significant sacrifice.The superficial demands of orthodoxy make it an inexpensive substitute\nfor virtue. And that in turn is one of the reasons orthodoxy is so\nattractive to bad people. You could be a horrible person, and yet\nas long as you're orthodox, you're better than everyone who isn't.[4] \nArguably there were two. The first had died down somewhat by\n2000, but was followed by a second in the 2010s, probably caused\nby social media.[5] \nFortunately most of those trying to suppress ideas today still\nrespect Enlightenment principles enough to pay lip service to them.\nThey know they're not supposed to ban ideas per se, so they have\nto recast the ideas as causing \"harm,\" which sounds like something\nthat can be banned. The more extreme try to claim speech itself is\nviolence, or even that silence is. But strange as it may sound,\nsuch gymnastics are a good sign. We'll know we're really in trouble\nwhen they stop bothering to invent pretenses for banning ideas —\nwhen, like the medieval church, they say \"Damn right we're banning\nideas, and in fact here's a list of them.\"[6] \nPeople only have the luxury of ignoring the medical consensus\nabout vaccines because vaccines have worked so well. If we didn't\nhave any vaccines at all, the mortality rate would be so high that\nmost current anti-vaxxers would be begging for them. And the situation\nwith freedom of expression is similar. It's only because they live\nin a world created by the Enlightenment that kids from the suburbs\ncan play at banning ideas.Thanks to Marc Andreessen, Chris Best, \nTrevor Blackwell, Nicholas\nChristakis, Daniel Gackle, Jonathan Haidt, Claire Lehmann, Jessica\nLivingston, Greg Lukianoff, Robert Morris, and Garry Tan for reading\ndrafts of this." }, { "path": "data/PaulGrahamEssays/heroes.txt", "content": "April 2008There are some topics I save up because they'll be so much fun to\nwrite about. This is one of them: a list of my heroes.I'm not claiming this is a list of the n most admirable people.\nWho could make such a list, even if they wanted to?Einstein isn't on the list, for example, even though he probably\ndeserves to be on any shortlist of admirable people. I once asked\na physicist friend if Einstein was really as smart as his fame\nimplies, and she said that yes, he was. So why isn't he on the\nlist? Because I had to ask. This is a list of people who've\ninfluenced me, not people who would have if I understood their work.My test was to think of someone and ask \"is this person my\nhero?\" It often returned surprising answers. For example,\nit returned false for Montaigne, who was arguably the inventor of\nthe essay. Why? When I thought\nabout what it meant to call someone a hero, it meant I'd decide what\nto do by asking what they'd do in the same situation. That's a \nstricter standard than admiration.After I made the list, I looked to see if there was a pattern, and\nthere was, a very clear one. Everyone on the list had two qualities:\nthey cared almost excessively about their work, and they were\nabsolutely honest. By honest I don't mean trustworthy so much as\nthat they never pander: they never say or do something because\nthat's what the audience wants. They are all fundamentally subversive\nfor this reason, though they conceal it to varying degrees.\nJack LambertI grew up in Pittsburgh in the 1970s. Unless you were there it's\nhard to imagine how that town felt about the Steelers. Locally,\nall the news was bad. The steel industry was dying. But the\nSteelers were the best team in football — and moreover, in a\nway that seemed to reflect the personality of the city. They didn't\ndo anything fancy. They just got the job done.Other players were more famous: Terry Bradshaw, Franco Harris, Lynn\nSwann. But they played offense, and you always get more attention\nfor that. It seemed to me as a twelve year old football expert\nthat the best of them all was \nJack Lambert. And what made him so\ngood was that he was utterly relentless. He didn't just care about\nplaying well; he cared almost too much. He seemed to regard it as\na personal insult when someone from the other team had possession\nof the ball on his side of the line of scrimmage.The suburbs of Pittsburgh in the 1970s were a pretty dull place.\nSchool was boring. All the adults around were bored with their\njobs working for big companies. Everything that came to us through\nthe mass media was (a) blandly uniform and (b) produced elsewhere.\nJack Lambert was the exception. He was like nothing else I'd seen.\nKenneth ClarkKenneth Clark is the best nonfiction writer I know of, on any\nsubject. Most people who write about art history don't really like\nart; you can tell from a thousand little signs. But Clark did, and\nnot just intellectually, but the way one anticipates a delicious\ndinner.What really makes him stand out, though, is the quality of his\nideas. His style is deceptively casual, but there is more in \nhis books than in a library\nof art monographs. Reading \nThe Nude is like a ride in a\nFerrari. Just as you're getting settled, you're slammed back in\nyour seat by the acceleration. Before you can adjust, you're thrown\nsideways as the car screeches into the first turn. His brain throws\noff ideas almost too fast to grasp them. Finally at the end of the\nchapter you come to a halt, with your eyes wide and a big smile on\nyour face.Kenneth Clark was a star in his day, thanks to the documentary\nseries \nCivilisation. And if you read only one book about\nart history, \nCivilisation is the one I'd recommend. It's\nmuch better than the drab Sears Catalogs of art that undergraduates\nare forced to buy for Art History 101.\nLarry MihalkoA lot of people have a great teacher at some point in their childhood.\nLarry Mihalko was mine. When I look back it's like there's a line\ndrawn between third and fourth grade. After Mr. Mihalko, everything\nwas different.Why? First of all, he was intellectually curious. I had a few\nother teachers who were smart, but I wouldn't describe them as\nintellectually curious. In retrospect, he was out of place as an\nelementary school teacher, and I think he knew it. That must have\nbeen hard for him, but it was wonderful for us, his students. His\nclass was a constant adventure. I used to like going to school\nevery day.The other thing that made him different was that he liked us. Kids\nare good at telling that. The other teachers were at best benevolently\nindifferent. But Mr. Mihalko seemed like he actually wanted to\nbe our friend. On the last day of fourth grade, he got out one of\nthe heavy school record players and played James Taylor's \"You've\nGot a Friend\" to us. Just call out my name, and you know wherever\nI am, I'll come running. He died at 59 of lung cancer. I've never\ncried like I cried at his funeral.\nLeonardoOne of the things I've learned about making things that I didn't\nrealize when I was a kid is that much of the best stuff isn't made\nfor audiences, but for oneself. You see paintings and drawings in\nmuseums and imagine they were made for you to look at. Actually a\nlot of the best ones were made as a way of exploring the world, not\nas a way to please other people. The best of these explorations\nare sometimes more pleasing than stuff made explicitly to please.Leonardo did a lot of things. One of his most admirable qualities\nwas that he did so many different things that were admirable. What\npeople know of him now is his paintings and his more flamboyant\ninventions, like flying machines. That makes him seem like some\nkind of dreamer who sketched artists' conceptions of rocket ships\non the side. In fact he made a large number of far more practical\ntechnical discoveries. He was as good an engineer as a painter.His most impressive work, to me, is his \ndrawings. They're clearly\nmade more as a way of studying the world than producing something\nbeautiful. And yet they can hold their own with any work of art\never made. No one else, before or since, was that good when no one\nwas looking.\nRobert MorrisRobert Morris has a very unusual quality: he's never wrong. It\nmight seem this would require you to be omniscient, but actually\nit's surprisingly easy. Don't say anything unless you're fairly\nsure of it. If you're not omniscient, you just don't end up saying\nmuch.More precisely, the trick is to pay careful attention to how you\nqualify what you say. By using this trick, Robert has, as far as\nI know, managed to be mistaken only once, and that was when he was\nan undergrad. When the Mac came out, he said that little desktop\ncomputers would never be suitable for real hacking.It's wrong to call it a trick in his case, though. If it were a\nconscious trick, he would have slipped in a moment of excitement.\nWith Robert this quality is wired-in. He has an almost superhuman\nintegrity. He's not just generally correct, but also correct about\nhow correct he is.You'd think it would be such a great thing never to be wrong that\neveryone would do this. It doesn't seem like that much extra work\nto pay as much attention to the error on an idea as to the idea\nitself. And yet practically no one does. I know how hard it is,\nbecause since meeting Robert I've tried to do in software what he\nseems to do in hardware.\nP. G. WodehousePeople are finally starting to admit that Wodehouse was a great\nwriter. If you want to be thought a great novelist in your own\ntime, you have to sound intellectual. If what you write is popular,\nor entertaining, or funny, you're ipso facto suspect. That makes\nWodehouse doubly impressive, because it meant that to write as he\nwanted to, he had to commit to being despised in his own lifetime.Evelyn Waugh called him a great writer, but to most people at the\ntime that would have read as a chivalrous or deliberately perverse\ngesture. At the time any random autobiographical novel by a recent\ncollege grad could count on more respectful treatment from the\nliterary establishment.Wodehouse may have begun with simple atoms, but the way he composed\nthem into molecules was near faultless. His rhythm in particular.\nIt makes me self-conscious to write about it. I can think of only\ntwo other writers who came near him for style: Evelyn Waugh and\nNancy Mitford. Those three used the English language like they\nowned it.But Wodehouse has something neither of them did. He's at ease.\nEvelyn Waugh and Nancy Mitford cared what other people thought of\nthem: he wanted to seem aristocratic; she was afraid she wasn't\nsmart enough. But Wodehouse didn't give a damn what anyone thought\nof him. He wrote exactly what he wanted.\nAlexander CalderCalder's on this list because he makes me happy. Can his work stand\nup to Leonardo's? Probably not. There might not be anything from\nthe 20th Century that can. But what was good about Modernism,\nCalder had, and had in a way that he made seem effortless.What was good about Modernism was its freshness. Art became stuffy\nin the nineteenth century. The paintings that were popular at the\ntime were mostly the art equivalent of McMansions—big,\npretentious, and fake. Modernism meant starting over, making things\nwith the same earnest motives that children might. The artists who\nbenefited most from this were the ones who had preserved a child's\nconfidence, like Klee and Calder.Klee was impressive because he could work in so many different\nstyles. But between the two I like Calder better, because his work\nseemed happier. Ultimately the point of art is to engage the viewer.\nIt's hard to predict what will; often something that seems interesting\nat first will bore you after a month. Calder's \nsculptures never\nget boring. They just sit there quietly radiating optimism, like\na battery that never runs out. As far as I can tell from books and\nphotographs, the happiness of Calder's work is his own happiness\nshowing through.\nJane AustenEveryone admires Jane Austen. Add my name to the list. To me she\nseems the best novelist of all time.I'm interested in how things work. When I read most novels, I pay\nas much attention to the author's choices as to the story. But in\nher novels I can't see the gears at work. Though I'd really like\nto know how she does what she does, I can't figure it out, because\nshe's so good that her stories don't seem made up. I feel like I'm\nreading a description of something that actually happened.I used to read a lot of novels when I was younger. I can't read\nmost anymore, because they don't have enough information in them.\nNovels seem so impoverished compared to history and biography. But \nreading Austen is like reading\nnonfiction. She writes so well you don't even notice her.\nJohn McCarthyJohn McCarthy invented Lisp, the field of (or at least the term)\nartificial intelligence, and was an early member of both of the top\ntwo computer science departments, MIT and Stanford. No one would\ndispute that he's one of the greats, but he's an especial hero to\nme because of \nLisp.It's hard for us now to understand what a conceptual leap that was\nat the time. Paradoxically, one of the reasons his achievement is\nhard to appreciate is that it was so successful. Practically every\nprogramming language invented in the last 20 years includes ideas\nfrom Lisp, and each year the median language gets more Lisplike.In 1958 these ideas were anything but obvious. In 1958 there seem\nto have been two ways of thinking about programming. Some people\nthought of it as math, and proved things about Turing Machines.\nOthers thought of it as a way to get things done, and designed\nlanguages all too influenced by the technology of the day. McCarthy\nalone bridged the gap. He designed a language that was math. But\ndesigned is not really the word; discovered is more like it.\nThe SpitfireAs I was making this list I found myself thinking of people like\nDouglas Bader \nand \nR.J. Mitchell\n and \nJeffrey Quill and I realized\nthat though all of them had done many things in their lives, there\nwas one factor above all that connected them: the Spitfire.This is supposed to be a list of heroes. How can a machine be on\nit? Because that machine was not just a machine. It was a lens\nof heroes. Extraordinary devotion went into it, and extraordinary\ncourage came out.It's a cliche to call World War II a contest between good and evil,\nbut between fighter designs, it really was. The Spitfire's original\nnemesis, the ME 109, was a brutally practical plane. It was a\nkilling machine. The Spitfire was optimism embodied. And not just\nin its beautiful lines: it was at the edge of what could be\nmanufactured. But taking the high road worked. In the air, beauty\nhad the edge, just.\nSteve JobsPeople alive when Kennedy was killed usually remember exactly where\nthey were when they heard about it. I remember exactly where I was\nwhen a friend asked if I'd heard Steve Jobs had cancer. It was\nlike the floor dropped out. A few seconds later she told me that\nit was a rare operable type, and that he'd be ok. But those seconds\nseemed long.I wasn't sure whether to include Jobs on this list. A lot of people\nat Apple seem to be afraid of him, which is a bad sign. But he\ncompels admiration.There's no name for what Steve Jobs is, because there hasn't been\nanyone quite like him before. He doesn't design Apple's products\nhimself. Historically the closest analogy to what he does are the\ngreat Renaissance patrons of the arts. As the CEO of a company,\nthat makes him unique.Most CEOs delegate \ntaste to a subordinate.\nThe \ndesign paradox\n means they're choosing more or less at random. But Steve\nJobs actually has taste himself — such good taste that he's shown\nthe world how much more important taste is than they realized.\nIsaac NewtonNewton has a strange role in my pantheon of heroes: he's the one I\nreproach myself with. He worked on big things, at least for part\nof his life. It's so easy to get distracted working on small stuff.\nThe questions you're answering are pleasantly familiar. You get\nimmediate rewards — in fact, you get bigger rewards in your\ntime if you work on matters of passing importance. But I'm\nuncomfortably aware that this is the route to well-deserved obscurity.To do really great things, you have to seek out questions people\ndidn't even realize were questions. There have probably been other\npeople who did this as well as Newton, for their time, but Newton\nis my model of this kind of thought. I can just begin to understand\nwhat it must have felt like for him.You only get one life. Why not do something huge? The phrase \"paradigm\nshift\" is overused now, but Kuhn was onto something. And you know\nmore are out there, separated from us by what will later seem a\nsurprisingly thin wall of laziness and stupidity. If we work like\nNewton.Thanks to Trevor Blackwell, Jessica Livingston, and Jackie McDonough for reading drafts of this." }, { "path": "data/PaulGrahamEssays/highres.txt", "content": "December 2008For nearly all of history the success of a society was proportionate\nto its ability to assemble large and disciplined organizations.\nThose who bet on economies of scale generally won, which meant the\nlargest organizations were the most successful ones.Things have already changed so much that this is hard for us to\nbelieve, but till just a few decades ago the largest organizations\ntended to be the most progressive. An ambitious kid graduating\nfrom college in 1960 wanted to work in the huge, gleaming offices\nof Ford, or General Electric, or NASA. Small meant small-time.\nSmall in 1960 didn't mean a cool little startup. It meant uncle\nSid's shoe store.When I grew up in the 1970s, the idea of the \"corporate ladder\" was\nstill very much alive. The standard plan was to try to get into a\ngood college, from which one would be drafted into some organization\nand then rise to positions of gradually increasing responsibility.\nThe more ambitious merely hoped to climb the same ladder faster.\n[1]But in the late twentieth century something changed. It turned out\nthat economies of scale were not the only force at work. Particularly\nin technology, the increase in speed one could get from smaller\ngroups started to trump the advantages of size.The future turned out to be different from the one we were expecting\nin 1970. The domed cities and flying cars we expected have failed\nto materialize. But fortunately so have the jumpsuits with badges\nindicating our specialty and rank. Instead of being dominated by\na few, giant tree-structured organizations, it's now looking like\nthe economy of the future will be a fluid network of smaller,\nindependent units.It's not so much that large organizations stopped working. There's\nno evidence that famously successful organizations like the Roman\narmy or the British East India Company were any less afflicted by\nprotocol and politics than organizations of the same size today.\nBut they were competing against opponents who couldn't change the\nrules on the fly by discovering new technology. Now it turns out\nthe rule \"large and disciplined organizations win\" needs to have a\nqualification appended: \"at games that change slowly.\" No one knew\ntill change reached a sufficient speed.Large organizations will start to do worse now, though,\nbecause for the first time in history they're no longer getting the\nbest people. An ambitious kid graduating from college now doesn't\nwant to work for a big company. They want to work for the hot\nstartup that's rapidly growing into one. If they're really ambitious,\nthey want to start it. \n[2]This doesn't mean big companies will disappear. To say that\nstartups will succeed implies that big companies will exist, because\nstartups that succeed either become big companies or are acquired\nby them. \n[3]\nBut large organizations will probably never again\nplay the leading role they did up till the last quarter of the\ntwentieth century.It's kind of surprising that a trend that lasted so long would ever\nrun out. How often does it happen that a rule works for thousands\nof years, then switches polarity?The millennia-long run of bigger-is-better left us with a lot of\ntraditions that are now obsolete, \nbut extremely deeply rooted.\nWhich means the ambitious can now do arbitrage on them. It will\nbe very valuable to understand precisely which ideas to keep and\nwhich can now be discarded.The place to look is where the spread of smallness began: in the\nworld of startups.There have always been occasional cases, particularly in the US,\nof ambitious people who grew the ladder under them instead of\nclimbing it. But till recently this was an anomalous route that\ntended to be followed only by outsiders. It was no coincidence\nthat the great industrialists of the nineteenth century had so\nlittle formal education. As huge as their companies eventually\nbecame, they were all essentially mechanics and shopkeepers at\nfirst. That was a social step no one with a college education would\ntake if they could avoid it. Till the rise of technology startups,\nand in particular, Internet startups, it was very unusual for\neducated people to start their own businesses.The eight men who left Shockley Semiconductor to found Fairchild\nSemiconductor, the original Silicon Valley startup, weren't even\ntrying to start a company at first. They were just looking for a\ncompany willing to hire them as a group. Then one of their parents\nintroduced them to a small investment bank that offered to find\nfunding for them to start their own, so they did. But starting a\ncompany was an alien idea to them; it was something they backed\ninto.\n[4]Now I would guess that practically every Stanford or Berkeley\nundergrad who knows how to program has at least considered the idea\nof starting a startup. East Coast universities are not far behind,\nand British universities only a little behind them. This pattern\nsuggests that attitudes at Stanford and Berkeley are not an anomaly,\nbut a leading indicator. This is the way the world is going.Of course, Internet startups are still only a fraction of the world's\neconomy. Could a trend based on them be that powerful?I think so. There's no reason to suppose there's any limit to the\namount of work that could be done in this area. Like science,\nwealth seems to expand fractally. Steam power was a sliver of the\nBritish economy when Watt started working on it. But his work led\nto more work till that sliver had expanded into something bigger\nthan the whole economy of which it had initially been a part.The same thing could happen with the Internet. If Internet startups\noffer the best opportunity for ambitious people, then a lot of\nambitious people will start them, and this bit of the economy will\nballoon in the usual fractal way.Even if Internet-related applications only become a tenth of the\nworld's economy, this component will set the tone for the rest.\nThe most dynamic part of the economy always does, in everything\nfrom salaries to standards of dress. Not just because of its\nprestige, but because the principles underlying the most dynamic\npart of the economy tend to be ones that work.For the future, the trend to bet on seems to be networks of small,\nautonomous groups whose performance is measured individually. And\nthe societies that win will be the ones with the least impedance.As with the original industrial revolution, some societies are going\nto be better at this than others. Within a generation of its birth\nin England, the Industrial Revolution had spread to continental\nEurope and North America. But it didn't spread everywhere. This\nnew way of doing things could only take root in places that were\nprepared for it. It could only spread to places that already had\na vigorous middle class.There is a similar social component to the transformation that began\nin Silicon Valley in the 1960s. Two new kinds of techniques were\ndeveloped there: techniques for building integrated circuits, and\ntechniques for building a new type of company designed to grow fast\nby creating new technology. The techniques for building integrated\ncircuits spread rapidly to other countries. But the techniques for\nbuilding startups didn't. Fifty years later, startups are ubiquitous\nin Silicon Valley and common in a handful of other US cities, but\nthey're still an anomaly in most of the world.Part of the reason—possibly the main reason—that startups\nhave not spread as broadly as the Industrial Revolution did is their\nsocial disruptiveness. Though it brought many social changes, the\nIndustrial Revolution was not fighting the principle that bigger\nis better. Quite the opposite: the two dovetailed beautifully.\nThe new industrial companies adapted the customs of existing large\norganizations like the military and the civil service, and the\nresulting hybrid worked well. \"Captains of industry\" issued orders\nto \"armies of workers,\" and everyone knew what they were supposed\nto do.Startups seem to go more against the grain, socially. It's hard\nfor them to flourish in societies that value hierarchy and stability,\njust as it was hard for industrialization to flourish in societies\nruled by people who stole at will from the merchant class. But\nthere were already a handful of countries past that stage when the\nIndustrial Revolution happened. There do not seem to be that many\nready this time.\nNotes[1]\nOne of the bizarre consequences of this model was that the usual\nway to make more money was to become a manager. This is one of the\nthings startups fix.[2]\nThere are a lot of reasons American car companies have been\ndoing so much worse than Japanese car companies, but at least one\nof them is a cause for optimism: American graduates have more\noptions.[3]\nIt's possible that companies will one day be able to grow big\nin revenues without growing big in people, but we are not very far\nalong that trend yet.[4]\nLecuyer, Christophe, Making Silicon Valley, MIT Press, 2006.Thanks to Trevor Blackwell, Paul Buchheit, Jessica Livingston,\nand Robert Morris for reading drafts of this." }, { "path": "data/PaulGrahamEssays/hiresfund.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nSeptember 2010The reason startups have been using \nmore convertible notes in angel\nrounds is that they make deals close faster. By making it easier\nfor startups to give different prices to different investors, they\nhelp them break the sort of deadlock that happens when investors\nall wait to see who else is going to invest.By far the biggest influence on investors' opinions of a startup\nis the opinion of other investors. There are very, very few who\nsimply decide for themselves. Any startup founder can tell you the\nmost common question they hear from investors is not about the\nfounders or the product, but \"who else is investing?\"That tends to produce deadlocks. Raising an old-fashioned \nfixed-size equity round can take weeks, because all the angels sit around\nwaiting for the others to commit, like competitors in a bicycle\nsprint who deliberately ride slowly at the start so they can follow\nwhoever breaks first.Convertible notes let startups beat such deadlocks by rewarding\ninvestors willing to move first with lower (effective) valuations.\nWhich they deserve because they're taking more risk. It's much\nsafer to invest in a startup Ron Conway has already invested in;\nsomeone who comes after him should pay a higher price.The reason convertible notes allow more flexibility in price is\nthat valuation caps aren't actual valuations, and notes are cheap\nand easy to do. So you can do high-resolution fundraising: if you\nwanted you could have a separate note with a different cap for each\ninvestor.That cap need not simply rise monotonically. A startup could \nalso give better deals to investors they expected to help\nthem most. The point is simply that different investors, \nwhether because of the help they offer or their willingness to\ncommit, have different values for\nstartups, and their terms should reflect that.Different terms for different investors is\nclearly the way of the future. Markets always evolve toward higher\nresolution. You may not need to use convertible notes to do it.\nWith sufficiently lightweight standardized equity terms (and some\nchanges in investors' and lawyers' expectations about equity rounds)\nyou might be able to do the same thing with equity instead of debt.\nEither would be fine with startups, so long as they can easily\nchange their valuation.Deadlocks weren't the only problem with fixed-size equity rounds.\nAnother was that startups had to decide in advance how much to\nraise. I think it's a mistake for a startup to fix upon a specific\nnumber. If investors are easily convinced, the startup should raise more\nnow, and if investors are skeptical, the startup should take a\nsmaller amount and use that to get the company to the point where\nit's more convincing.It's just not reasonable to expect startups to pick an optimal round\nsize in advance, because that depends on the reactions of investors,\nand those are impossible to predict.Fixed-size, multi-investor angel rounds are such a bad idea for\nstartups that one wonders why things were ever done that way. One\npossibility is that this custom reflects the way investors like to\ncollude when they can get away with it. But I think the actual\nexplanation is less sinister. I think angels (and their lawyers)\norganized rounds this way in unthinking imitation of VC series A\nrounds. In a series A, a fixed-size equity round with a lead makes\nsense, because there is usually just one big investor, who is\nunequivocally the lead. Fixed-size series A rounds already are\nhigh res. But the more investors you have in a round, the less\nsense it makes for everyone to get the same price.The most interesting question here may be what high res fundraising\nwill do to the world of investors. Bolder investors will now get\nrewarded with lower prices. But more important, in a\nhits-driven business, is that they'll be able to get into the deals\nthey want. Whereas the \"who else is investing?\" type of investors\nwill not only pay higher prices, but may not be able to get into\nthe best deals at all.Thanks to Immad Akhund, Sam Altman, John Bautista, Pete Koomen, \nJessica Livingston, Dan Siroker, Harj Taggar, and\nFred Wilson for reading drafts of this." }, { "path": "data/PaulGrahamEssays/hiring.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nMay 2005(This essay is derived from a talk at the Berkeley CSUA.)The three big powers on the Internet now are Yahoo, Google, and\nMicrosoft. Average age of their founders: 24. So it is pretty\nwell established now that grad students can start successful\ncompanies. And if grad students can do it, why not undergrads?Like everything else in technology, the cost of starting a startup\nhas decreased dramatically. Now it's so low that it has disappeared\ninto the noise. The main cost of starting a Web-based\nstartup is food and rent. Which means it doesn't cost much more\nto start a company than to be a total slacker. You can probably\nstart a startup on ten thousand dollars of seed funding, if you're\nprepared to live on ramen.The less it costs to start a company, the less you need the permission\nof investors to do it. So a lot of people will be able to start\ncompanies now who never could have before.The most interesting subset may be those in their early twenties.\nI'm not so excited about founders who have everything investors\nwant except intelligence, or everything except energy. The most\npromising group to be liberated by the new, lower threshold are\nthose who have everything investors want except experience.Market RateI once claimed that nerds were unpopular\nin secondary school mainly because they had better things to do\nthan work full-time at being popular. Some said I was just telling\npeople what they wanted to hear. Well, I'm now about to do that\nin a spectacular way: I think undergraduates are undervalued.Or more precisely, I think few realize the huge\nspread in the value of 20 year olds. Some, it's true, are not very\ncapable. But others are more capable than all but a handful of 30\nyear olds. [1]Till now the problem has always been that it's difficult to pick\nthem out. Every VC in the world, if they could go back in time,\nwould try to invest in Microsoft. But which would have then? How\nmany would have understood that this particular 19 year old was\nBill Gates?It's hard to judge the young because (a) they change rapidly, (b)\nthere is great variation between them, and (c) they're individually\ninconsistent. That last one is a big problem. When you're young,\nyou occasionally say and do stupid things even when you're smart.\nSo if the algorithm is to filter out people who say stupid things,\nas many investors and employers unconsciously do, you're going to\nget a lot of false positives.Most organizations who hire people right out of college are only\naware of the average value of 22 year olds, which is not that high. \nAnd so the idea for most of the twentieth century was that everyone\nhad to begin as a trainee in some \nentry-level job. Organizations \nrealized there was a lot of variation in the incoming stream, but\ninstead of pursuing this thought they tended to suppress it, in the\nbelief that it was good for even the most promising kids to start \nat the bottom, so they didn't get swelled heads.The most productive young people will always be undervalued\nby large organizations, because the young have no performance to\nmeasure yet, and any error in guessing their ability will tend \ntoward the mean.What's an especially productive 22 year old to do? One thing you \ncan do is go over the heads of organizations, directly to the users.\nAny company that hires you is, economically, acting as a proxy for\nthe customer. The rate at which they value you (though they may\nnot consciously realize it) is an attempt to guess your value to \nthe user. But there's a way to appeal their judgement. If you\nwant, you can opt to be valued directly by users, by starting your\nown company.The market is a lot more discerning than any employer. And it is\ncompletely non-discriminatory. On the Internet, nobody knows you're\na dog. And more to the point, nobody knows you're 22. All users\ncare about is whether your site or software gives them what they\nwant. They don't care if the person behind it is a high school \nkid.If you're really productive, why not make employers pay market rate\nfor you? Why go work as an ordinary employee for a big\ncompany, when you could start a startup and make them buy it to get\nyou?When most people hear the word \"startup,\" they think of the famous \nones that have gone public. But most startups that succeed do it\nby getting bought. And usually the acquirer doesn't just want the\ntechnology, but the people who created it as well.Often big companies buy startups before they're profitable. Obviously\nin such cases they're not after revenues. What they want is the \ndevelopment team and the software they've built so far. When a\nstartup gets bought for 2 or 3 million six months in, it's really\nmore of a hiring bonus than an acquisition.I think this sort of thing will happen more and more, and that it \nwill be better for everyone. It's obviously better for the people\nwho start the startup, because they get a big chunk of money up\nfront. But I think it will be better for the acquirers too. The\ncentral problem in big companies, and the main reason they're so \nmuch less productive than small companies, is the difficulty of\nvaluing each person's work. Buying larval startups solves that \nproblem for them: the acquirer doesn't pay till the developers have\nproven themselves. Acquirers are protected on the downside, but \nstill get most of the upside.Product DevelopmentBuying startups also solves another problem afflicting big companies:\nthey can't do product development. Big companies are good at\nextracting the value from existing products, but bad at creating \nnew ones.Why? It's worth studying this phenomenon in detail, because this \nis the raison d'etre of startups.To start with, most big companies have some kind of turf to protect,\nand this tends to warp their development decisions. For example,\nWeb-based applications are hot now, but\nwithin Microsoft there must\nbe a lot of ambivalence about them, because the very idea of Web-based\nsoftware threatens the desktop. So any Web-based application that \nMicrosoft ends up with, will probably, like Hotmail, be something \ndeveloped outside the company.Another reason big companies are bad at developing new products is\nthat the kind of people who do that tend not to have much power in\nbig companies (unless they happen to be the CEO). Disruptive\ntechnologies are developed by disruptive people. And they either\ndon't work for the big company, or have been outmaneuvered by yes-men\nand have comparatively little influence.Big companies also lose because they usually only build one of each\nthing. When you only have one Web browser, you can't do anything\nreally risky with it. If ten different startups design ten different\nWeb browsers and you take the best, you'll probably get something\nbetter.The more general version of this problem is that there are too many\nnew ideas for companies to explore them all. There might be 500 \nstartups right now who think they're making something Microsoft\nmight buy. Even Microsoft probably couldn't manage 500 development\nprojects in-house.Big companies also don't pay people the right way. People developing\na new product at a big company get paid roughly the same whether\nit succeeds or fails. People at a startup expect to get rich if\nthe product succeeds, and get nothing if it fails. [2] So naturally\nthe people at the startup work a lot harder.The mere bigness of big companies is an obstacle. In startups, \ndevelopers are often forced to talk directly to users, whether they\nwant to or not, because there is no one else to do sales and support.\nIt's painful doing sales, but you learn much more from\ntrying to sell people something than reading what \nthey said in focus groups.And then of course, big companies are bad at product development \nbecause they're bad at everything. Everything happens slower in\nbig companies than small ones, and product development is something\nthat has to happen fast, because you have to go through a lot of \niterations to get something good.TrendI think the trend of big companies buying startups will only\naccelerate. One of the biggest remaining obstacles is pride. Most \ncompanies, at least unconsciously, feel they ought to be able to\ndevelop stuff in house, and that buying startups is to some degree \nan admission of failure. And so, as people generally do with\nadmissions of failure, they put it off for as long as possible.\nThat makes the acquisition very expensive when it finally happens.What companies should do is go out and discover startups when they're\nyoung, before VCs have puffed them up into something that costs\nhundreds of millions to acquire. Much of what VCs add, the acquirer\ndoesn't need anyway.Why don't acquirers try to predict the companies they're going to\nhave to buy for hundreds of millions, and grab them early for a \ntenth or a twentieth of that? Because they can't predict the winners\nin advance? If they're only paying a twentieth as much, they only\nhave to predict a twentieth as well. Surely they can manage that.I think companies that acquire technology will gradually learn to \ngo after earlier stage startups. They won't necessarily buy them\noutright. The solution may be some hybrid of investment and\nacquisition: for example, to buy a chunk of the company and get an\noption to buy the rest later.When companies buy startups, they're effectively fusing recruiting \nand product development. And I think that's more efficient than \ndoing the two separately, because you always get people who are\nreally committed to what they're working on.Plus this method yields teams of developers who already work well\ntogether. Any conflicts between them have been ironed out under \nthe very hot iron of running a startup. By the time the acquirer \ngets them, they're finishing one another's sentences. That's \nvaluable in software, because so many bugs occur at the boundaries \nbetween different people's code.InvestorsThe increasing cheapness of starting a company doesn't just give\nhackers more power relative to employers. It also gives them more \npower relative to investors.The conventional wisdom among VCs is that hackers shouldn't be \nallowed to run their own companies. The founders are supposed to \naccept MBAs as their bosses, and themselves take on some title like \nChief Technical Officer. There may be cases where this is a good \nidea. But I think founders will increasingly be able to push back\nin the matter of control, because they just don't need the investors'\nmoney as much as they used to.Startups are a comparatively new phenomenon. Fairchild Semiconductor\nis considered the first VC-backed startup, and they were founded \nin 1959, less than fifty years ago. Measured on the time scale of \nsocial change, what we have now is pre-beta. So we shouldn't assume\nthe way startups work now is the way they have to work.Fairchild needed a lot of money to get started. They had to build\nactual factories. What does the first round of venture funding for\na Web-based startup get spent on today? More money can't get\nsoftware written faster; it isn't needed for facilities, because\nthose can now be quite cheap; all money can really buy you is sales\nand marketing. A sales force is worth something, I'll admit. But\nmarketing is increasingly irrelevant. On the Internet, anything\ngenuinely good will spread by word of mouth.Investors' power comes from money. When startups need less money, \ninvestors have less power over them. So future founders may not\nhave to accept new CEOs if they don't want them. The VCs will have \nto be dragged kicking and screaming down this road, but like many\nthings people have to be dragged kicking and screaming toward, it\nmay actually be good for them.Google is a sign of the way things are going. As a condition of\nfunding, their investors insisted they hire someone old and experienced\nas CEO. But from what I've heard the founders didn't just give in\nand take whoever the VCs wanted. They delayed for an entire year,\nand when they did finally take a CEO, they chose a guy with a PhD \nin computer science.It sounds to me as if the founders are still the most powerful\npeople in the company, and judging by Google's performance, their\nyouth and inexperience doesn't seem to have hurt them. Indeed, I\nsuspect Google has done better than they would have if the founders\nhad given the VCs what they wanted, when they wanted it, and let \nsome MBA take over as soon as they got their first round of funding.I'm not claiming the business guys installed by VCs have no value.\nCertainly they have. But they don't need to become the founders'\nbosses, which is what that title CEO means. I predict that in the \nfuture the executives installed by VCs will increasingly be COOs\nrather than CEOs. The founders will run engineering directly, and\nthe rest of the company through the COO.The Open CageWith both employers and investors, the balance of power is slowly\nshifting towards the young. And yet they seem the last to realize\nit. Only the most ambitious undergrads even consider starting their\nown company when they graduate. Most just want to get a job.Maybe this is as it should be. Maybe if the idea of starting a \nstartup is intimidating, you filter out the uncommitted. But I \nsuspect the filter is set a little too high. I think there are\npeople who could, if they tried, start successful startups, and who\ninstead let themselves be swept into the intake ducts of big\ncompanies.Have you ever noticed that when animals are let out of cages, they\ndon't always realize at first that the door's open? Often they\nhave to be poked with a stick to get them out. Something similar \nhappened with blogs. People could have been publishing online in \n1995, and yet blogging has only really taken off in the last couple\nyears. In 1995 we thought only professional writers were entitled\nto publish their ideas, and that anyone else who did was a crank.\nNow publishing online is becoming so popular that everyone wants \nto do it, even print journalists. But blogging has not taken off \nrecently because of any technical innovation; it just took eight\nyears for everyone to realize the cage was open.I think most undergrads don't realize yet that the economic cage \nis open. A lot have been told by their parents that the route to\nsuccess is to get a good job. This was true when their parents\nwere in college, but it's less true now. The route to success is\nto build something valuable, and you don't have to be working for \nan existing company to do that. Indeed, you can often do it better\nif you're not.When I talk to undergrads, what surprises me most about them is how\nconservative they are. Not politically, of course. I mean they\ndon't seem to want to take risks. This is a mistake, because the\nyounger you are, the more risk you can take.RiskRisk and reward are always proportionate. For example, stocks are\nriskier than bonds, and over time always have greater returns. So\nwhy does anyone invest in bonds? The catch is that phrase \"over\ntime.\" Stocks will generate greater returns over thirty years, but\nthey might lose value from year to year. So what you should invest\nin depends on how soon you need the money. If you're young, you \nshould take the riskiest investments you can find.All this talk about investing may seem very theoretical. Most\nundergrads probably have more debts than assets. They may feel\nthey have nothing to invest. But that's not true: they have their\ntime to invest, and the same rule about risk applies there. Your\nearly twenties are exactly the time to take insane career risks.The reason risk is always proportionate to reward is that market \nforces make it so. People will pay extra for stability. So if you\nchoose stability-- by buying bonds, or by going to work for a big\ncompany-- it's going to cost you.Riskier career moves pay better on average, because there is less\ndemand for them. Extreme choices like starting a startup are so \nfrightening that most people won't even try. So you don't end up \nhaving as much competition as you might expect, considering the\nprizes at stake.The math is brutal. While perhaps 9 out of 10 startups fail, the \none that succeeds will pay the founders more than 10 times what\nthey would have made in an ordinary job. [3]\nThat's the sense in\nwhich startups pay better \"on average.\"Remember that. If you start a startup, you'll probably fail. Most\nstartups fail. It's the nature of the business. But it's not\nnecessarily a mistake to try something that has a 90% chance of\nfailing, if you can afford the risk. Failing at 40, when you have \na family to support, could be serious. But if you fail at 22, so \nwhat? If you try to start a startup right out of college and it \ntanks, you'll end up at 23 broke and a lot smarter. Which, if you\nthink about it, is roughly what you hope to get from a graduate \nprogram.Even if your startup does tank, you won't harm your prospects with\nemployers. To make sure I asked some friends who work for big\ncompanies. I asked managers at Yahoo, Google, Amazon, Cisco and\nMicrosoft how they'd feel about two candidates, both 24, with equal\nability, one who'd tried to start a startup that tanked, and another\nwho'd spent the two years since college working as a developer at\na big company. Every one responded that they'd prefer the guy who'd\ntried to start his own company. Zod Nazem, who's in charge of \nengineering at Yahoo, said:\n I actually put more value on the guy with the failed\n startup. And you can quote me! \nSo there you have it. Want to get hired by Yahoo? Start your own \ncompany.The Man is the CustomerIf even big employers think highly of young hackers who start\ncompanies, why don't more do it? Why are undergrads so conservative?\nI think it's because they've spent so much time in institutions.The first twenty years of everyone's life consists of being piped\nfrom one institution to another. You probably didn't have much\nchoice about the secondary schools you went to. And after high\nschool it was probably understood that you were supposed to go to\ncollege. You may have had a few different colleges to choose\nbetween, but they were probably pretty similar. So by this point\nyou've been riding on a subway line for twenty years, and the next\nstop seems to be a job.Actually college is where the line ends. Superficially, going to\nwork for a company may feel like just the next in a series of \ninstitutions, but underneath, everything is different. The end of\nschool is the fulcrum of your life, the point where you go from \nnet consumer to net producer.The other big change is that now, you're steering. You can go\nanywhere you want. So it may be worth standing back and understanding\nwhat's going on, instead of just doing the default thing.All through college, and probably long before that, most undergrads \nhave been thinking about what employers want. But what really \nmatters is what customers want, because they're the ones who give\nemployers the money to pay you.So instead of thinking about what employers want, you're probably\nbetter off thinking directly about what users want. To the extent \nthere's any difference between the two, you can even use that to\nyour advantage if you start a company of your own. For example,\nbig companies like docile conformists. But this is merely an\nartifact of their bigness, not something customers need.Grad SchoolI didn't consciously realize all this when I was graduating from \ncollege-- partly because I went straight to grad school. Grad\nschool can be a pretty good deal, even if you think of one day \nstarting a startup. You can start one when you're done, or even\npull the ripcord part way through, like the founders of Yahoo and\nGoogle.Grad school makes a good launch pad for startups, because you're\ncollected together with a lot of smart people, and you have bigger \nchunks of time to work on your own projects than an undergrad or\ncorporate employee would. As long as you have a fairly tolerant\nadvisor, you can take your time developing an idea before turning \nit into a company. David Filo and Jerry Yang started the Yahoo \ndirectory in February 1994 and were getting a million hits a day\nby the fall, but they didn't actually drop out of grad school and\nstart a company till March 1995.You could also try the startup first, and if it doesn't work, then\ngo to grad school. When startups tank they usually do it fairly\nquickly. Within a year you'll know if you're wasting your time.If it fails, that is. If it succeeds, you may have to delay grad\nschool a little longer. But you'll have a much more enjoyable life \nonce there than you would on a regular grad student stipend.ExperienceAnother reason people in their early twenties don't start startups\nis that they feel they don't have enough experience. Most investors\nfeel the same.I remember hearing a lot of that word \"experience\" when I was in \ncollege. What do people really mean by it? Obviously it's not the\nexperience itself that's valuable, but something it changes in your\nbrain. What's different about your brain after you have \"experience,\"\nand can you make that change happen faster?I now have some data on this, and I can tell you what tends to be \nmissing when people lack experience. I've said that every \nstartup needs three things: to start with good people,\nto make something users want, and not to spend too much money. It's\nthe middle one you get wrong when you're inexperienced. There are \nplenty of undergrads with enough technical skill to write good\nsoftware, and undergrads are not especially prone to waste money.\nIf they get something wrong, it's usually not realizing they have \nto make something people want.This is not exclusively a failing of the young. It's common for\nstartup founders of all ages to build things no one wants.Fortunately, this flaw should be easy to fix. If undergrads were \nall bad programmers, the problem would be a lot harder. It can \ntake years to learn how to program. But I don't think it takes \nyears to learn how to make things people want. My hypothesis is\nthat all you have to do is smack hackers on the side of the head\nand tell them: Wake up. Don't sit here making up a priori theories\nabout what users need. Go find some users and see what they need.Most successful startups not only do something very specific, but \nsolve a problem people already know they have.The big change that \"experience\" causes in your brain is learning\nthat you need to solve people's problems. Once you grasp that, you\nadvance quickly to the next step, which is figuring out what those\nproblems are. And that takes some effort, because the way software\nactually gets used, especially by the people who pay the most for\nit, is not at all what you might expect. For example, the stated \npurpose of Powerpoint is to present ideas. Its real role is to \novercome people's fear of public speaking. It allows you to give\nan impressive-looking talk about nothing, and it causes the audience\nto sit in a dark room looking at slides, instead of a bright one \nlooking at you.This kind of thing is out there for anyone to see. The key is to\nknow to look for it-- to realize that having an idea for a startup\nis not like having an idea for a class project. The goal in a\nstartup is not to write a cool piece of software. It's to make \nsomething people want. And to do that you have to look at users--\nforget about hacking, and just look at users. This can be quite a\nmental adjustment, because little if any of the software you write\nin school even has users. A few steps before a Rubik's Cube is solved, it still looks like a\nmess. I think there are a lot of undergrads whose brains are in a \nsimilar position: they're only a few steps away from being able to\nstart successful startups, if they wanted to, but they don't realize\nit. They have more than enough technical skill. They just haven't\nrealized yet that the way to create wealth is to make what users \nwant, and that employers are just proxies for users in which risk \nis pooled.If you're young and smart, you don't need either of those. You\ndon't need someone else to tell you what users want, because you \ncan figure it out yourself. And you don't want to pool risk, because\nthe younger you are, the more risk you should take.A Public Service MessageI'd like to conclude with a joint message from me and your parents.\nDon't drop out of college to start a startup. There's no rush. \nThere will be plenty of time to start companies after you graduate.\nIn fact, it may be just as well to go work for an existing company\nfor a couple years after you graduate, to learn how companies work.And yet, when I think about it, I can't imagine telling Bill Gates\nat 19 that he should wait till he graduated to start a company. \nHe'd have told me to get lost. And could I have honestly claimed\nthat he was harming his future-- that he was learning less by working\nat ground zero of the microcomputer revolution than he would have\nif he'd been taking classes back at Harvard? No, probably not.And yes, while it is probably true that you'll learn some valuable\nthings by going to work for an existing company for a couple years\nbefore starting your own, you'd learn a thing or two running your \nown company during that time too.The advice about going to work for someone else would get an even\ncolder reception from the 19 year old Bill Gates. So I'm supposed \nto finish college, then go work for another company for two years,\nand then I can start my own? I have to wait till I'm 23? That's \nfour years. That's more than twenty percent of my life so\nfar. Plus in four years it will be way too late to make money \nwriting a Basic interpreter for the Altair.And he'd be right. The Apple II was launched just two years later.\nIn fact, if Bill had finished college and gone to work for another\ncompany as we're suggesting, he might well have gone to work for\nApple. And while that would probably have been better for all of\nus, it wouldn't have been better for him.So while I stand by our responsible advice to finish college and\nthen go work for a while before starting a startup, I have to admit\nit's one of those things the old tell the young, but don't expect\nthem to listen to. We say this sort of thing mainly so we can claim\nwe warned you. So don't say I didn't warn you.\nNotes[1]\nThe average B-17 pilot in World War II was in his early twenties.\n(Thanks to Tad Marko for pointing this out.)[2] If a company tried to pay employees this way, they'd be called\nunfair. And yet when they buy some startups and not others, no one\nthinks of calling that unfair. \n[3] The 1/10 success rate for startups is a bit of an urban legend.\nIt's suspiciously neat. My guess is the odds are slightly worse.Thanks to Jessica Livingston for reading drafts of this, to\nthe friends I promised anonymity to for their opinions about hiring,\nand to Karen Nguyen and the Berkeley CSUA for organizing this talk." }, { "path": "data/PaulGrahamEssays/hp.txt", "content": "May 2003(This essay is derived from a guest lecture at Harvard, which incorporated\nan earlier talk at Northeastern.)When I finished grad school in computer science I went\nto art school to study painting. A lot of people seemed surprised\nthat someone interested in computers would also be interested in painting.\nThey seemed to think that\nhacking and painting were very different kinds of work-- that\nhacking was cold, precise, and methodical, and that\npainting was the frenzied expression of some primal urge.Both of these images are wrong. Hacking and painting have a\nlot in common. In fact, of all the different types of people I've\nknown, hackers and painters are among the most alike.What hackers and painters have in common is that they're\nboth makers. Along with composers, architects, and writers,\nwhat hackers and painters are trying to do is make good things.\nThey're not doing research per se, though if in the course of\ntrying to make good things they discover some new technique,\nso much the better.I've never liked the term \"computer science.\" The main\nreason I don't like it is that there's no such thing.\nComputer science is a\ngrab bag of tenuously related areas thrown together\nby an accident of history, like Yugoslavia.\nAt one end you have people who are really mathematicians,\nbut call what they're doing computer science so they can get DARPA grants.\nIn the middle you have people working on\nsomething like the natural history of computers-- studying the\nbehavior of algorithms for routing data through\nnetworks, for example. And then at the other extreme you\nhave the hackers, who are trying to\nwrite interesting software, and for whom computers are just a\nmedium of expression, as concrete is for architects or\npaint for painters. It's as if\nmathematicians, physicists, and architects all had to be in\nthe same department.Sometimes what the hackers do is called \"software engineering,\"\nbut this term is just as misleading.\nGood software designers are no more engineers than architects are.\nThe border between architecture and engineering is not sharply\ndefined, but it's there.\nIt falls between what and how: architects decide what to do,\nand engineers figure out how to do it.What and how should not be kept too separate. You're\nasking for trouble if you try to decide what to do without\nunderstanding how to do it.\nBut hacking can certainly be more than just deciding how to\nimplement some spec. At its best, it's creating the spec-- though\nit turns out the best way to do that is to implement it.Perhaps one day\n\"computer science\" will, like Yugoslavia, get broken up into its\ncomponent parts. That might be a good thing. Especially if it\nmeant independence for my native land, hacking.Bundling all these different types of work together in one\ndepartment may be convenient administratively, but it's confusing\nintellectually. That's the other reason I don't like the name\n\"computer science.\" Arguably the people in the middle are doing\nsomething like an experimental science. But the people at either\nend, the hackers and the mathematicians, are not actually doing science.The mathematicians don't seem bothered by this. They happily\nset to work proving theorems like the other mathematicians\nover in the math department, and probably soon stop noticing\nthat the building they work in says ``computer science'' on the\noutside. But for the hackers this label is a problem.\nIf what they're doing is called science, it makes them feel they\nought to be acting scientific.\nSo instead of doing what they really want to do, which is \nto design beautiful software, hackers in universities and\nresearch labs feel they ought to be writing research papers.In the best case, the papers are just a formality. Hackers write\ncool software, and then write a paper about it, and the paper\nbecomes a proxy for the achievement represented by the software.\nBut often this mismatch causes problems. It's easy to\ndrift away from building beautiful things toward building ugly\nthings that make more suitable subjects for research papers.Unfortunately, beautiful things don't always make the\nbest subjects for papers.\nNumber one, research must be original-- and\nas anyone who has written a PhD dissertation knows, the way to\nbe sure that you're exploring virgin territory is to to stake\nout a piece of ground that no one wants. Number two, research must be\nsubstantial-- and awkward systems yield meatier papers,\nbecause you can write about the obstacles you have to overcome\nin order to get things done. Nothing yields meaty problems like\nstarting with the wrong assumptions. Most of AI is an example\nof this rule; if you assume that knowledge can be represented\nas a list of predicate logic expressions whose arguments represent\nabstract concepts, you'll have a lot of\npapers to write about how to make this work. As Ricky Ricardo\nused to say, \"Lucy, you got a lot of explaining to do.\"The way to create something beautiful is often to make subtle\ntweaks to something that already exists, or to combine existing\nideas in a slightly new way. This kind of work is hard to\nconvey in a research paper.So why do universities and research labs continue to judge\nhackers by publications?\nFor the same reason that \"scholastic aptitude\"\ngets measured by simple-minded standardized tests, or\nthe productivity of programmers gets measured in lines of code.\nThese tests\nare easy to apply, and there is nothing so tempting as an easy test\nthat kind of works.Measuring what hackers are actually trying to do, designing\nbeautiful software, would be much more difficult. You need\na good sense of design to judge \ngood design. And\nthere is no correlation, except possibly\na negative \none, between people's ability to recognize good\ndesign and their confidence that they can.The only external test is time. Over time, beautiful\nthings tend to thrive, and ugly\nthings tend to get discarded. Unfortunately, the amounts of time\ninvolved can be longer than human lifetimes. Samuel Johnson\nsaid it took a hundred years for a writer's reputation to\nconverge. You have to wait for the writer's\ninfluential friends to die, and then for all their followers\nto die.I think hackers just have to resign themselves to having a large random\ncomponent in their reputations. In this they are no different\nfrom other makers. In fact, they're lucky by comparison. \nThe influence of fashion is not nearly so great in hacking as it\nis in painting.There are worse things than having people misunderstand your\nwork. A worse danger is that you\nwill yourself misunderstand your work. Related fields are\nwhere you go looking for ideas. If you find yourself in the computer science\ndepartment, there is a natural temptation to believe, for example,\nthat hacking is the applied version of what theoretical computer\nscience is the theory of. All\nthe time I was in graduate school I had an uncomfortable feeling\nin the back of my mind that I ought to know more theory,\nand that it was very remiss of me to have forgotten all that\nstuff within three weeks of the final exam.Now I realize I was\nmistaken. Hackers need to understand the theory of computation\nabout as much as painters need to understand paint chemistry.\nYou need to know how to calculate time and\nspace complexity and about\nTuring completeness. You might also want to remember at\nleast the concept of a state machine, in case you have to write\na parser or a regular expression library. Painters in fact \nhave to remember a good deal more about paint chemistry than \nthat.I've found that the best sources of ideas\nare not the other fields that have the word \"computer\" in\ntheir names, but the other fields inhabited by makers.\nPainting has been a much richer source of ideas than the\ntheory of computation.For example, I was taught in college\nthat one ought to figure out a program\ncompletely on paper\nbefore even going near a computer. I found that I did not\nprogram this way. I found that I liked to program\nsitting in front of a computer, not a piece of paper. Worse\nstill, instead of patiently writing out a complete program\nand assuring myself it was correct, I tended to just spew\nout code that was hopelessly broken, and gradually beat it into\nshape. Debugging, I was taught, was a kind of final pass where\nyou caught typos and oversights. The way I worked, it\nseemed like programming consisted of debugging.For a long time I felt bad about this, just as I once\nfelt bad that I didn't hold my pencil the way they taught me\nto in elementary school.\nIf I had only looked over at\nthe other makers, the painters or the architects, I would\nhave realized that there was a name for what I was doing:\nsketching. As far as I can tell, the\nway they taught me to program in college was all wrong.\nYou should figure out programs as you're writing them,\njust as writers and painters and architects do.Realizing this has real implications for software design.\nIt means that a programming language should, above all, be\nmalleable. A programming language is for \nthinking of\nprograms, not for expressing programs you've already thought\nof. It should be a pencil, not a pen. Static typing would\nbe a fine idea if people actually did write programs the way\nthey taught me to in college. But that's not how any of the \nhackers I know write programs. We need a language that lets us\nscribble and smudge and smear, not a language where you have\nto sit with a teacup of types balanced on your knee and make\npolite conversation with a strict old aunt of a compiler.While we're on the subject of static typing, identifying with\nthe makers will save us from another problem that afflicts\nthe sciences: math envy. Everyone in the sciences\nsecretly believes that mathematicians are smarter than they are. \nI think mathematicians also believe this. At any rate,\nthe result is that scientists tend to make their\nwork look as mathematical as possible. In a field like\nphysics this probably doesn't do much harm, but the further you\nget from the natural sciences, the more of a problem it\nbecomes.A page of formulas just looks so impressive.\n(Tip: for extra impressiveness, use Greek variables.) And\nso there is a great temptation to work on problems you\ncan treat formally, rather than problems that are, say,\nimportant.If hackers identified with other makers, like writers and\npainters, they wouldn't feel tempted to do \nthis. Writers and painters don't suffer from math envy.\nThey feel as if they're doing something completely unrelated.\nSo are hackers, I think.If universities and research labs keep hackers from doing\nthe kind of work they want to do,\nperhaps the place for them is in companies.\nUnfortunately, most companies won't let hackers do what they\nwant either. Universities and research labs force hackers\nto be scientists, and companies force them to be engineers.I only discovered this myself quite recently. When Yahoo bought\nViaweb, they asked me what I wanted to do. I had never\nliked the business side very much, and said that I just wanted to\nhack. When I got to Yahoo, I found that what hacking meant\nto them was implementing software, not designing it. Programmers\nwere seen as technicians who translated the visions (if\nthat is the word) of product managers into code.This seems to be the\ndefault plan in big companies. They do it because\nit decreases the standard deviation of the outcome.\nOnly a small percentage of hackers can actually design software,\nand it's hard for the\npeople running a company to pick these out. So instead of\nentrusting the future of the software to\none brilliant hacker, most companies set things up so that it is\ndesigned by committee, and the hackers merely\nimplement the design.If you want to make money at some point, remember this,\nbecause this is one of the reasons startups win. Big companies want\nto decrease the standard deviation of design outcomes because they\nwant to avoid disasters. But when you damp oscillations, you\nlose the high points as well as the low. This is not a problem for\nbig companies, because they don't win by making great\nproducts. Big companies win by sucking less than other big companies.So if you can figure out a way to get in a\ndesign war with a company big enough that its software is \ndesigned by product managers, they'll never be able to keep up\nwith you. These opportunities are not easy to find, though.\nIt's hard to engage a big company in a design war,\njust as it's hard to engage an opponent inside a castle in hand\nto hand combat. It would be pretty easy to write a better\nword processor than Microsoft Word, for example, but Microsoft,\nwithin the castle of their operating system monopoly,\nprobably wouldn't even notice if you did.The place to fight design wars is in new markets, where no one\nhas yet managed to establish any fortifications. That's where\nyou can win big by taking the bold approach to design, and\nhaving the same people both design and implement the product. \nMicrosoft themselves did this at the start. So did Apple.\nAnd Hewlett-Packard. I suspect almost every successful startup\nhas.So one way to build great software is to start your own\nstartup. There are two problems with this, though. One is\nthat in a startup you have to do so much besides write software.\nAt Viaweb I considered myself lucky if I\ngot to hack a quarter of the time. And the things I had to \ndo the other three quarters of the time ranged from tedious\nto terrifying. I have a benchmark for this, because I\nonce had to leave a board meeting to have\nsome cavities filled. I remember sitting back in the\ndentist's chair, waiting for the drill, and feeling like\nI was on vacation.The other problem with startups is that there is not much\noverlap between the kind of software that makes money and the\nkind that's interesting to write. Programming languages\nare interesting to write, and Microsoft's first product was\none, in fact, but no one will pay for programming languages\nnow. If you want to make money, you tend to be forced to work\non problems that are too nasty for anyone to solve for free.All makers face this problem. Prices are\ndetermined by supply and demand, and there is just not as much\ndemand for things that are fun to work on as there is for\nthings that solve the mundane problems of individual customers.\nActing in off-Broadway plays just doesn't pay as well as\nwearing a gorilla suit in someone's booth at a\ntrade show. Writing novels doesn't pay as well as writing\nad copy for garbage disposals.\nAnd hacking programming languages doesn't pay as well\nas figuring out how to connect some company's\nlegacy database to their Web server.I think the answer to this problem, in the case of software,\nis a concept known to nearly all makers: the day job.\nThis phrase began with musicians, who\nperform at night. More generally, it means that you have one\nkind of work you do for money, and another for love.Nearly all makers have day jobs early in their careers.\nPainters and writers notoriously do. If you're lucky\nyou can get a day job that's closely\nrelated to your real work. Musicians often\nseem to work in record stores. A hacker working on some\nprogramming language or operating system might likewise be able to\nget a day job using it. [1]When I say that the answer is for hackers to have day jobs, \nand work on beautiful software on the side, I'm not proposing\nthis as a new idea. This is what open-source hacking is all \nabout. What I'm saying is that open-source is probably the right\nmodel, because it has been independently confirmed by all the \nother makers.It seems surprising to me that any employer would be reluctant\nto let hackers work on open-source projects.\nAt Viaweb, we would have been reluctant to hire anyone\nwho didn't. When we interviewed\nprogrammers, the main\nthing we cared about was what kind of software they\nwrote in their spare time.\nYou can't do anything really well unless\nyou love it, and if you love to hack you'll inevitably\nbe working on projects of your own. [2]Because hackers are makers rather than scientists,\nthe right place to look for metaphors is not in the\nsciences, but among other kinds of makers. What else can painting\nteach us about hacking?One thing we can learn, or at least confirm, from the\nexample of painting is how to learn to hack. You learn to\npaint mostly by doing it.\nDitto for hacking. Most hackers don't learn to hack by\ntaking college courses in programming. They learn to hack\nby writing programs of their own at age thirteen. Even in \ncollege classes, you learn to hack mostly by hacking. [3]Because painters leave a trail of work behind them, you\ncan watch them learn by doing. If you look at the work\nof a painter in chronological order, you'll find that each \npainting builds on things that have been learned in previous\nones. When there's something in\na painting that works very well, you can usually find version \n1 of it in a smaller form in some earlier painting.I think most makers work this way. Writers and architects seem\nto as well. Maybe it would be good for hackers\nto act more like painters, and regularly start over from scratch,\ninstead of continuing to work for years on one project, and\ntrying to incorporate all their later ideas as revisions.The fact that hackers learn to hack by doing it is another\nsign of how different hacking is from the sciences. Scientists\ndon't learn science by doing it, but by doing labs and problem sets.\nScientists start out doing work that's perfect, in the sense\nthat they're just trying to reproduce work someone else has \nalready done for them.\nEventually, they get\nto the point where they can do original work.\nWhereas hackers, from the start, are doing original work; it's\njust very bad. So hackers start original, and get good, and\nscientists start good, and get original.\nThe other way makers learn is from examples.\nFor a painter, a museum is a reference library of techniques.\nFor hundreds of years it has been part of the traditional\neducation of painters to copy the works of the great masters,\nbecause copying forces you to look closely\nat the way a painting is made.Writers do this too.\nBenjamin Franklin learned to write by summarizing the points \nin the essays of Addison and Steele and then trying to\nreproduce them. Raymond Chandler did the same thing\nwith detective stories.Hackers, likewise, can learn to program by looking at \ngood programs-- not just at what they do, but the source\ncode too. One of the less publicized benefits\nof the open-source movement is that it has made it easier\nto learn to program. When I learned to program, we had to rely\nmostly on examples in books. The one big chunk of\ncode available then was Unix, but even this was not \nopen source. Most of the people who read the source\nread it in illicit photocopies of John Lions' book, which\nthough written in 1977 was not allowed to be published\nuntil 1996.Another example we can take from painting is the way that\npaintings are created by gradual refinement. Paintings usually\nbegin with a sketch.\nGradually the details get filled in.\nBut it is not merely a process of filling in. Sometimes \nthe original plans turn out to be mistaken.\nCountless paintings,\nwhen you look at them in xrays, turn out to have limbs that\nhave been moved or facial features that have been readjusted.Here's a case where we can learn from painting. I think hacking\nshould work this way too. It's unrealistic\nto expect that the specifications for a program will be\nperfect. You're\nbetter off if you admit this up front, and write programs in\na way that allows specifications to change on the fly.(The structure of large companies makes this hard for them\nto do, so here is another place where startups have an advantage.)Everyone by now presumably knows about the danger of premature\noptimization. I think we should be just as worried about\npremature design-- deciding too early what\na program should do.The right tools can help us avoid\nthis danger.\nA good programming language should, like oil paint, make it\neasy to change your mind. Dynamic typing is a win here because\nyou don't have to\ncommit to specific data representations up front.\nBut the key to flexibility, I think, is to make the language\nvery abstract.\nThe easiest program to change is one that's very short.\nThis sounds like a paradox, but a great painting\nhas to be better than it has to be.\nFor example, when Leonardo\npainted the portrait of Ginevra de Benci\nin the National Gallery, he put a juniper bush behind her head.\nIn it he carefully\npainted each individual leaf. Many painters might have thought,\nthis is just something to put in the background to frame\nher head. No one will look that closely at it.Not Leonardo. How hard he worked on part of a painting didn't\ndepend at all on how closely he expected anyone to look at it.\nHe was like Michael Jordan. Relentless.Relentlessness wins because, in the aggregate, unseen details\nbecome visible.\nWhen people walk by the portrait of Ginevra de Benci,\ntheir attention is often immediately arrested by it,\neven before they look at the label and notice that it says\nLeonardo da Vinci. All those unseen details combine to produce\nsomething that's just stunning, like a thousand barely audible\nvoices all singing in tune.Great software, likewise, requires a fanatical devotion to\nbeauty. If you look inside good software, you find that\nparts no one is ever supposed to see are beautiful too.\nI'm not claiming I write great software, but I\nknow that when it comes to code I behave in a way that would\nmake me eligible for prescription drugs if I approached everyday\nlife the same way.\nIt drives me crazy to see code that's badly indented,\nor that uses ugly variable names.If a hacker were a mere implementor, turning a spec into code, then\nhe could just work his way through it from one end to the other like\nsomeone digging a ditch. But if the hacker is a creator, we have\nto take inspiration into account.In hacking, like painting,\nwork comes in cycles. Sometimes you get excited about some\nnew project and you want to work sixteen hours a day on it. \nOther times nothing seems interesting.To do good work you have to take these cycles into\naccount, because they're affected by how you react to them.\nWhen you're driving a\ncar with a manual transmission on a hill, you have to back off\nthe clutch sometimes to avoid stalling. Backing\noff can likewise prevent ambition from stalling.\nIn both painting and hacking there are some\ntasks that are terrifyingly ambitious, and others that are\ncomfortingly routine. It's a good idea to save some easy\ntasks for moments when you would otherwise stall.In hacking, this can literally mean saving up bugs.\nI like debugging: it's the\none time that hacking is as straightforward as \npeople think it is. You have a\ntotally constrained problem, and all you have to do is solve\nit. Your program is supposed to do x. Instead it does y.\nWhere does it go wrong? You know you're going to win\nin the end. It's as relaxing as painting a wall.The example of painting can teach us not only how to manage our\nown work, but how to work together. A lot of the\ngreat art of the past is the work of multiple hands, though\nthere may only be one name on the wall next to it in the\nmuseum. Leonardo was an apprentice in the workshop of\nVerrocchio and painted one of the angels in his Baptism of\nChrist. This sort of thing was the rule, not the exception.\nMichelangelo was considered especially dedicated for insisting\non painting all the figures on the ceiling of the Sistine\nChapel himself.As far as I know, when painters worked together on a painting,\nthey never worked on the same parts. It was common\nfor the master to paint the principal figures and for assistants\nto paint the others and the background. But you never had\none guy painting over the work of another.I think this is the right model for collaboration in software\ntoo. Don't push it too far. When a piece of code is\nbeing hacked by three or four different people, no one of whom\nreally owns it, it will end up being like a common-room. It will\ntend to feel bleak and abandoned, and accumulate cruft.\nThe right\nway to collaborate, I think, is to divide projects into sharply\ndefined modules, each with a definite owner, and with interfaces\nbetween them that are as carefully designed and, if possible,\nas articulated as programming languages.Like painting, most software is intended for\na human audience. And so hackers, like painters, must have\nempathy to do really great work. You have to be able to see\nthings from the user's point of view.When I was a kid I was always being told to look at things from\nsomeone else's point of view. What this always meant in\npractice was to do what someone else wanted, instead of what\nI wanted. This of course gave empathy a bad name, and I made a\npoint of not cultivating it.Boy, was I wrong. It turns out that looking at things from \nother people's point of view is practically the secret of\nsuccess. It doesn't necessarily mean being self-sacrificing.\nFar from it. Understanding how someone else sees things\ndoesn't imply that you'll act in his interest; in some\nsituations-- in war, for example-- you want to do exactly\nthe opposite. [4]Most makers make things for a human audience.\nAnd to engage an audience you have to understand what they need.\nNearly all the greatest paintings are paintings of people,\nfor example, because people are what people are interested in.Empathy is probably the single most important difference\nbetween a good hacker and a great one. Some hackers\nare quite smart, but when it comes to empathy are\npractically solipsists. It's hard for such \npeople to design great software [5], because they can't\nsee things from the user's point of view.One way to tell how good people are at empathy is to watch\nthem explain a technical question to someone without a technical\nbackground. We probably all know people who, though otherwise smart,\nare just comically bad at this. If someone asks them at\na dinner party what a programming language is, they'll\nsay something like ``Oh, a high-level language is what\nthe compiler uses as input to generate object code.''\nHigh-level language? Compiler? Object code? Someone who \ndoesn't know what a programming language is obviously doesn't\nknow what these things are, either.Part of what software has to do is explain itself. So to \nwrite good software you have to understand how little users \nunderstand.\nThey're going to walk up to the software with no preparation, and\nit had better do what they guess it will, because they're\nnot going to read the manual. The best system I've ever seen \nin this respect was the original Macintosh, in 1985.\nIt did what software almost never does: it just worked. [6]Source code, too, should explain itself. If I could get people to\nremember just one quote about programming, it would be the\none at the beginning of Structure and Interpretation of Computer\nPrograms.\n\nPrograms should be written for people to read, and\nonly incidentally for machines to execute.\n\nYou need to have \nempathy not just for your users, but for your readers. It's in \nyour interest, because you'll be one of them.\nMany a hacker has written a program only to\nfind on returning to it six months later that he has no idea \nhow it works. I know several people who've sworn off Perl after\nsuch experiences. [7]Lack of empathy is associated with intelligence, to the point\nthat there is even something of a fashion for it in some places.\nBut I don't think there's any correlation.\nYou can do well in math and\nthe natural sciences without having to learn empathy, and people in these\nfields tend to be smart, so the two qualities have come to be\nassociated. But there are plenty of dumb people who are bad at\nempathy too. Just listen to the people who call in with questions on\ntalk shows. They ask whatever it is they're asking in\nsuch a roundabout way\nthat the hosts often have to rephrase the question for them.So, if hacking works like painting and writing, is it as cool?\nAfter all, you only get one life.\nYou might as well spend it working on something great.Unfortunately, the question is hard to answer. There is always\na big time lag in prestige. It's like light from a distant star.\nPainting has prestige now because of great work people did five hundred\nyears ago. At the time, no one thought\nthese paintings were as important as we do today. It would have\nseemed very odd to people at the time that Federico da Montefeltro,\nthe Duke of Urbino, would one day be known mostly as the guy\nwith the strange nose in a painting \nby Piero della Francesca.So while I admit that hacking doesn't seem as cool as painting now,\nwe should remember that painting itself didn't seem as cool in\nits glory days as it does now.What we can say with some confidence is that these are the glory\ndays of hacking. In most fields the great work is done early on.\nThe paintings made between 1430 and 1500 are still unsurpassed.\nShakespeare appeared just as professional theater was being born,\n\nand pushed the medium\nso far that every playwright since has had to live in his shadow.\nAlbrecht Durer did the same thing with engraving, and Jane Austen\nwith the novel.Over and over we see the same pattern. A new medium appears, and\npeople are so excited about it that they explore most of its\npossibilities in the first couple generations. Hacking seems\nto be in this phase now.Painting was not, in Leonardo's time, as cool as his work\nhelped make it.\nHow cool hacking turns out to be will depend on what we can\ndo with this new medium. \n\nNotes[1] The greatest damage that photography has done\nto painting may be the fact that it killed the best day job.\nMost of the great painters in history supported\nthemselves by painting portraits. [2] I've been told that Microsoft discourages\nemployees from contributing to open-source projects, even in\ntheir spare time.\nBut so many of the best hackers work on open-source\nprojects now that the main effect of this policy may be\nto ensure that they won't be able to hire any first-rate\nprogrammers.[3] What you learn about programming in college is much like\nwhat you learn about books or clothes or dating: what bad taste you\nhad in high school.[4] Here's an example of applied empathy.\nAt Viaweb, if we couldn't decide between two alternatives, we'd\nask, what would our competitors hate most? At one point a\ncompetitor added a feature to their software that was basically\nuseless, but since it was one of few they had that we didn't, they\nmade much of it in the trade press.\nWe could have tried to explain that the feature was useless,\nbut we decided it would annoy our competitor more if we\njust implemented it ourselves, so we hacked together our own\nversion that afternoon.[5] Except text editors and compilers. Hackers don't need empathy to\ndesign these, because they are themselves typical users.[6] Well, almost. They overshot the available RAM somewhat,\ncausing much inconvenient disk swapping, but this could be fixed\nwithin a few months by buying an additional disk drive.[7] The way to make programs easy to read is not to\nstuff them with comments. I would take Abelson and Sussman's\nquote a step further. Programming languages should be designed\nto express algorithms, and only incidentally to tell computers\nhow to execute them. A good programming language\nought to be better for explaining software than English.\nYou should only\nneed comments when there is some kind of kludge you need to warn\nreaders about, just as on a road there are only\narrows on parts with unexpectedly sharp curves.\nThanks to Trevor Blackwell, Robert Morris, Dan Giffin, and Lisa\nRandall for reading drafts of this, and to Henry Leitner\nand Larry Finkelstein for inviting me to speak." }, { "path": "data/PaulGrahamEssays/hs.txt", "content": "January 2005(I wrote this talk for a\nhigh school. I never actually \ngave it, because the school authorities vetoed the plan to invite me.)When I said I was speaking at a high school, my friends were curious.\nWhat will you say to high school students? So I asked them, what\ndo you wish someone had told you in high school? Their answers\nwere remarkably similar. So I'm going to tell you what we all wish\nsomeone had told us.I'll start by telling you something you don't have to know in high\nschool: what you want to do with your life. People are always\nasking you this, so you think you're supposed to have an answer.\nBut adults ask this mainly as a conversation starter. They want\nto know what sort of person you are, and this question is just to\nget you talking. They ask it the way you might poke a hermit crab\nin a tide pool, to see what it does.If I were back in high school and someone asked about my plans, I'd\nsay that my first priority was to learn what the options were. You\ndon't need to be in a rush to choose your life's work. What you \nneed to do is discover what you like. You have to work on stuff \nyou like if you want to be good at what you do.It might seem that nothing would be easier than deciding what you\nlike, but it turns out to be hard, partly because it's hard to get\nan accurate picture of most jobs. Being a doctor is not the way\nit's portrayed on TV. Fortunately you can also watch real doctors,\nby volunteering in hospitals. [1]But there are other jobs you can't learn about, because no one is\ndoing them yet. Most of the work I've done in the last ten years\ndidn't exist when I was in high school. The world changes fast, \nand the rate at which it changes is itself speeding up. In such a\nworld it's not a good idea to have fixed plans.And yet every May, speakers all over the country fire up the Standard \nGraduation Speech, the theme of which is: don't give up on your\ndreams. I know what they mean, but this is a bad way to put it,\nbecause it implies you're supposed to be bound by some plan you\nmade early on. The computer world has a name for this: premature\noptimization. And it is synonymous with disaster. These speakers\nwould do better to say simply, don't give up.What they really mean is, don't get demoralized. Don't think that \nyou can't do what other people can. And I agree you shouldn't \nunderestimate your potential. People who've done great things tend\nto seem as if they were a race apart. And most biographies only \nexaggerate this illusion, partly due to the worshipful attitude \nbiographers inevitably sink into, and partly because, knowing how\nthe story ends, they can't help streamlining the plot till it seems\nlike the subject's life was a matter of destiny, the mere unfolding\nof some innate genius. In fact I suspect if you had the sixteen\nyear old Shakespeare or Einstein in school with you, they'd seem\nimpressive, but not totally unlike your other friends.Which is an uncomfortable thought. If they were just like us, then\nthey had to work very hard to do what they did. And that's one \nreason we like to believe in genius. It gives us an excuse for\nbeing lazy. If these guys were able to do what they did only because\nof some magic Shakespeareness or Einsteinness, then it's not our\nfault if we can't do something as good.I'm not saying there's no such thing as genius. But if you're\ntrying to choose between two theories and one gives you an excuse \nfor being lazy, the other one is probably right.So far we've cut the Standard Graduation Speech down from \"don't\ngive up on your dreams\" to \"what someone else can do, you can do.\"\nBut it needs to be cut still further. There is some variation\nin natural ability. Most people overestimate its role, but it does \nexist. If I were talking to a guy four feet tall whose ambition \nwas to play in the NBA, I'd feel pretty stupid saying, you can\ndo anything if you really try. [2]We need to cut the Standard Graduation Speech down to, \"what someone\nelse with your abilities can do, you can do; and don't underestimate\nyour abilities.\" But as so often happens, the closer you get to\nthe truth, the messier your sentence gets. We've taken a nice, \nneat (but wrong) slogan, and churned it up like a mud puddle. It\ndoesn't make a very good speech anymore. But worse still, it doesn't\ntell you what to do anymore. Someone with your abilities? What \nare your abilities?UpwindI think the solution is to work in the other direction. Instead\nof working back from a goal, work forward from promising situations.\nThis is what most successful people actually do anyway.In the graduation-speech approach, you decide where you want to be\nin twenty years, and then ask: what should I do now to get there? \nI propose instead that you don't commit to anything in the future,\nbut just look at the options available now, and choose those that\nwill give you the most promising range of options afterward.It's not so important what you work on, so long as you're not wasting\nyour time. Work on things that interest you and increase your\noptions, and worry later about which you'll take.Suppose you're a college freshman deciding whether to major in math \nor economics. Well, math will give you more options: you can go into\nalmost any field from math. If you major in math it will be easy\nto get into grad school in economics, but if you major in economics\nit will be hard to get into grad school in math.Flying a glider is a good metaphor here. Because a glider doesn't\nhave an engine, you can't fly into the wind without losing a lot\nof altitude. If you let yourself get far downwind of good places \nto land, your options narrow uncomfortably. As a rule you want to\nstay upwind. So I propose that as a replacement for \"don't give \nup on your dreams.\" Stay upwind.How do you do that, though? Even if math is upwind of economics,\nhow are you supposed to know that as a high school student?Well, you don't, and that's what you need to find out. Look for smart people\nand hard problems. Smart people tend to clump together, and if you\ncan find such a clump, it's probably worthwhile to join it. But\nit's not straightforward to find these, because there is a lot of \nfaking going on.To a newly arrived undergraduate, all university departments look\nmuch the same. The professors all seem forbiddingly intellectual\nand publish papers unintelligible to outsiders. But while in some\nfields the papers are unintelligible because they're full of hard\nideas, in others they're deliberately written in an obscure way to\nseem as if they're saying something important. This may seem a \nscandalous proposition, but it has been experimentally verified,\nin the famous Social Text affair. Suspecting that the papers\npublished by literary theorists were often just intellectual-sounding\nnonsense, a physicist deliberately wrote a paper full of\nintellectual-sounding nonsense, and submitted it to a literary\ntheory journal, which published it.The best protection is always to be working on hard problems. \nWriting novels is hard. Reading novels isn't. \nHard means worry: if you're not worrying that\nsomething you're making will come out badly, or that you won't be \nable to understand something you're studying, then it isn't hard\nenough. There has to be suspense.Well, this seems a grim view of the world, you may think. What I'm\ntelling you is that you should worry? Yes, but it's not as bad as\nit sounds. It's exhilarating to overcome worries. You don't see\nfaces much happier than people winning gold medals. And you know\nwhy they're so happy? Relief.I'm not saying this is the only way to be happy. Just that some\nkinds of worry are not as bad as they sound.AmbitionIn practice, \"stay upwind\" reduces to \"work on hard problems.\" And \nyou can start today. I wish I'd grasped that in\nhigh school.Most people like to be good at what they do. In the so-called real \nworld this need is a powerful force. But high school students\nrarely benefit from it, because they're given a fake thing to do. \nWhen I was in high school, I let myself believe that my job was to \nbe a high school student. And so I let my need to be good at what \nI did be satisfied by merely doing well in school.If you'd asked me in high school what the difference was between\nhigh school kids and adults, I'd have said it was that adults had \nto earn a living. Wrong. It's that adults take responsibility for\nthemselves. Making a living is only a small part of it.\nFar more important is to take intellectual responsibility for oneself.If I had to go through high school again, I'd treat it like a day\njob. I don't mean that I'd slack in school. Working at something\nas a day job doesn't mean doing it badly. It means not being defined\nby it. I mean I wouldn't think of myself as a high school student,\njust as a musician with a day job as a waiter doesn't think of \nhimself as a waiter. [3] And when I wasn't working at my day job\nI'd start trying to do real work.When I ask people what they regret most about high school, they\nnearly all say the same thing: that they wasted so much time. If\nyou're wondering what you're doing now that you'll regret most\nlater, that's probably it. [4]Some people say this is inevitable — that high school students\naren't capable of getting anything done yet. But I don't think\nthis is true. And the proof is that you're bored. You probably\nweren't bored when you were eight. When you're eight it's called\n\"playing\" instead of \"hanging out,\" but it's the same thing. And\nwhen I was eight, I was rarely bored. Give me a back yard and a\nfew other kids and I could play all day.The reason this got stale in middle school and high school, I now\nrealize, is that I was ready for something else. Childhood was\ngetting old.I'm not saying you shouldn't hang out with your friends — that you\nshould all become humorless little robots who do nothing but work.\nHanging out with friends is like chocolate cake. You enjoy it more\nif you eat it occasionally than if you eat nothing but chocolate \ncake for every meal. No matter how much you like chocolate cake,\nyou'll be pretty queasy after the third meal of it. And that's \nwhat the malaise one feels in high school is: mental queasiness.\n[5]You may be thinking, we have to do more than get good grades. We\nhave to have extracurricular activities. But you know\nperfectly well how bogus most of these are. Collecting donations\nfor a charity is an admirable thing to do, but it's not hard.\nIt's not getting something done. What I mean by getting something\ndone is learning how to write well, or how to program computers,\nor what life was really like in preindustrial societies, or how to \ndraw the human face from life. This sort of thing rarely translates\ninto a line item on a college application.CorruptionIt's dangerous to design your life around getting into college, \nbecause the people you have to impress to get into college are not \na very discerning audience. At most colleges, it's not the professors\nwho decide whether you get in, but admissions officers, and they\nare nowhere near as smart. They're the NCOs of the intellectual\nworld. They can't tell how smart you are.\nThe mere existence of prep schools is proof of that.Few parents\nwould pay so much for their kids to go to a school that didn't \nimprove their admissions prospects. Prep schools openly say this\nis one of their aims. But what that means, if you stop to \nthink about it, is that they can\nhack the admissions process: that they can take the very same kid\nand make him seem a more appealing candidate than he would if he \nwent to the local public school. [6]Right now most of you feel your job in life is to be a promising\ncollege applicant. But that means you're designing your life to\nsatisfy a process so mindless that there's a whole industry devoted\nto subverting it. No wonder you become cynical. The malaise you\nfeel is the same that a producer of reality TV shows or a tobacco \nindustry executive feels. And you don't even get paid a lot.So what do you do? What you should not do is rebel. That's what\nI did, and it was a mistake. I didn't realize exactly what was \nhappening to us, but I smelled a major rat. And so I just gave up.\nObviously the world sucked, so why bother?When I discovered that one of our teachers was herself using Cliff's\nNotes, it seemed par for the course. Surely it meant nothing to\nget a good grade in such a class.In retrospect this was stupid. It was like someone getting fouled\nin a soccer game and saying, hey, you fouled me, that's against the\nrules, and walking off the field in indignation. Fouls happen. \nThe thing to do when you get fouled is not to lose your cool. Just\nkeep playing. By putting you in this situation, society has fouled you. Yes, \nas you suspect, a lot of the stuff you learn in your classes is \ncrap. And yes, as you suspect, the college admissions process is\nlargely a charade. But like many fouls, this one was unintentional.\n[7] So just keep playing.Rebellion is almost as stupid as obedience. In either case you let\nyourself be defined by what they tell you to do. The best plan, I\nthink, is to step onto an orthogonal vector. Don't just do what \nthey tell you, and don't just refuse to. Instead treat school as\na day job. As day jobs go, it's pretty sweet. You're done at 3\no'clock, and you can even work on your own stuff while you're there.CuriosityAnd what's your real job supposed to be? Unless you're Mozart, \nyour first task is to figure that out. What are the great things\nto work on? Where are the imaginative people? And most importantly,\nwhat are you interested in? The word \"aptitude\" is misleading,\nbecause it implies something innate. The most powerful sort of\naptitude is a consuming interest in some question, and such interests\nare often acquired tastes.A distorted version of this idea has filtered into popular culture\nunder the name \"passion.\" I recently saw an ad for waiters saying\nthey wanted people with a \"passion for service.\" The real thing \nis not something one could have for waiting on tables. And passion\nis a bad word for it. A better name would be curiosity.Kids are curious, but the curiosity I mean has a different shape from kid\ncuriosity. Kid curiosity is broad and shallow; they ask why at\nrandom about everything. In most adults this curiosity dries up\nentirely. It has to: you can't get anything done if you're always\nasking why about everything. But in ambitious adults, instead of\ndrying up, curiosity becomes narrow and deep. The mud flat morphs\ninto a well.Curiosity turns work into play. For Einstein, relativity wasn't a\nbook full of hard stuff he had to learn for an exam. It was a\nmystery he was trying to solve. So it probably felt like less work\nto him to invent it than it would seem to someone now to learn it\nin a class.One of the most dangerous illusions you get from school is the idea\nthat doing great things requires a lot of discipline. Most subjects\nare taught in such a boring way that it's only by discipline that\nyou can flog yourself through them. So I was surprised when, early\nin college, I read a quote by Wittgenstein saying that he had no \nself-discipline and had never been able to deny himself anything, \nnot even a cup of coffee.Now I know a number of people who do great work, and it's the same\nwith all of them. They have little discipline. They're all terrible\nprocrastinators and find it almost impossible to make themselves\ndo anything they're not interested in. One still hasn't sent out\nhis half of the thank-you notes from his wedding, four years ago.\nAnother has 26,000 emails in her inbox.I'm not saying you can get away with zero self-discipline. You \nprobably need about the amount you need to go running. I'm often \nreluctant to go running, but once I do, I enjoy it. And if I don't \nrun for several days, I feel ill. It's the same with people who \ndo great things. They know they'll feel bad if they don't work,\nand they have enough discipline to get themselves to their desks\nto start working. But once they get started, interest takes over,\nand discipline is no longer necessary.Do you think Shakespeare was gritting his teeth and diligently\ntrying to write Great Literature? Of course not. He was having\nfun. That's why he's so good.If you want to do good work, what you need is a great curiosity \nabout a promising question. The critical moment for Einstein\nwas when he looked at Maxwell's equations and said, what the hell\nis going on here?It can take years to zero in on a productive question, because it\ncan take years to figure out what a subject is really about. To\ntake an extreme example, consider math. Most people think they\nhate math, but the boring stuff you do in school under the name\n\"mathematics\" is not at all like what mathematicians do.The great mathematician G. H. Hardy said he didn't like math in \nhigh school either. He only took it up because he was better at\nit than the other students. Only later did he realize math was\ninteresting — only later did he start to ask questions instead of\nmerely answering them correctly.When a friend of mine used to grumble because he had to write a\npaper for school, his mother would tell him: find a way to make it\ninteresting. That's what you need to do: find a question that makes\nthe world interesting. People who do great things look at the same\nworld everyone else does, but notice some odd detail that's\ncompellingly mysterious.And not only in intellectual matters. Henry Ford's great question \nwas, why do cars have to be a luxury item? What would happen if\nyou treated them as a commodity? Franz Beckenbauer's was, in effect,\nwhy does everyone have to stay in his position? Why can't defenders\nscore goals too?NowIf it takes years to articulate great questions, what do you do now,\nat sixteen? Work toward finding one. Great questions don't appear\nsuddenly. They gradually congeal in your head. And what makes\nthem congeal is experience. So the way to find great questions is\nnot to search for them — not to wander about thinking, what great \ndiscovery shall I make? You can't answer that; if you could, you'd \nhave made it.The way to get a big idea to appear in your head is not to hunt for\nbig ideas, but to put in a lot of time on work that interests you,\nand in the process keep your mind open enough that a big idea can\ntake roost. Einstein, Ford, and Beckenbauer all used this recipe.\nThey all knew their work like a piano player knows the keys. So \nwhen something seemed amiss to them, they had the confidence to\nnotice it.Put in time how and on what? Just pick a project that seems\ninteresting: to master some chunk of material, or to make something,\nor to answer some question. Choose a project that will take less\nthan a month, and make it something you have the means to finish.\nDo something hard enough to stretch you, but only just, especially \nat first. If you're deciding between two projects, choose whichever \nseems most fun. If one blows up in your face, start another. Repeat\ntill, like an internal combustion engine, the process becomes \nself-sustaining, and each project generates the next one. (This\ncould take years.)It may be just as well not to do a project \"for school,\" if that\nwill restrict you or make it seem like work. Involve your friends\nif you want, but not too many, and only if they're not flakes. \nFriends offer moral support (few startups are started by one person),\nbut secrecy also has its advantages. There's something pleasing\nabout a secret project. And you can take more risks, because no \none will know if you fail.Don't worry if a project doesn't seem to be on the path to some\ngoal you're supposed to have. Paths can bend a lot more than you\nthink. So let the path grow out the project. The most important\nthing is to be excited about it, because it's by doing that you \nlearn.Don't disregard unseemly motivations. One of the most powerful is\nthe desire to be better than other people at something. Hardy said\nthat's what got him started, and I think the only unusual thing \nabout him is that he admitted it. Another powerful motivator is\nthe desire to do, or know, things you're not supposed to. Closely\nrelated is the desire to do something audacious. Sixteen year olds\naren't supposed to write novels. So if you try, anything you achieve\nis on the plus side of the ledger; if you fail utterly, you're doing\nno worse than expectations. [8]Beware of bad models. Especially when they excuse laziness. When \nI was in high school I used to write \"existentialist\" short stories\nlike ones I'd seen by famous writers. My stories didn't have a lot\nof plot, but they were very deep. And they were less work to write\nthan entertaining ones would have been. I should have known that\nwas a danger sign. And in fact I found my stories pretty boring; \nwhat excited me was the idea of writing serious, intellectual stuff\nlike the famous writers.Now I have enough experience to realize that those famous writers\nactually sucked. Plenty of famous people do; in the short term,\nthe quality of one's work is only a small component of fame. \nI should have been less worried about doing something\nthat seemed cool, and just done something I liked. That's the\nactual road to coolness anyway.A key ingredient in many projects, almost a project on its own, is \nto find good books. Most books are bad. Nearly all textbooks are\nbad. [9] So don't assume a subject is to be learned from whatever\nbook on it happens to be closest. You have to search actively for \nthe tiny number of good books.The important thing is to get out there and do stuff. Instead of\nwaiting to be taught, go out and learn.Your life doesn't have to be shaped by admissions officers. It \ncould be shaped by your own curiosity. It is for all ambitious \nadults. And you don't have to wait to start. In fact, you don't \nhave to wait to be an adult. There's no switch inside you that\nmagically flips when you turn a certain age or graduate from some\ninstitution. You start being an adult when you decide to take\nresponsibility for your life. You can do that at any age. [10]This may sound like bullshit. I'm just a minor, you may think, I\nhave no money, I have to live at home, I have to do what adults \ntell me all day long. Well, most adults labor under restrictions \njust as cumbersome, and they manage to get things done. If you\nthink it's restrictive being a kid, imagine having kids.The only real difference between adults and high school kids is\nthat adults realize they need to get things done, and high school\nkids don't. That realization hits most people around 23. But I'm\nletting you in on the secret early. So get to work. Maybe you can\nbe the first generation whose greatest regret from high school isn't\nhow much time you wasted.\nNotes[1] A doctor friend warns that even this can give an inaccurate \npicture. \"Who knew how much time it would take up, how little\nautonomy one would have for endless years of training, and how\nunbelievably annoying it is to carry a beeper?\"[2] His best bet would probably be to become dictator and intimidate\nthe NBA into letting him play. So far the closest anyone has come\nis Secretary of Labor.[3] A day job is one you take to pay the bills so you can do what\nyou really want, like play in a band, or invent relativity.Treating high school as a day job might actually make it easier for\nsome students to get good grades. If you treat your classes\nas a game, you won't be demoralized if they seem pointless.However bad your classes, you need to get good grades in them to \nget into a decent college. And that is worth doing, because\nuniversities are where a lot of the clumps of smart people are these\ndays.[4] The second biggest regret was caring so much about unimportant\nthings. And especially about what other people thought of them.I think what they really mean, in the latter case, is caring what\nrandom people thought of them. Adults care just as much what other\npeople think, but they get to be more selective about the other\npeople.I have about thirty friends whose opinions I care about,\nand the opinion of the rest of the world barely affects me. The\nproblem in high school is that your peers are chosen for you by \naccidents of age and geography, rather than by you based on respect\nfor their judgement.[5] The key to wasting time is distraction. Without distractions\nit's too obvious to your brain that you're not doing anything with\nit, and you start to feel uncomfortable. If you want to measure \nhow dependent you've become on distractions, try this experiment:\nset aside a chunk of time on a weekend and sit alone and think.\nYou can have a notebook to write your thoughts down in, but nothing\nelse: no friends, TV, music, phone, IM, email, Web, games, books, \nnewspapers, or magazines. Within an hour most people will feel a \nstrong craving for distraction.[6] I don't mean to imply that the only function of prep schools\nis to trick admissions officers. They also generally provide a \nbetter education. But try this thought experiment: suppose prep\nschools supplied the same superior education but had a tiny (.001)\nnegative effect on college admissions. How many parents would still\nsend their kids to them?It might also be argued that kids who went to prep schools, because\nthey've learned more, are better college candidates. But\nthis seems empirically false. What you learn in even the best high\nschool is rounding error compared to what you learn in college. \nPublic school kids arrive at college with a slight disadvantage, \nbut they start to pull ahead in the sophomore year.(I'm not saying public school kids are smarter than preppies, just\nthat they are within any given college. That follows necessarily\nif you agree prep schools improve kids' admissions prospects.)[7] Why does society foul you? Indifference, mainly. There are\nsimply no outside forces pushing high school to be good. The air\ntraffic control system works because planes would crash otherwise.\nBusinesses have to deliver because otherwise competitors would take\ntheir customers. But no planes crash if your school sucks, and it\nhas no competitors. High school isn't evil; it's random; but random\nis pretty bad.[8] And then of course there is money. It's not a big factor in\nhigh school, because you can't do much that anyone wants. But a\nlot of great things were created mainly to make money. Samuel\nJohnson said \"no man but a blockhead ever wrote except for money.\"\n(Many hope he was exaggerating.)[9] Even college textbooks are bad. When you get to college,\nyou'll find that (with a few stellar exceptions) the textbooks are\nnot written by the leading scholars in the field they describe.\nWriting college textbooks is unpleasant work, done mostly by people\nwho need the money. It's unpleasant because the publishers exert\nso much control, and there are few things worse than close supervision\nby someone who doesn't understand what you're doing. This phenomenon\nis apparently \neven worse in the production of high school textbooks.[10] Your teachers are always telling you to behave like adults.\nI wonder if they'd like it if you did. You may be loud and\ndisorganized, but you're very docile compared to adults. If you\nactually started acting like adults, it would be just as if a bunch\nof adults had been transposed into your bodies. Imagine the reaction\nof an FBI agent or taxi driver or reporter to being told they had\nto ask permission to go the bathroom, and only one person could go\nat a time. To say nothing of the things you're taught. If a bunch\nof actual adults suddenly found themselves trapped in high school,\nthe first thing they'd do is form a union and renegotiate all the\nrules with the administration.Thanks to Ingrid Bassett, Trevor Blackwell, \nRich Draves, Dan Giffin, Sarah\nHarlin, Jessica Livingston, Jackie McDonough, Robert Morris, Mark Nitzberg, Lisa \nRandall, and Aaron Swartz for reading drafts of this, and to many\nothers for talking to me about high school." }, { "path": "data/PaulGrahamEssays/hubs.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nOctober 2011If you look at a list of US cities sorted by population, the number\nof successful startups per capita varies by orders of magnitude.\nSomehow it's as if most places were sprayed with startupicide.I wondered about this for years. I could see the average town was\nlike a roach motel for startup ambitions: smart, ambitious people\nwent in, but no startups came out. But I was never able to figure\nout exactly what happened inside the motel—exactly what was\nkilling all the potential startups.\n[1]A couple weeks ago I finally figured it out. I was framing the\nquestion wrong. The problem is not that most towns kill startups.\nIt's that death is the default for startups,\nand most towns don't save them. Instead of thinking of most places\nas being sprayed with startupicide, it's more accurate to think of\nstartups as all being poisoned, and a few places being sprayed with\nthe antidote.Startups in other places are just doing what startups naturally do:\nfail. The real question is, what's saving startups in places\nlike Silicon Valley?\n[2]EnvironmentI think there are two components to the antidote: being in a place\nwhere startups are the cool thing to do, and chance meetings with\npeople who can help you. And what drives them both is the number\nof startup people around you.The first component is particularly helpful in the first stage of\na startup's life, when you go from merely having an interest in\nstarting a company to actually doing it. It's quite a leap to start\na startup. It's an unusual thing to do. But in Silicon Valley it\nseems normal.\n[3]In most places, if you start a startup, people treat you as if\nyou're unemployed. People in the Valley aren't automatically\nimpressed with you just because you're starting a company, but they\npay attention. Anyone who's been here any amount of time knows not\nto default to skepticism, no matter how inexperienced you seem or\nhow unpromising your idea sounds at first, because they've all seen\ninexperienced founders with unpromising sounding ideas who a few\nyears later were billionaires.Having people around you care about what you're doing is an\nextraordinarily powerful force. Even the\nmost willful people are susceptible to it. About a year after we\nstarted Y Combinator I said something to a partner at a well known\nVC firm that gave him the (mistaken) impression I was considering\nstarting another startup. He responded so eagerly that for about\nhalf a second I found myself considering doing it.In most other cities, the prospect of starting a startup just doesn't\nseem real. In the Valley it's not only real but fashionable. That\nno doubt causes a lot of people to start startups who shouldn't.\nBut I think that's ok. Few people are suited to running a startup,\nand it's very hard to predict beforehand which are (as I know all\ntoo well from being in the business of trying to predict beforehand),\nso lots of people starting startups who shouldn't is probably the\noptimal state of affairs. As long as you're at a point in your\nlife when you can bear the risk of failure, the best way to find\nout if you're suited to running a startup is to try\nit.ChanceThe second component of the antidote is chance meetings with people\nwho can help you. This force works in both phases: both in the\ntransition from the desire to start a startup to starting one, and\nthe transition from starting a company to succeeding. The power\nof chance meetings is more variable than people around you caring\nabout startups, which is like a sort of background radiation that\naffects everyone equally, but at its strongest it is far stronger.Chance meetings produce miracles to compensate for the disasters\nthat characteristically befall startups. In the Valley, terrible\nthings happen to startups all the time, just like they do to startups\neverywhere. The reason startups are more likely to make it here\nis that great things happen to them too. In the Valley, lightning\nhas a sign bit.For example, you start a site for college students and you decide\nto move to the Valley for the summer to work on it. And then on a\nrandom suburban street in Palo Alto you happen to run into Sean\nParker, who understands the domain really well because he started\na similar startup himself, and also knows all the investors. And\nmoreover has advanced views, for 2004, on founders retaining control of their companies.You can't say precisely what the miracle will be, or even for sure\nthat one will happen. The best one can say is: if you're in a\nstartup hub, unexpected good things will probably happen to you,\nespecially if you deserve them.I bet this is true even for startups we fund. Even with us working\nto make things happen for them on purpose rather than by accident,\nthe frequency of helpful chance meetings in the Valley is so high\nthat it's still a significant increment on what we can deliver.Chance meetings play a role like the role relaxation plays in having\nideas. Most people have had the experience of working hard on some\nproblem, not being able to solve it, giving up and going to bed,\nand then thinking of the answer in the shower in the morning. What\nmakes the answer appear is letting your thoughts drift a bit—and thus drift off the wrong\npath you'd been pursuing last night and onto the right one adjacent\nto it.Chance meetings let your acquaintance drift in the same way taking\na shower lets your thoughts drift. The critical thing in both cases\nis that they drift just the right amount. The meeting between Larry\nPage and Sergey Brin was a good example. They let their acquaintance\ndrift, but only a little; they were both meeting someone they had\na lot in common with.For Larry Page the most important component of the antidote was\nSergey Brin, and vice versa. The antidote is \npeople. It's not the\nphysical infrastructure of Silicon Valley that makes it work, or\nthe weather, or anything like that. Those helped get it started,\nbut now that the reaction is self-sustaining what drives it is the\npeople.Many observers have noticed that one of the most distinctive things\nabout startup hubs is the degree to which people help one another\nout, with no expectation of getting anything in return. I'm not\nsure why this is so. Perhaps it's because startups are less of a\nzero sum game than most types of business; they are rarely killed\nby competitors. Or perhaps it's because so many startup founders\nhave backgrounds in the sciences, where collaboration is encouraged.A large part of YC's function is to accelerate that process. We're\na sort of Valley within the Valley, where the density of people\nworking on startups and their willingness to help one another are\nboth artificially amplified.NumbersBoth components of the antidote—an environment that encourages\nstartups, and chance meetings with people who help you—are\ndriven by the same underlying cause: the number of startup people\naround you. To make a startup hub, you need a lot of people\ninterested in startups.There are three reasons. The first, obviously, is that if you don't\nhave enough density, the chance meetings don't happen.\n[4]\nThe second is that different startups need such different things, so\nyou need a lot of people to supply each startup with what they need\nmost. Sean Parker was exactly what Facebook needed in 2004. Another\nstartup might have needed a database guy, or someone with connections\nin the movie business.This is one of the reasons we fund such a large number of companies,\nincidentally. The bigger the community, the greater the chance it\nwill contain the person who has that one thing you need most.The third reason you need a lot of people to make a startup hub is\nthat once you have enough people interested in the same problem,\nthey start to set the social norms. And it is a particularly\nvaluable thing when the atmosphere around you encourages you to do\nsomething that would otherwise seem too ambitious. In most places\nthe atmosphere pulls you back toward the mean.I flew into the Bay Area a few days ago. I notice this every time\nI fly over the Valley: somehow you can sense something is going on. \nObviously you can sense prosperity in how well kept a\nplace looks. But there are different kinds of prosperity. Silicon\nValley doesn't look like Boston, or New York, or LA, or DC. I tried\nasking myself what word I'd use to describe the feeling the Valley\nradiated, and the word that came to mind was optimism.Notes[1]\nI'm not saying it's impossible to succeed in a city with few\nother startups, just harder. If you're sufficiently good at\ngenerating your own morale, you can survive without external\nencouragement. Wufoo was based in Tampa and they succeeded. But\nthe Wufoos are exceptionally disciplined.[2]\nIncidentally, this phenomenon is not limited to startups. Most\nunusual ambitions fail, unless the person who has them manages to\nfind the right sort of community.[3]\nStarting a company is common, but starting a startup is rare.\nI've talked about the distinction between the two elsewhere, but\nessentially a startup is a new business designed for scale. Most\nnew businesses are service businesses and except in rare cases those\ndon't scale.[4]\nAs I was writing this, I had a demonstration of the density of\nstartup people in the Valley. Jessica and I bicycled to University\nAve in Palo Alto to have lunch at the fabulous Oren's Hummus. As\nwe walked in, we met Charlie Cheever sitting near the door. Selina\nTobaccowala stopped to say hello on her way out. Then Josh Wilson\ncame in to pick up a take out order. After lunch we went to get\nfrozen yogurt. On the way we met Rajat Suri. When we got to the\nyogurt place, we found Dave Shen there, and as we walked out we ran\ninto Yuri Sagalov. We walked with him for a block or so and we ran\ninto Muzzammil Zaveri, and then a block later we met Aydin Senkut.\nThis is everyday life in Palo Alto. I wasn't trying to meet people;\nI was just having lunch. And I'm sure for every startup founder\nor investor I saw that I knew, there were 5 more I didn't. If Ron\nConway had been with us he would have met 30 people he knew.Thanks to Sam Altman, Paul Buchheit, Jessica Livingston, and\nHarj Taggar for reading drafts of this." }, { "path": "data/PaulGrahamEssays/hundred.txt", "content": "April 2003(This essay is derived from a keynote talk at PyCon 2003.)It's hard to predict what\nlife will be like in a hundred years. There are only a few\nthings we can say with certainty. We know that everyone will\ndrive flying cars,\nthat zoning laws will be relaxed to allow buildings\nhundreds of stories tall, that it will be dark most of the\ntime, and that women will all be trained in the martial arts. \nHere I want to zoom in on one detail of this\npicture. What kind of programming language will they use to\nwrite the software controlling those flying cars?This is worth thinking about not so\nmuch because we'll actually get to use these languages as because,\nif we're lucky, we'll use languages on the path from this\npoint to that.I think that, like species, languages will form evolutionary trees,\nwith dead-ends branching off all over. We can see this\nhappening already.\nCobol, for all its sometime popularity, does not seem to have any\nintellectual descendants. It is an evolutionary dead-end-- a\nNeanderthal language.I predict a similar fate for Java. People\nsometimes send me mail saying, \"How can you say that Java\nwon't turn out to be a successful language? It's already\na successful language.\" And I admit that it is, if you\nmeasure success by shelf space taken up by books on it\n(particularly individual books on it), or by\nthe number of undergrads who believe they have to\nlearn it to get a job. When I say Java won't\nturn out to be a successful language, I mean something more\nspecific: that Java\nwill turn out to be an evolutionary dead-end, like Cobol.This is just a guess. I may be wrong. My point here is not to dis Java,\nbut to raise the issue of evolutionary\ntrees and get people asking, where on the tree is language X?\nThe reason to ask this question isn't just so that\nour ghosts can say, in a\nhundred years, I told you so. It's because staying close to \nthe main branches is a useful heuristic for finding languages that will\nbe good to program in now.At any given time, you're probably happiest on\nthe main branches of an evolutionary tree.\nEven when there were still plenty of Neanderthals, \nit must have sucked to be one. The\nCro-Magnons would have been constantly coming over and\nbeating you up and stealing your food.The reason I want to\nknow what languages will be like in a hundred years is so that\nI know what branch of the tree to bet on now.The evolution of languages differs from the evolution of species\nbecause branches can converge. The Fortran branch, for example,\nseems to be merging with the descendants\nof Algol. In theory this is possible for species too, but it's\nnot likely to have happened to any bigger than a cell.Convergence\nis more likely for languages partly because the space of\npossibilities is smaller, and partly because mutations\nare not random. Language designers deliberately incorporate\nideas from other languages.It's especially useful for language designers to think\nabout where the evolution of programming languages is likely\nto lead, because they can steer accordingly. \nIn that case, \"stay on a main branch\" becomes more than a\nway to choose a good language.\nIt becomes a heuristic for making the right decisions about\nlanguage design.Any programming language can be divided into\ntwo parts: some set of fundamental operators that play the role\nof axioms, and the rest of the language, which could in principle\nbe written in terms of these fundamental operators.I think the fundamental operators are the most important factor in a\nlanguage's long term survival. The rest you can change. It's\nlike the rule that in buying a house you should consider\nlocation first of all. Everything else you can fix later, but you\ncan't fix the location.I think it's important not just that the axioms be well chosen, \nbut that there be few of them. Mathematicians have always felt \nthis way about axioms-- the fewer, the better-- and I think they're\nonto something.At the very least, it has to be a useful exercise to look closely\nat the core of a language to see if there are any axioms that\ncould be weeded out. I've found in my long career as a slob that\ncruft breeds cruft, and I've seen this happen in software as\nwell as under beds and in the corners of rooms.I have a hunch that\nthe main branches of the evolutionary tree pass through the languages\nthat have the smallest, cleanest cores.\nThe more of a language you can write in itself,\nthe better.Of course, I'm making a big assumption in even asking what\nprogramming languages will be like in a hundred years.\nWill we even be writing programs in a hundred years? Won't\nwe just tell computers what we want them to do?There hasn't been a lot of progress in that department\nso far.\nMy guess is that a hundred years from now people will\nstill tell computers what to do using programs we would recognize\nas such. There may be tasks that we\nsolve now by writing programs and which in a hundred years\nyou won't have to write programs to solve, but I think\nthere will still be a good deal of\nprogramming of the type that we do today.It may seem presumptuous to think anyone can predict what\nany technology will look like in a hundred years. But\nremember that we already have almost fifty years of history behind us.\nLooking forward a hundred years is a graspable idea\nwhen we consider how slowly languages have evolved in the\npast fifty.Languages evolve slowly because they're not really technologies.\nLanguages are notation. A program is a formal description of \nthe problem you want a computer to solve for you. So the rate\nof evolution in programming languages is more like the\nrate of evolution in mathematical notation than, say,\ntransportation or communications.\nMathematical notation does evolve, but not with the giant\nleaps you see in technology.Whatever computers are made of in a hundred years, it seems \nsafe to predict they will be much faster than\nthey are now. If Moore's Law continues to put out, they will be 74\nquintillion (73,786,976,294,838,206,464) times faster. That's kind of\nhard to imagine. And indeed, the most likely prediction in the\nspeed department may be that Moore's Law will stop working.\nAnything that is supposed to double every eighteen months seems\nlikely to run up against some kind of fundamental limit eventually.\nBut I have no trouble believing that computers will be very much\nfaster. Even if they only end up being a paltry million\ntimes faster, that should change the ground rules for programming\nlanguages substantially. Among other things, there\nwill be more room for what\nwould now be considered slow languages, meaning languages\nthat don't yield very efficient code.And yet some applications will still demand speed.\nSome of the problems we want to solve with\ncomputers are created by computers; for example, the\nrate at which you have to process video images depends\non the rate at which another computer can\ngenerate them. And there is another class of problems\nwhich inherently have an unlimited capacity to soak up cycles:\nimage rendering, cryptography, simulations.If some applications can be increasingly inefficient while\nothers continue to demand all the speed the hardware can\ndeliver, faster computers will mean that languages have\nto cover an ever wider range of efficiencies. We've seen\nthis happening already. Current implementations of some\npopular new languages are shockingly wasteful by the\nstandards of previous decades.This isn't just something that happens with programming\nlanguages. It's a general historical trend. As technologies improve,\neach generation can do things that the previous generation\nwould have considered wasteful. People thirty years ago would\nbe astonished at how casually we make long distance phone calls.\nPeople a hundred years ago would be even more astonished that \na package would one day travel from Boston to New York via Memphis.I can already tell you what's going to happen to all those extra\ncycles that faster hardware is going to give us in the \nnext hundred years. They're nearly all going to be wasted.I learned to program when computer power was scarce.\nI can remember taking all the spaces out of my Basic programs\nso they would fit into the memory of a 4K TRS-80. The\nthought of all this stupendously inefficient software\nburning up cycles doing the same thing over and over seems\nkind of gross to me. But I think my intuitions here are wrong. I'm\nlike someone who grew up poor, and can't bear to spend money\neven for something important, like going to the doctor.Some kinds of waste really are disgusting. SUVs, for example, would\narguably be gross even if they ran on a fuel which would never\nrun out and generated no pollution. SUVs are gross because they're\nthe solution to a gross problem. (How to make minivans look more\nmasculine.)\nBut not all waste is bad. Now that we have the infrastructure\nto support it, counting the minutes of your long-distance\ncalls starts to seem niggling. If you have the\nresources, it's more elegant to think of all phone calls as\none kind of thing, no matter where the other person is.There's good waste, and bad waste. I'm interested\nin good waste-- the kind where, by spending more, we can get \nsimpler designs. How will we take advantage of the opportunities\nto waste cycles that we'll get from new, faster hardware?The desire for speed is so deeply engrained in us, with \nour puny computers, that it will take a conscious effort\nto overcome it. In language design, we should be consciously seeking out\nsituations where we can trade efficiency for even the\nsmallest increase in convenience.Most data structures exist because of speed. For example,\nmany languages today have both strings and lists. Semantically, strings\nare more or less a subset of lists in which the elements are\ncharacters. So why do you need a separate data type?\nYou don't, really. Strings only\nexist for efficiency. But it's lame to clutter up the semantics\nof the language with hacks to make programs run faster.\nHaving strings in a language seems to be a case of\npremature optimization.If we think of the core of a language as a set of axioms, \nsurely it's gross to have additional axioms that add no expressive\npower, simply for the sake of efficiency. Efficiency is\nimportant, but I don't think that's the right way to get it.The right way to solve that problem, I think, is to separate\nthe meaning of a program from the implementation details. \nInstead of having both lists and strings, have just lists,\nwith some way to give the compiler optimization advice that \nwill allow it to lay out strings as contiguous bytes if\nnecessary.Since speed doesn't matter in most of a program, you won't\nordinarily need to bother with\nthis sort of micromanagement.\nThis will be more and more true as computers get faster.Saying less about implementation should also make programs\nmore flexible.\nSpecifications change while a program is being written, and this is not\nonly inevitable, but desirable.The word \"essay\" comes\nfrom the French verb \"essayer\", which means \"to try\".\nAn essay, in the original sense, is something you\nwrite to try to figure something out. This happens in\nsoftware too. I think some of the best programs were essays,\nin the sense that the authors didn't know when they started\nexactly what they were trying to write.Lisp hackers already know about the value of being flexible\nwith data structures. We tend to write the first version of\na program so that it does everything with lists. These\ninitial versions can be so shockingly inefficient that it\ntakes a conscious effort not to think about what they're\ndoing, just as, for me at least, eating a steak requires a\nconscious effort not to think where it came from.What programmers in a hundred years will be looking for, most of\nall, is a language where you can throw together an unbelievably\ninefficient version 1 of a program with the least possible\neffort. At least, that's how we'd describe it in present-day\nterms. What they'll say is that they want a language that's\neasy to program in.Inefficient software isn't gross. What's gross is a language\nthat makes programmers do needless work. Wasting programmer time\nis the true inefficiency, not wasting machine time. This will\nbecome ever more clear as computers get faster.I think getting rid of strings is already something we\ncould bear to think about. We did it in Arc, and it seems\nto be a win; some operations that would be awkward to\ndescribe as regular expressions can be described\neasily as recursive functions.How far will this flattening of data structures go? I can think\nof possibilities that shock even me, with my conscientiously broadened\nmind. Will we get rid of arrays, for example? After all, they're\njust a subset of hash tables where the keys are vectors of\nintegers. Will we replace hash tables themselves with lists?There are more shocking prospects even than that. The Lisp\nthat McCarthy described in 1960, for example, didn't\nhave numbers. Logically, you don't need to have a separate notion\nof numbers, because you can represent them as lists: the integer\nn could be represented as a list of n elements. You can do math this\nway. It's just unbearably inefficient.No one actually proposed implementing numbers as lists in\npractice. In fact, McCarthy's 1960 paper was not, at the time,\nintended to be implemented at all. It was a theoretical exercise,\nan attempt to create a more elegant alternative to the Turing\nMachine. When someone did, unexpectedly, take this paper and\ntranslate it into a working Lisp interpreter, numbers certainly\nweren't represented as lists; they were represented in binary,\nas in every other language.Could a programming language go so far as to get rid of numbers\nas a fundamental data type? I ask this not so much as a serious\nquestion as as a way to play chicken with the future. It's like\nthe hypothetical case of an irresistible force meeting an \nimmovable object-- here, an unimaginably inefficient\nimplementation meeting unimaginably great resources.\nI don't see why not. The future is pretty long. If there's\nsomething we can do to decrease the number of axioms in the core\nlanguage, that would seem to be the side to bet on as t approaches\ninfinity. If the idea still seems unbearable in a hundred years,\nmaybe it won't in a thousand.Just to be clear about this, I'm not proposing that all numerical\ncalculations would actually be carried out using lists. I'm proposing\nthat the core language, prior to any additional notations about\nimplementation, be defined this way. In practice any program\nthat wanted to do any amount of math would probably represent\nnumbers in binary, but this would be an optimization, not part of\nthe core language semantics.Another way to burn up cycles is to have many layers of\nsoftware between the application and the hardware. This too is\na trend we see happening already: many recent languages are\ncompiled into byte code. Bill Woods once told me that,\nas a rule of thumb, each layer of interpretation costs a\nfactor of 10 in speed. This extra cost buys you flexibility.The very first version of Arc was an extreme case of this sort\nof multi-level slowness, with corresponding benefits. It\nwas a classic \"metacircular\" interpreter written\non top of Common Lisp, with a definite family resemblance\nto the eval function defined in McCarthy's original Lisp paper.\nThe whole thing was only a couple hundred lines of\ncode, so it was very easy to understand and change. The \nCommon Lisp we used, CLisp, itself runs on top\nof a byte code interpreter. So here we had two levels of\ninterpretation, one of them (the top one) shockingly inefficient,\nand the language was usable. Barely usable, I admit, but\nusable.Writing software as multiple layers is a powerful technique\neven within applications. Bottom-up programming means writing\na program as a series of layers, each of which serves as a\nlanguage for the one above. This approach tends to yield\nsmaller, more flexible programs. It's also the best route to \nthat holy grail, reusability. A language is by definition\nreusable. The more\nof your application you can push down into a language for writing\nthat type of application, the more of your software will be \nreusable.Somehow the idea of reusability got attached\nto object-oriented programming in the 1980s, and no amount of\nevidence to the contrary seems to be able to shake it free. But\nalthough some object-oriented software is reusable, what makes\nit reusable is its bottom-upness, not its object-orientedness.\nConsider libraries: they're reusable because they're language,\nwhether they're written in an object-oriented style or not.I don't predict the demise of object-oriented programming, by the\nway. Though I don't think it has much to offer good programmers,\nexcept in certain specialized domains, it is irresistible to \nlarge organizations. Object-oriented programming\noffers a sustainable way to write spaghetti code. It lets you accrete\nprograms as a series of patches.\n\nLarge organizations\nalways tend to develop software this way, and I expect this\nto be as true in a hundred years as it is today.\nAs long as we're talking about the future, we had better\ntalk about parallel computation, because that's where this \nidea seems to live. That is, no matter when you're talking, parallel\ncomputation seems to be something that is going to happen\nin the future.Will the future ever catch up with it? People have been\ntalking about parallel computation as something imminent \nfor at least 20\nyears, and it hasn't affected programming practice much so far.\nOr hasn't it? Already\nchip designers have to think about it, and so must\npeople trying to write systems software on multi-cpu computers.The real question is, how far up the ladder of abstraction will\nparallelism go?\nIn a hundred years will it affect even application programmers? Or\nwill it be something that compiler writers think about, but\nwhich is usually invisible in the source code of applications?One thing that does seem likely is that most opportunities for\nparallelism will be wasted. This is a special case of my more \ngeneral prediction that most of the extra computer power we're\ngiven will go to waste. I expect that, as with the stupendous\nspeed of the underlying hardware, parallelism will be something\nthat is available if you ask for it explicitly, but ordinarily\nnot used. This implies that the kind of parallelism we have in\na hundred years will not, except in special applications, be\nmassive parallelism. I expect for\nordinary programmers it will be more like being able to fork off\nprocesses that all end up running in parallel.And this will, like asking for specific implementations of data\nstructures, be something that you do fairly late in the life of a\nprogram, when you try to optimize it. Version 1s will ordinarily\nignore any advantages to be got from parallel computation, just\nas they will ignore advantages to be got from specific representations\nof data.Except in special kinds of applications, parallelism won't\npervade the programs that are written in a hundred years. It would be\npremature optimization if it did.How many programming languages will there\nbe in a hundred years? There seem to be a huge number of new\nprogramming languages lately. Part of the reason is that\nfaster hardware has allowed programmers to make different\ntradeoffs between speed and convenience, depending on the\napplication. If this is a real trend, the hardware we'll \nhave in a hundred years should only increase it.And yet there may be only a few widely-used languages in a\nhundred years. Part of the reason I say this\nis optimism: it seems that, if you did a really good job,\nyou could make a language that was ideal for writing a \nslow version 1, and yet with the right optimization advice\nto the compiler, would also yield very fast code when necessary.\nSo, since I'm optimistic, I'm going to predict that despite\nthe huge gap they'll have between acceptable and maximal\nefficiency, programmers in a hundred years will have languages \nthat can span most of it.As this gap widens, profilers will become increasingly important.\nLittle attention is paid to profiling now. Many people still\nseem to believe that the way to get fast applications is to\nwrite compilers that generate fast code. As the gap between \nacceptable and maximal performance widens, it will become\nincreasingly clear that the way to get fast applications is \nto have a good guide from one to the other.When I say there may only be a few languages, I'm not including\ndomain-specific \"little languages\". I think such embedded languages\nare a great idea, and I expect them to proliferate. But I expect\nthem to be written as thin enough skins that users can see\nthe general-purpose language underneath.Who will design the languages of the future? One of the most exciting\ntrends in the last ten years has been the rise of open-source \nlanguages like Perl, Python, and Ruby.\nLanguage design is being taken over by hackers. The results\nso far are messy, but encouraging. There are some stunningly \nnovel ideas in Perl, for example. Many are stunningly bad, but\nthat's always true of ambitious efforts. At its current rate\nof mutation, God knows what Perl might evolve into in a hundred\nyears.It's not true that those who can't do, teach (some of the best\nhackers I know are professors), but it is true that there are a\nlot of things that those who teach can't do. Research imposes\nconstraining caste restrictions. In any academic\nfield there are topics that are ok to work on and others that\naren't. Unfortunately the distinction between acceptable and\nforbidden topics is usually based on how intellectual\nthe work sounds when described in research papers, rather than\nhow important it is for getting good results. The extreme case\nis probably literature; people studying literature rarely \nsay anything that would be of the slightest use to those\nproducing it.Though the situation is better in the sciences,\nthe overlap between the kind of work you're allowed to do and the\nkind of work that yields good languages is distressingly small.\n(Olin Shivers has grumbled eloquently\nabout this.) For example, types seem to be an inexhaustible source\nof research papers, despite the fact that static typing\nseems to preclude true macros-- without which, in my opinion, no\nlanguage is worth using.The trend is not merely toward languages being developed\nas open-source projects rather than \"research\", but toward\nlanguages being designed by the application programmers who need\nto use them, rather than by compiler writers. This seems a good\ntrend and I expect it to continue.\nUnlike physics in a hundred years, which is almost necessarily\nimpossible to predict, I think it may be possible in principle\nto design a language now that would appeal to users in a hundred\nyears.One way to design a language is to just write down the program\nyou'd like to be able to write, regardless of whether there \nis a compiler that can translate it or hardware that can run it.\nWhen you do this you can assume unlimited resources. It seems\nlike we ought to be able to imagine unlimited resources as well\ntoday as in a hundred years.What program would one like to write? Whatever is least work.\nExcept not quite: whatever would be least work if your ideas about\nprogramming weren't already influenced by the languages you're \ncurrently used to. Such influence can be so pervasive that \nit takes a great effort to overcome it. You'd think it would\nbe obvious to creatures as lazy as us how to express a program\nwith the least effort. In fact, our ideas about what's possible\ntend to be so limited by whatever language we think in that\neasier formulations of programs seem very surprising. They're\nsomething you have to discover, not something you naturally\nsink into.One helpful trick here\nis to use the length of the program as an approximation for\nhow much work it is to write. Not the length in characters,\nof course, but the length in distinct syntactic elements-- basically,\nthe size of the parse tree. It may not be quite true that\nthe shortest program is the least work to write, but it's\nclose enough that you're better off aiming for the solid\ntarget of brevity than the fuzzy, nearby one of least work.\nThen the algorithm for language design becomes: look at a program\nand ask, is there any way to write this that's shorter?In practice, writing programs in an imaginary hundred-year\nlanguage will work to varying degrees depending\non how close you are to the core. Sort routines you can\nwrite now. But it would be\nhard to predict now what kinds of libraries might be needed in\na hundred years. Presumably many libraries will be for domains that\ndon't even exist yet. If SETI@home works, for example, we'll \nneed libraries for communicating with aliens. Unless of course\nthey are sufficiently advanced that they already communicate\nin XML.At the other extreme, I think you might be able to design the\ncore language today. In fact, some might argue that it was already\nmostly designed in 1958.If the hundred year language were available today, would we\nwant to program in it? One way to answer this question is to\nlook back. If present-day programming languages had been available\nin 1960, would anyone have wanted to use them?In some ways, the answer is no. Languages today assume\ninfrastructure that didn't exist in 1960. For example, a language\nin which indentation is significant, like Python, would not\nwork very well on printer terminals. But putting such problems\naside-- assuming, for example, that programs were all just\nwritten on paper-- would programmers of the 1960s have liked\nwriting programs in the languages we use now?I think so.\nSome of the less imaginative ones,\nwho had artifacts of early languages built into their ideas of \nwhat a program was, might have had trouble. (How can you manipulate\ndata without doing pointer arithmetic? How can you implement \nflow charts without gotos?) But I think the smartest programmers\nwould have had no trouble making the most of present-day\nlanguages, if they'd had them.If we had the hundred-year language now, it would at least make a\ngreat pseudocode. What about using it to write software? \nSince the hundred-year language\nwill need to generate fast code for some applications, presumably\nit could generate code efficient enough to run acceptably well\non our hardware. We might have to give more optimization advice\nthan users in a hundred years, but it still might be a net win.Now we have two ideas that, if you combine them, suggest interesting\npossibilities: (1) the hundred-year language could, in principle, be\ndesigned today, and (2) such a language, if it existed, might be good to\nprogram in today. When you see these ideas laid out like that,\nit's hard not to think, why not try writing the hundred-year language\nnow?When you're working on language design, I think it is good to\nhave such a target and to keep it consciously in mind. When you\nlearn to drive, one of the principles they teach you is to\nalign the car not by lining up the hood with the stripes painted\non the road, but by aiming at some point in the distance. Even\nif all you care about is what happens in the next ten feet, this\nis the right answer. I\nthink we can and should do the same thing with programming languages.\nNotesI believe Lisp Machine Lisp was the first language to embody\nthe principle that declarations (except those of dynamic variables)\nwere merely optimization advice,\nand would not change the meaning of a correct program. Common Lisp\nseems to have been the first to state this explicitly.Thanks to Trevor Blackwell, Robert Morris, and Dan Giffin for\nreading drafts of this, and to Guido van Rossum, Jeremy Hylton, and the\nrest of the Python crew for inviting me to speak at PyCon." }, { "path": "data/PaulGrahamEssays/hw.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nOctober 2012One advantage of Y Combinator's early, broad focus is that we\nsee trends before most other people. And one of the most conspicuous\ntrends in the last batch was the large number of hardware startups.\nOut of 84 companies, 7 were making hardware. On the whole\nthey've done better than the companies that weren't.They've faced resistance from investors of course. Investors have\na deep-seated bias against hardware. But investors' opinions are\na trailing indicator. The best founders are better at seeing the\nfuture than the best investors, because the best founders are making\nit.There is no one single force driving this trend. Hardware does\nwell on crowdfunding sites. The spread of tablets makes it\npossible to build new things controlled\nby and even incorporating\nthem. Electric motors\n have improved.\nWireless connectivity of various types can now be taken for granted.\nIt's getting more straightforward to get things manufactured.\nArduinos, 3D printing, laser cutters, and more accessible CNC milling are making hardware easier to prototype.\nRetailers are less of a bottleneck as customers increasingly buy\nonline.One question I can answer is why hardware is suddenly cool.\nIt always was cool.\nPhysical things are great. They just haven't\nbeen as great a way to start a rapidly growing business\nas software. But that rule may not be permanent. It's not even\nthat old; it only dates from about 1990. Maybe the advantage\nof software will turn out to have been temporary. Hackers love to\nbuild hardware, and customers love to buy it. So if the ease of\nshipping hardware even approached the ease of shipping software,\nwe'd see a lot more hardware startups.It wouldn't be the first time something was a bad idea till it\nwasn't. And it wouldn't be the first time investors learned that\nlesson from founders.So if you want to work on hardware, don't be deterred from doing\nit because you worry investors will discriminate against you. And\nin particular, don't be deterred from applying to Y Combinator\nwith a hardware idea, because we're especially interested in hardware\nstartups.We know there's room for the next Steve Jobs.\nBut there's almost certainly also room for the first \n.\nThanks to Sam Altman, Trevor Blackwell, David Cann, Sanjay Dastoor, \nPaul Gerhardt, Cameron Robertson, Harj Taggar, and Garry Tan for reading drafts of this." }, { "path": "data/PaulGrahamEssays/hwh.txt", "content": "June 2021It might not seem there's much to learn about how to work hard.\nAnyone who's been to school knows what it entails, even if they\nchose not to do it. There are 12 year olds who work amazingly hard. And\nyet when I ask if I know more about working hard now than when I\nwas in school, the answer is definitely yes.One thing I know is that if you want to do great things, you'll\nhave to work very hard. I wasn't sure of that as a kid. Schoolwork\nvaried in difficulty; one didn't always have to work super hard to\ndo well. And some of the things famous adults did, they seemed to\ndo almost effortlessly. Was there, perhaps, some way to evade hard\nwork through sheer brilliance? Now I know the answer to that question.\nThere isn't.The reason some subjects seemed easy was that my school had low\nstandards. And the reason famous adults seemed to do things\neffortlessly was years of practice; they made it look easy.Of course, those famous adults usually had a lot of natural ability\ntoo. There are three ingredients in great work: natural ability,\npractice, and effort. You can do pretty well with just two, but to\ndo the best work you need all three: you need great natural ability\nand to have practiced a lot and to be trying very hard. \n[1]Bill Gates, for example, was among the smartest people in business\nin his era, but he was also among the hardest working. \"I never\ntook a day off in my twenties,\" he said. \"Not one.\" It was similar\nwith Lionel Messi. He had great natural ability, but when his youth\ncoaches talk about him, what they remember is not his talent but\nhis dedication and his desire to win. P. G. Wodehouse would probably\nget my vote for best English writer of the 20th century, if I had\nto choose. Certainly no one ever made it look easier. But no one\never worked harder. At 74, he wrote\n\n with each new book of mine I have, as I say, the feeling that\n this time I have picked a lemon in the garden of literature. A\n good thing, really, I suppose. Keeps one up on one's toes and\n makes one rewrite every sentence ten times. Or in many cases\n twenty times.\n\nSounds a bit extreme, you think. And yet Bill Gates sounds even\nmore extreme. Not one day off in ten years? These two had about\nas much natural ability as anyone could have, and yet they also\nworked about as hard as anyone could work. You need both.That seems so obvious, and yet in practice we find it slightly hard\nto grasp. There's a faint xor between talent and hard work. It comes\npartly from popular culture, where it seems to run very deep, and\npartly from the fact that the outliers are so rare. If great talent\nand great drive are both rare, then people with both are rare\nsquared. Most people you meet who have a lot of one will have less\nof the other. But you'll need both if you want to be an outlier\nyourself. And since you can't really change how much natural talent\nyou have, in practice doing great work, insofar as you can, reduces\nto working very hard.It's straightforward to work hard if you have clearly defined,\nexternally imposed goals, as you do in school. There is some technique\nto it: you have to learn not to lie to yourself, not to procrastinate\n(which is a form of lying to yourself), not to get distracted, and\nnot to give up when things go wrong. But this level of discipline\nseems to be within the reach of quite young children, if they want\nit.What I've learned since I was a kid is how to work toward goals\nthat are neither clearly defined nor externally imposed. You'll\nprobably have to learn both if you want to do really great things.The most basic level of which is simply to feel you should be working\nwithout anyone telling you to. Now, when I'm not working hard, alarm\nbells go off. I can't be sure I'm getting anywhere when I'm working\nhard, but I can be sure I'm getting nowhere when I'm not, and it\nfeels awful.\n[2]There wasn't a single point when I learned this. Like most little\nkids, I enjoyed the feeling of achievement when I learned or did\nsomething new. As I grew older, this morphed into a feeling of\ndisgust when I wasn't achieving anything. The one precisely dateable\nlandmark I have is when I stopped watching TV, at age 13.Several people I've talked to remember getting serious about work\naround this age. When I asked Patrick Collison when he started to\nfind idleness distasteful, he said\n\n I think around age 13 or 14. I have a clear memory from around\n then of sitting in the sitting room, staring outside, and wondering\n why I was wasting my summer holiday.\n\nPerhaps something changes at adolescence. That would make sense.Strangely enough, the biggest obstacle to getting serious about\nwork was probably school, which made work (what they called work)\nseem boring and pointless. I had to learn what real work was before\nI could wholeheartedly desire to do it. That took a while, because\neven in college a lot of the work is pointless; there are entire\ndepartments that are pointless. But as I learned the shape of real\nwork, I found that my desire to do it slotted into it as if they'd\nbeen made for each other.I suspect most people have to learn what work is before they can\nlove it. Hardy wrote eloquently about this in A Mathematician's\nApology:\n\n I do not remember having felt, as a boy, any passion for\n mathematics, and such notions as I may have had of the career of\n a mathematician were far from noble. I thought of mathematics in\n terms of examinations and scholarships: I wanted to beat other\n boys, and this seemed to be the way in which I could do so most\n decisively.\n\nHe didn't learn what math was really about till part way through\ncollege, when he read Jordan's Cours d'analyse.\n\n I shall never forget the astonishment with which I read that\n remarkable work, the first inspiration for so many mathematicians\n of my generation, and learnt for the first time as I read it what\n mathematics really meant.\n\nThere are two separate kinds of fakeness you need to learn to\ndiscount in order to understand what real work is. One is the kind\nHardy encountered in school. Subjects get distorted when they're\nadapted to be taught to kids — often so distorted that they're\nnothing like the work done by actual practitioners.\n[3]\nThe other\nkind of fakeness is intrinsic to certain types of work. Some types\nof work are inherently bogus, or at best mere busywork.There's a kind of solidity to real work. It's not all writing the\nPrincipia, but it all feels necessary. That's a vague criterion,\nbut it's deliberately vague, because it has to cover a lot of\ndifferent types.\n[4]Once you know the shape of real work, you have to learn how many\nhours a day to spend on it. You can't solve this problem by simply\nworking every waking hour, because in many kinds of work there's a\npoint beyond which the quality of the result will start to decline.That limit varies depending on the type of work and the person.\nI've done several different kinds of work, and the limits were\ndifferent for each. My limit for the harder types of writing or\nprogramming is about five hours a day. Whereas when I was running\na startup, I could\nwork all the time. At least for the three years I did it; if I'd\nkept going much longer, I'd probably have needed to take occasional\nvacations.\n[5]The only way to find the limit is by crossing it. Cultivate a\nsensitivity to the quality of the work you're doing, and then you'll\nnotice if it decreases because you're working too hard. Honesty is\ncritical here, in both directions: you have to notice when you're\nbeing lazy, but also when you're working too hard. And if you think\nthere's something admirable about working too hard, get that idea\nout of your head. You're not merely getting worse results, but\ngetting them because you're showing off — if not to other people,\nthen to yourself.\n[6]Finding the limit of working hard is a constant, ongoing process,\nnot something you do just once. Both the difficulty of the work and\nyour ability to do it can vary hour to hour, so you need to be\nconstantly judging both how hard you're trying and how well you're\ndoing.Trying hard doesn't mean constantly pushing yourself to work, though.\nThere may be some people who do, but I think my experience is fairly\ntypical, and I only have to push myself occasionally when I'm\nstarting a project or when I encounter some sort of check. That's\nwhen I'm in danger of procrastinating. But once I get rolling, I\ntend to keep going.What keeps me going depends on the type of work. When I was working\non Viaweb, I was driven by fear of failure. I barely procrastinated\nat all then, because there was always something that needed doing,\nand if I could put more distance between me and the pursuing beast\nby doing it, why wait? [7]\nWhereas what drives me now, writing\nessays, is the flaws in them. Between essays I fuss for a few days,\nlike a dog circling while it decides exactly where to lie down. But\nonce I get started on one, I don't have to push myself to work,\nbecause there's always some error or omission already pushing me.I do make some amount of effort to focus on important topics. Many\nproblems have a hard core at the center, surrounded by easier stuff\nat the edges. Working hard means aiming toward the center to the\nextent you can. Some days you may not be able to; some days you'll\nonly be able to work on the easier, peripheral stuff. But you should\nalways be aiming as close to the center as you can without stalling.The bigger question of what to do with your life is one of these\nproblems with a hard core. There are important problems at the\ncenter, which tend to be hard, and less important, easier ones at\nthe edges. So as well as the small, daily adjustments involved in\nworking on a specific problem, you'll occasionally have to make\nbig, lifetime-scale adjustments about which type of work to do.\nAnd the rule is the same: working hard means aiming toward the\ncenter — toward the most ambitious problems.By center, though, I mean the actual center, not merely the current\nconsensus about the center. The consensus about which problems are\nmost important is often mistaken, both in general and within specific\nfields. If you disagree with it, and you're right, that could\nrepresent a valuable opportunity to do something new.The more ambitious types of work will usually be harder, but although\nyou should not be in denial about this, neither should you treat\ndifficulty as an infallible guide in deciding what to do. If you\ndiscover some ambitious type of work that's a bargain in the sense\nof being easier for you than other people, either because of the\nabilities you happen to have, or because of some new way you've\nfound to approach it, or simply because you're more excited about\nit, by all means work on that. Some of the best work is done by\npeople who find an easy way to do something hard.As well as learning the shape of real work, you need to figure out\nwhich kind you're suited for. And that doesn't just mean figuring\nout which kind your natural abilities match the best; it doesn't\nmean that if you're 7 feet tall, you have to play basketball. What\nyou're suited for depends not just on your talents but perhaps even\nmore on your interests. A deep interest \nin a topic makes people\nwork harder than any amount of discipline can.It can be harder to discover your interests than your talents.\nThere are fewer types of talent than interest, and they start to\nbe judged early in childhood, whereas interest in a topic is a\nsubtle thing that may not mature till your twenties, or even later.\nThe topic may not even exist earlier. Plus there are some powerful\nsources of error you need to learn to discount. Are you really\ninterested in x, or do you want to work on it because you'll make\na lot of money, or because other people will be impressed with you,\nor because your parents want you to?\n[8]The difficulty of figuring out what to work on varies enormously\nfrom one person to another. That's one of the most important things\nI've learned about work since I was a kid. As a kid, you get the\nimpression that everyone has a calling, and all they have to do is\nfigure out what it is. That's how it works in movies, and in the\nstreamlined biographies fed to kids. Sometimes it works that way\nin real life. Some people figure out what to do as children and\njust do it, like Mozart. But others, like Newton, turn restlessly\nfrom one kind of work to another. Maybe in retrospect we can identify\none as their calling — we can wish Newton spent more time on math\nand physics and less on alchemy and theology — but this is an\nillusion induced by hindsight bias. \nThere was no voice calling to him that he could have heard.So while some people's lives converge fast, there will be others\nwhose lives never converge. And for these people, figuring out what\nto work on is not so much a prelude to working hard as an ongoing\npart of it, like one of a set of simultaneous equations. For these\npeople, the process I described earlier has a third component: along\nwith measuring both how hard you're working and how well you're\ndoing, you have to think about whether you should keep working in\nthis field or switch to another. If you're working hard but not\ngetting good enough results, you should switch. It sounds simple\nexpressed that way, but in practice it's very difficult. You shouldn't\ngive up on the first day just because you work hard and don't get\nanywhere. You need to give yourself time to get going. But how much\ntime? And what should you do if work that was going well stops going\nwell? How much time do you give yourself then?\n[9]What even counts as good results? That can be really hard to decide.\nIf you're exploring an area few others have worked in, you may not\neven know what good results look like. History is full of examples\nof people who misjudged the importance of what they were working\non.The best test of whether it's worthwhile to work on something is\nwhether you find it interesting. That may sound like a dangerously\nsubjective measure, but it's probably the most accurate one you're\ngoing to get. You're the one working on the stuff. Who's in a better\nposition than you to judge whether it's important, and what's a\nbetter predictor of its importance than whether it's interesting?For this test to work, though, you have to be honest with yourself.\nIndeed, that's the most striking thing about the whole question of\nworking hard: how at each point it depends on being honest with\nyourself.Working hard is not just a dial you turn up to 11. It's a complicated,\ndynamic system that has to be tuned just right at each point. You\nhave to understand the shape of real work, see clearly what kind\nyou're best suited for, aim as close to the true core of it as you\ncan, accurately judge at each moment both what you're capable of\nand how you're doing, and put in as many hours each day as you can\nwithout harming the quality of the result. This network is too\ncomplicated to trick. But if you're consistently honest and\nclear-sighted, it will automatically assume an optimal shape, and\nyou'll be productive in a way few people are.Notes[1]\nIn \"The Bus Ticket Theory of Genius\" I said the three ingredients\nin great work were natural ability, determination, and interest.\nThat's the formula in the preceding stage; determination and interest\nyield practice and effort.[2]\nI mean this at a resolution of days, not hours. You'll often\nget somewhere while not working in the sense that the solution to\na problem comes to you while taking a \nshower, or even in your sleep,\nbut only because you were working hard on it the day before.It's good to go on vacation occasionally, but when I go on vacation,\nI like to learn new things. I wouldn't like just sitting on a beach.[3]\nThe thing kids do in school that's most like the real version\nis sports. Admittedly because many sports originated as games played\nin schools. But in this one area, at least, kids are doing exactly\nwhat adults do.In the average American high school, you have a choice of pretending\nto do something serious, or seriously doing something pretend.\nArguably the latter is no worse.[4]\nKnowing what you want to work on doesn't mean you'll be able\nto. Most people have to spend a lot of their time working on things\nthey don't want to, especially early on. But if you know what you\nwant to do, you at least know what direction to nudge your life in.[5]\nThe lower time limits for intense work suggest a solution to\nthe problem of having less time to work after you have kids: switch\nto harder problems. In effect I did that, though not deliberately.[6]\nSome cultures have a tradition of performative hard work. I\ndon't love this idea, because (a) it makes a parody of something\nimportant and (b) it causes people to wear themselves out doing\nthings that don't matter. I don't know enough to say for sure whether\nit's net good or bad, but my guess is bad.[7]\nOne of the reasons people work so hard on startups is that\nstartups can fail, and when they do, that failure tends to be both\ndecisive and conspicuous.[8]\nIt's ok to work on something to make a lot of money. You need\nto solve the money problem somehow, and there's nothing wrong with\ndoing that efficiently by trying to make a lot at once. I suppose\nit would even be ok to be interested in money for its own sake;\nwhatever floats your boat. Just so long as you're conscious of your\nmotivations. The thing to avoid is unconsciously letting the need\nfor money warp your ideas about what kind of work you find most\ninteresting.[9]\nMany people face this question on a smaller scale with\nindividual projects. But it's easier both to recognize and to accept\na dead end in a single project than to abandon some type of work\nentirely. The more determined you are, the harder it gets. Like a\nSpanish Flu victim, you're fighting your own immune system: Instead\nof giving up, you tell yourself, I should just try harder. And who\ncan say you're not right?\nThanks to Trevor Blackwell, John Carmack, John Collison, Patrick Collison,\nRobert Morris, Geoff Ralston, and Harj Taggar for reading drafts of this." }, { "path": "data/PaulGrahamEssays/icad.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nMay 2002\n\n\n\n\"We were after the C++ programmers. We managed to drag a \nlot of them about halfway to Lisp.\"- Guy Steele, co-author of the Java spec\n\n\n\n\nIn the software business there is an ongoing\nstruggle between the pointy-headed academics, and another\nequally formidable force, the pointy-haired bosses. Everyone\nknows who the pointy-haired boss is, right? I think most\npeople in the technology world not only recognize this\ncartoon character, but know the actual person in their company\nthat he is modelled upon.The pointy-haired boss miraculously combines two qualities\nthat are common by themselves, but rarely seen together:\n(a) he knows nothing whatsoever about technology, and\n(b) he has very strong opinions about it.Suppose, for example, you need to write a piece of software.\nThe pointy-haired boss has no idea how this software\nhas to work, and can't tell one programming language from\nanother, and yet he knows what language you should write it in.\nExactly. He thinks you should write it in Java.Why does he think this? Let's\ntake a look inside the brain of the pointy-haired boss. What\nhe's thinking is something like this. Java is a standard.\nI know it must be, because I read about it in the press all the time.\nSince it is a standard, I won't get in trouble for using it.\nAnd that also means there will always be lots of Java programmers,\nso if the programmers working for me now quit, as programmers\nworking for me mysteriously always do, I can easily replace\nthem.Well, this doesn't sound that unreasonable. But it's all\nbased on one unspoken assumption, and that assumption\nturns out to be false. The pointy-haired boss believes that all\nprogramming languages are pretty much equivalent.\nIf that were true, he would be right on\ntarget. If languages are all equivalent, sure, use whatever \nlanguage everyone else is using.But all languages are not equivalent, and I think I can prove\nthis to you without even getting into the differences between them.\nIf you asked the pointy-haired boss in 1992 what language \nsoftware should be written in, he would have answered with as\nlittle hesitation as he does today. Software should be \nwritten in C++. But if languages are all equivalent, why should the\npointy-haired boss's opinion ever change? In fact, why should\nthe developers of Java have even bothered to create a new\nlanguage?Presumably, if you create a new language, it's because you think\nit's better in some way than what people already had. And in fact, Gosling\nmakes it clear in the first Java white paper that Java\nwas designed to fix some problems with C++.\nSo there you have it: languages are not all equivalent.\nIf you follow the\ntrail through the pointy-haired boss's brain to Java and then\nback through Java's history to its origins, you end up holding\nan idea that contradicts the assumption you started with.So, who's right? James Gosling, or the pointy-haired boss?\nNot surprisingly, Gosling is right. Some languages are better,\nfor certain problems, than others. And you know, that raises some\ninteresting questions. Java was designed to be better, for certain\nproblems, than C++. What problems? When is Java better and \nwhen is C++? Are there situations where other languages are\nbetter than either of them?Once you start considering this question, you have opened a\nreal can of worms. If the pointy-haired boss had to think\nabout the problem in its full complexity, it would make his\nbrain explode. As long as he considers all languages \nequivalent, all he has to do is choose the one\nthat seems to have the most momentum, and since that is more\na question of fashion than technology, even he\ncan probably get the right answer.\nBut if languages vary, he suddenly\nhas to solve two simultaneous equations, trying to find\nan optimal balance between two things he knows nothing \nabout: the relative suitability of the twenty or so leading\nlanguages for the problem he needs to solve, and the odds of\nfinding programmers, libraries, etc. for each.\nIf that's what's on the other side of the door, it\nis no surprise that the pointy-haired boss doesn't want to open it.The disadvantage of believing that all programming languages\nare equivalent is that it's not true. But the advantage is \nthat it makes your life a lot simpler.\nAnd I think that's the main reason the idea is so widespread.\nIt is a comfortable idea.We know that Java must be pretty good, because it is the\ncool, new programming language. Or is it? If you look at the world of\nprogramming languages from a distance, it looks like Java is\nthe latest thing. (From far enough away, all you can see is\nthe large, flashing billboard paid for by Sun.)\nBut if you look at this world\nup close, you find that there are degrees of coolness. Within\nthe hacker subculture, there is another language called Perl\nthat is considered a lot cooler than Java. Slashdot, for\nexample, is generated by Perl. I don't think you would find\nthose guys using Java Server Pages. But there is another,\nnewer language, called Python, whose users tend to look down on Perl,\nand more waiting in the wings.If you look at these languages in order, Java, Perl, Python,\nyou notice an interesting pattern. At least, you notice this\npattern if you are a Lisp hacker. Each one is progressively \nmore like Lisp. Python copies even features\nthat many Lisp hackers consider to be mistakes.\nYou could translate simple Lisp programs into Python line for line.\nIt's 2002, and programming languages have almost caught up \nwith 1958.Catching Up with MathWhat I mean is that\nLisp was first discovered by John McCarthy in 1958,\nand popular programming languages are only now\ncatching up with the ideas he developed then.Now, how could that be true? Isn't computer technology something\nthat changes very rapidly? I mean, in 1958, computers were\nrefrigerator-sized behemoths with the processing power of \na wristwatch. How could any technology that old even be\nrelevant, let alone superior to the latest developments?I'll tell you how. It's because Lisp was not really\ndesigned to be a programming language, at least not in the sense\nwe mean today. What we mean by a programming language is\nsomething we use to tell a computer what to do. McCarthy\ndid eventually intend to develop a programming language in\nthis sense, but the Lisp that we actually ended up with was based\non something separate that he did as a \ntheoretical exercise-- an effort\nto define a more convenient alternative to the Turing Machine.\nAs McCarthy said later,\n\nAnother way to show that Lisp was neater than Turing machines\nwas to write a universal Lisp function\nand show that it is briefer and more comprehensible than the\ndescription of a universal Turing machine.\nThis was the Lisp function eval..., \nwhich computes the value of\na Lisp expression....\nWriting eval required inventing a notation representing Lisp\nfunctions as Lisp data, and such a notation\nwas devised for the purposes of the paper with no thought that\nit would be used to express Lisp programs in practice.\n\nWhat happened next was that, some time in late 1958, Steve Russell,\none of McCarthy's\ngrad students, looked at this definition of eval and realized \nthat if he translated it into machine language, the result\nwould be a Lisp interpreter.This was a big surprise at the time.\nHere is what McCarthy said about it later in an interview:\n\nSteve Russell said, look, why don't I program this eval..., and\nI said to him, ho, ho, you're confusing theory with practice,\nthis eval is intended for reading, not for\ncomputing. But he went ahead and did it. That is, he compiled the eval\nin my paper into [IBM] 704 machine\ncode, fixing bugs, and then advertised this as a Lisp interpreter,\nwhich it certainly was. So at that point Lisp\nhad essentially the form that it has today....\n\nSuddenly, in a matter of weeks I think, McCarthy found his theoretical\nexercise transformed into an actual programming language-- and a\nmore powerful one than he had intended.So the short explanation of why this 1950s language is not\nobsolete is that it was not technology but math, and\nmath doesn't get stale. The right thing to compare Lisp\nto is not 1950s hardware, but, say, the Quicksort\nalgorithm, which was discovered in 1960 and is still\nthe fastest general-purpose sort.There is one other language still\nsurviving from the 1950s, Fortran, and it represents the\nopposite approach to language design. Lisp was a\npiece of theory that unexpectedly got turned into a\nprogramming language. Fortran was developed intentionally as\na programming language, but what we would now consider a\nvery low-level one.Fortran I, the language that was\ndeveloped in 1956, was a very different animal from present-day\nFortran. Fortran I was pretty much assembly\nlanguage with math. In some ways it was less\npowerful than more recent assembly languages; there were no \nsubroutines, for example, only branches.\nPresent-day Fortran is now arguably closer to Lisp than to\nFortran I.Lisp and Fortran were the trunks of two separate evolutionary trees, \none rooted in math and one rooted in machine architecture.\nThese two trees have been converging ever since.\nLisp started out powerful, and over the next twenty years\ngot fast. So-called mainstream languages started out\nfast, and over the next forty years gradually got more powerful,\nuntil now the most advanced\nof them are fairly close to Lisp.\nClose, but they are still missing a few things....What Made Lisp DifferentWhen it was first developed, Lisp embodied nine new\nideas. Some of these we now take for granted, others are\nonly seen in more advanced languages, and two are still\nunique to Lisp. The nine ideas are, in order of their\nadoption by the mainstream,\n\n Conditionals. A conditional is an if-then-else\nconstruct. We take these for granted now, but Fortran I\ndidn't have them. It had only a conditional goto\nclosely based on the underlying machine instruction. A function type. In Lisp, functions are\na data type just like integers or strings.\nThey have a literal representation, can be stored in variables,\ncan be passed as arguments, and so on. Recursion. Lisp was the first programming language to\nsupport it. Dynamic typing. In Lisp, all variables\nare effectively pointers. Values are what\nhave types, not variables, and assigning or binding\nvariables means copying pointers, not what they point to. Garbage-collection. Programs composed of expressions. Lisp programs are\ntrees of expressions, each of which returns a value.\nThis is in contrast to Fortran\nand most succeeding languages, which distinguish between\nexpressions and statements.It was natural to have this\ndistinction in Fortran I because\nyou could not nest statements. And\nso while you needed expressions for math to work, there was\nno point in making anything else return a value, because\nthere could not be anything waiting for it.This limitation\nwent away with the arrival of block-structured languages,\nbut by then it was too late. The distinction between\nexpressions and statements was entrenched. It spread from\nFortran into Algol and then to both their descendants. A symbol type. Symbols are effectively pointers to strings\nstored in a hash table. So\nyou can test equality by comparing a pointer,\ninstead of comparing each character. A notation for code using trees of symbols and constants. The whole language there all the time. There is\nno real distinction between read-time, compile-time, and runtime.\nYou can compile or run code while reading, read or run code\nwhile compiling, and read or compile code at runtime.Running code at read-time lets users reprogram Lisp's syntax;\nrunning code at compile-time is the basis of macros; compiling\nat runtime is the basis of Lisp's use as an extension\nlanguage in programs like Emacs; and reading at runtime\nenables programs to communicate using s-expressions, an\nidea recently reinvented as XML.\n\nWhen Lisp first appeared, these ideas were far\nremoved from ordinary programming practice, which was\ndictated largely by the hardware available in the late 1950s.\nOver time, the default language, embodied\nin a succession of popular languages, has\ngradually evolved toward Lisp. Ideas 1-5 are now widespread.\nNumber 6 is starting to appear in the mainstream. \nPython has a form of 7, though there doesn't seem to be \nany syntax for it.As for number 8, this may be the most interesting of the\nlot. Ideas 8 and 9 only became part of Lisp\nby accident, because Steve Russell implemented\nsomething McCarthy had never intended to be implemented.\nAnd yet these ideas turn out to be responsible for\nboth Lisp's strange appearance and its most distinctive\nfeatures. Lisp looks strange not so much because\nit has a strange syntax as because it has no syntax;\nyou express programs directly in the parse trees that\nget built behind the scenes when other languages are\nparsed, and these trees are made\nof lists, which are Lisp data structures.Expressing the language in its own data structures turns\nout to be a very powerful feature. Ideas 8 and 9\ntogether mean that you\ncan write programs that write programs. That may sound\nlike a bizarre idea, but it's an everyday thing in Lisp. \nThe most common way to do it is with something called a \nmacro.The term \"macro\" does not mean in Lisp what it means in other\nlanguages.\nA Lisp macro can be anything from an abbreviation\nto a compiler for a new language.\nIf you want to really understand Lisp,\nor just expand your programming horizons, I would \nlearn more about macros.Macros (in the Lisp sense) are still, as far as\nI know, unique to Lisp.\nThis is partly because in order to have macros you\nprobably have to make your language look as strange as\nLisp. It may also be because if you do add that final\nincrement of power, you can no\nlonger claim to have invented a new language, but only\na new dialect of Lisp.I mention this mostly\nas a joke, but it is quite true. If you define\na language that has car, cdr, cons, quote, cond, atom,\neq, and\na notation for functions expressed as lists, then you\ncan build all the rest of Lisp out of it. That is in\nfact the defining quality of Lisp: it was in order to\nmake this so that McCarthy gave Lisp the shape it has.Where Languages MatterSo suppose Lisp does represent a kind of limit \nthat mainstream languages are approaching asymptotically-- does\nthat mean you should actually use it to write software?\nHow much do you lose by using a less powerful language?\nIsn't it wiser, sometimes, not to be\nat the very edge of innovation?\nAnd isn't popularity to some extent\nits own justification? Isn't the pointy-haired boss right,\nfor example, to want to use a language for which he can easily\nhire programmers?There are, of course, projects where the choice of programming\nlanguage doesn't matter much. As a\nrule, the more demanding the application, the more\nleverage you get from using a powerful language. But\nplenty of projects are not demanding at all.\nMost programming probably consists of writing \nlittle glue programs, and for \nlittle glue programs you\ncan use any language that you're already\nfamiliar with and that has good libraries for whatever you\nneed to do. If you just need to feed data from one \nWindows app to another, sure, use Visual Basic.You can write little glue programs in Lisp too\n(I use it as a desktop calculator), but the biggest win\nfor languages like Lisp is at the other end of\nthe spectrum, where you need to write sophisticated\nprograms to solve hard problems in the face of fierce competition.\nA good example is the\nairline fare search program that ITA Software licenses to\nOrbitz. These\nguys entered a market already dominated by two big,\nentrenched competitors, Travelocity and Expedia, and \nseem to have just humiliated them technologically.The core of ITA's application is a 200,000 line Common Lisp program\nthat searches many orders of magnitude more possibilities\nthan their competitors, who apparently\nare still using mainframe-era programming techniques.\n(Though ITA is also in a sense\nusing a mainframe-era programming language.)\nI have never seen any of ITA's code, but according to\none of their top hackers they use a lot of macros,\nand I am not surprised to hear it.Centripetal ForcesI'm not saying there is no cost to using uncommon \ntechnologies. The pointy-haired boss is not completely\nmistaken to worry about this. But because he doesn't understand\nthe risks, he tends to magnify them.I can think of three problems that could arise from using\nless common languages. Your programs might not work well with\nprograms written in other languages. You might have fewer\nlibraries at your disposal. And you might have trouble\nhiring programmers.How much of a problem is each of these? The importance of\nthe first varies depending on whether you have control\nover the whole system. If you're writing software that has\nto run on a remote user's machine on top of a buggy,\nclosed operating system (I mention no names), there may be\nadvantages to writing your application in the\nsame language as the OS.\nBut if you control the whole system and\nhave the source code of all the parts, as ITA presumably does, you\ncan use whatever languages you want. If\nany incompatibility arises, you can fix it yourself.In server-based applications you can\nget away with using the most advanced technologies,\nand I think this is the main\ncause of what Jonathan Erickson calls the \"programming language\nrenaissance.\" This is why we even hear about new\nlanguages like Perl and Python. We're not hearing about these\nlanguages because people are using them to write Windows\napps, but because people are using them on servers. And as\nsoftware shifts \noff the desktop and onto servers (a future even\nMicrosoft seems resigned to), there will be less\nand less pressure to use middle-of-the-road technologies.As for libraries, their importance also\ndepends on the application. For less demanding problems,\nthe availability of libraries can outweigh the intrinsic power\nof the language. Where is the breakeven point? Hard to say\nexactly, but wherever it is, it is short of anything you'd\nbe likely to call an application. If a company considers\nitself to be in the software business, and they're writing\nan application that will be one of their products,\nthen it will probably involve several hackers and take at\nleast six months to write. In a project of that\nsize, powerful languages probably start to outweigh\nthe convenience of pre-existing libraries.The third worry of the pointy-haired boss, the difficulty\nof hiring programmers, I think is a red herring. How many\nhackers do you need to hire, after all? Surely by now we\nall know that software is best developed by teams of less\nthan ten people. And you shouldn't have trouble hiring\nhackers on that scale for any language anyone has ever heard\nof. If you can't find ten Lisp hackers, then your company is\nprobably based in the wrong city for developing software.In fact, choosing a more powerful language probably decreases the\nsize of the team you need, because (a) if you use a more powerful\nlanguage you probably won't need as many hackers,\nand (b) hackers who work in more advanced languages are likely\nto be smarter.I'm not saying that you won't get a lot of pressure to use\nwhat are perceived as \"standard\" technologies. At Viaweb\n(now Yahoo Store),\nwe raised some eyebrows among VCs and potential acquirers by\nusing Lisp. But we also raised eyebrows by using\ngeneric Intel boxes as servers instead of\n\"industrial strength\" servers like Suns, for using a\nthen-obscure open-source Unix variant called FreeBSD instead\nof a real commercial OS like Windows NT, for ignoring\na supposed e-commerce standard called \nSET that no one now\neven remembers, and so on.You can't let the suits make technical decisions for you.\nDid it\nalarm some potential acquirers that we used Lisp? Some, slightly,\nbut if we hadn't used Lisp, we wouldn't have been\nable to write the software that made them want to buy us.\nWhat seemed like an anomaly to them was in fact\ncause and effect.If you start a startup, don't design your product to please\nVCs or potential acquirers. Design your product to please\nthe users. If you win the users, everything else will\nfollow. And if you don't, no one will care\nhow comfortingly orthodox your technology choices were.The Cost of Being AverageHow much do you lose by using a less powerful language? \nThere is actually some data out there about that.The most convenient measure of power is probably \ncode size.\nThe point of high-level\nlanguages is to give you bigger abstractions-- bigger bricks,\nas it were, so you don't need as many to build\na wall of a given size.\nSo the more powerful\nthe language, the shorter the program (not simply in\ncharacters, of course, but in distinct elements).How does a more powerful language enable you to write\nshorter programs? One technique you can use, if the language will\nlet you, is something called \nbottom-up programming. Instead of\nsimply writing your application in the base language, you\nbuild on top of the base language a language for writing\nprograms like yours, then write your program\nin it. The combined code can be much shorter than if you\nhad written your whole program in the base language-- indeed,\nthis is how most compression algorithms work.\nA bottom-up program should be easier to modify as well, \nbecause in many cases the language layer won't have to change\nat all.Code size is important, because the time it takes\nto write a program depends mostly on its length.\nIf your program would be three times as long in another\nlanguage, it will take three times as long to write-- and\nyou can't get around this by hiring more people, because\nbeyond a certain size new hires are actually a net lose.\nFred Brooks described this phenomenon in his famous\nbook The Mythical Man-Month, and everything I've seen\nhas tended to confirm what he said.So how much shorter are your programs if you write them in\nLisp? Most of the numbers I've heard for Lisp\nversus C, for example, have been around 7-10x.\nBut a recent article about ITA in \nNew\nArchitect magazine said that\n\"one line of Lisp can replace 20 lines of C,\" and since\nthis article was full of quotes from ITA's president, I\nassume they got this number from ITA. If so then\nwe can put some faith in it; ITA's software includes a lot\nof C and C++ as well as Lisp, so they are speaking from\nexperience.My guess is that these multiples aren't even constant.\nI think they increase when\nyou face harder problems and also when you have smarter\nprogrammers. A really good hacker can squeeze more\nout of better tools.As one data point on the curve, at any rate,\nif you were to compete with ITA and\nchose to write your software in C, they would be able to develop\nsoftware twenty times faster than you.\nIf you spent a year on a new feature, they'd be able to\nduplicate it in less than three weeks. Whereas if they spent\njust three months developing something new, it would be\nfive years before you had it too.And you know what? That's the best-case scenario.\nWhen you talk about code-size ratios, you're implicitly assuming\nthat you can actually write the program in the weaker language.\nBut in fact there are limits on what programmers can do.\nIf you're trying to solve a hard problem with a language that's\ntoo low-level, you reach a point where there is just too \nmuch to keep in your head at once.So when I say it would take ITA's imaginary\ncompetitor five years to duplicate something ITA could\nwrite in Lisp in three months, I mean five years\nif nothing goes wrong. In fact, the way things work in \nmost companies, any\ndevelopment project that would take five years is\nlikely never to get finished at all.I admit this is an extreme case. ITA's hackers seem to\nbe unusually smart, and C is a pretty low-level language.\nBut in a competitive market, even a differential of two or\nthree to one would\nbe enough to guarantee that you'd always be behind.A RecipeThis is the kind of possibility that the pointy-haired boss\ndoesn't even want to think about. And so most of them don't.\nBecause, you know, when it comes down to it, the pointy-haired\nboss doesn't mind if his company gets their ass kicked, so\nlong as no one can prove it's his fault.\nThe safest plan for him personally\nis to stick close to the center of the herd.Within large organizations, the phrase used to\ndescribe this approach is \"industry best practice.\"\nIts purpose is to shield the pointy-haired\nboss from responsibility: if he chooses\nsomething that is \"industry best practice,\" and the company\nloses, he can't be blamed. He didn't choose, the industry did.I believe this term was originally used to describe\naccounting methods and so on. What it means, roughly,\nis don't do anything weird. And in accounting that's\nprobably a good idea. The terms \"cutting-edge\" and \n\"accounting\" do not sound good together. But when you import\nthis criterion into decisions about technology, you start\nto get the wrong answers.Technology often should be\ncutting-edge. In programming languages, as Erann Gat\nhas pointed out, what \"industry best practice\" actually\ngets you is not the best, but merely the\naverage. When a decision causes you to develop software at\na fraction of the rate of more aggressive competitors, \n\"best practice\" is a misnomer.\nSo here we have two pieces of information that I think are\nvery valuable. In fact, I know it from my own experience.\nNumber 1, languages vary in power. Number 2, most managers\ndeliberately ignore this. Between them, these two facts\nare literally a recipe for making money. ITA is an example\nof this recipe in action.\nIf you want to win in a software\nbusiness, just take on the hardest problem you can find,\nuse the most powerful language you can get, and wait for\nyour competitors' pointy-haired bosses to revert to the mean.\n\nAppendix: PowerAs an illustration of what I mean about the relative power\nof programming languages, consider the following problem.\nWe want to write a function that generates accumulators-- a\nfunction that takes a number n, and\nreturns a function that takes another number i and\nreturns n incremented by i.(That's incremented by, not plus. An accumulator\nhas to accumulate.)In Common Lisp this would be\n\n(defun foo (n)\n (lambda (i) (incf n i)))\n\nand in Perl 5,\n\nsub foo { \n my ($n) = @_;\n sub {$n += shift}\n}\n\nwhich has more elements than the Lisp version because\nyou have to extract parameters manually in Perl.In Smalltalk the code is slightly longer than in Lisp\n\nfoo: n \n |s| \n s := n. \n ^[:i| s := s+i. ] \n\nbecause although in general lexical variables work, you can't\ndo an assignment to a parameter, so you have to create a\nnew variable s.In Javascript the example is, again, slightly longer, because \nJavascript retains\nthe distinction between statements and\nexpressions, so you need explicit return statements\nto return values:\n\nfunction foo(n) { \n return function (i) { \n return n += i } }\n\n(To be fair, Perl also retains\nthis distinction, but deals with it in typical Perl fashion\nby letting you omit returns.)If you try to translate the Lisp/Perl/Smalltalk/Javascript code into \nPython you run into some limitations. Because Python\ndoesn't fully support lexical variables,\nyou have to create a data structure to hold the value of n.\nAnd although\nPython does have a function data type, there is no\nliteral representation for one (unless the body is\nonly a single expression) so you need to create a named\nfunction to return. This is what you end up with:\n\ndef foo(n):\n s = [n]\n def bar(i):\n s[0] += i\n return s[0] \n return bar\n\nPython users might legitimately ask why they can't\njust write\n\ndef foo(n):\n return lambda i: return n += i\n\nor even\n\ndef foo(n):\n lambda i: n += i\n\nand my guess is that they probably will, one day.\n(But if they don't want to wait for Python to evolve the rest\nof the way into Lisp, they could always just...)\nIn OO languages, you can, to a limited extent, simulate\na closure (a function that refers to variables defined in\nenclosing scopes) by defining a class with one method\nand a field to replace each variable from an enclosing\nscope. This makes the programmer do the kind of code\nanalysis that would be done by the compiler in a language\nwith full support for lexical scope, and it won't work\nif more than one function refers to the same variable,\nbut it is enough in simple cases like this.Python experts seem to agree that this is the\npreferred way to solve the problem in Python, writing\neither\n\ndef foo(n):\n class acc:\n def __init__(self, s):\n self.s = s\n def inc(self, i):\n self.s += i\n return self.s\n return acc(n).inc\n\nor\n\nclass foo:\n def __init__(self, n):\n self.n = n\n def __call__(self, i):\n self.n += i\n return self.n\n\nI include these because I wouldn't want Python\nadvocates to say I was misrepresenting the language, \nbut both seem to me more complex than the first \nversion. You're doing the same thing, setting up\na separate place to hold the accumulator; it's just\na field in an object instead of the head of a list.\nAnd the use of these special,\nreserved field names, especially __call__, seems\na bit of a hack.In the rivalry between Perl and Python, the claim of the\nPython hackers seems to be that\nthat Python is a more elegant alternative to Perl, but what\nthis case shows is that power is the ultimate elegance:\nthe Perl program is simpler (has fewer elements), even if the\nsyntax is a bit uglier.How about other languages? In the other languages\nmentioned in this talk-- Fortran, C, C++, Java, and\nVisual Basic-- it is not clear whether you can actually\nsolve this problem.\nKen Anderson says that the following code is about as close\nas you can get in Java:\n\npublic interface Inttoint {\n public int call(int i);\n}\n\n\npublic static Inttoint foo(final int n) {\n return new Inttoint() {\n int s = n;\n public int call(int i) {\n s = s + i;\n return s;\n }};\n}\n\nThis falls short of the spec because it only works for\nintegers. After many email exchanges with Java hackers,\nI would say that writing a properly polymorphic version\nthat behaves like the preceding examples is somewhere\nbetween damned awkward and impossible. If anyone wants to\nwrite one I'd be very curious to see it, but I personally\nhave timed out.It's not literally true that you can't solve this\nproblem in other languages, of course. The fact\nthat all these languages are Turing-equivalent means\nthat, strictly speaking, you can write any program in\nany of them. So how would you do it? In the limit case,\nby writing a Lisp\ninterpreter in the less powerful language.That sounds like a joke, but it happens so often to\nvarying degrees in large programming projects that\nthere is a name for the phenomenon, Greenspun's Tenth\nRule:\n\n Any sufficiently\n complicated C or Fortran program contains an ad hoc\n informally-specified bug-ridden slow implementation of half of\n Common Lisp.\n\nIf you try to solve a\nhard problem, the question is not whether you will use\na powerful enough language, but whether you will (a)\nuse a powerful language, (b) write a de facto interpreter\nfor one, or (c) yourself become a human compiler for one.\nWe see this already\nbegining to happen in the Python example, where we are\nin effect simulating the code that a compiler\nwould generate to implement a lexical variable.This practice is not only common, but institutionalized. For example,\nin the OO world you hear a good deal about \n\"patterns\".\nI wonder if these patterns are not sometimes evidence of case (c),\nthe human compiler, at work. When I see patterns in my programs,\nI consider it a sign of trouble. The shape of a program\nshould reflect only the problem it needs to solve.\nAny other regularity in the code is a sign, to me at\nleast, that I'm using abstractions that aren't powerful\nenough-- often that I'm generating by hand the\nexpansions of some macro that I need to write.Notes\n The IBM 704 CPU was about the size of a refrigerator,\nbut a lot heavier. The CPU weighed 3150 pounds,\nand the 4K of RAM was in a separate\nbox weighing another 4000 pounds. The\nSub-Zero 690, one of the largest household refrigerators,\nweighs 656 pounds. Steve Russell also wrote the first (digital) computer\ngame, Spacewar, in 1962. If you want to trick a pointy-haired boss into letting you\nwrite software in Lisp, you could try telling him it's XML. Here is the accumulator generator in other Lisp dialects:\n\nScheme: (define (foo n) \n (lambda (i) (set! n (+ n i)) n))\nGoo: (df foo (n) (op incf n _)))\nArc: (def foo (n) [++ n _])\n\n Erann Gat's sad tale about\n\"industry best practice\" at JPL inspired me to address\nthis generally misapplied phrase. Peter Norvig found that\n16 of the 23 patterns in Design Patterns were \n\"invisible\nor simpler\" in Lisp. Thanks to the many people who answered my questions about\nvarious languages and/or read drafts of this, including\nKen Anderson, Trevor Blackwell, Erann Gat, Dan Giffin, Sarah Harlin,\nJeremy Hylton, Robert Morris, Peter Norvig, Guy Steele, and Anton\nvan Straaten.\nThey bear no blame for any opinions expressed.\nRelated:Many people have responded to this talk,\nso I have set up an additional page to deal with the issues they have\nraised: Re: Revenge of the Nerds.It also set off an extensive and often useful discussion on the \nLL1\nmailing list. See particularly the mail by Anton van Straaten on semantic\ncompression.Some of the mail on LL1 led me to try to go deeper into the subject\nof language power in Succinctness is Power.A larger set of canonical implementations of the accumulator\ngenerator benchmark are collected together on their own page.Japanese Translation, Spanish\nTranslation, \nChinese Translation" }, { "path": "data/PaulGrahamEssays/ideas.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nOctober 2005(This essay is derived from a talk at the 2005 \nStartup School.)How do you get good ideas for \nstartups? That's probably the number\none question people ask me.I'd like to reply with another question: why do people think it's\nhard to come up with ideas for startups?That might seem a stupid thing to ask. Why do they think\nit's hard? If people can't do it, then it is hard, at least\nfor them. Right?Well, maybe not. What people usually say is not that they can't\nthink of ideas, but that they don't have any. That's not quite the\nsame thing. It could be the reason they don't have any is that\nthey haven't tried to generate them.I think this is often the case. I think people believe that coming\nup with ideas for startups is very hard-- that it must be\nvery hard-- and so they don't try do to it. They assume ideas are\nlike miracles: they either pop into your head or they don't.I also have a theory about why people think this. They overvalue\nideas. They think creating a startup is just a matter of implementing\nsome fabulous initial idea. And since a successful startup is worth\nmillions of dollars, a good idea is therefore a million dollar idea.If coming up with an idea for a startup equals coming up with a\nmillion dollar idea, then of course it's going to seem hard. Too\nhard to bother trying. Our instincts tell us something so valuable\nwould not be just lying around for anyone to discover.Actually, startup ideas are not million dollar ideas, and here's\nan experiment you can try to prove it: just try to sell one. Nothing\nevolves faster than markets. The fact that there's no market for\nstartup ideas suggests there's no demand. Which means, in the\nnarrow sense of the word, that startup ideas are worthless.QuestionsThe fact is, most startups end up nothing like the initial idea.\nIt would be closer to the truth to say the main value of your initial\nidea is that, in the process of discovering it's broken, you'll\ncome up with your real idea.The initial idea is just a starting point-- not a blueprint, but a\nquestion. It might help if they were expressed that way. Instead\nof saying that your idea is to make a collaborative, web-based\nspreadsheet, say: could one make a collaborative, web-based\nspreadsheet? A few grammatical tweaks, and a woefully incomplete\nidea becomes a promising question to explore.There's a real difference, because an assertion provokes objections\nin a way a question doesn't. If you say: I'm going to build a\nweb-based spreadsheet, then critics-- the most dangerous of which\nare in your own head-- will immediately reply that you'd be competing\nwith Microsoft, that you couldn't give people the kind of UI they\nexpect, that users wouldn't want to have their data on your servers,\nand so on.A question doesn't seem so challenging. It becomes: let's try\nmaking a web-based spreadsheet and see how far we get. And everyone\nknows that if you tried this you'd be able to make something\nuseful. Maybe what you'd end up with wouldn't even be a spreadsheet.\nMaybe it would be some kind of new spreasheet-like collaboration\ntool that doesn't even have a name yet. You wouldn't have thought\nof something like that except by implementing your way toward it.Treating a startup idea as a question changes what you're looking\nfor. If an idea is a blueprint, it has to be right. But if it's\na question, it can be wrong, so long as it's wrong in a way that\nleads to more ideas.One valuable way for an idea to be wrong is to be only a partial\nsolution. When someone's working on a problem that seems too\nbig, I always ask: is there some way to bite off some subset of the\nproblem, then gradually expand from there? That will generally\nwork unless you get trapped on a local maximum, like 1980s-style\nAI, or C.UpwindSo far, we've reduced the problem from thinking of a million dollar\nidea to thinking of a mistaken question. That doesn't seem so hard,\ndoes it?To generate such questions you need two things: to be familiar with \npromising new technologies, and to have the right kind of friends.\nNew technologies are the ingredients startup ideas are made of, and\nconversations with friends are the kitchen they're cooked in.Universities have both, and that's why so many startups grow out\nof them. They're filled with new technologies, because they're\ntrying to produce research, and only things that are new count as\nresearch. And they're full of exactly the right kind of people to \nhave ideas with: the other students, who will be not only smart but\nelastic-minded to a fault.The opposite extreme would be a well-paying but boring job at a big\ncompany. Big companies are biased against new technologies, and\nthe people you'd meet there would be wrong too.In an essay I wrote for high school students, \nI said a good rule of thumb was to stay upwind-- to\nwork on things that maximize your future options. The principle\napplies for adults too, though perhaps it has to be modified to:\nstay upwind for as long as you can, then cash in the potential\nenergy you've accumulated when you need to pay for kids.I don't think people consciously realize this, but one reason\ndownwind jobs like churning out Java for a bank pay so well is \nprecisely that they are downwind. The market price for that kind\nof work is higher because it gives you fewer options for the future.\nA job that lets you work on exciting new stuff will tend to pay\nless, because part of the compensation is in the form of the new\nskills you'll learn.Grad school is the other end of the spectrum from a coding job at\na big company: the pay's low but you spend most of your time working\non new stuff. And of course, it's called \"school,\" which makes\nthat clear to everyone, though in fact all jobs are some percentage\nschool.The right environment for having startup ideas need not be a\nuniversity per se. It just has to be a situation with a large\npercentage of school.It's obvious why you want exposure to new technology, but why do \nyou need other people? Can't you just think of new ideas yourself?\nThe empirical answer is: no. Even Einstein needed people to bounce\nideas off. Ideas get developed in the process of explaining them\nto the right kind of person. You need that resistance, just\nas a carver needs the resistance of the wood.This is one reason Y Combinator has a rule against investing in \nstartups with only one founder. Practically every successful company\nhas at least two. And because startup founders work under great \npressure, it's critical they be friends.I didn't realize it till I was writing this, but that may help\nexplain why there are so few female startup founders. I read on\nthe Internet (so it must be true) that only 1.7% of VC-backed\nstartups are founded by women. The percentage of female hackers\nis small, but not that small. So why the discrepancy?When you realize that successful startups tend to have multiple\nfounders who were already friends, a\npossible explanation emerges. People's best friends are likely to \nbe of the same sex, and if one group is a minority in some population,\npairs of them will be a minority squared.\n[1]DoodlingWhat these groups of co-founders do together is more complicated \nthan just sitting down and trying to think of ideas. I suspect the \nmost productive setup is a kind of together-alone-together sandwich.\nTogether you talk about some hard problem, probably getting nowhere.\nThen, the next morning, one of you has an idea in the shower about\nhow to solve it. He runs eagerly to to tell the others, and together\nthey work out the kinks.What happens in that shower? It seems to me that ideas just pop\ninto my head. But can we say more than that?Taking a shower is like a form of meditation. You're alert, but\nthere's nothing to distract you. It's in a situation like this,\nwhere your mind is free to roam, that it bumps into new ideas.What happens when your mind wanders? It may be like doodling. Most\npeople have characteristic ways of doodling. This habit is \nunconscious, but not random: I found my doodles changed after I \nstarted studying painting. I started to make the kind of gestures\nI'd make if I were drawing from life. They were atoms of drawing, \nbut arranged randomly.\n[2]Perhaps letting your mind wander is like doodling with ideas. You\nhave certain mental gestures you've learned in your work, and when\nyou're not paying attention, you keep making these same gestures, \nbut somewhat randomly. In effect, you call the same functions on\nrandom arguments. That's what a metaphor is: a function applied \nto an argument of the wrong type.Conveniently, as I was writing this, my mind wandered: would it be\nuseful to have metaphors in a programming language? I don't know;\nI don't have time to think about this. But it's convenient because\nthis is an example of what I mean by habits of mind. I spend a lot\nof time thinking about language design, and my habit of always \nasking \"would x be useful in a programming language\" just got\ninvoked.If new ideas arise like doodles, this would explain why you have\nto work at something for a while before you have any. It's not\njust that you can't judge ideas till you're an expert in a field.\nYou won't even generate ideas, because you won't have any habits\nof mind to invoke.Of course the habits of mind you invoke on some field don't have\nto be derived from working in that field. In fact, it's often\nbetter if they're not. You're not just looking for good ideas, but\nfor good new ideas, and you have a better chance of generating\nthose if you combine stuff from distant fields. As hackers, one\nof our habits of mind is to ask, could one open-source x? For \nexample, what if you made an open-source operating system? A fine\nidea, but not very novel. Whereas if you ask, could you make an\nopen-source play? you might be onto something.Are some kinds of work better sources of habits of mind than others?\nI suspect harder fields may be better sources, because to attack\nhard problems you need powerful solvents. I find math is a good\nsource of metaphors-- good enough that it's worth studying just for\nthat. Related fields are also good sources, especially when they're\nrelated in unexpected ways. Everyone knows computer science and\nelectrical engineering are related, but precisely because everyone\nknows it, importing ideas from one to the other doesn't yield great\nprofits. It's like importing something from Wisconsin to Michigan. \nWhereas (I claim) hacking and painting are\nalso related, in the sense that hackers and painters are both \nmakers,\nand this source of new ideas is practically virgin territory.ProblemsIn theory you could stick together ideas at random and see what you\ncame up with. What if you built a peer-to-peer dating site? Would\nit be useful to have an automatic book? Could you turn theorems\ninto a commodity? When you assemble ideas at random like this, \nthey may not be just stupid, but semantically ill-formed. What \nwould it even mean to make theorems a commodity? You got me. I\ndidn't think of that idea, just its name.You might come up with something useful this way, but I never have.\nIt's like knowing a fabulous sculpture is hidden inside a block of\nmarble, and all you have to do is remove the marble that isn't part\nof it. It's an encouraging thought, because it reminds you there \nis an answer, but it's not much use in practice because the search\nspace is too big.I find that to have good ideas I need to be working on some problem.\nYou can't start with randomness. You have to start with a problem,\nthen let your mind wander just far enough for new ideas to form.In a way, it's harder to see problems than their solutions. Most \npeople prefer to remain in denial about problems. It's obvious\nwhy: problems are irritating. They're problems! Imagine if people\nin 1700 saw their lives the way we'd see them. It would have been\nunbearable. This denial is such a powerful force that, even when \npresented with possible solutions, people often prefer to believe\nthey wouldn't work.I saw this phenomenon when I worked on spam filters. In 2002, most\npeople preferred to ignore spam, and most of those who didn't\npreferred to believe the heuristic filters then available were the\nbest you could do.I found spam intolerable, and I felt it had to be possible to\nrecognize it statistically. And it turns out that was all you \nneeded to solve the problem. The algorithm I used was ridiculously\nsimple. Anyone who'd really tried to solve the problem would have\nfound it. It was just that no one had really tried to solve the\nproblem.\n[3]Let me repeat that recipe: finding the problem intolerable and \nfeeling it must be possible to solve it. Simple as it seems, that's\nthe recipe for a lot of startup ideas.WealthSo far most of what I've said applies to ideas in general. What's \nspecial about startup ideas? Startup ideas are ideas for companies,\nand companies have to make money. And the way to make money is to\nmake something people want.Wealth is what people want. I don't mean that as some kind of \nphilosophical statement; I mean it as a tautology.So an idea for a startup is an idea for something people want.\nWouldn't any good idea be something people want? Unfortunately \nnot. I think new theorems are a fine thing to create, but there\nis no great demand for them. Whereas there appears to be great\ndemand for celebrity gossip magazines. Wealth is defined democratically.\nGood ideas and valuable ideas are not quite the same thing; the\ndifference is individual tastes.But valuable ideas are very close to good ideas, especially in\ntechnology. I think they're so close that you can get away with\nworking as if the goal were to discover good ideas, so long as, in\nthe final stage, you stop and ask: will people actually pay for \nthis? Only a few ideas are likely to make it that far and then get\nshot down; RPN calculators might be one example.One way to make something people want is to look at stuff people \nuse now that's broken. Dating sites are a prime example. They \nhave millions of users, so they must be promising something people \nwant. And yet they work horribly. Just ask anyone who uses them. \nIt's as if they used the worse-is-better approach but stopped after\nthe first stage and handed the thing over to marketers.Of course, the most obvious breakage in the average computer user's \nlife is Windows itself. But this is a special case: you can't\ndefeat a monopoly by a frontal attack. Windows can and will be \noverthrown, but not by giving people a better desktop OS. The way\nto kill it is to redefine the problem as a superset of the current \none. The problem is not, what operating system should people use\non desktop computers? but how should people use applications?\nThere are answers to that question that don't even involve desktop\ncomputers.Everyone thinks Google is going to solve this problem, but it is a\nvery subtle one, so subtle that a company as big as Google might\nwell get it wrong. I think the odds are better than 50-50 that the\nWindows killer-- or more accurately, Windows transcender-- will\ncome from some little startup.Another classic way to make something people want is to take a\nluxury and make it into a commmodity. People must want something\nif they pay a lot for it. And it is a very rare product that can't\nbe made dramatically cheaper if you try.This was Henry Ford's plan. He made cars, which had been a luxury\nitem, into a commodity. But the idea is much older than Henry Ford.\nWater mills transformed mechanical power from a luxury into a\ncommodity, and they were used in the Roman empire. Arguably\npastoralism transformed a luxury into a commodity.When you make something cheaper you can sell more of them. But if\nyou make something dramatically cheaper you often get qualitative\nchanges, because people start to use it in different ways. For\nexample, once computers get so cheap that most people can have one\nof their own, you can use them as communication devices.Often to make something dramatically cheaper you have to redefine \nthe problem. The Model T didn't have all the features previous\ncars did. It only came in black, for example. But it solved the\nproblem people cared most about, which was getting from place to\nplace.One of the most useful mental habits I know I learned from Michael\nRabin: that the best way to solve a problem is often to redefine\nit. A lot of people use this technique without being consciously\naware of it, but Rabin was spectacularly explicit. You need a big\nprime number? Those are pretty expensive. How about if I give you\na big number that only has a 10 to the minus 100 chance of not being\nprime? Would that do? Well, probably; I mean, that's probably\nsmaller than the chance that I'm imagining all this anyway.Redefining the problem is a particularly juicy heuristic when you\nhave competitors, because it's so hard for rigid-minded people to \nfollow. You can work in plain sight and they don't realize the \ndanger. Don't worry about us. We're just working on search. Do \none thing and do it well, that's our motto.Making things cheaper is actually a subset of a more general\ntechnique: making things easier. For a long time it was most of \nmaking things easier, but now that the things we build are so\ncomplicated, there's another rapidly growing subset: making things \neasier to use.This is an area where there's great room for improvement. What you\nwant to be able to say about technology is: it just works. How\noften do you say that now?Simplicity takes effort-- genius, even. The average programmer \nseems to produce UI designs that are almost willfully bad. I was \ntrying to use the stove at my mother's house a couple weeks ago. \nIt was a new one, and instead of physical knobs it had buttons and\nan LED display. I tried pressing some buttons I thought would cause\nit to get hot, and you know what it said? \"Err.\" Not even \"Error.\"\n\"Err.\" You can't just say \"Err\" to the user of a stove.\nYou should design the UI so that errors are impossible. And the \nboneheads who designed this stove even had an example of such a UI\nto work from: the old one. You turn one knob to set the temperature\nand another to set the timer. What was wrong with that? It just\nworked.It seems that, for the average engineer, more options just means\nmore rope to hang yourself. So if you want to start a startup, you\ncan take almost any existing technology produced by a big company, \nand assume you could build something way easier to use.Design for ExitSuccess for a startup approximately equals getting bought. You\nneed some kind of exit strategy, because you can't get the smartest\npeople to work for you without giving them options likely to be\nworth something. Which means you either have to get bought or go\npublic, and the number of startups that go public is very small.If success probably means getting bought, should you make that a\nconscious goal? The old answer was no: you were supposed to pretend\nthat you wanted to create a giant, public company, and act surprised\nwhen someone made you an offer. Really, you want to buy us? Well,\nI suppose we'd consider it, for the right price.I think things are changing. If 98% of the time success means \ngetting bought, why not be open about it? If 98% of the time you're\ndoing product development on spec for some big company, why not\nthink of that as your task? One advantage of this approach is that\nit gives you another source of ideas: look at big companies, think\nwhat they should \nbe doing, and do it yourself. Even if\nthey already know it, you'll probably be done faster.Just be sure to make something multiple acquirers will want. Don't\nfix Windows, because the only potential acquirer is Microsoft, and \nwhen there's only one acquirer, they don't have to hurry. They can\ntake their time and copy you instead of buying you. If you want\nto get market price, work on something where there's competition.If an increasing number of startups are created to do product\ndevelopment on spec, it will be a natural counterweight to monopolies.\nOnce some type of technology is captured by a monopoly, it will \nonly evolve at big company rates instead of startup rates, whereas\nalternatives will evolve with especial speed. A free market\ninterprets monopoly as damage and routes around it.The Woz RouteThe most productive way to generate startup ideas is also the\nmost unlikely-sounding: by accident. If you look at how famous\nstartups got started, a lot of them weren't initially supposed to \nbe startups. Lotus began with a program Mitch Kapor wrote for a\nfriend. Apple got started because Steve Wozniak wanted to build\nmicrocomputers, and his employer, Hewlett-Packard, wouldn't let him\ndo it at work. Yahoo began as David Filo's personal collection of\nlinks.This is not the only way to start startups. You can sit down and\nconsciously come up with an idea for a company; we did. But measured\nin total market cap, the build-stuff-for-yourself model might be \nmore fruitful. It certainly has to be the most fun way to come up\nwith startup ideas. And since a startup ought to have multiple\nfounders who were already friends before they decided to start a \ncompany, the rather surprising conclusion is that the best way to \ngenerate startup ideas is to do what hackers do for fun: cook up\namusing hacks with your friends.It seems like it violates some kind of conservation law, but there\nit is: the best way to get a \"million dollar idea\" is just to do\nwhat hackers enjoy doing anyway.\nNotes[1]\nThis phenomenon may account for a number of discrepancies\ncurrently blamed on various forbidden isms. Never attribute to \nmalice what can be explained by math.[2] \nA lot of classic abstract expressionism is doodling of this type:\nartists trained to paint from life using the same gestures but\nwithout using them to represent anything. This explains why such\npaintings are (slightly) more interesting than random marks would be.[3]\nBill Yerazunis had solved the problem, but he got there by\nanother path. He made a general-purpose file classifier so good\nthat it also worked for spam." }, { "path": "data/PaulGrahamEssays/identity.txt", "content": "February 2009I finally realized today why politics and religion yield such\nuniquely useless discussions.As a rule, any mention of religion on an online forum degenerates\ninto a religious argument. Why? Why does this happen with religion\nand not with Javascript or baking or other topics people talk about\non forums?What's different about religion is that people don't feel they need\nto have any particular expertise to have opinions about\nit. All they need is strongly held beliefs, and anyone can have\nthose. No thread about Javascript will grow as fast as one about\nreligion, because people feel they have to be over some threshold\nof expertise to post comments about that. But on religion everyone's\nan expert.Then it struck me: this is the problem with politics too. Politics,\nlike religion, is a topic where there's no threshold of expertise\nfor expressing an opinion. All you need is strong convictions.Do religion and politics have something in common that explains\nthis similarity? One possible explanation is that they deal with\nquestions that have no definite answers, so there's no back pressure\non people's opinions. Since no one can be proven wrong, every\nopinion is equally valid, and sensing this, everyone lets fly with\ntheirs.But this isn't true. There are certainly some political questions\nthat have definite answers, like how much a new government policy\nwill cost. But the more precise political questions suffer the\nsame fate as the vaguer ones.I think what religion and politics have in common is that they\nbecome part of people's identity, and people can never have a\nfruitful argument about something that's part of their identity.\nBy definition they're partisan.Which topics engage people's identity depends on the people, not\nthe topic. For example, a discussion about a battle that included\ncitizens of one or more of the countries involved would probably\ndegenerate into a political argument. But a discussion today about\na battle that took place in the Bronze Age probably wouldn't. No\none would know what side to be on. So it's not politics that's the\nsource of the trouble, but identity. When people say a discussion\nhas degenerated into a religious war, what they really mean is that\nit has started to be driven mostly by people's identities.\n[1]Because the point at which this happens depends on the people rather\nthan the topic, it's a mistake to conclude that because a question\ntends to provoke religious wars, it must have no answer. For example,\nthe question of the relative merits of programming languages often\ndegenerates into a religious war, because so many programmers\nidentify as X programmers or Y programmers. This sometimes leads\npeople to conclude the question must be unanswerable—that all\nlanguages are equally good. Obviously that's false: anything else\npeople make can be well or badly designed; why should this be\nuniquely impossible for programming languages? And indeed, you can\nhave a fruitful discussion about the relative merits of programming\nlanguages, so long as you exclude people who respond from identity.More generally, you can have a fruitful discussion about a topic\nonly if it doesn't engage the identities of any of the\nparticipants. What makes politics and religion such minefields is\nthat they engage so many people's identities. But you could in\nprinciple have a useful conversation about them with some people.\nAnd there are other topics that might seem harmless, like the\nrelative merits of Ford and Chevy pickup trucks, that you couldn't\nsafely talk about with others.The most intriguing thing about this theory, if it's right, is that\nit explains not merely which kinds of discussions to avoid, but how\nto have better ideas. If people can't think clearly about anything\nthat has become part of their identity, then all other things being\nequal, the best plan is to let as few things into your identity as\npossible. \n[2]Most people reading this will already be fairly tolerant. But there\nis a step beyond thinking of yourself as x but tolerating y: not\neven to consider yourself an x. The more labels you have for\nyourself, the dumber they make you.Notes[1]\nWhen that happens, it tends to happen fast, like a core going\ncritical. The threshold for participating goes down to zero, which\nbrings in more people. And they tend to say incendiary things,\nwhich draw more and angrier counterarguments.[2]\nThere may be some things it's a net win to include in your\nidentity. For example, being a scientist. But arguably that is\nmore of a placeholder than an actual label—like putting NMI on a\nform that asks for your middle initial—because it doesn't commit\nyou to believing anything in particular. A scientist isn't committed\nto believing in natural selection in the same way a biblical\nliteralist is committed to rejecting it. All he's committed to is\nfollowing the evidence wherever it leads.Considering yourself a scientist is equivalent to putting a sign\nin a cupboard saying \"this cupboard must be kept empty.\" Yes,\nstrictly speaking, you're putting something in the cupboard, but\nnot in the ordinary sense.Thanks to Sam Altman, Trevor Blackwell, Paul Buchheit, and Robert\nMorris for reading drafts of this." }, { "path": "data/PaulGrahamEssays/iflisp.txt", "content": "May 2003If Lisp is so great, why don't more people use it? I was \nasked this question by a student in the audience at a \ntalk I gave recently. Not for the first time, either.In languages, as in so many things, there's not much \ncorrelation between popularity and quality. Why does \nJohn Grisham (King of Torts sales rank, 44) outsell\nJane Austen (Pride and Prejudice sales rank, 6191)?\nWould even Grisham claim that it's because he's a better\nwriter?Here's the first sentence of Pride and Prejudice:\n\nIt is a truth universally acknowledged, that a single man \nin possession of a good fortune must be in want of a\nwife.\n\n\"It is a truth universally acknowledged?\" Long words for\nthe first sentence of a love story.Like Jane Austen, Lisp looks hard. Its syntax, or lack\nof syntax, makes it look completely unlike \nthe languages\nmost people are used to. Before I learned Lisp, I was afraid\nof it too. I recently came across a notebook from 1983\nin which I'd written:\n\nI suppose I should learn Lisp, but it seems so foreign.\n\nFortunately, I was 19 at the time and not too resistant to learning\nnew things. I was so ignorant that learning\nalmost anything meant learning new things.People frightened by Lisp make up other reasons for not\nusing it. The standard\nexcuse, back when C was the default language, was that Lisp\nwas too slow. Now that Lisp dialects are among\nthe faster\nlanguages available, that excuse has gone away.\nNow the standard excuse is openly circular: that other languages\nare more popular.(Beware of such reasoning. It gets you Windows.)Popularity is always self-perpetuating, but it's especially\nso in programming languages. More libraries\nget written for popular languages, which makes them still\nmore popular. Programs often have to work with existing programs,\nand this is easier if they're written in the same language,\nso languages spread from program to program like a virus.\nAnd managers prefer popular languages, because they give them \nmore leverage over developers, who can more easily be replaced.Indeed, if programming languages were all more or less equivalent,\nthere would be little justification for using any but the most\npopular. But they aren't all equivalent, not by a long\nshot. And that's why less popular languages, like Jane Austen's \nnovels, continue to survive at all. When everyone else is reading \nthe latest John Grisham novel, there will always be a few people \nreading Jane Austen instead." }, { "path": "data/PaulGrahamEssays/ineq.txt", "content": "\nJanuary 2016Since the 1970s, economic inequality in the US has increased\ndramatically. And in particular, the rich have gotten a lot richer.\nNearly everyone who writes about the topic says that economic inequality\nshould be decreased.I'm interested in this question because I was one of the founders of\na company called Y Combinator that helps people start startups.\nAlmost by definition, if a startup succeeds, its founders become\nrich. Which means by helping startup founders I've been helping to\nincrease economic inequality. If economic inequality should be \ndecreased, I shouldn't be helping founders. No one should\nbe.But that doesn't sound right. What's going on here? What's going\non is that while economic inequality is a single measure (or more\nprecisely, two: variation in income, and variation in wealth), it\nhas multiple causes. Many of these causes are bad, like tax loopholes\nand drug addiction. But some are good, like Larry Page and\nSergey Brin starting the company you use to find things online.If you want to understand economic inequality — and more importantly,\nif you actually want to fix the bad aspects of it — you have to\ntease apart the components. And yet the trend in nearly everything\nwritten about the subject is to do the opposite: to squash together\nall the aspects of economic inequality as if it were a single\nphenomenon.Sometimes this is done for ideological reasons. Sometimes it's\nbecause the writer only has very high-level data and so draws\nconclusions from that, like the proverbial drunk who looks for his\nkeys under the lamppost, instead of where he dropped them, because the\nlight is better there. Sometimes it's because the writer doesn't\nunderstand critical aspects of inequality, like the role of technology\nin wealth creation. Much of the time, perhaps most of the time,\nwriting about economic inequality combines all three.___The most common mistake people make about economic inequality is\nto treat it as a single phenomenon. The most naive version of which\nis the one based on the pie fallacy: that the rich get rich by\ntaking money from the poor.Usually this is an assumption people start from rather than a\nconclusion they arrive at by examining the evidence. Sometimes the\npie fallacy is stated explicitly:\n\n ...those at the top are grabbing an increasing fraction of the\n nation's income — so much of a larger share that what's left over\n for the rest is diminished....\n[1]\n\nOther times it's more unconscious. But the unconscious form is very\nwidespread. I think because we grow up in a world where the pie\nfallacy is actually true. To kids, wealth is a fixed pie\nthat's shared out, and if one person gets more, it's at the expense\nof another. It takes a conscious effort to remind oneself that the\nreal world doesn't work that way.In the real world you can create wealth as well as taking it from\nothers. A woodworker creates wealth. He makes a chair, and you\nwillingly give him money in return for it. A high-frequency trader\ndoes not. He makes a dollar only when someone on the other end of\na trade loses a dollar.If the rich people in a society got that way by taking wealth from\nthe poor, then you have the degenerate case of economic inequality,\nwhere the cause of poverty is the same as the cause of wealth. But\ninstances of inequality don't have to be instances of the degenerate\ncase. If one woodworker makes 5 chairs and another makes none, the\nsecond woodworker will have less money, but not because anyone took\nanything from him.Even people sophisticated enough to know about the pie fallacy are\nled toward it by the custom of describing economic inequality as a\nratio of one quantile's income or wealth to another's. It's so\neasy to slip from talking about income shifting from one quantile\nto another, as a figure of speech, into believing that is literally\nwhat's happening.Except in the degenerate case, economic inequality can't be described\nby a ratio or even a curve. In the general case it consists of\nmultiple ways people become poor, and multiple ways people become\nrich. Which means to understand economic inequality in a country,\nyou have to go find individual people who are poor or rich and\nfigure out why.\n[2]If you want to understand change in economic inequality, you\nshould ask what those people would have done when it was different.\nThis is one way I know the rich aren't all getting richer simply\nfrom some new system for transferring wealth to them from\neveryone else. When you use the would-have method with startup\nfounders, you find what most would have done \nback in 1960, when\neconomic inequality was lower, was to join big companies or become\nprofessors. Before Mark Zuckerberg started Facebook, his default\nexpectation was that he'd end up working at Microsoft. The reason\nhe and most other startup founders are richer than they would have\nbeen in the mid 20th century is not because of some right turn the\ncountry took during the Reagan administration, but because progress\nin technology has made it much easier to start a new company that\ngrows fast.Traditional economists seem strangely averse to studying individual\nhumans. It seems to be a rule with them that everything has to start\nwith statistics. So they give you very precise numbers about\nvariation in wealth and income, then follow it with the most naive\nspeculation about the underlying causes.But while there are a lot of people who get rich through rent-seeking\nof various forms, and a lot who get rich by playing zero-sum games, \nthere are also a significant number\nwho get rich by creating wealth. And creating wealth, as a source\nof economic inequality, is different from taking it — not just\nmorally, but also practically, in the sense that it is harder to\neradicate. One reason is that variation in productivity is\naccelerating. The rate at which individuals can create wealth\ndepends on the technology available to them, and that grows\nexponentially. The other reason creating wealth is such a tenacious\nsource of inequality is that it can expand to accommodate a lot of\npeople.___I'm all for shutting down the crooked ways to get rich. But that\nwon't eliminate great variations in wealth, because as long as you leave\nopen the option of getting rich by creating wealth, people who want\nto get rich will do that instead.Most people who get rich tend to be fairly driven. Whatever their\nother flaws, laziness is usually not one of them. Suppose new\npolicies make it hard to make a fortune in finance. Does it seem\nplausible that the people who currently go into finance to make\ntheir fortunes will continue to do so, but be content to work for\nordinary salaries? The reason they go into finance is not because\nthey love finance but because they want to get rich. If the only\nway left to get rich is to start startups, they'll start startups.\nThey'll do well at it too, because determination is the main factor\nin the success of a startup. \n[3]\nAnd while it would probably be\na good thing for the world if people who wanted to get rich switched\nfrom playing zero-sum games to creating wealth, that would not only\nnot eliminate great variations in wealth, but might even \nexacerbate them.\nIn a zero-sum game there is at least a limit to the upside. Plus\na lot of the new startups would create new technology that further\naccelerated variation in productivity.Variation in productivity is far from the only source of economic\ninequality, but it is the irreducible core of it, in the sense that\nyou'll have that left when you eliminate all other sources. And if\nyou do, that core will be big, because it will have expanded to\ninclude the efforts of all the refugees. Plus it will have a large\nBaumol penumbra around it: anyone who could get rich by creating\nwealth on their own account will have to be paid enough to prevent\nthem from doing it.You can't prevent great variations in wealth without preventing people\nfrom getting rich, and you can't do that without preventing them\nfrom starting startups.So let's be clear about that. Eliminating great variations in wealth would\nmean eliminating startups. And that doesn't seem a wise move.\nEspecially since it would only mean you eliminated\nstartups in your own country. Ambitious people already move halfway\naround the world to further their careers, and startups can operate\nfrom anywhere nowadays. So if you made it impossible to get rich\nby creating wealth in your country, people who wanted to do that\nwould just leave and do it somewhere else. Which would\ncertainly get you a lower Gini coefficient, along with a lesson in\nbeing careful what you ask for. \n[4]I think rising economic inequality is the inevitable fate of countries\nthat don't choose something worse. We had a 40 year stretch in the\nmiddle of the 20th century that convinced some people otherwise.\nBut as I explained in The Refragmentation,\nthat was an anomaly — a\nunique combination of circumstances that compressed American society\nnot just economically but culturally too.\n[5]And while some of the growth in economic inequality we've seen since\nthen has been due to bad behavior of various kinds, there has\nsimultaneously been a huge increase in individuals' ability to\ncreate wealth. Startups are almost entirely a product of this\nperiod. And even within the startup world, there has been a qualitative\nchange in the last 10 years. Technology has decreased the cost of\nstarting a startup so much that founders now have the upper hand\nover investors. Founders get less diluted, and it is now common\nfor them to retain \nboard control as well. Both further increase\neconomic inequality, the former because founders own more stock,\nand the latter because, as investors have learned, founders tend\nto be better at running their companies than investors.While the surface manifestations change, the underlying forces are\nvery, very old. The acceleration of productivity we see in Silicon\nValley has been happening for thousands of years. If you look at\nthe history of stone tools, technology was already accelerating in\nthe Mesolithic. The acceleration would have been too slow to\nperceive in one lifetime. Such is the nature of the leftmost part\nof an exponential curve. But it was the same curve.You do not want to design your society in a way that's incompatible\nwith this curve. The evolution of technology is one of the most\npowerful forces in history.Louis Brandeis said \"We may have democracy, or we may have wealth\nconcentrated in the hands of a few, but we can't have both.\" That\nsounds plausible. But if I have to choose between ignoring him and\nignoring an exponential curve that has been operating for thousands\nof years, I'll bet on the curve. Ignoring any trend that has been\noperating for thousands of years is dangerous. But exponential\ngrowth, especially, tends to bite you.___If accelerating variation in productivity is always going to produce\nsome baseline growth in economic inequality, it would be a good\nidea to spend some time thinking about that future. Can you have\na healthy society with great variation in wealth? What would it\nlook like?Notice how novel it feels to think about that. The public conversation\nso far has been exclusively about the need to decrease economic\ninequality. We've barely given a thought to how to live with it.I'm hopeful we'll be able to. Brandeis was a product of the Gilded\nAge, and things have changed since then. It's harder to hide\nwrongdoing now. And to get rich now you don't have to buy politicians\nthe way railroad or oil magnates did. \n[6]\nThe great concentrations\nof wealth I see around me in Silicon Valley don't seem to be\ndestroying democracy.There are lots of things wrong with the US that have economic\ninequality as a symptom. We should fix those things. In the process\nwe may decrease economic inequality. But we can't start from the\nsymptom and hope to fix the underlying causes.\n[7]The most obvious is poverty. I'm sure most of those who want to\ndecrease economic inequality want to do it mainly to help the poor,\nnot to hurt the rich. \n[8]\nIndeed, a good number are merely being\nsloppy by speaking of decreasing economic inequality when what they\nmean is decreasing poverty. But this is a situation where it would\nbe good to be precise about what we want. Poverty and economic\ninequality are not identical. When the city is turning off your\nwater\nbecause you can't pay the bill, it doesn't make any difference\nwhat Larry Page's net worth is compared to yours. He might only\nbe a few times richer than you, and it would still be just as much\nof a problem that your water was getting turned off.Closely related to poverty is lack of social mobility. I've seen\nthis myself: you don't have to grow up rich or even upper middle\nclass to get rich as a startup founder, but few successful founders\ngrew up desperately poor. But again, the problem here is not simply\neconomic inequality. There is an enormous difference in wealth\nbetween the household Larry Page grew up in and that of a successful\nstartup founder, but that didn't prevent him from joining their\nranks. It's not economic inequality per se that's blocking social\nmobility, but some specific combination of things that go wrong\nwhen kids grow up sufficiently poor.One of the most important principles in Silicon Valley is that \"you\nmake what you measure.\" It means that if you pick some number to\nfocus on, it will tend to improve, but that you have to choose the\nright number, because only the one you choose will improve; another\nthat seems conceptually adjacent might not. For example, if you're\na university president and you decide to focus on graduation rates,\nthen you'll improve graduation rates. But only graduation rates,\nnot how much students learn. Students could learn less, if to\nimprove graduation rates you made classes easier.Economic inequality is sufficiently far from identical with the\nvarious problems that have it as a symptom that we'll probably only\nhit whichever of the two we aim at. If we aim at economic inequality,\nwe won't fix these problems. So I say let's aim at the problems.For example, let's attack poverty, and if necessary damage wealth\nin the process. That's much more likely to work than attacking\nwealth in the hope that you will thereby fix poverty.\n[9]\nAnd if\nthere are people getting rich by tricking consumers or lobbying the\ngovernment for anti-competitive regulations or tax loopholes, then\nlet's stop them. Not because it's causing economic inequality, but\nbecause it's stealing.\n[10]If all you have is statistics, it seems like that's what you need\nto fix. But behind a broad statistical measure like economic\ninequality there are some things that are good and some that are\nbad, some that are historical trends with immense momentum and\nothers that are random accidents. If we want to fix the world\nbehind the statistics, we have to understand it, and focus our\nefforts where they'll do the most good.Notes[1]\nStiglitz, Joseph. The Price of Inequality. Norton, 2012. p.\n32.[2]\nParticularly since economic inequality is a matter of outliers,\nand outliers are disproportionately likely to have gotten where\nthey are by ways that have little do with the sort of things\neconomists usually think about, like wages and productivity, but\nrather by, say, ending up on the wrong side of the \"War on Drugs.\"[3]\nDetermination is the most important factor in deciding between\nsuccess and failure, which in startups tend to be sharply differentiated.\nBut it takes more than determination to create one of the hugely\nsuccessful startups. Though most founders start out excited about\nthe idea of getting rich, purely mercenary founders will usually\ntake one of the big acquisition offers most successful startups get\non the way up. The founders who go on to the next stage tend to\nbe driven by a sense of mission. They have the same attachment to\ntheir companies that an artist or writer has to their work. But\nit is very hard to predict at the outset which founders will do\nthat. It's not simply a function of their initial attitude. Starting\na company changes people.[4]\nAfter reading a draft of this essay, Richard Florida told me\nhow he had once talked to a group of Europeans \"who said\n they wanted to make Europe more entrepreneurial and more\n like Silicon Valley. I said by definition this will give you more\n inequality. They thought I was insane — they could not process\n it.\"[5]\nEconomic inequality has been decreasing globally. But this\nis mainly due to the erosion of the kleptocracies that formerly\ndominated all the poorer countries. Once the playing field is\nleveler politically, we'll see economic inequality start to rise\nagain. The US is the bellwether. The situation we face here, the\nrest of the world will sooner or later.[6]\nSome people still get rich by buying politicians. My point is that\nit's no longer a precondition.[7]\nAs well as problems that have economic inequality as a symptom,\nthere are those that have it as a cause. But in most if not all,\neconomic inequality is not the primary cause. There is usually\nsome injustice that is allowing economic inequality to turn into\nother forms of inequality, and that injustice is what we need to\nfix. For example, the police in the US treat the poor worse than\nthe rich. But the solution is not to make people richer. It's to\nmake the police treat people more equitably. Otherwise they'll\ncontinue to maltreat people who are weak in other ways.[8]\nSome who read this essay will say that I'm clueless or even\nbeing deliberately misleading by focusing so much on the richer end\nof economic inequality — that economic inequality is really about\npoverty. But that is exactly the point I'm making, though sloppier\nlanguage than I'd use to make it. The real problem is poverty, not\neconomic inequality. And if you conflate them you're aiming at the\nwrong target.Others will say I'm clueless or being misleading by focusing on\npeople who get rich by creating wealth — that startups aren't the\nproblem, but corrupt practices in finance, healthcare, and so on.\nOnce again, that is exactly my point. The problem is not economic\ninequality, but those specific abuses.It's a strange task to write an essay about why something isn't the\nproblem, but that's the situation you find yourself in when so many\npeople mistakenly think it is.[9]\nParticularly since many causes of poverty are only partially\ndriven by people trying to make money from them. For example,\nAmerica's abnormally high incarceration rate is a major cause of\npoverty. But although for-profit prison companies and \nprison guard unions both spend \na lot lobbying for harsh sentencing laws, they\nare not the original source of them.[10]\nIncidentally, tax loopholes are definitely not a product\nof some power shift due to recent increases in economic inequality.\nThe golden age of economic equality in the mid 20th century was\nalso the golden age of tax avoidance. Indeed, it was so widespread\nand so effective that I'm skeptical whether economic inequality was\nreally so low then as we think. In a period when people are trying\nto hide wealth from the government, it will tend to be hidden from\nstatistics too. One sign of the potential magnitude of the problem\nis the discrepancy between government receipts as a percentage of\nGDP, which have remained more or less constant during the entire\nperiod from the end of World War II to the present, and tax rates,\nwhich have varied dramatically.\nThanks to Sam Altman, Tiffani Ashley Bell, Patrick Collison, Ron\nConway, Richard Florida, Ben Horowitz, Jessica Livingston, Robert\nMorris, Tim O'Reilly, Max Roser, and Alexia Tsotsis for reading\ndrafts of this.Note: This is a new version from which I\nremoved a pair of metaphors that made a lot of people mad, \nessentially by macroexpanding them. If anyone wants to see \nthe old version, I put it here.Related:" }, { "path": "data/PaulGrahamEssays/inequality.txt", "content": "August 2005(This essay is derived from a talk at Defcon 2005.)Suppose you wanted to get rid of economic inequality. There are\ntwo ways to do it: give money to the poor, or take it away from the \nrich. But they amount to the same thing, because if you want to\ngive money to the poor, you have to get it from somewhere. You\ncan't get it from the poor, or they just end up where they started.\nYou have to get it from the rich.There is of course a way to make the poor richer without simply\nshifting money from the rich. You could help the poor become more\nproductive — for example, by improving access to education. Instead\nof taking money from engineers and giving it to checkout clerks,\nyou could enable people who would have become checkout clerks to\nbecome engineers.This is an excellent strategy for making the poor richer. But the\nevidence of the last 200 years shows that it doesn't reduce economic\ninequality, because it makes the rich richer too. If there\nare more engineers, then there are more opportunities to hire them\nand to sell them things. Henry Ford couldn't have made a fortune \nbuilding cars in a society in which most people were still subsistence\nfarmers; he would have had neither workers nor customers.If you want to reduce economic inequality instead of just improving\nthe overall standard of living, it's not enough just to raise up \nthe poor. What if one of your newly minted engineers gets ambitious\nand goes on to become another Bill Gates? Economic inequality will\nbe as bad as ever. If you actually want to compress the gap between\nrich and poor, you have to push down on the top as well as pushing\nup on the bottom.How do you push down on the top? You could try to decrease the\nproductivity of the people who make the most money: make the best \nsurgeons operate with their left hands, force popular actors to\novereat, and so on. But this approach is hard to implement. The\nonly practical solution is to let people do the best work they can,\nand then (either by taxation or by limiting what they can charge)\nto confiscate whatever you deem to be surplus.So let's be clear what reducing economic inequality means. It is \nidentical with taking money from the rich.When you transform a mathematical expression into another form, you\noften notice new things. So it is in this case. Taking money from\nthe rich turns out to have consequences one might not foresee when\none phrases the same idea in terms of \"reducing inequality.\"The problem is, risk and reward have to be proportionate. A bet \nwith only a 10% chance of winning has to pay more than one with a\n50% chance of winning, or no one will take it. So if you lop off\nthe top of the possible rewards, you thereby decrease people's\nwillingness to take risks.Transposing into our original expression, we get: decreasing economic\ninequality means decreasing the risk people are willing to take.There are whole classes of risks that are no longer worth taking \nif the maximum return is decreased. One reason high tax rates are\ndisastrous is that this class of risks includes starting new\ncompanies.InvestorsStartups are intrinsically risky. A startup\nis like a small boat\nin the open sea. One big wave and you're sunk. A competing product,\na downturn in the economy, a delay in getting funding or regulatory\napproval, a patent suit, changing technical standards, the departure\nof a key employee, the loss of a big account — any one of these can\ndestroy you overnight. It seems only about 1 in 10 startups succeeds.\n[1]Our startup paid its first round of outside investors 36x. Which \nmeant, with current US tax rates, that it made sense to invest in\nus if we had better than a 1 in 24 chance of succeeding. That \nsounds about right. That's probably roughly how we looked when we\nwere a couple of nerds with no business experience operating out\nof an apartment.If that kind of risk doesn't pay, venture investing, as we know it,\ndoesn't happen.That might be ok if there were other sources of capital for new\ncompanies. Why not just have the government, or some large\nalmost-government organization like Fannie Mae, do the venture\ninvesting instead of private funds?I'll tell you why that wouldn't work. Because then you're asking\ngovernment or almost-government employees to do the one thing they \nare least able to do: take risks.As anyone who has worked for the government knows, the important\nthing is not to make the right choices, but to make choices that\ncan be justified later if they fail. If there is a safe option,\nthat's the one a bureaucrat will choose. But that is exactly the \nwrong way to do venture investing. The nature of the business means\nthat you want to make terribly risky choices, if the upside looks\ngood enough.VCs are currently \npaid in a way that makes them \nfocus on the upside:\nthey get a percentage of the fund's gains. And that helps overcome\ntheir understandable fear of investing in a company run by nerds\nwho look like (and perhaps are) college students.If VCs weren't allowed to get rich, they'd behave like bureaucrats.\nWithout hope of gain, they'd have only fear of loss. And so they'd\nmake the wrong choices. They'd turn down the nerds in favor of the\nsmooth-talking MBA in a suit, because that investment would be\neasier to justify later if it failed.FoundersBut even if you could somehow redesign venture funding to work\nwithout allowing VCs to become rich, there's another kind of investor\nyou simply cannot replace: the startups' founders and early employees.What they invest is their time and ideas. But these are equivalent\nto money; the proof is that investors are willing (if forced) to\ntreat them as interchangeable, granting the same status to \"sweat \nequity\" and the equity they've purchased with cash.The fact that you're investing time doesn't change the relationship\nbetween risk and reward. If you're going to invest your time in\nsomething with a small chance of succeeding, you'll only do it if\nthere is a proportionately large payoff.\n[2]\nIf large payoffs aren't allowed, you may as well play it safe.Like many startup founders, I did it to get rich. But not because \nI wanted to buy expensive things. What I wanted was security. I \nwanted to make enough money that I didn't have to worry about money.\nIf I'd been forbidden to make enough from a startup to do this, I\nwould have sought security by some other means: for example, by\ngoing to work for a big, stable organization from which it would\nbe hard to get fired. Instead of busting my ass in a startup, I \nwould have tried to get a nice, low-stress job at a big research \nlab, or tenure at a university.That's what everyone does in societies where risk isn't rewarded.\nIf you can't ensure your own security, the next best thing is to\nmake a nest for yourself in some large organization where your\nstatus depends mostly on seniority.\n[3]Even if we could somehow replace investors, I don't see how we could\nreplace founders. Investors mainly contribute money, which in\nprinciple is the same no matter what the source. But the founders\ncontribute ideas. You can't replace those.Let's rehearse the chain of argument so far. I'm heading for a \nconclusion to which many readers will have to be dragged kicking \nand screaming, so I've tried to make each link unbreakable. Decreasing\neconomic inequality means taking money from the rich. Since risk\nand reward are equivalent, decreasing potential rewards automatically\ndecreases people's appetite for risk. Startups are intrinsically\nrisky. Without the prospect of rewards proportionate to the risk,\nfounders will not invest their time in a startup. Founders are\nirreplaceable. So eliminating economic inequality means eliminating\nstartups.Economic inequality is not just a consequence of startups.\nIt's the engine that drives them, in the same way a fall of water \ndrives a water mill. People start startups in the hope of becoming\nmuch richer than they were before. And if your society tries to\nprevent anyone from being much richer than anyone else, it will\nalso prevent one person from being much richer at t2 than t1.GrowthThis argument applies proportionately. It's not just that if you \neliminate economic inequality, you get no startups. To the extent \nyou reduce economic inequality, you decrease the number of startups.\n[4]\nIncrease taxes, and willingness to take risks decreases in\nproportion.And that seems bad for everyone. New technology and new jobs both\ncome disproportionately from new companies. Indeed, if you don't\nhave startups, pretty soon you won't have established companies\neither, just as, if you stop having kids, pretty soon you won't\nhave any adults.It sounds benevolent to say we ought to reduce economic inequality. \nWhen you phrase it that way, who can argue with you? Inequality\nhas to be bad, right? It sounds a good deal less benevolent to say\nwe ought to reduce the rate at which new companies are founded.\nAnd yet the one implies the other.Indeed, it may be that reducing investors' appetite for risk doesn't\nmerely kill off larval startups, but kills off the most promising\nones especially. Startups yield faster growth at greater risk than\nestablished companies. Does this trend also hold among startups?\nThat is, are the riskiest startups the ones that generate most\ngrowth if they succeed? I suspect the answer is yes. And that's \na chilling thought, because it means that if you cut investors'\nappetite for risk, the most beneficial startups are the first to \ngo.Not all rich people got that way from startups, of course. What\nif we let people get rich by starting startups, but taxed away all\nother surplus wealth? Wouldn't that at least decrease inequality?Less than you might think. If you made it so that people could\nonly get rich by starting startups, people who wanted to get rich\nwould all start startups. And that might be a great thing. But I\ndon't think it would have much effect on the distribution of wealth.\nPeople who want to get rich will do whatever they have to. If\nstartups are the only way to do it, you'll just get far more people\nstarting startups. (If you write the laws very carefully, that is.\nMore likely, you'll just get a lot of people doing things that can\nbe made to look on paper like startups.)If we're determined to eliminate economic inequality, there is still\none way out: we could say that we're willing to go ahead and do\nwithout startups. What would happen if we did?At a minimum, we'd have to accept lower rates of technological \ngrowth. If you believe that large, established companies could \nsomehow be made to develop new technology as fast as startups, the\nball is in your court to explain how. (If you can come up with a \nremotely plausible story, you can make a fortune writing business\nbooks and consulting for large companies.)\n[5]Ok, so we get slower growth. Is that so bad? Well, one reason\nit's bad in practice is that other countries might not agree to\nslow down with us. If you're content to develop new technologies\nat a slower rate than the rest of the world, what happens is that\nyou don't invent anything at all. Anything you might discover has\nalready been invented elsewhere. And the only thing you can offer \nin return is raw materials and cheap labor. Once you sink that\nlow, other countries can do whatever they like with you: install\npuppet governments, siphon off your best workers, use your women\nas prostitutes, dump their toxic waste on your territory — all the\nthings we do to poor countries now. The only defense is to isolate\nyourself, as communist countries did in the twentieth century. But\nthe problem then is, you have to become a police state to enforce \nit.\nWealth and PowerI realize startups are not the main target of those who want to\neliminate economic inequality. What they really dislike is the\nsort of wealth that becomes self-perpetuating through an alliance\nwith power. For example, construction firms that fund politicians'\ncampaigns in return for government contracts, or rich parents who \nget their children into good colleges by sending them to expensive\nschools designed for that purpose. But if you try to attack this type of wealth\nthrough economic policy, it's hard to hit without destroying\nstartups as collateral damage.The problem here is not wealth, but corruption. So why not go after\ncorruption?We don't need to prevent people from being rich if we can prevent\nwealth from translating into power. And there has been progress\non that front. Before he died of drink in 1925, Commodore Vanderbilt's\nwastrel grandson Reggie ran down pedestrians on five separate \noccasions, killing two of them. By 1969, when Ted Kennedy drove \noff the bridge at Chappaquiddick, the limit seemed to be down to \none. Today it may well be zero. But what's changed is not variation\nin wealth. What's changed is the ability to translate wealth into\npower.How do you break the connection between wealth and power? Demand \ntransparency. Watch closely how power is exercised, and demand an\naccount of how decisions are made. Why aren't all police interrogations\nvideotaped? Why did 36% of Princeton's class of 2007 come from\nprep schools, when only 1.7% of American kids attend them? Why did\nthe US really invade Iraq? Why don't government officials disclose\nmore about their finances, and why only during their term of office?A friend of mine who knows a lot about computer security says the\nsingle most important step is to log everything. Back when he was\na kid trying to break into computers, what worried him most was the\nidea of leaving a trail. He was more inconvenienced by the need \nto avoid that than by any obstacle deliberately put in his path.Like all illicit connections, the connection between wealth and \npower flourishes in secret. Expose all transactions, and you will\ngreatly reduce it. Log everything. That's a strategy that already\nseems to be working, and it doesn't have the side effect of making\nyour whole country poor.I don't think many people realize there is a connection between\neconomic inequality and risk. I didn't fully grasp it till recently.\nI'd known for years of course that if one didn't score in a startup,\nthe other alternative was to get a cozy, tenured research job. But\nI didn't understand the equation governing my behavior. Likewise, \nit's obvious empirically that a country that doesn't let people get\nrich is headed for disaster, whether it's Diocletian's Rome or \nHarold Wilson's Britain. But I did not till recently understand\nthe role risk played.If you try to attack wealth, you end up nailing risk as well, and \nwith it growth. If we want a fairer world, I think we're better \noff attacking one step downstream, where wealth turns into power.Notes\n[1]\nSuccess here is defined from the initial investors' point of\nview: either an IPO, or an acquisition for more than the valuation\nat the last round of funding. The conventional 1 in 10 success rate\nis suspiciously neat, but conversations with VCs suggest it's roughly\ncorrect for startups overall. Top VC firms expect to do better.[2]\nI'm not claiming founders sit down and calculate the expected \nafter-tax return from a startup. They're motivated by examples of\nother people who did it. And those examples do reflect after-tax returns.[3]\nConjecture: The variation in wealth in a (non-corrupt) \ncountry or organization\nwill be inversely proportional to the prevalence of systems of\nseniority. So if you suppress variation in wealth, seniority will\nbecome correspondingly more important. So far, I know of no\ncounterexamples, though in very corrupt countries you may get \nboth simultaneously. (Thanks to Daniel Sobral for pointing\nthis out.)[4]\nIn a country with a truly feudal economy, you might be able to\nredistribute wealth successfully, because there are no startups to\nkill.[5]\nThe speed at which startups develop new techology is the other \nreason they pay so well. As I explained in \"How to Make Wealth\", what you do in a startup is compress a\nlifetime's worth of work into a few years. It seems as\ndumb to discourage that as to discourage risk-taking.\nThanks to Chris Anderson, Trevor Blackwell, Dan Giffin,\nJessica Livingston, and Evan Williams for reading drafts of this\nessay, and to Langley Steinert, Sangam Pant, and Mike Moritz for\ninformation about venture investing." }, { "path": "data/PaulGrahamEssays/investors.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nAugust 2006, rev. April 2007, September 2010In a few days it will be Demo Day, when the startups we funded\nthis summer present to investors. Y Combinator funds startups twice\na year, in January and June. Ten weeks later we invite all the\ninvestors we know to hear them present what they've built so far.Ten weeks is not much time. The average startup probably doesn't\nhave much to show for itself after ten weeks. But the average\nstartup fails. When you look at the ones that went on to do great\nthings, you find a lot that began with someone pounding out a\nprototype in a week or two of nonstop work. Startups are a\ncounterexample to the rule that haste makes waste.(Too much money seems to be as bad for startups as too much time,\nso we don't give them much money either.)A week before Demo Day, we have a dress rehearsal called Rehearsal Day.\nAt other Y Combinator events we allow outside guests, but not at\nRehearsal Day. No one except the other founders gets to see the rehearsals.The presentations on Rehearsal Day are often pretty rough. But this is\nto be expected. We try to pick founders who are good at building\nthings, not ones who are slick presenters. Some of the founders\nare just out of college, or even still in it, and have never spoken\nto a group of people they didn't already know.So we concentrate on the basics. On Demo Day each startup will\nonly get ten minutes, so we encourage them to focus on just two\ngoals: (a) explain what you're doing, and (b) explain why users\nwill want it.That might sound easy, but it's not when the speakers have no\nexperience presenting, and they're explaining technical matters to\nan audience that's mostly non-technical.This situation is constantly repeated when startups present to\ninvestors: people who are bad at explaining, talking to people who\nare bad at understanding. Practically every successful startup,\nincluding stars like Google, presented at some point to investors\nwho didn't get it and turned them down. Was it because the founders\nwere bad at presenting, or because the investors were obtuse? It's\nprobably always some of both.At the most recent Rehearsal Day, we four Y Combinator partners found\nourselves saying a lot of the same things we said at the last two.\nSo at dinner afterward we collected all our tips about presenting\nto investors. Most startups face similar challenges, so we hope\nthese will be useful to a wider audience.\n1. Explain what you're doing.Investors' main question when judging a very early startup is whether\nyou've made a compelling product. Before they can judge whether\nyou've built a good x, they have to understand what kind of x you've\nbuilt. They will get very frustrated if instead of telling them\nwhat you do, you make them sit through some kind of preamble.Say what you're doing as soon as possible, preferably in the first\nsentence. \"We're Jeff and Bob and we've built an easy to use web-based\ndatabase. Now we'll show it to you and explain why people need\nthis.\"If you're a great public speaker you may be able to violate this\nrule. Last year one founder spent the whole first half of his talk\non a fascinating analysis of the limits of the conventional desktop\nmetaphor. He got away with it, but unless you're a captivating\nspeaker, which most hackers aren't, it's better to play it safe.2. Get rapidly to demo.This section is now obsolete for YC founders presenting\nat Demo Day, because Demo Day presentations are now so short\nthat they rarely include much if any demo. They seem to work\njust as well without, however, which makes me think I was\nwrong to emphasize demos so much before.A demo explains what you've made more effectively than any verbal\ndescription. The only thing worth talking about first is the problem\nyou're trying to solve and why it's important. But don't spend\nmore than a tenth of your time on that. Then demo.When you demo, don't run through a catalog of features. Instead\nstart with the problem you're solving, and then show how your product\nsolves it. Show features in an order driven by some kind of purpose,\nrather than the order in which they happen to appear on the screen.If you're demoing something web-based, assume that the network\nconnection will mysteriously die 30 seconds into your presentation,\nand come prepared with a copy of the server software running on\nyour laptop.3. Better a narrow description than a vague one.One reason founders resist describing their projects concisely is\nthat, at this early stage, there are all kinds of possibilities.\nThe most concise descriptions seem misleadingly narrow. So for\nexample a group that has built an easy web-based database might\nresist calling their applicaton that, because it could be so much\nmore. In fact, it could be anything...The problem is, as you approach (in the calculus sense) a description\nof something that could be anything, the content of your description\napproaches zero. If you describe your web-based database as \"a\nsystem to allow people to collaboratively leverage the value of\ninformation,\" it will go in one investor ear and out the other.\nThey'll just discard that sentence as meaningless boilerplate, and\nhope, with increasing impatience, that in the next sentence you'll\nactually explain what you've made.Your primary goal is not to describe everything your system might\none day become, but simply to convince investors you're worth talking\nto further. So approach this like an algorithm that gets the right\nanswer by successive approximations. Begin with a description\nthat's gripping but perhaps overly narrow, then flesh it out to the\nextent you can. It's the same principle as incremental development:\nstart with a simple prototype, then add features, but at every point\nhave working code. In this case, \"working code\" means a working\ndescription in the investor's head.4. Don't talk and drive.Have one person talk while another uses the computer. If the same\nperson does both, they'll inevitably mumble downwards at the computer\nscreen instead of talking clearly at the audience.As long as you're standing near the audience and looking at them,\npoliteness (and habit) compel them to pay attention to you. Once\nyou stop looking at them to fuss with something on your computer,\ntheir minds drift off to the errands they have to run later.5. Don't talk about secondary matters at length.If you only have a few minutes, spend them explaining what your\nproduct does and why it's great. Second order issues like competitors\nor resumes should be single slides you go through quickly at the\nend. If you have impressive resumes, just flash them on the screen\nfor 15 seconds and say a few words. For competitors, list the top\n3 and explain in one sentence each what they lack\nthat you have. And put this kind of thing at the end, after you've\nmade it clear what you've built.6. Don't get too deeply into business models.It's good to talk about how you plan to make money, but mainly\nbecause it shows you care about that and have thought about it.\nDon't go into detail about your business model, because (a) that's\nnot what smart investors care about in a brief presentation, and\n(b) any business model you have at this point is probably wrong\nanyway.Recently a VC who came to speak at Y Combinator talked about a\ncompany he just invested in. He said their business model was wrong\nand would probably change three times before they got it right.\nThe founders were experienced guys who'd done startups before and\nwho'd just succeeded in getting millions from one of the top VC\nfirms, and even their business model was crap. (And yet he invested\nanyway, because he expected it to be crap at this stage.)If you're solving an important problem, you're going to sound a lot\nsmarter talking about that than the business model. The business\nmodel is just a bunch of guesses, and guesses about stuff that's\nprobably not your area of expertise. So don't spend your precious\nfew minutes talking about crap when you could be talking about\nsolid, interesting things you know a lot about: the problem you're\nsolving and what you've built so far.As well as being a bad use of time, if your business model seems\nspectacularly wrong, that will push the stuff you want investors\nto remember out of their heads. They'll just remember you as the\ncompany with the boneheaded plan for making money, rather than the\ncompany that solved that important problem.7. Talk slowly and clearly at the audience.Everyone at Rehearsal Day could see the difference between the people\nwho'd been out in the world for a while and had presented to groups,\nand those who hadn't.You need to use a completely different voice and manner talking to\na roomful of people than you would in conversation. Everyday life\ngives you no practice in this. If you can't already do it, the\nbest solution is to treat it as a consciously artificial trick,\nlike juggling.However, that doesn't mean you should talk like some kind of\nannouncer. Audiences tune that out. What you need to do is talk\nin this artificial way, and yet make it seem conversational. (Writing\nis the same. Good writing is an elaborate effort to seem spontaneous.)If you want to write out your whole presentation beforehand and\nmemorize it, that's ok. That has worked for some groups in the\npast. But make sure to write something that sounds like spontaneous,\ninformal speech, and deliver it that way too.Err on the side of speaking slowly. At Rehearsal Day, one of the founders\nmentioned a rule actors use: if you feel you're speaking too slowly,\nyou're speaking at about the right speed.8. Have one person talk.Startups often want to show that all the founders are equal partners.\nThis is a good instinct; investors dislike unbalanced teams. But\ntrying to show it by partitioning the presentation is going too\nfar. It's distracting. You can demonstrate your respect\nfor one another in more subtle ways. For example, when one of the\ngroups presented at Demo Day, the more extroverted of the two\nfounders did most of the talking, but he described his co-founder\nas the best hacker he'd ever met, and you could tell he meant it.Pick the one or at most two best speakers, and have them do most\nof the talking.Exception: If one of the founders is an expert in some specific\ntechnical field, it can be good for them to talk about that for a\nminute or so. This kind of \"expert witness\" can add credibility,\neven if the audience doesn't understand all the details. If Jobs\nand Wozniak had 10 minutes to present the Apple II, it might be a good plan\nto have Jobs speak for 9 minutes and have Woz speak for a minute\nin the middle about some of the technical feats he'd pulled off in\nthe design. (Though of course if it were actually those two, Jobs\nwould speak for the entire 10 minutes.)9. Seem confident.Between the brief time available and their lack of technical\nbackground, many in the audience will have a hard time evaluating\nwhat you're doing. Probably the single biggest piece of evidence,\ninitially, will be your own confidence in it. You have\nto show you're impressed with what you've made.And I mean show, not tell. Never say \"we're passionate\" or \"our\nproduct is great.\" People just ignore that—or worse, write you\noff as bullshitters. Such messages must be implicit.What you must not do is seem nervous and apologetic. If you've\ntruly made something good, you're doing investors a favor by\ntelling them about it. If you don't genuinely believe that, perhaps\nyou ought to change what your company is doing. If you don't believe\nyour startup has such promise that you'd be doing them a favor by\nletting them invest, why are you investing your time in it?10. Don't try to seem more than you are.Don't worry if your company is just a few months old and doesn't\nhave an office yet, or your founders are technical people with no\nbusiness experience. Google was like that once, and they turned out\nok. Smart investors can see past such superficial flaws. They're\nnot looking for finished, smooth presentations. They're looking\nfor raw talent. All you need to convince them of is that you're\nsmart and that you're onto something good. If you try too hard to\nconceal your rawness—by trying to seem corporate, or pretending\nto know about stuff you don't—you may just conceal your talent.You can afford to be candid about what you haven't figured out yet.\nDon't go out of your way to bring it up (e.g. by having a slide\nabout what might go wrong), but don't try to pretend either that\nyou're further along than you are. If you're a hacker and you're\npresenting to experienced investors, they're probably better at\ndetecting bullshit than you are at producing it.11. Don't put too many words on slides.When there are a lot of words on a slide, people just skip reading\nit. So look at your slides and ask of each word \"could I cross\nthis out?\" This includes gratuitous clip art. Try to get your\nslides under 20 words if you can.Don't read your slides. They should be something in the background\nas you face the audience and talk to them, not something you face\nand read to an audience sitting behind you.Cluttered sites don't do well in demos, especially when they're\nprojected onto a screen. At the very least, crank up the font size\nbig enough to make all the text legible. But cluttered sites are\nbad anyway, so perhaps you should use this opportunity to make your\ndesign simpler.12. Specific numbers are good.If you have any kind of data, however preliminary, tell the audience.\nNumbers stick in people's heads. If you can claim that the median\nvisitor generates 12 page views, that's great.But don't give them more than four or five numbers, and only give\nthem numbers specific to you. You don't need to tell them the size\nof the market you're in. Who cares, really, if it's 500 million\nor 5 billion a year? Talking about that is like an actor at the\nbeginning of his career telling his parents how much Tom Hanks\nmakes. Yeah, sure, but first you have to become Tom Hanks. The\nimportant part is not whether he makes ten million a year or a\nhundred, but how you get there.13. Tell stories about users.The biggest fear of investors looking at early stage startups is\nthat you've built something based on your own a priori theories of\nwhat the world needs, but that no one will actually want. So it's\ngood if you can talk about problems specific users have and how you\nsolve them.Greg Mcadoo said one thing Sequoia looks for is the \"proxy for\ndemand.\" What are people doing now, using inadequate tools, that\nshows they need what you're making?Another sign of user need is when people pay a lot for something.\nIt's easy to convince investors there will be demand for\na cheaper alternative to something popular, if you preserve\nthe qualities that made it popular.The best stories about user needs are about your own. A remarkable\nnumber of famous startups grew out of some need the founders had:\nApple, Microsoft, Yahoo, Google. Experienced investors know that,\nso stories of this type will get their attention. The next best\nthing is to talk about the needs of people you know personally,\nlike your friends or siblings.14. Make a soundbite stick in their heads.Professional investors hear a lot of pitches. After a while they\nall blur together. The first cut is simply to be one of those\nthey remember. And the way to ensure that is to create a descriptive\nphrase about yourself that sticks in their heads.In Hollywood, these phrases seem to be of the form \"x meets y.\"\n\nIn the startup world, they're usually \"the x of y\" or \"the x y.\"\nViaweb's was \"the Microsoft Word of ecommerce.\"Find one and launch it clearly (but apparently casually) in your\ntalk, preferably near the beginning.It's a good exercise for you, too, to sit down and try to figure\nout how to describe your startup in one compelling phrase. If you\ncan't, your plans may not be sufficiently focused." }, { "path": "data/PaulGrahamEssays/invtrend.txt", "content": "June 2013(This talk was written for an audience of investors.)Y Combinator has now funded 564 startups including the current\nbatch, which has 53. The total valuation of the 287 that have\nvaluations (either by raising an equity round, getting acquired,\nor dying) is about $11.7 billion, and the 511 prior to the current\nbatch have collectively raised about $1.7 billion.\n[1]As usual those numbers are dominated by a few big winners. The top\n10 startups account for 8.6 of that 11.7 billion. But there is a\npeloton of younger startups behind them. There are about 40 more\nthat have a shot at being really big.Things got a little out of hand last summer when we had 84 companies\nin the batch, so we tightened up our filter to decrease the batch\nsize. \n[2]\nSeveral journalists have tried to interpret that as\nevidence for some macro story they were telling, but the reason had\nnothing to do with any external trend. The reason was that we\ndiscovered we were using an n² algorithm, and we needed to buy\ntime to fix it. Fortunately we've come up with several techniques\nfor sharding YC, and the problem now seems to be fixed. With a new\nmore scaleable model and only 53 companies, the current batch feels\nlike a walk in the park. I'd guess we can grow another 2 or 3x\nbefore hitting the next bottleneck. \n[3]One consequence of funding such a large number of startups is that\nwe see trends early. And since fundraising is one of the main\nthings we help startups with, we're in a good position to notice\ntrends in investing.I'm going to take a shot at describing where these trends are\nleading. Let's start with the most basic question: will the future\nbe better or worse than the past? Will investors, in the aggregate,\nmake more money or less?I think more. There are multiple forces at work, some of which\nwill decrease returns, and some of which will increase them. I\ncan't predict for sure which forces will prevail, but I'll describe\nthem and you can decide for yourself.There are two big forces driving change in startup funding: it's\nbecoming cheaper to start a startup, and startups are becoming a\nmore normal thing to do.When I graduated from college in 1986, there were essentially two\noptions: get a job or go to grad school. Now there's a third: start\nyour own company.\nThat's a big change. In principle it was possible to start your\nown company in 1986 too, but it didn't seem like a real possibility.\nIt seemed possible to start a consulting company, or a niche product\ncompany, but it didn't seem possible to start a company that would\nbecome big.\n[4]That kind of change, from 2 paths to 3, is the sort of big social\nshift that only happens once every few generations. I think we're\nstill at the beginning of this one. It's hard to predict how big\na deal it will be. As big a deal as the Industrial Revolution?\nMaybe. Probably not. But it will be a big enough deal that it\ntakes almost everyone by surprise, because those big social shifts\nalways do.One thing we can say for sure is that there will be a lot more\nstartups. The monolithic, hierarchical companies of the mid 20th\ncentury are being replaced by networks\nof smaller companies. This process is not just something happening\nnow in Silicon Valley. It started decades ago, and it's happening\nas far afield as the car industry. It has a long way to run. \n[5]\nThe other big driver of change is that startups are becoming cheaper\nto start. And in fact the two forces are related: the decreasing\ncost of starting a startup is one of the reasons startups are\nbecoming a more normal thing to do.The fact that startups need less money means founders will increasingly\nhave the upper hand over investors. You still need just as much\nof their energy and imagination, but they don't need as much of\nyour money. Because founders have the upper hand, they'll retain\nan increasingly large share of the stock in, and control of, their\ncompanies. Which means investors will get less stock and less\ncontrol.Does that mean investors will make less money? Not necessarily,\nbecause there will be more good startups. The total amount of\ndesirable startup stock available to investors will probably increase,\nbecause the number of desirable startups will probably grow faster\nthan the percentage they sell to investors shrinks.There's a rule of thumb in the VC business that there are about 15\ncompanies a year that will be really successful. Although a lot\nof investors unconsciously treat this number as if it were some\nsort of cosmological constant, I'm certain it isn't. There are\nprobably limits on the rate at which technology can develop, but\nthat's not the limiting factor now. If it were, each successful\nstartup would be founded the month it became possible, and that is\nnot the case. Right now the limiting factor on the number of big\nhits is the number of sufficiently good founders starting companies,\nand that number can and will increase. There are still a lot of\npeople who'd make great founders who never end up starting a company.\nYou can see that from how randomly some of the most successful\nstartups got started. So many of the biggest startups almost didn't\nhappen that there must be a lot of equally good startups that\nactually didn't happen.There might be 10x or even 50x more good founders out there. As\nmore of them go ahead and start startups, those 15 big hits a year\ncould easily become 50 or even 100.\n[6]What about returns, though? Are we heading for a world in which\nreturns will be pinched by increasingly high valuations? I think\nthe top firms will actually make more money than they have in the\npast. High returns don't come from investing at low valuations.\nThey come from investing in the companies that do really well. So\nif there are more of those to be had each year, the best pickers\nshould have more hits.This means there should be more variability in the VC business.\nThe firms that can recognize and attract the best startups will do\neven better, because there will be more of them to recognize and\nattract. Whereas the bad firms will get the leftovers, as they do\nnow, and yet pay a higher price for them.Nor do I think it will be a problem that founders keep control of\ntheir companies for longer. The empirical evidence on that is\nalready clear: investors make more money as founders' bitches than\ntheir bosses. Though somewhat humiliating, this is actually good\nnews for investors, because it takes less time to serve founders\nthan to micromanage them.What about angels? I think there is a lot of opportunity there.\nIt used to suck to be an angel investor. You couldn't get access\nto the best deals, unless you got lucky like Andy Bechtolsheim, and\nwhen you did invest in a startup, VCs might try to strip you of\nyour stock when they arrived later. Now an angel can go to something\nlike Demo Day or AngelList and have access to the same deals VCs\ndo. And the days when VCs could wash angels out of the cap table\nare long gone.I think one of the biggest unexploited opportunities in startup\ninvesting right now is angel-sized investments made quickly. Few\ninvestors understand the cost that raising money from them imposes\non startups. When the company consists only of the founders,\neverything grinds to a halt during fundraising, which can easily\ntake 6 weeks. The current high cost of fundraising means there is\nroom for low-cost investors to undercut the rest. And in this\ncontext, low-cost means deciding quickly. If there were a reputable\ninvestor who invested $100k on good terms and promised to decide\nyes or no within 24 hours, they'd get access to almost all the best\ndeals, because every good startup would approach them first. It\nwould be up to them to pick, because every bad startup would approach\nthem first too, but at least they'd see everything. Whereas if an\ninvestor is notorious for taking a long time to make up their mind\nor negotiating a lot about valuation, founders will save them for\nlast. And in the case of the most promising startups, which tend\nto have an easy time raising money, last can easily become never.Will the number of big hits grow linearly with the total number of\nnew startups? Probably not, for two reasons. One is that the\nscariness of starting a startup in the old days was a pretty effective\nfilter. Now that the cost of failing is becoming lower, we should\nexpect founders to do it more. That's not a bad thing. It's common\nin technology for an innovation that decreases the cost of failure\nto increase the number of failures and yet leave you net ahead.The other reason the number of big hits won't grow proportionately\nto the number of startups is that there will start to be an increasing\nnumber of idea clashes. Although the finiteness of the number of\ngood ideas is not the reason there are only 15 big hits a year, the\nnumber has to be finite, and the more startups there are, the more\nwe'll see multiple companies doing the same thing at the same time.\nIt will be interesting, in a bad way, if idea clashes become a lot\nmore common. \n[7]Mostly because of the increasing number of early failures, the startup\nbusiness of the future won't simply be the same shape, scaled up.\nWhat used to be an obelisk will become a pyramid. It will be a\nlittle wider at the top, but a lot wider at the bottom.What does that mean for investors? One thing it means is that there\nwill be more opportunities for investors at the earliest stage,\nbecause that's where the volume of our imaginary solid is growing\nfastest. Imagine the obelisk of investors that corresponds to\nthe obelisk of startups. As it widens out into a pyramid to match\nthe startup pyramid, all the contents are adhering to the top,\nleaving a vacuum at the bottom.That opportunity for investors mostly means an opportunity for new\ninvestors, because the degree of risk an existing investor or firm\nis comfortable taking is one of the hardest things for them to\nchange. Different types of investors are adapted to different\ndegrees of risk, but each has its specific degree of risk deeply\nimprinted on it, not just in the procedures they follow but in the\npersonalities of the people who work there.I think the biggest danger for VCs, and also the biggest opportunity,\nis at the series A stage. Or rather, what used to be the series A\nstage before series As turned into de facto series B rounds.Right now, VCs often knowingly invest too much money at the series\nA stage. They do it because they feel they need to get a big chunk\nof each series A company to compensate for the opportunity cost of\nthe board seat it consumes. Which means when there is a lot of\ncompetition for a deal, the number that moves is the valuation (and\nthus amount invested) rather than the percentage of the company\nbeing sold. Which means, especially in the case of more promising\nstartups, that series A investors often make companies take more\nmoney than they want.Some VCs lie and claim the company really needs that much. Others\nare more candid, and admit their financial models require them to\nown a certain percentage of each company. But we all know the\namounts being raised in series A rounds are not determined by asking\nwhat would be best for the companies. They're determined by VCs\nstarting from the amount of the company they want to own, and the\nmarket setting the valuation and thus the amount invested.Like a lot of bad things, this didn't happen intentionally. The\nVC business backed into it as their initial assumptions gradually\nbecame obsolete. The traditions and financial models of the VC\nbusiness were established when founders needed investors more. In\nthose days it was natural for founders to sell VCs a big chunk of\ntheir company in the series A round. Now founders would prefer to\nsell less, and VCs are digging in their heels because they're not\nsure if they can make money buying less than 20% of each series A\ncompany.The reason I describe this as a danger is that series A investors\nare increasingly at odds with the startups they supposedly serve,\nand that tends to come back to bite you eventually. The reason I\ndescribe it as an opportunity is that there is now a lot of potential\nenergy built up, as the market has moved away from VCs' traditional\nbusiness model. Which means the first VC to break ranks and start\nto do series A rounds for as much equity as founders want to sell\n(and with no \"option pool\" that comes only from the founders' shares)\nstands to reap huge benefits.What will happen to the VC business when that happens? Hell if I\nknow. But I bet that particular firm will end up ahead. If one\ntop-tier VC firm started to do series A rounds that started from\nthe amount the company needed to raise and let the percentage\nacquired vary with the market, instead of the other way around,\nthey'd instantly get almost all the best startups. And that's where\nthe money is.You can't fight market forces forever. Over the last decade we've\nseen the percentage of the company sold in series A rounds creep\ninexorably downward. 40% used to be common. Now VCs are fighting\nto hold the line at 20%. But I am daily waiting for the line to\ncollapse. It's going to happen. You may as well anticipate it,\nand look bold.Who knows, maybe VCs will make more money by doing the right thing.\nIt wouldn't be the first time that happened. Venture capital is a\nbusiness where occasional big successes generate hundredfold returns.\nHow much confidence can you really have in financial models for\nsomething like that anyway? The\nbig successes only have to get a tiny bit less occasional to\ncompensate for a 2x decrease in the stock sold in series A rounds.If you want to find new opportunities for investing, look for things\nfounders complain about. Founders are your customers, and the\nthings they complain about are unsatisfied demand. I've given two\nexamples of things founders complain about most—investors who\ntake too long to make up their minds, and excessive dilution in\nseries A rounds—so those are good places to look now. But\nthe more general recipe is: do something founders want.\nNotes[1]\nI realize revenue and not fundraising is the proper test of\nsuccess for a startup. The reason we quote statistics about\nfundraising is because those are the numbers we have. We couldn't\ntalk meaningfully about revenues without including the numbers from\nthe most successful startups, and we don't have those. We often\ndiscuss revenue growth with the earlier stage startups, because\nthat's how we gauge their progress, but when companies reach a\ncertain size it gets presumptuous for a seed investor to do that.In any case, companies' market caps do eventually become a function\nof revenues, and post-money valuations of funding rounds are at\nleast guesses by pros about where those market caps will end up.The reason only 287 have valuations is that the rest have mostly\nraised money on convertible notes, and although convertible notes\noften have valuation caps, a valuation cap is merely an upper bound\non a valuation.[2]\nWe didn't try to accept a particular number. We have no way\nof doing that even if we wanted to. We just tried to be significantly\npickier.[3]\nThough you never know with bottlenecks, I'm guessing the next\none will be coordinating efforts among partners.[4]\nI realize starting a company doesn't have to mean starting a\nstartup. There will be lots of people starting normal companies\ntoo. But that's not relevant to an audience of investors.Geoff Ralston reports that in Silicon Valley it seemed thinkable\nto start a startup in the mid 1980s. It would have started there.\nBut I know it didn't to undergraduates on the East Coast.[5]\nThis trend is one of the main causes of the increase in\neconomic inequality in the US since the mid twentieth century. The\nperson who would in 1950 have been the general manager of the x\ndivision of Megacorp is now the founder of the x company, and owns\nsignificant equity in it.[6]\nIf Congress passes the founder\nvisa in a non-broken form, that alone could in principle get\nus up to 20x, since 95% of the world's population lives outside the\nUS.[7]\nIf idea clashes got bad enough, it could change what it means\nto be a startup. We currently advise startups mostly to ignore\ncompetitors. We tell them startups are competitive like running,\nnot like soccer; you don't have to go and steal the ball away from\nthe other team. But if idea clashes became common enough, maybe\nyou'd start to have to. That would be unfortunate.Thanks to Sam Altman, Paul Buchheit, Dalton Caldwell,\nPatrick Collison, Jessica\nLivingston, Andrew Mason, Geoff Ralston, and Garry Tan for reading\ndrafts of this." }, { "path": "data/PaulGrahamEssays/island.txt", "content": "July 2006I've discovered a handy test for figuring out what you're addicted\nto. Imagine you were going to spend the weekend at a friend's house\non a little island off the coast of Maine. There are no shops on\nthe island and you won't be able to leave while you're there. Also,\nyou've never been to this house before, so you can't assume it will\nhave more than any house might.What, besides clothes and toiletries, do you make a point of packing?\nThat's what you're addicted to. For example, if you find yourself\npacking a bottle of vodka (just in case), you may want to stop and\nthink about that.For me the list is four things: books, earplugs, a notebook, and a\npen.There are other things I might bring if I thought of it, like music,\nor tea, but I can live without them. I'm not so addicted to caffeine\nthat I wouldn't risk the house not having any tea, just for a\nweekend.Quiet is another matter. I realize it seems a bit eccentric to\ntake earplugs on a trip to an island off the coast of Maine. If\nanywhere should be quiet, that should. But what if the person in\nthe next room snored? What if there was a kid playing basketball?\n(Thump, thump, thump... thump.) Why risk it? Earplugs are small.Sometimes I can think with noise. If I already have momentum on\nsome project, I can work in noisy places. I can edit an essay or\ndebug code in an airport. But airports are not so bad: most of the\nnoise is whitish. I couldn't work with the sound of a sitcom coming\nthrough the wall, or a car in the street playing thump-thump music.And of course there's another kind of thinking, when you're starting\nsomething new, that requires complete quiet. You never\nknow when this will strike. It's just as well to carry plugs.The notebook and pen are professional equipment, as it were. Though\nactually there is something druglike about them, in the sense that\ntheir main purpose is to make me feel better. I hardly ever go\nback and read stuff I write down in notebooks. It's just that if\nI can't write things down, worrying about remembering one idea gets\nin the way of having the next. Pen and paper wick ideas.The best notebooks I've found are made by a company called Miquelrius.\nI use their smallest size, which is about 2.5 x 4 in.\nThe secret to writing on such\nnarrow pages is to break words only when you run out of space, like\na Latin inscription. I use the cheapest plastic Bic ballpoints,\npartly because their gluey ink doesn't seep through pages, and\npartly so I don't worry about losing them.I only started carrying a notebook about three years ago. Before\nthat I used whatever scraps of paper I could find. But the problem\nwith scraps of paper is that they're not ordered. In a notebook\nyou can guess what a scribble means by looking at the pages\naround it. In the scrap era I was constantly finding notes I'd\nwritten years before that might say something I needed to remember,\nif I could only figure out what.As for books, I know the house would probably have something to\nread. On the average trip I bring four books and only read one of\nthem, because I find new books to read en route. Really bringing\nbooks is insurance.I realize this dependence on books is not entirely good—that what\nI need them for is distraction. The books I bring on trips are\noften quite virtuous, the sort of stuff that might be assigned\nreading in a college class. But I know my motives aren't virtuous.\nI bring books because if the world gets boring I need to be able\nto slip into another distilled by some writer. It's like eating\njam when you know you should be eating fruit.There is a point where I'll do without books. I was walking in\nsome steep mountains once, and decided I'd rather just think, if I\nwas bored, rather than carry a single unnecessary ounce. It wasn't\nso bad. I found I could entertain myself by having ideas instead\nof reading other people's. If you stop eating jam, fruit starts\nto taste better.So maybe I'll try not bringing books on some future trip. They're\ngoing to have to pry the plugs out of my cold, dead ears, however." }, { "path": "data/PaulGrahamEssays/javacover.txt", "content": "April 2001This essay developed out of conversations I've had with\nseveral other programmers about why Java smelled suspicious. It's not\na critique of Java! It is a case study of hacker's radar.Over time, hackers develop a nose for good (and bad) technology.\nI thought it might be interesting to try and write down what\nmade Java seem suspect to me.Some people who've read this think it's an interesting attempt to write about\nsomething that hasn't been written about before. Others say I\nwill get in trouble for appearing to be writing about\nthings I don't understand. So, just in\ncase it does any good, let me clarify that I'm not writing here\nabout Java (which I have never used) but about hacker's radar\n(which I have thought about a lot).The aphorism \"you can't tell a book by its cover\" originated in\nthe times when books were sold in plain cardboard covers, to be\nbound by each purchaser according to his own taste. In those days,\nyou couldn't tell a book by its cover. But publishing has advanced\nsince then: present-day publishers work hard to make the cover\nsomething you can tell a book by.I spend a lot of time in bookshops and I feel as if I have by now\nlearned to understand everything publishers mean to tell me about\na book, and perhaps a bit more. The time I haven't spent in\nbookshops I've spent mostly in front of computers, and I feel as\nif I've learned, to some degree, to judge technology by its cover\nas well. It may be just luck, but I've saved myself from a few\ntechnologies that turned out to be real stinkers.So far, Java seems like a stinker to me. I've never written a Java\nprogram, never more than glanced over reference books about it,\nbut I have a hunch that it won't be a very successful language.\nI may turn out to be mistaken; making predictions about technology\nis a dangerous business. But for what it's worth, as a sort of\ntime capsule, here's why I don't like the look of Java:\n1. It has been so energetically hyped. Real standards don't have\nto be promoted. No one had to promote C, or Unix, or HTML. A real\nstandard tends to be already established by the time most people\nhear about it. On the hacker radar screen, Perl is as big as Java,\nor bigger, just on the strength of its own merits.2. It's aimed low. In the original Java white paper, Gosling\nexplicitly says Java was designed not to be too difficult for\nprogrammers used to C. It was designed to be another C++: C plus\na few ideas taken from more advanced languages. Like the creators\nof sitcoms or junk food or package tours, Java's designers were\nconsciously designing a product for people not as smart as them.\nHistorically, languages designed for other people to use have been\nbad: Cobol, PL/I, Pascal, Ada, C++. The good languages have been\nthose that were designed for their own creators: C, Perl, Smalltalk,\nLisp.3. It has ulterior motives. Someone once said that the world would\nbe a better place if people only wrote books because they had\nsomething to say, rather than because they wanted to write a book.\nLikewise, the reason we hear about Java all the time is not because\nit has something to say about programming languages. We hear about\nJava as part of a plan by Sun to undermine Microsoft.4. No one loves it. C, Perl, Python, Smalltalk, and Lisp programmers\nlove their languages. I've never heard anyone say that they loved\nJava.5. People are forced to use it. A lot of the people I know using\nJava are using it because they feel they have to. Either it's\nsomething they felt they had to do to get funded, or something they\nthought customers would want, or something they were told to do by\nmanagement. These are smart people; if the technology was good,\nthey'd have used it voluntarily.6. It has too many cooks. The best programming languages have been\ndeveloped by small groups. Java seems to be run by a committee.\nIf it turns out to be a good language, it will be the first time\nin history that a committee has designed a good language.7. It's bureaucratic. From what little I know about Java, there\nseem to be a lot of protocols for doing things. Really good\nlanguages aren't like that. They let you do what you want and get\nout of the way.8. It's pseudo-hip. Sun now pretends that Java is a grassroots,\nopen-source language effort like Perl or Python. This one just\nhappens to be controlled by a giant company. So the language is\nlikely to have the same drab clunkiness as anything else that comes\nout of a big company.9. It's designed for large organizations. Large organizations have\ndifferent aims from hackers. They want languages that are (believed\nto be) suitable for use by large teams of mediocre programmers--\nlanguages with features that, like the speed limiters in U-Haul\ntrucks, prevent fools from doing too much damage. Hackers don't\nlike a language that talks down to them. Hackers just want power.\nHistorically, languages designed for large organizations (PL/I,\nAda) have lost, while hacker languages (C, Perl) have won. The\nreason: today's teenage hacker is tomorrow's CTO.10. The wrong people like it. The programmers I admire most are\nnot, on the whole, captivated by Java. Who does like Java? Suits,\nwho don't know one language from another, but know that they keep\nhearing about Java in the press; programmers at big companies, who\nare amazed to find that there is something even better than C++;\nand plug-and-chug undergrads, who are ready to like anything that\nmight get them a job (will this be on the test?). These people's\nopinions change with every wind.11. Its daddy is in a pinch. Sun's business model is being undermined\non two fronts. Cheap Intel processors, of the same type used in\ndesktop machines, are now more than fast enough for servers. And\nFreeBSD seems to be at least as good an OS for servers as Solaris.\nSun's advertising implies that you need Sun servers for industrial\nstrength applications. If this were true, Yahoo would be first in\nline to buy Suns; but when I worked there, the servers were all\nIntel boxes running FreeBSD. This bodes ill for Sun's future. If\nSun runs into trouble, they could drag Java down with them.12. The DoD likes it. The Defense Department is encouraging\ndevelopers to use Java. This seems to me the most damning sign of\nall. The Defense Department does a fine (though expensive) job of\ndefending the country, but they love plans and procedures and\nprotocols. Their culture is the opposite of hacker culture; on\nquestions of software they will tend to bet wrong. The last time\nthe DoD really liked a programming language, it was Ada.\nBear in mind, this is not a critique of Java, but a critique of\nits cover. I don't know Java well enough to like it or dislike\nit. This is just an explanation of why I don't find that I'm eager\nto learn it.It may seem cavalier to dismiss a language before you've even tried\nwriting programs in it. But this is something all programmers have\nto do. There are too many technologies out there to learn them\nall. You have to learn to judge by outward signs which will be\nworth your time. I have likewise cavalierly dismissed Cobol, Ada,\nVisual Basic, the IBM AS400, VRML, ISO 9000, the SET protocol, VMS,\nNovell Netware, and CORBA, among others. They just smelled wrong.It could be that in Java's case I'm mistaken. It could be that a\nlanguage promoted by one big company to undermine another, designed\nby a committee for a \"mainstream\" audience, hyped to the skies,\nand beloved of the DoD, happens nonetheless to be a clean, beautiful,\npowerful language that I would love programming in. It could be,\nbut it seems very unlikely." }, { "path": "data/PaulGrahamEssays/jessica.txt", "content": "November 2015A few months ago an article about Y Combinator said that early on\nit had been a \"one-man show.\" It's sadly common to read that sort\nof thing. But the problem with that description is not just that\nit's unfair. It's also misleading. Much of what's most novel about\nYC is due to Jessica Livingston. If you don't understand her, you\ndon't understand YC. So let me tell you a little about Jessica.YC had 4 founders. Jessica and I decided one night to start it,\nand the next day we recruited my friends Robert Morris and Trevor\nBlackwell. Jessica and I ran YC day to day, and Robert and Trevor\nread applications and did interviews with us.Jessica and I were already dating when we started YC. At first we\ntried to act \"professional\" about this, meaning we tried to conceal\nit. In retrospect that seems ridiculous, and we soon dropped the\npretense. And the fact that Jessica and I were a couple is a big\npart of what made YC what it was. YC felt like a family. The\nfounders early on were mostly young. We all had dinner together\nonce a week, cooked for the first couple years by me. Our first\nbuilding had been a private home. The overall atmosphere was\nshockingly different from a VC's office on Sand Hill Road, in a way\nthat was entirely for the better. There was an authenticity that\neveryone who walked in could sense. And that didn't just mean that\npeople trusted us. It was the perfect quality to instill in startups.\nAuthenticity is one of the most important things YC looks for in\nfounders, not just because fakers and opportunists are annoying,\nbut because authenticity is one of the main things that separates\nthe most successful startups from the rest.Early YC was a family, and Jessica was its mom. And the culture\nshe defined was one of YC's most important innovations. Culture\nis important in any organization, but at YC culture wasn't just how\nwe behaved when we built the product. At YC, the culture was the\nproduct.Jessica was also the mom in another sense: she had the last word.\nEverything we did as an organization went through her first — who\nto fund, what to say to the public, how to deal with other companies,\nwho to hire, everything.Before we had kids, YC was more or less our life. There was no real\ndistinction between working hours and not. We talked about YC all\nthe time. And while there might be some businesses that it would\nbe tedious to let infect your private life, we liked it. We'd started\nYC because it was something we were interested in. And some of the\nproblems we were trying to solve were endlessly difficult. How do\nyou recognize good founders? You could talk about that for years,\nand we did; we still do.I'm better at some things than Jessica, and she's better at some\nthings than me. One of the things she's best at is judging people.\nShe's one of those rare individuals with x-ray vision for character.\nShe can see through any kind of faker almost immediately. Her\nnickname within YC was the Social Radar, and this special power of\nhers was critical in making YC what it is. The earlier you pick\nstartups, the more you're picking the founders. Later stage investors\nget to try products and look at growth numbers. At the stage where\nYC invests, there is often neither a product nor any numbers.Others thought YC had some special insight about the future of\ntechnology. Mostly we had the same sort of insight Socrates claimed:\nwe at least knew we knew nothing. What made YC successful was being\nable to pick good founders. We thought Airbnb was a bad idea. We\nfunded it because we liked the founders.During interviews, Robert and Trevor and I would pepper the applicants\nwith technical questions. Jessica would mostly watch. A lot of\nthe applicants probably read her as some kind of secretary, especially\nearly on, because she was the one who'd go out and get each new\ngroup and she didn't ask many questions. She was ok with that. It\nwas easier for her to watch people if they didn't notice her. But\nafter the interview, the three of us would turn to Jessica and ask\n\"What does the Social Radar say?\"\n[1]Having the Social Radar at interviews wasn't just how we picked\nfounders who'd be successful. It was also how we picked founders\nwho were good people. At first we did this because we couldn't\nhelp it. Imagine what it would feel like to have x-ray vision for\ncharacter. Being around bad people would be intolerable. So we'd\nrefuse to fund founders whose characters we had doubts about even\nif we thought they'd be successful.Though we initially did this out of self-indulgence, it turned out\nto be very valuable to YC. We didn't realize it in the beginning,\nbut the people we were picking would become the YC alumni network.\nAnd once we picked them, unless they did something really egregious,\nthey were going to be part of it for life. Some now think YC's\nalumni network is its most valuable feature. I personally think\nYC's advice is pretty good too, but the alumni network is certainly\namong the most valuable features. The level of trust and helpfulness\nis remarkable for a group of such size. And Jessica is the main\nreason why.(As we later learned, it probably cost us little to reject people\nwhose characters we had doubts about, because how good founders are\nand how well they do are not orthogonal. If bad founders succeed\nat all, they tend to sell early. The most successful founders are\nalmost all good.)If Jessica was so important to YC, why don't more people realize\nit? Partly because I'm a writer, and writers always get disproportionate\nattention. YC's brand was initially my brand, and our applicants\nwere people who'd read my essays. But there is another reason:\nJessica hates attention. Talking to reporters makes her nervous.\nThe thought of giving a talk paralyzes her. She was even uncomfortable\nat our wedding, because the bride is always the center of attention.\n[2]It's not just because she's shy that she hates attention, but because\nit throws off the Social Radar. She can't be herself. You can't\nwatch people when everyone is watching you.Another reason attention worries her is that she hates bragging.\nIn anything she does that's publicly visible, her biggest fear\n(after the obvious fear that it will be bad) is that it will seem\nostentatious. She says being too modest is a common problem for\nwomen. But in her case it goes beyond that. She has a horror of\nostentation so visceral it's almost a phobia.She also hates fighting. She can't do it; she just shuts down. And\nunfortunately there is a good deal of fighting in being the public\nface of an organization.So although Jessica more than anyone made YC unique, the very\nqualities that enabled her to do it mean she tends to get written\nout of YC's history. Everyone buys this story that PG started YC\nand his wife just kind of helped. Even YC's haters buy it. A\ncouple years ago when people were attacking us for not funding more\nfemale founders (than exist), they all treated YC as identical with\nPG. It would have spoiled the narrative to acknowledge Jessica's\ncentral role at YC.Jessica was boiling mad that people were accusing her company of\nsexism. I've never seen her angrier about anything. But she did\nnot contradict them. Not publicly. In private there was a great\ndeal of profanity. And she wrote three separate essays about the\nquestion of female founders. But she could never bring herself to\npublish any of them. She'd seen the level of vitriol in this debate,\nand she shrank from engaging.\n[3]It wasn't just because she disliked fighting. She's so sensitive\nto character that it repels her even to fight with dishonest people.\nThe idea of mixing it up with linkbait journalists or Twitter trolls\nwould seem to her not merely frightening, but disgusting.But Jessica knew her example as a successful female founder would\nencourage more women to start companies, so last year she did\nsomething YC had never done before and hired a PR firm to get her\nsome interviews. At one of the first she did, the reporter brushed\naside her insights about startups and turned it into a sensationalistic\nstory about how some guy had tried to chat her up as she was waiting\noutside the bar where they had arranged to meet. Jessica was\nmortified, partly because the guy had done nothing wrong, but more\nbecause the story treated her as a victim significant only for being\na woman, rather than one of the most knowledgeable investors in the\nValley.After that she told the PR firm to stop.You're not going to be hearing in the press about what Jessica has\nachieved. So let me tell you what Jessica has achieved. Y Combinator\nis fundamentally a nexus of people, like a university. It doesn't\nmake a product. What defines it is the people. Jessica more than\nanyone curated and nurtured that collection of people. In that\nsense she literally made YC.Jessica knows more about the qualities of startup founders than\nanyone else ever has. Her immense data set and x-ray vision are the\nperfect storm in that respect. The qualities of the founders are\nthe best predictor of how a startup will do. And startups are in\nturn the most important source of growth in mature economies.The person who knows the most about the most important factor in\nthe growth of mature economies — that is who Jessica Livingston is.\nDoesn't that sound like someone who should be better known?Notes[1]\nHarj Taggar reminded me that while Jessica didn't ask many\nquestions, they tended to be important ones:\"She was always good at sniffing out any red flags about the team\nor their determination and disarmingly asking the right question,\nwhich usually revealed more than the founders realized.\"[2]\nOr more precisely, while she likes getting attention in the\nsense of getting credit for what she has done, she doesn't like\ngetting attention in the sense of being watched in real time.\nUnfortunately, not just for her but for a lot of people, how much\nyou get of the former depends a lot on how much you get of the\nlatter.Incidentally, if you saw Jessica at a public event, you would never\nguess she\nhates attention, because (a) she is very polite and (b) when she's\nnervous, she expresses it by smiling more.[3]\nThe existence of people like Jessica is not just something\nthe mainstream media needs to learn to acknowledge, but something\nfeminists need to learn to acknowledge as well. There are successful\nwomen who don't like to fight. Which means if the public conversation\nabout women consists of fighting, their voices will be silenced.There's a sort of Gresham's Law of conversations. If a conversation\nreaches a certain level of incivility, the more thoughtful people\nstart to leave. No one understands female founders better than\nJessica. But it's unlikely anyone will ever hear her speak candidly\nabout the topic. She ventured a toe in that water a while ago, and\nthe reaction was so violent that she decided \"never again.\"\nThanks to Sam Altman, Paul Buchheit, Patrick Collison, \nDaniel Gackle, Carolynn\nLevy, Jon Levy, Kirsty Nathoo, Robert Morris, Geoff Ralston, and\nHarj Taggar for reading drafts of this. And yes, Jessica Livingston,\nwho made me cut surprisingly little." }, { "path": "data/PaulGrahamEssays/judgement.txt", "content": "April 2007There are two different ways people judge you. Sometimes judging\nyou correctly is the end goal. But there's a second much more\ncommon type of judgement where it isn't. We tend to regard all\njudgements of us as the first type. We'd probably be happier if\nwe realized which are and which aren't.The first type of judgement, the type where judging you is the end\ngoal, include court cases, grades in classes, and most competitions.\nSuch judgements can of course be mistaken, but because the goal is\nto judge you correctly, there's usually some kind of appeals process.\nIf you feel you've been misjudged, you can protest that you've been\ntreated unfairly.Nearly all the judgements made on children are of this type, so we\nget into the habit early in life of thinking that all judgements\nare.But in fact there is a second much larger class of judgements where\njudging you is only a means to something else. These include college\nadmissions, hiring and investment decisions, and of course the\njudgements made in dating. This kind of judgement is not really\nabout you.Put yourself in the position of someone selecting players for a\nnational team. Suppose for the sake of simplicity that this is a\ngame with no positions, and that you have to select 20 players.\nThere will be a few stars who clearly should make the team, and\nmany players who clearly shouldn't. The only place your judgement\nmakes a difference is in the borderline cases. Suppose you screw\nup and underestimate the 20th best player, causing him not to make\nthe team, and his place to be taken by the 21st best. You've still\npicked a good team. If the players have the usual distribution of\nability, the 21st best player will be only slightly worse than the\n20th best. Probably the difference between them will be less than\nthe measurement error.The 20th best player may feel he has been misjudged. But your goal\nhere wasn't to provide a service estimating people's ability. It\nwas to pick a team, and if the difference between the 20th and 21st\nbest players is less than the measurement error, you've still done\nthat optimally.It's a false analogy even to use the word unfair to describe this\nkind of misjudgement. It's not aimed at producing a correct estimate\nof any given individual, but at selecting a reasonably optimal set.One thing that leads us astray here is that the selector seems to\nbe in a position of power. That makes him seem like a judge. If\nyou regard someone judging you as a customer instead of a judge,\nthe expectation of fairness goes away. The author of a good novel\nwouldn't complain that readers were unfair for preferring a\npotboiler with a racy cover. Stupid, perhaps, but not unfair.Our early training and our self-centeredness combine to make us\nbelieve that every judgement of us is about us. In fact most aren't.\nThis is a rare case where being less self-centered will make people\nmore confident. Once you realize how little most people judging\nyou care about judging you accurately—once you realize that because\nof the normal distribution of most applicant pools, it matters least\nto judge accurately in precisely the cases where judgement has the\nmost effect—you won't take rejection so personally.And curiously enough, taking rejection less personally may help you\nto get rejected less often. If you think someone judging you will\nwork hard to judge you correctly, you can afford to be passive.\nBut the more you realize that most judgements are greatly influenced\nby random, extraneous factors—that most people judging you are\nmore like a fickle novel buyer than a wise and perceptive \nmagistrate—the more you realize you can do things to influence the\noutcome.One good place to apply this principle is in college applications.\nMost high school students applying to college do it with the usual\nchild's mix of inferiority and self-centeredness: inferiority in\nthat they assume that admissions committees must be all-seeing;\nself-centeredness in that they assume admissions committees care\nenough about them to dig down into their application and figure out\nwhether they're good or not. These combine to make applicants\npassive in applying and hurt when they're rejected. If college\napplicants realized how quick and impersonal most selection processes\nare, they'd make more effort to sell themselves, and take the outcome\nless personally." }, { "path": "data/PaulGrahamEssays/kate.txt", "content": "August 2009Kate Courteau is the architect who designed Y Combinator's office.\nRecently we managed to recruit her to help us run YC when she's not\nbusy with architectural projects. Though she'd heard a lot about\nYC since the beginning, the last 9 months have been a total immersion.I've been around the startup world for so long that it seems normal\nto me, so I was curious to hear what had surprised her most about\nit. This was her list:1. How many startups fail.Kate knew in principle that startups\nwere very risky, but she was surprised to see how constant the\nthreat of failure was — not just for the minnows, but even for the\nfamous startups whose founders came to speak at YC dinners.\n2. How much startups' ideas change.As usual, by Demo Day about\nhalf the startups were doing something significantly different than\nthey started with. We encourage that. Starting a startup is like\nscience in that you have to follow the truth wherever it leads. In\nthe rest of the world, people don't start things till they're sure\nwhat they want to do, and once started they tend to continue on their\ninitial path even if it's mistaken.\n3. How little money it can take to start a startup.In Kate's\nworld, everything is still physical and expensive. You can barely\nrenovate a bathroom for the cost of starting a startup.\n4. How scrappy founders are.That was her actual word. I agree\nwith her, but till she mentioned this it never occurred to me how\nlittle this quality is appreciated in most of the rest of the world.\nIt wouldn't be a compliment in most organizations to call someone\nscrappy.What does it mean, exactly? It's basically the diminutive form of\nbelligerent. Someone who's scrappy manages to be both threatening\nand undignified at the same time. Which seems to me exactly what\none would want to be, in any kind of work. If you're not threatening,\nyou're probably not doing anything new, and dignity is merely a\nsort of plaque.\n5. How tech-saturated Silicon Valley is.\"It seems like everybody\nhere is in the industry.\" That isn't literally true, but there is\na qualitative difference between Silicon Valley and other places.\nYou tend to keep your voice down, because there's a good chance the\nperson at the next table would know some of the people you're talking\nabout. I never felt that in Boston. The good news is, there's\nalso a good chance the person at the next table could help you in\nsome way.\n6. That the speakers at YC were so consistent in their advice.\nActually, I've noticed this too. I always worry the speakers will\nput us in an embarrassing position by contradicting what we tell the\nstartups, but it happens surprisingly rarely.When I asked her what specific things she remembered speakers always\nsaying, she mentioned: that the way to succeed was to launch something\nfast, listen to users, and then iterate; that startups required\nresilience because they were always an emotional rollercoaster; and\nthat most VCs were sheep.I've been impressed by how consistently the speakers advocate\nlaunching fast and iterating. That was contrarian advice 10 years\nago, but it's clearly now the established practice.\n7. How casual successful startup founders are.Most of the famous\nfounders in Silicon Valley are people you'd overlook on the street.\nIt's not merely that they don't dress up. They don't project any\nkind of aura of power either. \"They're not trying to impress\nanyone.\"Interestingly, while Kate said that she could never pick out\nsuccessful founders, she could recognize VCs, both by the way they\ndressed and the way they carried themselves.\n8. How important it is for founders to have people to ask for advice.(I swear I didn't prompt this one.) Without advice \"they'd just\nbe sort of lost.\" Fortunately, there are a lot of people to help\nthem. There's a strong tradition within YC of helping other YC-funded\nstartups. But we didn't invent that idea: it's just a slightly\nmore concentrated form of existing Valley culture.\n9. What a solitary task startups are.Architects are constantly\ninteracting face to face with other people, whereas doing a technology\nstartup, at least, tends to require long stretches of uninterrupted\ntime to work. \"You could do it in a box.\"By inverting this list, we can get a portrait of the \"normal\" world.\nIt's populated by people who talk a lot with one another as they\nwork slowly but harmoniously on conservative, expensive projects\nwhose destinations are decided in advance, and who carefully adjust\ntheir manner to reflect their position in the hierarchy.That's also a fairly accurate description of the past. So startup\nculture may not merely be different in the way you'd expect any\nsubculture to be, but a leading indicator." }, { "path": "data/PaulGrahamEssays/kids.txt", "content": "December 2019Before I had kids, I was afraid of having kids. Up to that point I\nfelt about kids the way the young Augustine felt about living\nvirtuously. I'd have been sad to think I'd never have children.\nBut did I want them now? No.If I had kids, I'd become a parent, and parents, as I'd known since\nI was a kid, were uncool. They were dull and responsible and had\nno fun. And while it's not surprising that kids would believe that,\nto be honest I hadn't seen much as an adult to change my mind.\nWhenever I'd noticed parents with kids, the kids seemed to be\nterrors, and the parents pathetic harried creatures, even when they\nprevailed.When people had babies, I congratulated them enthusiastically,\nbecause that seemed to be what one did. But I didn't feel it at\nall. \"Better you than me,\" I was thinking.Now when people have babies I congratulate them enthusiastically and\nI mean it. Especially the first one. I feel like they just got the best gift in the world.What changed, of course, is that I had kids. Something I dreaded\nturned out to be wonderful.Partly, and I won't deny it, this is because of serious chemical\nchanges that happened almost instantly when our first child was\nborn. It was like someone flipped a switch. I suddenly felt\nprotective not just toward our child, but toward all children. As I was\ndriving my wife and new son home from the hospital, I approached a\ncrosswalk full of pedestrians, and I found myself thinking \"I have\nto be really careful of all these people. Every one of them is\nsomeone's child!\"So to some extent you can't trust me when I say having kids is\ngreat. To some extent I'm like a religious cultist telling you\nthat you'll be happy if you join the cult too — but only because\njoining the cult will alter your mind in a way that will make you\nhappy to be a cult member.But not entirely. There were some things\nabout having kids that I clearly got wrong before I had them.For example, there was a huge amount of selection bias in my\nobservations of parents and children. Some parents may have noticed\nthat I wrote \"Whenever I'd noticed parents with kids.\" Of course\nthe times I noticed kids were when things were going wrong. I only\nnoticed them when they made noise. And where was I when I noticed\nthem? Ordinarily I never went to places with kids, so the only\ntimes I encountered them were in shared bottlenecks like airplanes.\nWhich is not exactly a representative sample. Flying with a toddler\nis something very few parents enjoy.What I didn't notice, because they tend to be much quieter, were\nall the great moments parents had with kids. People don't talk about\nthese much — the magic is hard to put into words, and all other\nparents know about them anyway — but one of the great things about\nhaving kids is that there are so many times when you feel there is\nnowhere else you'd rather be, and nothing else you'd rather be\ndoing. You don't have to be doing anything special. You could just\nbe going somewhere together, or putting them to bed, or pushing\nthem on the swings at the park. But you wouldn't trade these moments\nfor anything. One doesn't tend to associate kids with peace, but\nthat's what you feel. You don't need to look any\nfurther than where you are right now.Before I had kids, I had moments of this kind of peace, but they\nwere rarer. With kids it can happen several times a day.My other source of data about kids was my own childhood, and that\nwas similarly misleading. I was pretty bad, and was always in trouble\nfor something or other. So it seemed to me that parenthood was\nessentially law enforcement. I didn't realize there were good times\ntoo.I remember my mother telling me once when I was about 30 that she'd\nreally enjoyed having me and my sister. My god, I thought, this\nwoman is a saint. She not only endured all the pain we subjected\nher to, but actually enjoyed it? Now I realize she was simply telling\nthe truth.She said that one reason she liked having us was that we'd been\ninteresting to talk to. That took me by surprise when I had kids.\nYou don't just love them. They become your friends too. They're\nreally interesting. And while I admit small children are disastrously\nfond of repetition (anything worth doing once is worth doing fifty\ntimes) it's often genuinely fun to play with them. That surprised\nme too. Playing with a 2 year old was fun when I was 2 and definitely\nnot fun when I was 6. Why would it become fun again later? But it\ndoes.There are of course times that are pure drudgery. Or worse still,\nterror. Having kids is one of those intense types of experience\nthat are hard to imagine unless you've had them. But it is not, as I\nimplicitly believed before having kids, simply your DNA heading for\nthe lifeboats.Some of my worries about having kids were right, though. They\ndefinitely make you less productive. I know having kids makes some\npeople get their act together, but if your act was already together,\nyou're going to have less time to do it in. In particular, you're\ngoing to have to work to a schedule. Kids have schedules. I'm not\nsure if it's because that's how kids are, or because it's the only\nway to integrate their lives with adults', but once you have kids,\nyou tend to have to work on their schedule.You will have chunks of time to work. But you can't let work spill\npromiscuously through your whole life, like I used to before I had\nkids. You're going to have to work at the same time every day,\nwhether inspiration is flowing or not, and there are going to be\ntimes when you have to stop, even if it is.I've been able to adapt to working this way. Work, like love, finds\na way. If there are only certain times it can happen, it happens\nat those times. So while I don't get as much done as before I had\nkids, I get enough done.I hate to say this, because being ambitious has always been a part\nof my identity, but having kids may make one less ambitious. It\nhurts to see that sentence written down. I squirm to avoid it. But\nif there weren't something real there, why would I squirm? The\nfact is, once you have kids, you're probably going to care more\nabout them than you do about yourself. And attention is a zero-sum\ngame. Only one idea at a time can be the \ntop idea in your mind.\nOnce you have kids, it will often be your kids, and that means it\nwill less often be some project you're working on.I have some hacks for sailing close to this wind. For example, when\nI write essays, I think about what I'd want my kids to know. That\ndrives me to get things right. And when I was writing \nBel, I told\nmy kids that once I finished it I'd take them to Africa. When you\nsay that sort of thing to a little kid, they treat it as a promise.\nWhich meant I had to finish or I'd be taking away their trip to\nAfrica. Maybe if I'm really lucky such tricks could put me net\nahead. But the wind is there, no question.On the other hand, what kind of wimpy ambition do you have if it\nwon't survive having kids? Do you have so little to spare?And while having kids may be warping my present judgement, it hasn't\noverwritten my memory. I remember perfectly well what life was like\nbefore. Well enough to miss some things a lot, like the\nability to take off for some other country at a moment's notice.\nThat was so great. Why did I never do that?See what I did there? The fact is, most of the freedom I had before\nkids, I never used. I paid for it in loneliness, but I never used\nit.I had plenty of happy times before I had kids. But if I count up\nhappy moments, not just potential happiness but actual happy moments,\nthere are more after kids than before. Now I practically have it\non tap, almost any bedtime.People's experiences as parents\nvary a lot, and I know I've been lucky. But I think the worries I\nhad before having kids must be pretty common, and judging by other\nparents' faces when they see their kids, so must the happiness that\nkids bring.\nNote[1] Adults are sophisticated enough to see 2 year olds for the\nfascinatingly complex characters they are, whereas to most 6 year\nolds, 2 year olds are just defective 6 year olds.Thanks to Trevor Blackwell, Jessica Livingston, and Robert Morris\nfor reading drafts of this." }, { "path": "data/PaulGrahamEssays/know.txt", "content": "December 2014I've read Villehardouin's chronicle of the Fourth Crusade at least\ntwo times, maybe three. And yet if I had to write down everything\nI remember from it, I doubt it would amount to much more than a\npage. Multiply this times several hundred, and I get an uneasy\nfeeling when I look at my bookshelves. What use is it to read all\nthese books if I remember so little from them?A few months ago, as I was reading Constance Reid's excellent\nbiography of Hilbert, I figured out if not the answer to this\nquestion, at least something that made me feel better about it.\nShe writes:\n\n Hilbert had no patience with mathematical lectures which filled\n the students with facts but did not teach them how to frame a\n problem and solve it. He often used to tell them that \"a perfect\n formulation of a problem is already half its solution.\"\n\nThat has always seemed to me an important point, and I was even\nmore convinced of it after hearing it confirmed by Hilbert.But how had I come to believe in this idea in the first place? A\ncombination of my own experience and other things I'd read. None\nof which I could at that moment remember! And eventually I'd forget\nthat Hilbert had confirmed it too. But my increased belief in the\nimportance of this idea would remain something I'd learned from\nthis book, even after I'd forgotten I'd learned it.Reading and experience train your model of the world. And even if\nyou forget the experience or what you read, its effect on your model\nof the world persists. Your mind is like a compiled program you've\nlost the source of. It works, but you don't know why.The place to look for what I learned from Villehardouin's chronicle\nis not what I remember from it, but my mental models of the crusades,\nVenice, medieval culture, siege warfare, and so on. Which doesn't\nmean I couldn't have read more attentively, but at least the harvest\nof reading is not so miserably small as it might seem.This is one of those things that seem obvious in retrospect. But\nit was a surprise to me and presumably would be to anyone else who\nfelt uneasy about (apparently) forgetting so much they'd read.Realizing it does more than make you feel a little better about\nforgetting, though. There are specific implications.For example, reading and experience are usually \"compiled\" at the\ntime they happen, using the state of your brain at that time. The\nsame book would get compiled differently at different points in\nyour life. Which means it is very much worth reading important\nbooks multiple times. I always used to feel some misgivings about\nrereading books. I unconsciously lumped reading together with work\nlike carpentry, where having to do something again is a sign you\ndid it wrong the first time. Whereas now the phrase \"already read\"\nseems almost ill-formed.Intriguingly, this implication isn't limited to books. Technology\nwill increasingly make it possible to relive our experiences. When\npeople do that today it's usually to enjoy them again (e.g. when\nlooking at pictures of a trip) or to find the origin of some bug in\ntheir compiled code (e.g. when Stephen Fry succeeded in remembering\nthe childhood trauma that prevented him from singing). But as\ntechnologies for recording and playing back your life improve, it\nmay become common for people to relive experiences without any goal\nin mind, simply to learn from them again as one might when rereading\na book.Eventually we may be able not just to play back experiences but\nalso to index and even edit them. So although not knowing how you\nknow things may seem part of being human, it may not be.\nThanks to Sam Altman, Jessica Livingston, and Robert Morris for reading \ndrafts of this." }, { "path": "data/PaulGrahamEssays/ladder.txt", "content": "August 2005Thirty years ago, one was supposed to work one's way up the corporate\nladder. That's less the rule now. Our generation wants to get\npaid up front. Instead of developing a product for some big company\nin the expectation of getting job security in return, we develop\nthe product ourselves, in a startup, and sell it to the big company.\nAt the very least we want options.Among other things, this shift has created the appearance of a rapid\nincrease in economic inequality. But really the two cases are not\nas different as they look in economic statistics.Economic statistics are misleading because they ignore the value\nof safe jobs. An easy job from which one can't be fired is worth\nmoney; exchanging the two is one of the commonest forms of\ncorruption. A sinecure is, in effect, an annuity. Except sinecures\ndon't appear in economic statistics. If they did, it would be clear\nthat in practice socialist countries have nontrivial disparities\nof wealth, because they usually have a class of powerful bureaucrats\nwho are paid mostly by seniority and can never be fired.While not a sinecure, a position on the corporate ladder was genuinely\nvaluable, because big companies tried not to fire people, and\npromoted from within based largely on seniority. A position on the\ncorporate ladder had a value analogous to the \"goodwill\" that is a\nvery real element in the valuation of companies. It meant one could\nexpect future high paying jobs.One of main causes of the decay of the corporate ladder is the trend\nfor takeovers that began in the 1980s. Why waste your time climbing\na ladder that might disappear before you reach the top?And, by no coincidence, the corporate ladder was one of the reasons\nthe early corporate raiders were so successful. It's not only\neconomic statistics that ignore the value of safe jobs. Corporate\nbalance sheets do too. One reason it was profitable to carve up 1980s\ncompanies and sell them for parts was that they hadn't formally\nacknowledged their implicit debt to employees who had done good\nwork and expected to be rewarded with high-paying executive jobs\nwhen their time came.In the movie Wall Street, Gordon Gekko\nridicules a company overloaded with vice presidents. But the company\nmay not be as corrupt as it seems; those VPs' cushy jobs were\nprobably payment for work done earlier.I like the new model better. For one thing, it seems a bad plan\nto treat jobs as rewards. Plenty of good engineers got made into\nbad managers that way. And the old system meant people had to deal\nwith a lot more corporate politics, in order to protect the work\nthey'd invested in a position on the ladder.The big disadvantage of the new system is that it involves more risk. If you develop ideas in a startup instead\nof within a big company, any number of random factors could sink\nyou before you can finish. But maybe the older generation would\nlaugh at me for saying that the way we do things is riskier. After\nall, projects within big companies were always getting cancelled\nas a result of arbitrary decisions from higher up. My father's\nentire industry (breeder reactors) disappeared that way.For better or worse, the idea of the corporate ladder is probably\ngone for good. The new model seems more liquid, and more efficient.\nBut it is less of a change, financially, than one might think. Our\nfathers weren't that stupid." }, { "path": "data/PaulGrahamEssays/langdes.txt", "content": "May 2001\n\n(These are some notes I made\nfor a panel discussion on programming language design\nat MIT on May 10, 2001.)1. Programming Languages Are for People.Programming languages\nare how people talk to computers. The computer would be just as\nhappy speaking any language that was unambiguous. The reason we\nhave high level languages is because people can't deal with\nmachine language. The point of programming\nlanguages is to prevent our poor frail human brains from being \noverwhelmed by a mass of detail.Architects know that some kinds of design problems are more personal\nthan others. One of the cleanest, most abstract design problems\nis designing bridges. There your job is largely a matter of spanning\na given distance with the least material. The other end of the\nspectrum is designing chairs. Chair designers have to spend their\ntime thinking about human butts.Software varies in the same way. Designing algorithms for routing\ndata through a network is a nice, abstract problem, like designing\nbridges. Whereas designing programming languages is like designing\nchairs: it's all about dealing with human weaknesses.Most of us hate to acknowledge this. Designing systems of great\nmathematical elegance sounds a lot more appealing to most of us\nthan pandering to human weaknesses. And there is a role for mathematical\nelegance: some kinds of elegance make programs easier to understand.\nBut elegance is not an end in itself.And when I say languages have to be designed to suit human weaknesses,\nI don't mean that languages have to be designed for bad programmers.\nIn fact I think you ought to design for the \nbest programmers, but\neven the best programmers have limitations. I don't think anyone\nwould like programming in a language where all the variables were\nthe letter x with integer subscripts.2. Design for Yourself and Your Friends.If you look at the history of programming languages, a lot of the best\nones were languages designed for their own authors to use, and a\nlot of the worst ones were designed for other people to use.When languages are designed for other people, it's always a specific\ngroup of other people: people not as smart as the language designer.\nSo you get a language that talks down to you. Cobol is the most\nextreme case, but a lot of languages are pervaded by this spirit.It has nothing to do with how abstract the language is. C is pretty\nlow-level, but it was designed for its authors to use, and that's\nwhy hackers like it.The argument for designing languages for bad programmers is that\nthere are more bad programmers than good programmers. That may be\nso. But those few good programmers write a disproportionately\nlarge percentage of the software.I'm interested in the question, how do you design a language that\nthe very best hackers will like? I happen to think this is\nidentical to the question, how do you design a good programming\nlanguage?, but even if it isn't, it is at least an interesting\nquestion.3. Give the Programmer as Much Control as Possible.Many languages\n(especially the ones designed for other people) have the attitude\nof a governess: they try to prevent you from\ndoing things that they think aren't good for you. I like the \nopposite approach: give the programmer as much\ncontrol as you can.When I first learned Lisp, what I liked most about it was\nthat it considered me an equal partner. In the other languages\nI had learned up till then, there was the language and there was my \nprogram, written in the language, and the two were very separate.\nBut in Lisp the functions and macros I wrote were just like those\nthat made up the language itself. I could rewrite the language\nif I wanted. It had the same appeal as open-source software.4. Aim for Brevity.Brevity is underestimated and even scorned.\nBut if you look into the hearts of hackers, you'll see that they\nreally love it. How many times have you heard hackers speak fondly\nof how in, say, APL, they could do amazing things with just a couple\nlines of code? I think anything that really smart people really\nlove is worth paying attention to.I think almost anything\nyou can do to make programs shorter is good. There should be lots\nof library functions; anything that can be implicit should be;\nthe syntax should be terse to a fault; even the names of things\nshould be short.And it's not only programs that should be short. The manual should\nbe thin as well. A good part of manuals is taken up with clarifications\nand reservations and warnings and special cases. If you force \nyourself to shorten the manual, in the best case you do it by fixing\nthe things in the language that required so much explanation.5. Admit What Hacking Is.A lot of people wish that hacking was\nmathematics, or at least something like a natural science. I think\nhacking is more like architecture. Architecture is\nrelated to physics, in the sense that architects have to design\nbuildings that don't fall down, but the actual goal of architects\nis to make great buildings, not to make discoveries about statics.What hackers like to do is make great programs.\nAnd I think, at least in our own minds, we have to remember that it's\nan admirable thing to write great programs, even when this work \ndoesn't translate easily into the conventional intellectual\ncurrency of research papers. Intellectually, it is just as\nworthwhile to design a language programmers will love as it is to design a\nhorrible one that embodies some idea you can publish a paper\nabout.1. How to Organize Big Libraries?Libraries are becoming an\nincreasingly important component of programming languages. They're\nalso getting bigger, and this can be dangerous. If it takes longer\nto find the library function that will do what you want than it\nwould take to write it yourself, then all that code is doing nothing\nbut make your manual thick. (The Symbolics manuals were a case in \npoint.) So I think we will have to work on ways to organize\nlibraries. The ideal would be to design them so that the programmer\ncould guess what library call would do the right thing.2. Are People Really Scared of Prefix Syntax?This is an open\nproblem in the sense that I have wondered about it for years and\nstill don't know the answer. Prefix syntax seems perfectly natural\nto me, except possibly for math. But it could be that a lot of \nLisp's unpopularity is simply due to having an unfamiliar syntax. \nWhether to do anything about it, if it is true, is another question. \n\n3. What Do You Need for Server-Based Software?\n\nI think a lot of the most exciting new applications that get written\nin the next twenty years will be Web-based applications, meaning\nprograms that sit on the server and talk to you through a Web\nbrowser. And to write these kinds of programs we may need some\nnew things.One thing we'll need is support for the new way that server-based \napps get released. Instead of having one or two big releases a\nyear, like desktop software, server-based apps get released as a\nseries of small changes. You may have as many as five or ten\nreleases a day. And as a rule everyone will always use the latest\nversion.You know how you can design programs to be debuggable?\nWell, server-based software likewise has to be designed to be\nchangeable. You have to be able to change it easily, or at least\nto know what is a small change and what is a momentous one.Another thing that might turn out to be useful for server based\nsoftware, surprisingly, is continuations. In Web-based software\nyou can use something like continuation-passing style to get the\neffect of subroutines in the inherently \nstateless world of a Web\nsession. Maybe it would be worthwhile having actual continuations,\nif it was not too expensive.4. What New Abstractions Are Left to Discover?I'm not sure how\nreasonable a hope this is, but one thing I would really love to \ndo, personally, is discover a new abstraction-- something that would\nmake as much of a difference as having first class functions or\nrecursion or even keyword parameters. This may be an impossible\ndream. These things don't get discovered that often. But I am always\nlooking.1. You Can Use Whatever Language You Want.Writing application\nprograms used to mean writing desktop software. And in desktop\nsoftware there is a big bias toward writing the application in the\nsame language as the operating system. And so ten years ago,\nwriting software pretty much meant writing software in C.\nEventually a tradition evolved:\napplication programs must not be written in unusual languages. \nAnd this tradition had so long to develop that nontechnical people\nlike managers and venture capitalists also learned it.Server-based software blows away this whole model. With server-based\nsoftware you can use any language you want. Almost nobody understands\nthis yet (especially not managers and venture capitalists).\nA few hackers understand it, and that's why we even hear\nabout new, indy languages like Perl and Python. We're not hearing\nabout Perl and Python because people are using them to write Windows\napps.What this means for us, as people interested in designing programming\nlanguages, is that there is now potentially an actual audience for\nour work.2. Speed Comes from Profilers.Language designers, or at least\nlanguage implementors, like to write compilers that generate fast\ncode. But I don't think this is what makes languages fast for users.\nKnuth pointed out long ago that speed only matters in a few critical\nbottlenecks. And anyone who's tried it knows that you can't guess\nwhere these bottlenecks are. Profilers are the answer.Language designers are solving the wrong problem. Users don't need\nbenchmarks to run fast. What they need is a language that can show\nthem what parts of their own programs need to be rewritten. That's\nwhere speed comes from in practice. So maybe it would be a net \nwin if language implementors took half the time they would\nhave spent doing compiler optimizations and spent it writing a\ngood profiler instead.3. You Need an Application to Drive the Design of a Language.This may not be an absolute rule, but it seems like the best languages\nall evolved together with some application they were being used to\nwrite. C was written by people who needed it for systems programming.\nLisp was developed partly to do symbolic differentiation, and\nMcCarthy was so eager to get started that he was writing differentiation\nprograms even in the first paper on Lisp, in 1960.It's especially good if your application solves some new problem.\nThat will tend to drive your language to have new features that \nprogrammers need. I personally am interested in writing\na language that will be good for writing server-based applications.[During the panel, Guy Steele also made this point, with the\nadditional suggestion that the application should not consist of\nwriting the compiler for your language, unless your language\nhappens to be intended for writing compilers.]4. A Language Has to Be Good for Writing Throwaway Programs.You know what a throwaway program is: something you write quickly for\nsome limited task. I think if you looked around you'd find that \na lot of big, serious programs started as throwaway programs. I\nwould not be surprised if most programs started as throwaway\nprograms. And so if you want to make a language that's good for\nwriting software in general, it has to be good for writing throwaway\nprograms, because that is the larval stage of most software.5. Syntax Is Connected to Semantics.It's traditional to think of\nsyntax and semantics as being completely separate. This will\nsound shocking, but it may be that they aren't.\nI think that what you want in your language may be related\nto how you express it.I was talking recently to Robert Morris, and he pointed out that\noperator overloading is a bigger win in languages with infix\nsyntax. In a language with prefix syntax, any function you define\nis effectively an operator. If you want to define a plus for a\nnew type of number you've made up, you can just define a new function\nto add them. If you do that in a language with infix syntax,\nthere's a big difference in appearance between the use of an\noverloaded operator and a function call.1. New Programming Languages.Back in the 1970s\nit was fashionable to design new programming languages. Recently\nit hasn't been. But I think server-based software will make new \nlanguages fashionable again. With server-based software, you can\nuse any language you want, so if someone does design a language that\nactually seems better than others that are available, there will be\npeople who take a risk and use it.2. Time-Sharing.Richard Kelsey gave this as an idea whose time\nhas come again in the last panel, and I completely agree with him.\nMy guess (and Microsoft's guess, it seems) is that much computing\nwill move from the desktop onto remote servers. In other words, \ntime-sharing is back. And I think there will need to be support\nfor it at the language level. For example, I know that Richard\nand Jonathan Rees have done a lot of work implementing process \nscheduling within Scheme 48.3. Efficiency.Recently it was starting to seem that computers\nwere finally fast enough. More and more we were starting to hear\nabout byte code, which implies to me at least that we feel we have\ncycles to spare. But I don't think we will, with server-based\nsoftware. Someone is going to have to pay for the servers that\nthe software runs on, and the number of users they can support per\nmachine will be the divisor of their capital cost.So I think efficiency will matter, at least in computational\nbottlenecks. It will be especially important to do i/o fast,\nbecause server-based applications do a lot of i/o.It may turn out that byte code is not a win, in the end. Sun and\nMicrosoft seem to be facing off in a kind of a battle of the byte\ncodes at the moment. But they're doing it because byte code is a\nconvenient place to insert themselves into the process, not because\nbyte code is in itself a good idea. It may turn out that this\nwhole battleground gets bypassed. That would be kind of amusing.1. Clients.This is just a guess, but my guess is that\nthe winning model for most applications will be purely server-based.\nDesigning software that works on the assumption that everyone will \nhave your client is like designing a society on the assumption that\neveryone will just be honest. It would certainly be convenient, but\nyou have to assume it will never happen.I think there will be a proliferation of devices that have some\nkind of Web access, and all you'll be able to assume about them is\nthat they can support simple html and forms. Will you have a\nbrowser on your cell phone? Will there be a phone in your palm \npilot? Will your blackberry get a bigger screen? Will you be able\nto browse the Web on your gameboy? Your watch? I don't know. \nAnd I don't have to know if I bet on\neverything just being on the server. It's\njust so much more robust to have all the \nbrains on the server.2. Object-Oriented Programming.I realize this is a\ncontroversial one, but I don't think object-oriented programming\nis such a big deal. I think it is a fine model for certain kinds\nof applications that need that specific kind of data structure, \nlike window systems, simulations, and cad programs. But I don't\nsee why it ought to be the model for all programming.I think part of the reason people in big companies like object-oriented\nprogramming is because it yields a lot of what looks like work.\nSomething that might naturally be represented as, say, a list of\nintegers, can now be represented as a class with all kinds of\nscaffolding and hustle and bustle.Another attraction of\nobject-oriented programming is that methods give you some of the\neffect of first class functions. But this is old news to Lisp\nprogrammers. When you have actual first class functions, you can\njust use them in whatever way is appropriate to the task at hand,\ninstead of forcing everything into a mold of classes and methods.What this means for language design, I think, is that you shouldn't\nbuild object-oriented programming in too deeply. Maybe the\nanswer is to offer more general, underlying stuff, and let people design\nwhatever object systems they want as libraries.3. Design by Committee.Having your language designed by a committee is a big pitfall, \nand not just for the reasons everyone knows about. Everyone\nknows that committees tend to yield lumpy, inconsistent designs. \nBut I think a greater danger is that they won't take risks.\nWhen one person is in charge he can take risks\nthat a committee would never agree on.Is it necessary to take risks to design a good language though?\nMany people might suspect\nthat language design is something where you should stick fairly\nclose to the conventional wisdom. I bet this isn't true.\nIn everything else people do, reward is proportionate to risk.\nWhy should language design be any different?" }, { "path": "data/PaulGrahamEssays/laundry.txt", "content": "October 2004\nAs E. B. White said, \"good writing is rewriting.\" I didn't\nrealize this when I was in school. In writing, as in math and \nscience, they only show you the finished product.\nYou don't see all the false starts. This gives students a\nmisleading view of how things get made.Part of the reason it happens is that writers don't want \npeople to see their mistakes. But I'm willing to let people\nsee an early draft if it will show how much you have\nto rewrite to beat an essay into shape.Below is the oldest version I can find of\nThe Age of the Essay \n(probably the second or third day), with\ntext that ultimately survived in \nred and text that later\ngot deleted in gray.\nThere seem to be several categories of cuts: things I got wrong,\nthings that seem like bragging, flames,\ndigressions, stretches of awkward prose, and unnecessary words.I discarded more from the beginning. That's\nnot surprising; it takes a while to hit your stride. There\nare more digressions at the start, because I'm not sure where\nI'm heading.The amount of cutting is about average. I probably write\nthree to four words for every one that appears in the final\nversion of an essay.(Before anyone gets mad at me for opinions expressed here, remember\nthat anything you see here that's not in the final version is obviously\nsomething I chose not to publish, often because I disagree\nwith it.)\nRecently a friend said that what he liked about\nmy essays was that they weren't written the way\nwe'd been taught to write essays in school. You\nremember: topic sentence, introductory paragraph,\nsupporting paragraphs, conclusion. It hadn't\noccurred to me till then that those horrible things\nwe had to write in school were even connected to\nwhat I was doing now. But sure enough, I thought,\nthey did call them \"essays,\" didn't they?Well, they're not. Those things you have to write\nin school are not only not essays, they're one of the\nmost pointless of all the pointless hoops you have\nto jump through in school. And I worry that they\nnot only teach students the wrong things about writing,\nbut put them off writing entirely.So I'm going to give the other side of the story: what\nan essay really is, and how you write one. Or at least,\nhow I write one. Students be forewarned: if you actually write\nthe kind of essay I describe, you'll probably get bad\ngrades. But knowing how it's really done should\nat least help you to understand the feeling of futility\nyou have when you're writing the things they tell you to.\nThe most obvious difference between real essays and\nthe things one has to write in school is that real\nessays are not exclusively about English literature.\nIt's a fine thing for schools to\n\nteach students how to\nwrite. But for some bizarre reason (actually, a very specific bizarre\nreason that I'll explain in a moment),\n\nthe teaching of\nwriting has gotten mixed together with the study\nof literature. And so all over the country, students are\nwriting not about how a baseball team with a small budget \nmight compete with the Yankees, or the role of color in\nfashion, or what constitutes a good dessert, but about\nsymbolism in Dickens.With obvious \nresults. Only a few people really\n\ncare about\nsymbolism in Dickens. The teacher doesn't.\nThe students don't. Most of the people who've had to write PhD\ndisserations about Dickens don't. And certainly\n\nDickens himself would be more interested in an essay\nabout color or baseball.How did things get this way? To answer that we have to go back\nalmost a thousand years. Between about 500 and 1000, life was\nnot very good in Europe. The term \"dark ages\" is presently\nout of fashion as too judgemental (the period wasn't dark; \nit was just different), but if this label didn't already\nexist, it would seem an inspired metaphor. What little\noriginal thought there was took place in lulls between\nconstant wars and had something of the character of\nthe thoughts of parents with a new baby.\nThe most amusing thing written during this\nperiod, Liudprand of Cremona's Embassy to Constantinople, is,\nI suspect, mostly inadvertantly so.Around 1000 Europe began to catch its breath.\nAnd once they\nhad the luxury of curiosity, one of the first things they discovered\nwas what we call \"the classics.\"\nImagine if we were visited \nby aliens. If they could even get here they'd presumably know a\nfew things we don't. Immediately Alien Studies would become\nthe most dynamic field of scholarship: instead of painstakingly\ndiscovering things for ourselves, we could simply suck up\neverything they'd discovered. So it was in Europe in 1200.\nWhen classical texts began to circulate in Europe, they contained\nnot just new answers, but new questions. (If anyone proved\na theorem in christian Europe before 1200, for example, there\nis no record of it.)For a couple centuries, some of the most important work\nbeing done was intellectual archaelogy. Those were also\nthe centuries during which schools were first established.\nAnd since reading ancient texts was the essence of what\nscholars did then, it became the basis of the curriculum.By 1700, someone who wanted to learn about\nphysics didn't need to start by mastering Greek in order to read Aristotle. But schools\nchange slower than scholarship: the study of\nancient texts\nhad such prestige that it remained the backbone of \neducation\nuntil the late 19th century. By then it was merely a tradition.\nIt did serve some purposes: reading a foreign language was difficult,\nand thus taught discipline, or at least, kept students busy;\nit introduced students to\ncultures quite different from their own; and its very uselessness\nmade it function (like white gloves) as a social bulwark.\nBut it certainly wasn't\ntrue, and hadn't been true for centuries, that students were\nserving apprenticeships in the hottest area of scholarship.Classical scholarship had also changed. In the early era, philology\nactually mattered. The texts that filtered into Europe were\nall corrupted to some degree by the errors of translators and\ncopyists. Scholars had to figure out what Aristotle said\nbefore they could figure out what he meant. But by the modern\nera such questions were answered as well as they were ever\ngoing to be. And so the study of ancient texts became less\nabout ancientness and more about texts.The time was then ripe for the question: if the study of\nancient texts is a valid field for scholarship, why not modern\ntexts? The answer, of course, is that the raison d'etre\nof classical scholarship was a kind of intellectual archaelogy that\ndoes not need to be done in the case of contemporary authors.\nBut for obvious reasons no one wanted to give that answer.\nThe archaeological work being mostly done, it implied that\nthe people studying the classics were, if not wasting their\ntime, at least working on problems of minor importance.And so began the study of modern literature. There was some\ninitial resistance, but it didn't last long.\nThe limiting\nreagent in the growth of university departments is what\nparents will let undergraduates study. If parents will let\ntheir children major in x, the rest follows straightforwardly.\nThere will be jobs teaching x, and professors to fill them.\nThe professors will establish scholarly journals and publish\none another's papers. Universities with x departments will\nsubscribe to the journals. Graduate students who want jobs\nas professors of x will write dissertations about it. It may\ntake a good long while for the more prestigious universities\nto cave in and establish departments in cheesier xes, but\nat the other end of the scale there are so many universities\ncompeting to attract students that the mere establishment of\na discipline requires little more than the desire to do it.High schools imitate universities.\nAnd so once university\nEnglish departments were established in the late nineteenth century,\nthe 'riting component of the 3 Rs \nwas morphed into English.\nWith the bizarre consequence that high school students now\nhad to write about English literature-- to write, without\neven realizing it, imitations of whatever\nEnglish professors had been publishing in their journals a\nfew decades before. It's no wonder if this seems to the\nstudent a pointless exercise, because we're now three steps\nremoved from real work: the students are imitating English\nprofessors, who are imitating classical scholars, who are\nmerely the inheritors of a tradition growing out of what\nwas, 700 years ago, fascinating and urgently needed work.Perhaps high schools should drop English and just teach writing.\nThe valuable part of English classes is learning to write, and\nthat could be taught better by itself. Students learn better\nwhen they're interested in what they're doing, and it's hard\nto imagine a topic less interesting than symbolism in Dickens.\nMost of the people who write about that sort of thing professionally\nare not really interested in it. (Though indeed, it's been a\nwhile since they were writing about symbolism; now they're\nwriting about gender.)I have no illusions about how eagerly this suggestion will \nbe adopted. Public schools probably couldn't stop teaching\nEnglish even if they wanted to; they're probably required to by\nlaw. But here's a related suggestion that goes with the grain\ninstead of against it: that universities establish a\nwriting major. Many of the students who now major in English\nwould major in writing if they could, and most would\nbe better off.It will be argued that it is a good thing for students to be\nexposed to their literary heritage. Certainly. But is that\nmore important than that they learn to write well? And are\nEnglish classes even the place to do it? After all,\nthe average public high school student gets zero exposure to \nhis artistic heritage. No disaster results.\nThe people who are interested in art learn about it for\nthemselves, and those who aren't don't. I find that American\nadults are no better or worse informed about literature than\nart, despite the fact that they spent years studying literature\nin high school and no time at all studying art. Which presumably\nmeans that what they're taught in school is rounding error \ncompared to what they pick up on their own.Indeed, English classes may even be harmful. In my case they\nwere effectively aversion therapy. Want to make someone dislike\na book? Force him to read it and write an essay about it.\nAnd make the topic so intellectually bogus that you\ncould not, if asked, explain why one ought to write about it.\nI love to read more than anything, but by the end of high school\nI never read the books we were assigned. I was so disgusted with\nwhat we were doing that it became a point of honor\nwith me to write nonsense at least as good at the other students'\nwithout having more than glanced over the book to learn the names\nof the characters and a few random events in it.I hoped this might be fixed in college, but I found the same\nproblem there. It was not the teachers. It was English. \nWe were supposed to read novels and write essays about them.\nAbout what, and why? That no one seemed to be able to explain.\nEventually by trial and error I found that what the teacher \nwanted us to do was pretend that the story had really taken\nplace, and to analyze based on what the characters said and did (the\nsubtler clues, the better) what their motives must have been.\nOne got extra credit for motives having to do with class,\nas I suspect one must now for those involving gender and \nsexuality. I learned how to churn out such stuff well enough\nto get an A, but I never took another English class.And the books we did these disgusting things to, like those\nwe mishandled in high school, I find still have black marks\nagainst them in my mind. The one saving grace was that \nEnglish courses tend to favor pompous, dull writers like\nHenry James, who deserve black marks against their names anyway.\nOne of the principles the IRS uses in deciding whether to\nallow deductions is that, if something is fun, it isn't work.\nFields that are intellectually unsure of themselves rely on\na similar principle. Reading P.G. Wodehouse or Evelyn Waugh or\nRaymond Chandler is too obviously pleasing to seem like\nserious work, as reading Shakespeare would have been before \nEnglish evolved enough to make it an effort to understand him. [sh]\nAnd so good writers (just you wait and see who's still in\nprint in 300 years) are less likely to have readers turned \nagainst them by clumsy, self-appointed tour guides.\nThe other big difference between a real essay and the \nthings\nthey make you write in school is that a real essay doesn't \ntake a position and then defend it. That principle,\nlike the idea that we ought to be writing about literature, \nturns out to be another intellectual hangover of long\nforgotten origins. It's often mistakenly believed that\nmedieval universities were mostly seminaries. In fact they\nwere more law schools. And at least in our tradition\nlawyers are advocates: they are\ntrained to be able to\ntake\neither side of an argument and make as good a case for it \nas they can. Whether or not this is a good idea (in the case of prosecutors,\nit probably isn't), it tended to pervade\nthe atmosphere of\nearly universities. After the lecture the most common form\nof discussion was the disputation. This idea\nis at least\nnominally preserved in our present-day thesis defense-- indeed,\nin the very word thesis. Most people treat the words \nthesis\nand dissertation as interchangeable, but originally, at least,\na thesis was a position one took and the dissertation was\nthe argument by which one defended it.I'm not complaining that we blur these two words together.\nAs far as I'm concerned, the sooner we lose the original\nsense of the word thesis, the better. For many, perhaps most, \ngraduate students, it is stuffing a square peg into a round\nhole to try to recast one's work as a single thesis. And\nas for the disputation, that seems clearly a net lose.\nArguing two sides of a case may be a necessary evil in a\nlegal dispute, but it's not the best way to get at the truth,\nas I think lawyers would be the first to admit.\nAnd yet this principle is built into the very structure of \nthe essays\nthey teach you to write in high school. The topic\nsentence is your thesis, chosen in advance, the supporting \nparagraphs the blows you strike in the conflict, and the\nconclusion--- uh, what it the conclusion? I was never sure \nabout that in high school. If your thesis was well expressed,\nwhat need was there to restate it? In theory it seemed that\nthe conclusion of a really good essay ought not to need to \nsay any more than QED.\nBut when you understand the origins\nof this sort of \"essay\", you can see where the\nconclusion comes from. It's the concluding remarks to the \njury.\nWhat other alternative is there? To answer that\nwe have to\nreach back into history again, though this time not so far.\nTo Michel de Montaigne, inventor of the essay.\nHe was\ndoing something quite different from what a\nlawyer does,\nand\nthe difference is embodied in the name. Essayer is the French\nverb meaning \"to try\" (the cousin of our word assay),\n\nand an \"essai\" is an effort.\nAn essay is something you\nwrite in order\nto figure something out.Figure out what? You don't know yet. And so you can't begin with a\nthesis, because you don't have one, and may never have \none. An essay doesn't begin with a statement, but with a \nquestion. In a real essay, you don't take a position and\ndefend it. You see a door that's ajar, and you open it and\nwalk in to see what's inside.If all you want to do is figure things out, why do you need\nto write anything, though? Why not just sit and think? Well,\nthere precisely is Montaigne's great discovery. Expressing\nideas helps to form them. Indeed, helps is far too weak a\nword. 90%\nof what ends up in my essays was stuff\nI only\nthought of when I sat down to write them. That's why I\nwrite them.So there's another difference between essays and\nthe things\nyou have to write in school. In school\n\nyou are, in theory,\nexplaining yourself to someone else. In the best case---if\nyou're really organized---you're just writing it down.\nIn a real essay you're writing for yourself. You're\nthinking out loud.But not quite. Just as inviting people over forces you to\nclean up your apartment, writing something that you know\n\nother people will read forces you to think well. So it\ndoes matter to have an audience. The things I've written\njust for myself are no good. Indeed, they're bad in\na particular way:\nthey tend to peter out. When I run into\ndifficulties, I notice that I\ntend to conclude with a few vague\nquestions and then drift off to get a cup of tea.This seems a common problem.\nIt's practically the standard\nending in blog entries--- with the addition of a \"heh\" or an \nemoticon, prompted by the all too accurate sense that\nsomething is missing.And indeed, a lot of\npublished essays peter out in this\nsame way.\nParticularly the sort written by the staff writers of newsmagazines. Outside writers tend to supply\neditorials of the defend-a-position variety, which\nmake a beeline toward a rousing (and\nforeordained) conclusion. But the staff writers feel\nobliged to write something more\nbalanced, which in\npractice ends up meaning blurry.\nSince they're\nwriting for a popular magazine, they start with the\nmost radioactively controversial questions, from which\n(because they're writing for a popular magazine)\nthey then proceed to recoil from\nin terror.\nGay marriage, for or\nagainst? This group says one thing. That group says\nanother. One thing is certain: the question is a\ncomplex one. (But don't get mad at us. We didn't\ndraw any conclusions.)Questions aren't enough. An essay has to come up with answers.\nThey don't always, of course. Sometimes you start with a \npromising question and get nowhere. But those you don't\npublish. Those are like experiments that get inconclusive\nresults. Something you publish ought to tell the reader \nsomething he didn't already know.\nBut what you tell him doesn't matter, so long as \nit's interesting. I'm sometimes accused of meandering.\nIn defend-a-position writing that would be a flaw.\nThere you're not concerned with truth. You already\nknow where you're going, and you want to go straight there,\nblustering through obstacles, and hand-waving\nyour way across swampy ground. But that's not what\nyou're trying to do in an essay. An essay is supposed to\nbe a search for truth. It would be suspicious if it didn't\nmeander.The Meander is a river in Asia Minor (aka\nTurkey).\nAs you might expect, it winds all over the place.\nBut does it\ndo this out of frivolity? Quite the opposite.\nLike all rivers, it's rigorously following the laws of physics.\nThe path it has discovered,\nwinding as it is, represents\nthe most economical route to the sea.The river's algorithm is simple. At each step, flow down.\nFor the essayist this translates to: flow interesting.\nOf all the places to go next, choose\nwhichever seems\nmost interesting.I'm pushing this metaphor a bit. An essayist\ncan't have\nquite as little foresight as a river. In fact what you do\n(or what I do) is somewhere between a river and a roman\nroad-builder. I have a general idea of the direction\nI want to go in, and\nI choose the next topic with that in mind. This essay is\nabout writing, so I do occasionally yank it back in that\ndirection, but it is not all the sort of essay I\nthought I was going to write about writing.Note too that hill-climbing (which is what this algorithm is\ncalled) can get you in trouble.\nSometimes, just\nlike a river,\nyou\nrun up against a blank wall. What\nI do then is just \nwhat the river does: backtrack.\nAt one point in this essay\nI found that after following a certain thread I ran out\nof ideas. I had to go back n\nparagraphs and start over\nin another direction. For illustrative purposes I've left\nthe abandoned branch as a footnote.\nErr on the side of the river. An essay is not a reference\nwork. It's not something you read looking for a specific\nanswer, and feel cheated if you don't find it. I'd much\nrather read an essay that went off in an unexpected but\ninteresting direction than one that plodded dutifully along\na prescribed course.So what's interesting? For me, interesting means surprise.\nDesign, as Matz\nhas said, should follow the principle of\nleast surprise.\nA button that looks like it will make a\nmachine stop should make it stop, not speed up. Essays\nshould do the opposite. Essays should aim for maximum\nsurprise.I was afraid of flying for a long time and could only travel\nvicariously. When friends came back from faraway places,\nit wasn't just out of politeness that I asked them about\ntheir trip.\nI really wanted to know. And I found that\nthe best way to get information out of them was to ask\nwhat surprised them. How was the place different from what\nthey expected? This is an extremely useful question.\nYou can ask it of even\nthe most unobservant people, and it will\nextract information they didn't even know they were\nrecording. Indeed, you can ask it in real time. Now when I go somewhere\nnew, I make a note of what surprises me about it. Sometimes I\neven make a conscious effort to visualize the place beforehand,\nso I'll have a detailed image to diff with reality.\nSurprises are facts\nyou didn't already \nknow.\nBut they're\nmore than that. They're facts\nthat contradict things you\nthought you knew. And so they're the most valuable sort of\nfact you can get. They're like a food that's not merely\nhealthy, but counteracts the unhealthy effects of things\nyou've already eaten.\nHow do you find surprises? Well, therein lies half\nthe work of essay writing. (The other half is expressing\nyourself well.) You can at least\nuse yourself as a\nproxy for the reader. You should only write about things\nyou've thought about a lot. And anything you come across\nthat surprises you, who've thought about the topic a lot,\nwill probably surprise most readers.For example, in a recent essay I pointed out that because\nyou can only judge computer programmers by working with\nthem, no one knows in programming who the heroes should\nbe.\nI\ncertainly\ndidn't realize this when I started writing\nthe \nessay, and even now I find it kind of weird. That's\nwhat you're looking for.So if you want to write essays, you need two ingredients:\nyou need\na few topics that you think about a lot, and you\nneed some ability to ferret out the unexpected.What should you think about? My guess is that it\ndoesn't matter. Almost everything is\ninteresting if you get deeply\nenough into it. The one possible exception\nare\nthings\nlike working in fast food, which\nhave deliberately had all\nthe variation sucked out of them.\nIn retrospect, was there\nanything interesting about working in Baskin-Robbins?\nWell, it was interesting to notice\nhow important color was\nto the customers. Kids a certain age would point into\nthe case and say that they wanted yellow. Did they want\nFrench Vanilla or Lemon? They would just look at you\nblankly. They wanted yellow. And then there was the\nmystery of why the perennial favorite Pralines n' Cream\nwas so appealing. I'm inclined now to\nthink it was the salt.\nAnd the mystery of why Passion Fruit tasted so disgusting.\nPeople would order it because of the name, and were always\ndisappointed. It should have been called In-sink-erator\nFruit.\nAnd there was\nthe difference in the way fathers and\nmothers bought ice cream for their kids.\nFathers tended to\nadopt the attitude of\nbenevolent kings bestowing largesse,\nand mothers that of\nharried bureaucrats,\ngiving in to\npressure against their better judgement.\nSo, yes, there does seem to be material, even in\nfast food.What about the other half, ferreting out the unexpected?\nThat may require some natural ability. I've noticed for\na long time that I'm pathologically observant. ....[That was as far as I'd gotten at the time.]Notes[sh] In Shakespeare's own time, serious writing meant theological\ndiscourses, not the bawdy plays acted over on the other \nside of the river among the bear gardens and whorehouses.The other extreme, the work that seems formidable from the moment\nit's created (indeed, is deliberately intended to be)\nis represented by Milton. Like the Aeneid, Paradise Lost is a\nrock imitating a butterfly that happened to get fossilized.\nEven Samuel Johnson seems to have balked at this, on the one \nhand paying Milton the compliment of an extensive biography,\nand on the other writing of Paradise Lost that \"none who read it\never wished it longer.\"" }, { "path": "data/PaulGrahamEssays/lesson.txt", "content": "December 2019\nThe most damaging thing you learned in school wasn't something you\nlearned in any specific class. It was learning to get good grades.When I was in college, a particularly earnest philosophy grad student\nonce told me that he never cared what grade he got in a class, only\nwhat he learned in it. This stuck in my mind because it was the\nonly time I ever heard anyone say such a thing.For me, as for most students, the measurement of what I was learning\ncompletely dominated actual learning in college. I was fairly\nearnest; I was genuinely interested in most of the classes I took,\nand I worked hard. And yet I worked by far the hardest when I was\nstudying for a test.In theory, tests are merely what their name implies: tests of what\nyou've learned in the class. In theory you shouldn't have to prepare\nfor a test in a class any more than you have to prepare for a blood\ntest. In theory you learn from taking the class, from going to the\nlectures and doing the reading and/or assignments, and the test\nthat comes afterward merely measures how well you learned.In practice, as almost everyone reading this will know, things are\nso different that hearing this explanation of how classes and tests\nare meant to work is like hearing the etymology of a word whose\nmeaning has changed completely. In practice, the phrase \"studying\nfor a test\" was almost redundant, because that was when one really\nstudied. The difference between diligent and slack students was\nthat the former studied hard for tests and the latter didn't. No\none was pulling all-nighters two weeks into the semester.Even though I was a diligent student, almost all the work I did in\nschool was aimed at getting a good grade on something.To many people, it would seem strange that the preceding sentence\nhas a \"though\" in it. Aren't I merely stating a tautology? Isn't\nthat what a diligent student is, a straight-A student? That's how\ndeeply the conflation of learning with grades has infused our\nculture.Is it so bad if learning is conflated with grades? Yes, it is bad.\nAnd it wasn't till decades after college, when I was running Y Combinator, that I realized how bad it is.I knew of course when I was a student that studying for a test is\nfar from identical with actual learning. At the very least, you\ndon't retain knowledge you cram into your head the night before an\nexam. But the problem is worse than that. The real problem is that\nmost tests don't come close to measuring what they're supposed to.If tests truly were tests of learning, things wouldn't be so bad.\nGetting good grades and learning would converge, just a little late.\nThe problem is that nearly all tests given to students are terribly\nhackable. Most people who've gotten good grades know this, and know\nit so well they've ceased even to question it. You'll see when you\nrealize how naive it sounds to act otherwise.Suppose you're taking a class on medieval history and the final\nexam is coming up. The final exam is supposed to be a test of your\nknowledge of medieval history, right? So if you have a couple days\nbetween now and the exam, surely the best way to spend the time,\nif you want to do well on the exam, is to read the best books you\ncan find about medieval history. Then you'll know a lot about it,\nand do well on the exam.No, no, no, experienced students are saying to themselves. If you\nmerely read good books on medieval history, most of the stuff you\nlearned wouldn't be on the test. It's not good books you want to\nread, but the lecture notes and assigned reading in this class.\nAnd even most of that you can ignore, because you only have to worry\nabout the sort of thing that could turn up as a test question.\nYou're looking for sharply-defined chunks of information. If one\nof the assigned readings has an interesting digression on some\nsubtle point, you can safely ignore that, because it's not the sort\nof thing that could be turned into a test question. But if the\nprofessor tells you that there were three underlying causes of the\nSchism of 1378, or three main consequences of the Black Death, you'd\nbetter know them. And whether they were in fact the causes or\nconsequences is beside the point. For the purposes of this class\nthey are.At a university there are often copies of old exams floating around,\nand these narrow still further what you have to learn. As well as\nlearning what kind of questions this professor asks, you'll often\nget actual exam questions. Many professors re-use them. After\nteaching a class for 10 years, it would be hard not to, at least\ninadvertently.In some classes, your professor will have had some sort of political\naxe to grind, and if so you'll have to grind it too. The need for\nthis varies. In classes in math or the hard sciences or engineering\nit's rarely necessary, but at the other end of the spectrum there\nare classes where you couldn't get a good grade without it.Getting a good grade in a class on x is so different from learning\na lot about x that you have to choose one or the other, and you\ncan't blame students if they choose grades. Everyone judges them\nby their grades — graduate programs, employers, scholarships, even\ntheir own parents.I liked learning, and I really enjoyed some of the papers and\nprograms I wrote in college. But did I ever, after turning in a\npaper in some class, sit down and write another just for fun? Of\ncourse not. I had things due in other classes. If it ever came to\na choice of learning or grades, I chose grades. I hadn't come to\ncollege to do badly.Anyone who cares about getting good grades has to play this game,\nor they'll be surpassed by those who do. And at elite universities,\nthat means nearly everyone, since someone who didn't care about\ngetting good grades probably wouldn't be there in the first place.\nThe result is that students compete to maximize the difference\nbetween learning and getting good grades.Why are tests so bad? More precisely, why are they so hackable?\nAny experienced programmer could answer that. How hackable is\nsoftware whose author hasn't paid any attention to preventing it\nfrom being hacked? Usually it's as porous as a colander.Hackable is the default for any test imposed by an authority. The\nreason the tests you're given are so consistently bad — so consistently\nfar from measuring what they're supposed to measure — is simply\nthat the people creating them haven't made much effort to prevent\nthem from being hacked.But you can't blame teachers if their tests are hackable. Their job\nis to teach, not to create unhackable tests. The real problem is\ngrades, or more precisely, that grades have been overloaded. If\ngrades were merely a way for teachers to tell students what they\nwere doing right and wrong, like a coach giving advice to an athlete,\nstudents wouldn't be tempted to hack tests. But unfortunately after\na certain age grades become more than advice. After a certain age,\nwhenever you're being taught, you're usually also being judged.I've used college tests as an example, but those are actually the\nleast hackable. All the tests most students take their whole lives\nare at least as bad, including, most spectacularly of all, the test\nthat gets them into college. If getting into college were merely a\nmatter of having the quality of one's mind measured by admissions\nofficers the way scientists measure the mass of an object, we could\ntell teenage kids \"learn a lot\" and leave it at that. You can tell\nhow bad college admissions are, as a test, from how unlike high\nschool that sounds. In practice, the freakishly specific nature of\nthe stuff ambitious kids have to do in high school is directly\nproportionate to the hackability of college admissions. The classes\nyou don't care about that are mostly memorization, the random\n\"extracurricular activities\" you have to participate in to show\nyou're \"well-rounded,\" the standardized tests as artificial as\nchess, the \"essay\" you have to write that's presumably meant to hit\nsome very specific target, but you're not told what.As well as being bad in what it does to kids, this test is also bad\nin the sense of being very hackable. So hackable that whole industries\nhave grown up to hack it. This is the explicit purpose of test-prep\ncompanies and admissions counsellors, but it's also a significant\npart of the function of private schools.Why is this particular test so hackable? I think because of what\nit's measuring. Although the popular story is that the way to get\ninto a good college is to be really smart, admissions officers at\nelite colleges neither are, nor claim to be, looking only for that.\nWhat are they looking for? They're looking for people who are not\nsimply smart, but admirable in some more general sense. And how\nis this more general admirableness measured? The admissions officers\nfeel it. In other words, they accept who they like.So what college admissions is a test of is whether you suit the\ntaste of some group of people. Well, of course a test like that is\ngoing to be hackable. And because it's both very hackable and there's\n(thought to be) a lot at stake, it's hacked like nothing else.\nThat's why it distorts your life so much for so long.It's no wonder high school students often feel alienated. The shape\nof their lives is completely artificial.But wasting your time is not the worst thing the educational system\ndoes to you. The worst thing it does is to train you that the way\nto win is by hacking bad tests. This is a much subtler problem\nthat I didn't recognize until I saw it happening to other people.When I started advising startup founders at Y Combinator, especially\nyoung ones, I was puzzled by the way they always seemed to make\nthings overcomplicated. How, they would ask, do you raise money?\nWhat's the trick for making venture capitalists want to invest in\nyou? The best way to make VCs want to invest in you, I would explain,\nis to actually be a good investment. Even if you could trick VCs\ninto investing in a bad startup, you'd be tricking yourselves too.\nYou're investing time in the same company you're asking them to\ninvest money in. If it's not a good investment, why are you even\ndoing it?Oh, they'd say, and then after a pause to digest this revelation,\nthey'd ask: What makes a startup a good investment?So I would explain that what makes a startup promising, not just\nin the eyes of investors but in fact, is \ngrowth. \nIdeally in revenue,\nbut failing that in usage. What they needed to do was get lots of\nusers.How does one get lots of users? They had all kinds of ideas about\nthat. They needed to do a big launch that would get them \"exposure.\"\nThey needed influential people to talk about them. They even knew\nthey needed to launch on a tuesday, because that's when one gets\nthe most attention.No, I would explain, that is not how to get lots of users. The way\nyou get lots of users is to make the product really great. Then\npeople will not only use it but recommend it to their friends, so\nyour growth will be exponential once you \nget it started.At this point I've told the founders something you'd think would\nbe completely obvious: that they should make a good company by\nmaking a good product. And yet their reaction would be something\nlike the reaction many physicists must have had when they first\nheard about the theory of relativity: a mixture of astonishment at\nits apparent genius, combined with a suspicion that anything so\nweird couldn't possibly be right. Ok, they would say, dutifully.\nAnd could you introduce us to such-and-such influential person? And\nremember, we want to launch on Tuesday.It would sometimes take founders years to grasp these simple lessons.\nAnd not because they were lazy or stupid. They just seemed blind\nto what was right in front of them.Why, I would ask myself, do they always make things so complicated?\nAnd then one day I realized this was not a rhetorical question.Why did founders tie themselves in knots doing the wrong things\nwhen the answer was right in front of them? Because that was what\nthey'd been trained to do. Their education had taught them that the\nway to win was to hack the test. And without even telling them they\nwere being trained to do this. The younger ones, the recent graduates,\nhad never faced a non-artificial test. They thought this was just\nhow the world worked: that the first thing you did, when facing any\nkind of challenge, was to figure out what the trick was for hacking\nthe test. That's why the conversation would always start with how\nto raise money, because that read as the test. It came at the end\nof YC. It had numbers attached to it, and higher numbers seemed to\nbe better. It must be the test.There are certainly big chunks of the world where the way to win\nis to hack the test. This phenomenon isn't limited to schools. And\nsome people, either due to ideology or ignorance, claim that this\nis true of startups too. But it isn't. In fact, one of the most\nstriking things about startups is the degree to which you win by\nsimply doing good work. There are edge cases, as there are in\nanything, but in general you win by getting users, and what users\ncare about is whether the product does what they want.Why did it take me so long to understand why founders made startups\novercomplicated? Because I hadn't realized explicitly that schools\ntrain us to win by hacking bad tests. And not just them, but me!\nI'd been trained to hack bad tests too, and hadn't realized it till\ndecades later.I had lived as if I realized it, but without knowing why. For\nexample, I had avoided working for big companies. But if you'd asked\nwhy, I'd have said it was because they were bogus, or bureaucratic.\nOr just yuck. I never understood how much of my dislike of big\ncompanies was due to the fact that you win by hacking bad tests.Similarly, the fact that the tests were unhackable was a lot of\nwhat attracted me to startups. But again, I hadn't realized that\nexplicitly.I had in effect achieved by successive approximations something\nthat may have a closed-form solution. I had gradually undone my\ntraining in hacking bad tests without knowing I was doing it. Could\nsomeone coming out of school banish this demon just by knowing its\nname, and saying begone? It seems worth trying.Merely talking explicitly about this phenomenon is likely to make\nthings better, because much of its power comes from the fact that\nwe take it for granted. After you've noticed it, it seems the\nelephant in the room, but it's a pretty well camouflaged elephant.\nThe phenomenon is so old, and so pervasive. And it's simply the\nresult of neglect. No one meant things to be this way. This is just\nwhat happens when you combine learning with grades, competition,\nand the naive assumption of unhackability.It was mind-blowing to realize that two of the things I'd puzzled\nabout the most — the bogusness of high school, and the difficulty\nof getting founders to see the obvious — both had the same cause.\nIt's rare for such a big block to slide into place so late.Usually when that happens it has implications in a lot of different\nareas, and this case seems no exception. For example, it suggests\nboth that education could be done better, and how you might fix it.\nBut it also suggests a potential answer to the question all big\ncompanies seem to have: how can we be more like a startup? I'm not\ngoing to chase down all the implications now. What I want to focus\non here is what it means for individuals.To start with, it means that most ambitious kids graduating from\ncollege have something they may want to unlearn. But it also changes\nhow you look at the world. Instead of looking at all the different\nkinds of work people do and thinking of them vaguely as more or\nless appealing, you can now ask a very specific question that will\nsort them in an interesting way: to what extent do you win at this\nkind of work by hacking bad tests?It would help if there was a way to recognize bad tests quickly.\nIs there a pattern here? It turns out there is.Tests can be divided into two kinds: those that are imposed by\nauthorities, and those that aren't. Tests that aren't imposed by\nauthorities are inherently unhackable, in the sense that no one is\nclaiming they're tests of anything more than they actually test. A\nfootball match, for example, is simply a test of who wins, not which\nteam is better. You can tell that from the fact that commentators\nsometimes say afterward that the better team won. Whereas tests\nimposed by authorities are usually proxies for something else. A\ntest in a class is supposed to measure not just how well you did\non that particular test, but how much you learned in the class.\nWhile tests that aren't imposed by authorities are inherently\nunhackable, those imposed by authorities have to be made unhackable.\nUsually they aren't. So as a first approximation, bad tests are\nroughly equivalent to tests imposed by authorities.You might actually like to win by hacking bad tests. Presumably\nsome people do. But I bet most people who find themselves doing\nthis kind of work don't like it. They just take it for granted that\nthis is how the world works, unless you want to drop out and be\nsome kind of hippie artisan.I suspect many people implicitly assume that working in a\nfield with bad tests is the price of making lots of money. But that,\nI can tell you, is false. It used to be true. In the mid-twentieth\ncentury, when the economy was \ncomposed of oligopolies, \nthe only way\nto the top was by playing their game. But it's not true now. There\nare now ways to get rich by doing good work, and that's part of the\nreason people are so much more excited about getting rich than they\nused to be. When I was a kid, you could either become an engineer\nand make cool things, or make lots of money by becoming an \"executive.\"\nNow you can make lots of money by making cool things.Hacking bad tests is becoming less important as the link between\nwork and authority erodes. The erosion of that link is one of the\nmost important trends happening now, and we see its effects in\nalmost every kind of work people do. Startups are one of the most\nvisible examples, but we see much the same thing in writing. Writers\nno longer have to submit to publishers and editors to reach readers;\nnow they can go direct.The more I think about this question, the more optimistic I get.\nThis seems one of those situations where we don't realize how much\nsomething was holding us back until it's eliminated. And I can\nforesee the whole bogus edifice crumbling. Imagine what happens as\nmore and more people start to ask themselves if they want to win\nby hacking bad tests, and decide that they don't. The kinds of\nwork where you win by hacking bad tests will be starved of talent,\nand the kinds where you win by doing good work will see an influx\nof the most ambitious people. And as hacking bad tests shrinks in\nimportance, education will evolve to stop training us to do it.\nImagine what the world could look like if that happened.This is not just a lesson for individuals to unlearn, but one for\nsociety to unlearn, and we'll be amazed at the energy that's liberated\nwhen we do.\nNotes[1] If using tests only to measure learning sounds impossibly\nutopian, that is already the way things work at Lambda School.\nLambda School doesn't have grades. You either graduate or you don't.\nThe only purpose of tests is to decide at each stage of the curriculum\nwhether you can continue to the next. So in effect the whole school\nis pass/fail.[2] If the final exam consisted of a long conversation with the\nprofessor, you could prepare for it by reading good books on medieval\nhistory. A lot of the hackability of tests in schools is due to the\nfact that the same test has to be given to large numbers of students.[3] Learning is the naive algorithm for getting good grades.[4] Hacking has \nmultiple senses. There's a narrow sense in which\nit means to compromise something. That's the sense in which one\nhacks a bad test. But there's another, more general sense, meaning\nto find a surprising solution to a problem, often by thinking\ndifferently about it. Hacking in this sense is a wonderful thing.\nAnd indeed, some of the hacks people use on bad tests are impressively\ningenious; the problem is not so much the hacking as that, because\nthe tests are hackable, they don't test what they're meant to.[5] The people who pick startups at Y Combinator are similar to\nadmissions officers, except that instead of being arbitrary, their\nacceptance criteria are trained by a very tight feedback loop. If\nyou accept a bad startup or reject a good one, you will usually know it\nwithin a year or two at the latest, and often within a month.[6] I'm sure admissions officers are tired of reading applications\nfrom kids who seem to have no personality beyond being willing to\nseem however they're supposed to seem to get accepted. What they\ndon't realize is that they are, in a sense, looking in a mirror.\nThe lack of authenticity in the applicants is a reflection of the\narbitrariness of the application process. A dictator might just as\nwell complain about the lack of authenticity in the people around\nhim.[7] By good work, I don't mean morally good, but good in the sense\nin which a good craftsman does good work.[8] There are borderline cases where it's hard to say which category\na test falls in. For example, is raising venture capital like college\nadmissions, or is it like selling to a customer?[9] Note that a good test is merely one that's unhackable. Good\nhere doesn't mean morally good, but good in the sense of working\nwell. The difference between fields with bad tests and good ones\nis not that the former are bad and the latter are good, but that\nthe former are bogus and the latter aren't. But those two measures\nare not unrelated. As Tara Ploughman said, the path from good to\nevil goes through bogus.[10] People who think the recent increase in \neconomic inequality is\ndue to changes in tax policy seem very naive to anyone with experience\nin startups. Different people are getting rich now than used to,\nand they're getting much richer than mere tax savings could make\nthem.[11] Note to tiger parents: you may think you're training your kids\nto win, but if you're training them to win by hacking bad tests,\nyou are, as parents so often do, training them to fight the last\nwar.Thanks to Austen Allred, Trevor Blackwell, Patrick Collison,\nJessica Livingston, Robert Morris, and Harj Taggar for reading\ndrafts of this." }, { "path": "data/PaulGrahamEssays/lies.txt", "content": "May 2008Adults lie constantly to kids. I'm not saying we should stop, but\nI think we should at least examine which lies we tell and why.There may also be a benefit to us. We were all lied to as kids,\nand some of the lies we were told still affect us. So by studying\nthe ways adults lie to kids, we may be able to clear our heads of\nlies we were told.I'm using the word \"lie\" in a very general sense: not just overt\nfalsehoods, but also all the more subtle ways we mislead kids.\nThough \"lie\" has negative connotations, I don't mean to suggest we\nshould never do this—just that we should pay attention when\nwe do.\n[1]One of the most remarkable things about the way we lie to kids is\nhow broad the conspiracy is. All adults know what their culture \nlies to kids about: they're the questions you answer \"Ask\nyour parents.\" If a kid asked who won the World Series in 1982\nor what the atomic weight of carbon was, you could just tell him.\nBut if a kid asks you \"Is there a God?\" or \"What's a prostitute?\"\nyou'll probably say \"Ask your parents.\"Since we all agree, kids see few cracks in the view of the world\npresented to them. The biggest disagreements are between parents\nand schools, but even those are small. Schools are careful what\nthey say about controversial topics, and if they do contradict what\nparents want their kids to believe, parents either pressure the\nschool into keeping \nquiet or move their kids to a new school.The conspiracy is so thorough that most kids who discover it do so\nonly by discovering internal contradictions in what they're told.\nIt can be traumatic for the ones who wake up during the operation.\nHere's what happened to Einstein:\n\n Through the reading of popular scientific books I soon reached\n the conviction that much in the stories of the Bible could not\n be true. The consequence was a positively fanatic freethinking\n coupled with the impression that youth is intentionally being\n deceived by the state through lies: it was a crushing impression.\n [2]\n\nI remember that feeling. By 15 I was convinced the world was corrupt\nfrom end to end. That's why movies like The Matrix have such\nresonance. Every kid grows up in a fake world. In a way it would\nbe easier if the forces behind it were as clearly differentiated\nas a bunch of evil machines, and one could make a clean break just by\ntaking a pill.\nProtectionIf you ask adults why they lie to kids, the most common reason they\ngive is to protect them. And kids do need protecting. The environment\nyou want to create for a newborn child will be quite unlike the\nstreets of a big city.That seems so obvious it seems wrong to call it a lie. It's certainly\nnot a bad lie to tell, to give a baby the impression the world is\nquiet and warm and safe. But this harmless type of lie can turn\nsour if left unexamined.Imagine if you tried to keep someone in as protected an environment\nas a newborn till age 18. To mislead someone so grossly about the\nworld would seem not protection but abuse. That's an extreme\nexample, of course; when parents do that sort of thing it becomes\nnational news. But you see the same problem on a smaller scale in\nthe malaise teenagers feel in suburbia.The main purpose of suburbia is to provide a protected environment\nfor children to grow up in. And it seems great for 10 year olds.\nI liked living in suburbia when I was 10. I didn't notice how\nsterile it was. My whole world was no bigger than a few friends'\nhouses I bicycled to and some woods I ran around in. On a log scale\nI was midway between crib and globe. A suburban street was just\nthe right size. But as I grew older, suburbia started to feel\nsuffocatingly fake.Life can be pretty good at 10 or 20, but it's often frustrating at\n15. This is too big a problem to solve here, but certainly one\nreason life sucks at 15 is that kids are trapped in a world designed\nfor 10 year olds.What do parents hope to protect their children from by raising them\nin suburbia? A friend who moved out of Manhattan said merely that\nher 3 year old daughter \"saw too much.\" Off the top of my head,\nthat might include: people who are high or drunk, poverty, madness,\ngruesome medical conditions, sexual behavior of various degrees of\noddness, and violent anger.I think it's the anger that would worry me most if I had a 3 year\nold. I was 29 when I moved to New York and I was surprised even\nthen. I wouldn't want a 3 year old to see some of the disputes I\nsaw. It would be too frightening. A lot of the things adults\nconceal from smaller children, they conceal because they'd be\nfrightening, not because they want to conceal the existence of such\nthings. Misleading the child is just a byproduct.This seems one of the most justifiable types of lying adults do to\nkids. But because the lies are indirect we don't keep a very strict\naccounting of them. Parents know they've concealed the facts about\nsex, and many at some point sit their kids down and explain more.\nBut few tell their kids about the differences between the real world\nand the cocoon they grew up in. Combine this with the confidence\nparents try to instill in their kids, and every year you get a new\ncrop of 18 year olds who think they know how to run the world.Don't all 18 year olds think they know how to run the world? Actually\nthis seems to be a recent innovation, no more than about 100 years old.\nIn preindustrial times teenage kids were junior members of the adult\nworld and comparatively well aware of their shortcomings. They\ncould see they weren't as strong or skillful as the village smith.\nIn past times people lied to kids about some things more than we\ndo now, but the lies implicit in an artificial, protected environment\nare a recent invention. Like a lot of new inventions, the rich got\nthis first. Children of kings and great magnates were the first\nto grow up out of touch with the world. Suburbia means half the\npopulation can live like kings in that respect.\nSex (and Drugs)I'd have different worries about raising teenage kids in New York.\nI'd worry less about what they'd see, and more about what they'd\ndo. I went to college with a lot of kids who grew up in Manhattan,\nand as a rule they seemed pretty jaded. They seemed to have lost\ntheir virginity at an average of about 14 and by college had tried\nmore drugs than I'd even heard of.The reasons parents don't want their teenage kids having sex are\ncomplex. There are some obvious dangers: pregnancy and sexually\ntransmitted diseases. But those aren't the only reasons parents\ndon't want their kids having sex. The average parents of a 14 year\nold girl would hate the idea of her having sex even if there were\nzero risk of pregnancy or sexually transmitted diseases.Kids can probably sense they aren't being told the whole story.\nAfter all, pregnancy and sexually transmitted diseases are just as\nmuch a problem for adults, and they have sex.What really bothers parents about their teenage kids having sex?\nTheir dislike of the idea is so visceral it's probably inborn. But\nif it's inborn it should be universal, and there are plenty of\nsocieties where parents don't mind if their teenage kids have\nsex—indeed, where it's normal for 14 year olds to become\nmothers. So what's going on? There does seem to be a universal\ntaboo against sex with prepubescent children. One can imagine\nevolutionary reasons for that. And I think this is the main reason\nparents in industrialized societies dislike teenage kids having\nsex. They still think of them as children, even though biologically\nthey're not, so the taboo against child sex still has force.One thing adults conceal about sex they also conceal about drugs:\nthat it can cause great pleasure. That's what makes sex and drugs\nso dangerous. The desire for them can cloud one's judgement—which\nis especially frightening when the judgement being clouded is the\nalready wretched judgement of a teenage kid.Here parents' desires conflict. Older societies told kids they had\nbad judgement, but modern parents want their children to be confident.\nThis may well be a better plan than the old one of putting them in\ntheir place, but it has the side effect that after having implicitly\nlied to kids about how good their judgement is, we then have to lie\nagain about all the things they might get into trouble with if they\nbelieved us.If parents told their kids the truth about sex and drugs, it would\nbe: the reason you should avoid these things is that you have lousy\njudgement. People with twice your experience still get burned by\nthem. But this may be one of those cases where the truth wouldn't\nbe convincing, because one of the symptoms of bad judgement is\nbelieving you have good judgement. When you're too weak to lift\nsomething, you can tell, but when you're making a decision impetuously,\nyou're all the more sure of it.\nInnocenceAnother reason parents don't want their kids having sex is that\nthey want to keep them innocent. Adults have a certain model of\nhow kids are supposed to behave, and it's different from what they\nexpect of other adults.One of the most obvious differences is the words kids are allowed\nto use. Most parents use words when talking to other adults that\nthey wouldn't want their kids using. They try to hide even the\nexistence of these words for as long as they can. And this is\nanother of those conspiracies everyone participates in: everyone\nknows you're not supposed to swear in front of kids.I've never heard more different explanations for anything parents\ntell kids than why they shouldn't swear. Every parent I know forbids\ntheir children to swear, and yet no two of them have the same\njustification. It's clear most start with not wanting kids to\nswear, then make up the reason afterward.So my theory about what's going on is that the function of\nswearwords is to mark the speaker as an adult. There's no difference\nin the meaning of \"shit\" and \"poopoo.\" So why should one be ok for\nkids to say and one forbidden? The only explanation is: by definition.\n[3]Why does it bother adults so much when kids do things reserved for\nadults? The idea of a foul-mouthed, cynical 10 year old leaning\nagainst a lamppost with a cigarette hanging out of the corner of\nhis mouth is very disconcerting. But why?One reason we want kids to be innocent is that we're programmed to\nlike certain kinds of helplessness. I've several times heard mothers\nsay they deliberately refrained from correcting their young children's\nmispronunciations because they were so cute. And if you think about\nit, cuteness is helplessness. Toys and cartoon characters meant to\nbe cute always have clueless expressions and stubby, ineffectual\nlimbs.It's not surprising we'd have an inborn desire to love and protect\nhelpless creatures, considering human offspring are so helpless for\nso long. Without the helplessness that makes kids cute, they'd be\nvery annoying. They'd merely seem like incompetent adults. But\nthere's more to it than that. The reason our hypothetical jaded\n10 year old bothers me so much is not just that he'd be annoying,\nbut that he'd have cut off his prospects for growth so early. To\nbe jaded you have to think you know how the world works, and any\ntheory a 10 year old had about that would probably be a pretty\nnarrow one.Innocence is also open-mindedness. We want kids to be innocent so\nthey can continue to learn. Paradoxical as it sounds, there are\nsome kinds of knowledge that get in the way of other kinds of\nknowledge. If you're going to learn that the world is a brutal\nplace full of people trying to take advantage of one another, you're\nbetter off learning it last. Otherwise you won't bother learning\nmuch more.Very smart adults often seem unusually innocent, and I don't think\nthis is a coincidence. I think they've deliberately avoided learning\nabout certain things. Certainly I do. I used to think I wanted\nto know everything. Now I know I don't.\nDeathAfter sex, death is the topic adults lie most conspicuously about\nto kids. Sex I believe they conceal because of deep taboos. But\nwhy do we conceal death from kids? Probably because small children\nare particularly horrified by it. They want to feel safe, and death\nis the ultimate threat.One of the most spectacular lies our parents told us was about the\ndeath of our first cat. Over the years, as we asked for more\ndetails, they were compelled to invent more, so the story grew quite\nelaborate. The cat had died at the vet's office. Of what? Of the\nanaesthesia itself. Why was the cat at the vet's office? To be\nfixed. And why had such a routine operation killed it? It wasn't\nthe vet's fault; the cat had a congenitally weak heart; the anaesthesia\nwas too much for it; but there was no way anyone could have\nknown this in advance. It was not till we were in our twenties\nthat the truth came out: my sister, then about three, had accidentally\nstepped on the cat and broken its back.They didn't feel the need to tell us the cat was now happily in cat\nheaven. My parents never claimed that people or animals who died\nhad \"gone to a better place,\" or that we'd meet them again. It\ndidn't seem to harm us.My grandmother told us an edited version of the death of my\ngrandfather. She said they'd been sitting reading one day, and\nwhen she said something to him, he didn't answer. He seemed to be\nasleep, but when she tried to rouse him, she couldn't. \"He was\ngone.\" Having a heart attack sounded like falling asleep. Later I\nlearned it hadn't been so neat, and the heart attack had taken most\nof a day to kill him.Along with such outright lies, there must have been a lot of changing\nthe subject when death came up. I can't remember that, of course,\nbut I can infer it from the fact that I didn't really grasp I was\ngoing to die till I was about 19. How could I have missed something\nso obvious for so long? Now that I've seen parents managing the\nsubject, I can see how: questions about death are gently but firmly\nturned aside.On this topic, especially, they're met half-way by kids. Kids often\nwant to be lied to. They want to believe they're living in a\ncomfortable, safe world as much as their parents want them to believe\nit.\n[4]\nIdentitySome parents feel a strong adherence to an ethnic or religious group\nand want their kids to feel it too. This usually requires two\ndifferent kinds of lying: the first is to tell the child that he\nor she is an X, and the second is whatever specific lies Xes\ndifferentiate themselves by believing.\n[5]Telling a child they have a particular ethnic or religious identity\nis one of the stickiest things you can tell them. Almost anything\nelse you tell a kid, they can change their mind about later when\nthey start to think for themselves. But if you tell a kid they're\na member of a certain group, that seems nearly impossible to shake.This despite the fact that it can be one of the most premeditated\nlies parents tell. When parents are of different religions, they'll\noften agree between themselves that their children will be \"raised\nas Xes.\" And it works. The kids obligingly grow up considering\nthemselves as Xes, despite the fact that if their parents had chosen\nthe other way, they'd have grown up considering themselves as Ys.One reason this works so well is the second kind of lie involved.\nThe truth is common property. You can't distinguish your group by\ndoing things that are rational, and believing things that are true.\nIf you want to set yourself apart from other people, you have to\ndo things that are arbitrary, and believe things that are false.\nAnd after having spent their whole lives doing things that are arbitrary\nand believing things that are false, and being regarded as odd by\n\"outsiders\" on that account, the cognitive dissonance pushing\nchildren to regard themselves as Xes must be enormous. If they\naren't an X, why are they attached to all these arbitrary beliefs\nand customs? If they aren't an X, why do all the non-Xes call them\none?This form of lie is not without its uses. You can use it to carry\na payload of beneficial beliefs, and they will also become part of\nthe child's identity. You can tell the child that in addition to\nnever wearing the color yellow, believing the world was created by\na giant rabbit, and always snapping their fingers before eating\nfish, Xes are also particularly honest and industrious. Then X\nchildren will grow up feeling it's part of their identity to be\nhonest and industrious.This probably accounts for a lot of the spread of modern religions,\nand explains why their doctrines are a combination of the useful\nand the bizarre. The bizarre half is what makes the religion stick,\nand the useful half is the payload.\n[6]\nAuthorityOne of the least excusable reasons adults lie to kids is to maintain\npower over them. Sometimes these lies are truly sinister, like a\nchild molester telling his victims they'll get in trouble if they\ntell anyone what happened to them. Others seem more innocent; it\ndepends how badly adults lie to maintain their power, and what they\nuse it for.Most adults make some effort to conceal their flaws from children.\nUsually their motives are mixed. For example, a father who has an\naffair generally conceals it from his children. His motive is\npartly that it would worry them, partly that this would introduce\nthe topic of sex, and partly (a larger part than he would admit)\nthat he doesn't want to tarnish himself in their eyes.If you want to learn what lies are told to kids, read almost any\nbook written to teach them about \"issues.\"\n[7]\nPeter Mayle wrote\none called Why Are We Getting a Divorce? It begins with the three\nmost important things to remember about divorce, one of which is:\n\n You shouldn't put the blame on one parent, because divorce is\n never only one person's fault.\n [8]\n\nReally? When a man runs off with his secretary, is it always partly\nhis wife's fault? But I can see why Mayle might have said this.\nMaybe it's more important for kids to respect their parents than\nto know the truth about them.But because adults conceal their flaws, and at the same time insist\non high standards of behavior for kids, a lot of kids grow up feeling\nthey fall hopelessly short. They walk around feeling horribly evil\nfor having used a swearword, while in fact most of the adults around\nthem are doing much worse things.This happens in intellectual as well as moral questions. The more\nconfident people are, the more willing they seem to be to answer a\nquestion \"I don't know.\" Less confident people feel they have to\nhave an answer or they'll look bad. My parents were pretty good\nabout admitting when they didn't know things, but I must have been\ntold a lot of lies of this type by teachers, because I rarely heard\na teacher say \"I don't know\" till I got to college. I remember\nbecause it was so surprising to hear someone say that in front of\na class.The first hint I had that teachers weren't omniscient came in sixth\ngrade, after my father contradicted something I'd learned in school.\nWhen I protested that the teacher had said the opposite, my father\nreplied that the guy had no idea what he was talking about—that\nhe was just an elementary school teacher, after all.Just a teacher? The phrase seemed almost grammatically ill-formed.\nDidn't teachers know everything about the subjects they taught?\nAnd if not, why were they the ones teaching us?The sad fact is, US public school teachers don't generally understand\nthe stuff they're teaching very well. There are some sterling\nexceptions, but as a rule people planning to go into teaching rank\nacademically near the bottom of the college population. So the\nfact that I still thought at age 11 that teachers were infallible\nshows what a job the system must have done on my brain.\nSchoolWhat kids get taught in school is a complex mix of lies. The most\nexcusable are those told to simplify ideas to make them easy to\nlearn. The problem is, a lot of propaganda gets slipped into the\ncurriculum in the name of simplification.Public school textbooks represent a compromise between what various\npowerful groups want kids to be told. The lies are rarely overt.\nUsually they consist either of omissions or of over-emphasizing\ncertain topics at the expense of others. The view of history we\ngot in elementary school was a crude hagiography, with at least one\nrepresentative of each powerful group.The famous scientists I remember were Einstein, Marie Curie, and\nGeorge Washington Carver. Einstein was a big deal because his\nwork led to the atom bomb. Marie Curie was involved with X-rays.\nBut I was mystified about Carver. He seemed to have done stuff\nwith peanuts.It's obvious now that he was on the list because he was black (and\nfor that matter that Marie Curie was on it because she was a woman),\nbut as a kid I was confused for years about him. I wonder if it\nwouldn't have been better just to tell us the truth: that there\nweren't any famous black scientists. Ranking George Washington\nCarver with Einstein misled us not only about science, but about\nthe obstacles blacks faced in his time.As subjects got softer, the lies got more frequent. By the time\nyou got to politics and recent history, what we were taught was\npretty much pure propaganda. For example, we were taught to regard\npolitical leaders as saints—especially the recently martyred\nKennedy and King. It was astonishing to learn later that they'd\nboth been serial womanizers, and that Kennedy was a speed freak to\nboot. (By the time King's plagiarism emerged, I'd lost the ability\nto be surprised by the misdeeds of famous people.)I doubt you could teach kids recent history without teaching them\nlies, because practically everyone who has anything to say about\nit has some kind of spin to put on it. Much recent history consists\nof spin. It would probably be better just to teach them metafacts\nlike that.Probably the biggest lie told in schools, though, is that the way\nto succeed is through following \"the rules.\" In fact most such\nrules are just hacks to manage large groups efficiently.\nPeaceOf all the reasons we lie to kids, the most powerful is probably\nthe same mundane reason they lie to us.Often when we lie to people it's not part of any conscious strategy,\nbut because they'd react violently to the truth. Kids, almost by\ndefinition, lack self-control. They react violently to things—and\nso they get lied to a lot. \n[9]A few Thanksgivings ago, a friend of mine found himself in a situation\nthat perfectly illustrates the complex motives we have when we lie\nto kids. As the roast turkey appeared on the table, his alarmingly\nperceptive 5 year old son suddenly asked if the turkey had wanted\nto die. Foreseeing disaster, my friend and his wife rapidly\nimprovised: yes, the turkey had wanted to die, and in fact had lived\nits whole life with the aim of being their Thanksgiving dinner.\nAnd that (phew) was the end of that.Whenever we lie to kids to protect them, we're usually also lying\nto keep the peace.One consequence of this sort of calming lie is that we grow up\nthinking horrible things are normal. It's hard for us to feel a\nsense of urgency as adults over something we've literally been\ntrained not to worry about. When I was about 10 I saw a documentary\non pollution that put me into a panic. It seemed the planet was\nbeing irretrievably ruined. I went to my mother afterward to ask\nif this was so. I don't remember what she said, but she made me\nfeel better, so I stopped worrying about it.That was probably the best way to handle a frightened 10 year old.\nBut we should understand the price. This sort of lie is one of the\nmain reasons bad things persist: we're all trained to ignore them.\nDetoxA sprinter in a race almost immediately enters a state called \"oxygen\ndebt.\" His body switches to an emergency source of energy that's\nfaster than regular aerobic respiration. But this process builds\nup waste products that ultimately require extra oxygen to break\ndown, so at the end of the race he has to stop and pant for a while\nto recover.We arrive at adulthood with a kind of truth debt. We were told a\nlot of lies to get us (and our parents) through our childhood. Some\nmay have been necessary. Some probably weren't. But we all arrive\nat adulthood with heads full of lies.There's never a point where the adults sit you down and explain all\nthe lies they told you. They've forgotten most of them. So if\nyou're going to clear these lies out of your head, you're going to\nhave to do it yourself.Few do. Most people go through life with bits of packing material\nadhering to their minds and never know it. You probably never can\ncompletely undo the effects of lies you were told as a kid, but\nit's worth trying. I've found that whenever I've been able to undo\na lie I was told, a lot of other things fell into place.Fortunately, once you arrive at adulthood you get a valuable new\nresource you can use to figure out what lies you were told. You're\nnow one of the liars. You get to watch behind the scenes as adults\nspin the world for the next generation of kids.The first step in clearing your head is to realize how far you are\nfrom a neutral observer. When I left high school I was, I thought,\na complete skeptic. I'd realized high school was crap. I thought\nI was ready to question everything I knew. But among the many other\nthings I was ignorant of was how much debris there already was in\nmy head. It's not enough to consider your mind a blank slate. You\nhave to consciously erase it.\nNotes[1]\nOne reason I stuck with such a brutally simple word is that\nthe lies we tell kids are probably not quite as harmless as we\nthink. If you look at what adults told children in the past, it's\nshocking how much they lied to them. Like us, they did it with the\nbest intentions. So if we think we're as open as one could reasonably\nbe with children, we're probably fooling ourselves. Odds are people\nin 100 years will be as shocked at some of the lies we tell as we\nare at some of the lies people told 100 years ago.I can't predict which these will be, and I don't want to write an\nessay that will seem dumb in 100 years. So instead of using special\neuphemisms for lies that seem excusable according to present fashions,\nI'm just going to call all our lies lies.(I have omitted one type: lies told to play games with kids'\ncredulity. These range from \"make-believe,\" which is not really a\nlie because it's told with a wink, to the frightening lies told by\nolder siblings. There's not much to say about these: I wouldn't\nwant the first type to go away, and wouldn't expect the second type\nto.)[2]\nCalaprice, Alice (ed.), The Quotable Einstein, Princeton\nUniversity Press, 1996.[3]\nIf you ask parents why kids shouldn't swear, the less educated\nones usually reply with some question-begging answer like \"it's\ninappropriate,\" while the more educated ones come up with elaborate\nrationalizations. In fact the less educated parents seem closer\nto the truth.[4]\nAs a friend with small children pointed out, it's easy for small\nchildren to consider themselves immortal, because time seems to\npass so slowly for them. To a 3 year old, a day feels like a month\nmight to an adult. So 80 years sounds to him like 2400 years would\nto us.[5]\nI realize I'm going to get endless grief for classifying religion\nas a type of lie. Usually people skirt that issue with some\nequivocation implying that lies believed for a sufficiently long\ntime by sufficiently large numbers of people are immune to the usual\nstandards for truth. But because I can't predict which lies future\ngenerations will consider inexcusable, I can't safely omit any type\nwe tell. Yes, it seems unlikely that religion will be out of fashion\nin 100 years, but no more unlikely than it would have seemed to\nsomeone in 1880 that schoolchildren in 1980 would be taught that\nmasturbation was perfectly normal and not to feel guilty about it.[6]\nUnfortunately the payload can consist of bad customs as well\nas good ones. For example, there are certain qualities that some\ngroups in America consider \"acting white.\" In fact most of them\ncould as accurately be called \"acting Japanese.\" There's nothing\nspecifically white about such customs. They're common to all cultures\nwith long traditions of living in cities. So it is probably a\nlosing bet for a group to consider behaving the opposite way as\npart of its identity.[7]\nIn this context, \"issues\" basically means \"things we're going\nto lie to them about.\" That's why there's a special name for these\ntopics.[8]\nMayle, Peter, Why Are We Getting a Divorce?, Harmony, 1988.[9]\nThe ironic thing is, this is also the main reason kids lie to\nadults. If you freak out when people tell you alarming things,\nthey won't tell you them. Teenagers don't tell their parents what\nhappened that night they were supposed to be staying at a friend's\nhouse for the same reason parents don't tell 5 year olds the truth\nabout the Thanksgiving turkey. They'd freak if they knew.\nThanks to Sam Altman, Marc Andreessen, Trevor Blackwell,\nPatrick Collison, Jessica Livingston, Jackie McDonough, Robert\nMorris, and David Sloo for reading drafts of this. And since there\nare some controversial ideas here, I should add that none of them\nagreed with everything in it." }, { "path": "data/PaulGrahamEssays/love.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nJanuary 2006To do something well you have to like it. That idea is not exactly\nnovel. We've got it down to four words: \"Do what you love.\" But\nit's not enough just to tell people that. Doing what you love is\ncomplicated.The very idea is foreign to what most of us learn as kids. When I\nwas a kid, it seemed as if work and fun were opposites by definition.\nLife had two states: some of the time adults were making you do\nthings, and that was called work; the rest of the time you could\ndo what you wanted, and that was called playing. Occasionally the\nthings adults made you do were fun, just as, occasionally, playing\nwasn't—for example, if you fell and hurt yourself. But except\nfor these few anomalous cases, work was pretty much defined as\nnot-fun.And it did not seem to be an accident. School, it was implied, was\ntedious because it was preparation for grownup work.The world then was divided into two groups, grownups and kids.\nGrownups, like some kind of cursed race, had to work. Kids didn't,\nbut they did have to go to school, which was a dilute version of\nwork meant to prepare us for the real thing. Much as we disliked\nschool, the grownups all agreed that grownup work was worse, and\nthat we had it easy.Teachers in particular all seemed to believe implicitly that work\nwas not fun. Which is not surprising: work wasn't fun for most of\nthem. Why did we have to memorize state capitals instead of playing\ndodgeball? For the same reason they had to watch over a bunch of\nkids instead of lying on a beach. You couldn't just do what you\nwanted.I'm not saying we should let little kids do whatever they want.\nThey may have to be made to work on certain things. But if we make\nkids work on dull stuff, it might be wise to tell them that tediousness\nis not the defining quality of work, and indeed that the reason\nthey have to work on dull stuff now is so they can work on more\ninteresting stuff later.\n[1]Once, when I was about 9 or 10, my father told me I could be whatever\nI wanted when I grew up, so long as I enjoyed it. I remember that\nprecisely because it seemed so anomalous. It was like being told\nto use dry water. Whatever I thought he meant, I didn't think he\nmeant work could literally be fun—fun like playing. It\ntook me years to grasp that.JobsBy high school, the prospect of an actual job was on the horizon.\nAdults would sometimes come to speak to us about their work, or we\nwould go to see them at work. It was always understood that they\nenjoyed what they did. In retrospect I think one may have: the\nprivate jet pilot. But I don't think the bank manager really did.The main reason they all acted as if they enjoyed their work was\npresumably the upper-middle class convention that you're supposed\nto. It would not merely be bad for your career to say that you\ndespised your job, but a social faux-pas.Why is it conventional to pretend to like what you do? The first\nsentence of this essay explains that. If you have to like something\nto do it well, then the most successful people will all like what\nthey do. That's where the upper-middle class tradition comes from.\nJust as houses all over America are full of \nchairs\nthat are, without\nthe owners even knowing it, nth-degree imitations of chairs designed\n250 years ago for French kings, conventional attitudes about work\nare, without the owners even knowing it, nth-degree imitations of\nthe attitudes of people who've done great things.What a recipe for alienation. By the time they reach an age to\nthink about what they'd like to do, most kids have been thoroughly\nmisled about the idea of loving one's work. School has trained\nthem to regard work as an unpleasant duty. Having a job is said\nto be even more onerous than schoolwork. And yet all the adults\nclaim to like what they do. You can't blame kids for thinking \"I\nam not like these people; I am not suited to this world.\"Actually they've been told three lies: the stuff they've been taught\nto regard as work in school is not real work; grownup work is not\n(necessarily) worse than schoolwork; and many of the adults around\nthem are lying when they say they like what they do.The most dangerous liars can be the kids' own parents. If you take\na boring job to give your family a high standard of living, as so\nmany people do, you risk infecting your kids with the idea that\nwork is boring. \n[2]\nMaybe it would be better for kids in this one\ncase if parents were not so unselfish. A parent who set an example\nof loving their work might help their kids more than an expensive\nhouse.\n[3]It was not till I was in college that the idea of work finally broke\nfree from the idea of making a living. Then the important question\nbecame not how to make money, but what to work on. Ideally these\ncoincided, but some spectacular boundary cases (like Einstein in\nthe patent office) proved they weren't identical.The definition of work was now to make some original contribution\nto the world, and in the process not to starve. But after the habit\nof so many years my idea of work still included a large component\nof pain. Work still seemed to require discipline, because only\nhard problems yielded grand results, and hard problems couldn't\nliterally be fun. Surely one had to force oneself to work on them.If you think something's supposed to hurt, you're less likely to\nnotice if you're doing it wrong. That about sums up my experience\nof graduate school.BoundsHow much are you supposed to like what you do? Unless you\nknow that, you don't know when to stop searching. And if, like most\npeople, you underestimate it, you'll tend to stop searching too\nearly. You'll end up doing something chosen for you by your parents,\nor the desire to make money, or prestige—or sheer inertia.Here's an upper bound: Do what you love doesn't mean, do what you\nwould like to do most this second. Even Einstein probably\nhad moments when he wanted to have a cup of coffee, but told himself\nhe ought to finish what he was working on first.It used to perplex me when I read about people who liked what they\ndid so much that there was nothing they'd rather do. There didn't\nseem to be any sort of work I liked that much. If I had a\nchoice of (a) spending the next hour working on something or (b)\nbe teleported to Rome and spend the next hour wandering about, was\nthere any sort of work I'd prefer? Honestly, no.But the fact is, almost anyone would rather, at any given moment,\nfloat about in the Carribbean, or have sex, or eat some delicious\nfood, than work on hard problems. The rule about doing what you\nlove assumes a certain length of time. It doesn't mean, do what\nwill make you happiest this second, but what will make you happiest\nover some longer period, like a week or a month.Unproductive pleasures pall eventually. After a while you get tired\nof lying on the beach. If you want to stay happy, you have to do\nsomething.As a lower bound, you have to like your work more than any unproductive\npleasure. You have to like what you do enough that the concept of\n\"spare time\" seems mistaken. Which is not to say you have to spend\nall your time working. You can only work so much before you get\ntired and start to screw up. Then you want to do something else—even something mindless. But you don't regard this time as the\nprize and the time you spend working as the pain you endure to earn\nit.I put the lower bound there for practical reasons. If your work\nis not your favorite thing to do, you'll have terrible problems\nwith procrastination. You'll have to force yourself to work, and\nwhen you resort to that the results are distinctly inferior.To be happy I think you have to be doing something you not only\nenjoy, but admire. You have to be able to say, at the end, wow,\nthat's pretty cool. This doesn't mean you have to make something.\nIf you learn how to hang glide, or to speak a foreign language\nfluently, that will be enough to make you say, for a while at least,\nwow, that's pretty cool. What there has to be is a test.So one thing that falls just short of the standard, I think, is\nreading books. Except for some books in math and the hard sciences,\nthere's no test of how well you've read a book, and that's why\nmerely reading books doesn't quite feel like work. You have to do\nsomething with what you've read to feel productive.I think the best test is one Gino Lee taught me: to try to do things\nthat would make your friends say wow. But it probably wouldn't\nstart to work properly till about age 22, because most people haven't\nhad a big enough sample to pick friends from before then.SirensWhat you should not do, I think, is worry about the opinion of\nanyone beyond your friends. You shouldn't worry about prestige.\nPrestige is the opinion of the rest of the world. When you can ask\nthe opinions of people whose judgement you respect, what does it\nadd to consider the opinions of people you don't even know? \n[4]This is easy advice to give. It's hard to follow, especially when\nyou're young. \n[5]\nPrestige is like a powerful magnet that warps\neven your beliefs about what you enjoy. It causes you to work not\non what you like, but what you'd like to like.That's what leads people to try to write novels, for example. They\nlike reading novels. They notice that people who write them win\nNobel prizes. What could be more wonderful, they think, than to\nbe a novelist? But liking the idea of being a novelist is not\nenough; you have to like the actual work of novel-writing if you're\ngoing to be good at it; you have to like making up elaborate lies.Prestige is just fossilized inspiration. If you do anything well\nenough, you'll make it prestigious. Plenty of things we now\nconsider prestigious were anything but at first. Jazz comes to\nmind—though almost any established art form would do. So just\ndo what you like, and let prestige take care of itself.Prestige is especially dangerous to the ambitious. If you want to\nmake ambitious people waste their time on errands, the way to do\nit is to bait the hook with prestige. That's the recipe for getting\npeople to give talks, write forewords, serve on committees, be\ndepartment heads, and so on. It might be a good rule simply to\navoid any prestigious task. If it didn't suck, they wouldn't have\nhad to make it prestigious.Similarly, if you admire two kinds of work equally, but one is more\nprestigious, you should probably choose the other. Your opinions\nabout what's admirable are always going to be slightly influenced\nby prestige, so if the two seem equal to you, you probably have\nmore genuine admiration for the less prestigious one.The other big force leading people astray is money. Money by itself\nis not that dangerous. When something pays well but is regarded\nwith contempt, like telemarketing, or prostitution, or personal\ninjury litigation, ambitious people aren't tempted by it. That\nkind of work ends up being done by people who are \"just trying to\nmake a living.\" (Tip: avoid any field whose practitioners say\nthis.) The danger is when money is combined with prestige, as in,\nsay, corporate law, or medicine. A comparatively safe and prosperous\ncareer with some automatic baseline prestige is dangerously tempting\nto someone young, who hasn't thought much about what they really\nlike.The test of whether people love what they do is whether they'd do\nit even if they weren't paid for it—even if they had to work at\nanother job to make a living. How many corporate lawyers would do\ntheir current work if they had to do it for free, in their spare\ntime, and take day jobs as waiters to support themselves?This test is especially helpful in deciding between different kinds\nof academic work, because fields vary greatly in this respect. Most\ngood mathematicians would work on math even if there were no jobs\nas math professors, whereas in the departments at the other end of\nthe spectrum, the availability of teaching jobs is the driver:\npeople would rather be English professors than work in ad agencies,\nand publishing papers is the way you compete for such jobs. Math\nwould happen without math departments, but it is the existence of\nEnglish majors, and therefore jobs teaching them, that calls into\nbeing all those thousands of dreary papers about gender and identity\nin the novels of Conrad. No one does \nthat \nkind of thing for fun.The advice of parents will tend to err on the side of money. It\nseems safe to say there are more undergrads who want to be novelists\nand whose parents want them to be doctors than who want to be doctors\nand whose parents want them to be novelists. The kids think their\nparents are \"materialistic.\" Not necessarily. All parents tend to\nbe more conservative for their kids than they would for themselves,\nsimply because, as parents, they share risks more than rewards. If\nyour eight year old son decides to climb a tall tree, or your teenage\ndaughter decides to date the local bad boy, you won't get a share\nin the excitement, but if your son falls, or your daughter gets\npregnant, you'll have to deal with the consequences.DisciplineWith such powerful forces leading us astray, it's not surprising\nwe find it so hard to discover what we like to work on. Most people\nare doomed in childhood by accepting the axiom that work = pain.\nThose who escape this are nearly all lured onto the rocks by prestige\nor money. How many even discover something they love to work on?\nA few hundred thousand, perhaps, out of billions.It's hard to find work you love; it must be, if so few do. So don't\nunderestimate this task. And don't feel bad if you haven't succeeded\nyet. In fact, if you admit to yourself that you're discontented,\nyou're a step ahead of most people, who are still in denial. If\nyou're surrounded by colleagues who claim to enjoy work that you\nfind contemptible, odds are they're lying to themselves. Not\nnecessarily, but probably.Although doing great work takes less discipline than people think—because the way to do great work is to find something you like so\nmuch that you don't have to force yourself to do it—finding\nwork you love does usually require discipline. Some people are\nlucky enough to know what they want to do when they're 12, and just\nglide along as if they were on railroad tracks. But this seems the\nexception. More often people who do great things have careers with\nthe trajectory of a ping-pong ball. They go to school to study A,\ndrop out and get a job doing B, and then become famous for C after\ntaking it up on the side.Sometimes jumping from one sort of work to another is a sign of\nenergy, and sometimes it's a sign of laziness. Are you dropping\nout, or boldly carving a new path? You often can't tell yourself.\nPlenty of people who will later do great things seem to be disappointments\nearly on, when they're trying to find their niche.Is there some test you can use to keep yourself honest? One is to\ntry to do a good job at whatever you're doing, even if you don't\nlike it. Then at least you'll know you're not using dissatisfaction\nas an excuse for being lazy. Perhaps more importantly, you'll get\ninto the habit of doing things well.Another test you can use is: always produce. For example, if you\nhave a day job you don't take seriously because you plan to be a\nnovelist, are you producing? Are you writing pages of fiction,\nhowever bad? As long as you're producing, you'll know you're not\nmerely using the hazy vision of the grand novel you plan to write\none day as an opiate. The view of it will be obstructed by the all\ntoo palpably flawed one you're actually writing.\"Always produce\" is also a heuristic for finding the work you love.\nIf you subject yourself to that constraint, it will automatically\npush you away from things you think you're supposed to work on,\ntoward things you actually like. \"Always produce\" will discover\nyour life's work the way water, with the aid of gravity, finds the\nhole in your roof.Of course, figuring out what you like to work on doesn't mean you\nget to work on it. That's a separate question. And if you're\nambitious you have to keep them separate: you have to make a conscious\neffort to keep your ideas about what you want from being contaminated\nby what seems possible. \n[6]It's painful to keep them apart, because it's painful to observe\nthe gap between them. So most people pre-emptively lower their\nexpectations. For example, if you asked random people on the street\nif they'd like to be able to draw like Leonardo, you'd find most\nwould say something like \"Oh, I can't draw.\" This is more a statement\nof intention than fact; it means, I'm not going to try. Because\nthe fact is, if you took a random person off the street and somehow\ngot them to work as hard as they possibly could at drawing for the\nnext twenty years, they'd get surprisingly far. But it would require\na great moral effort; it would mean staring failure in the eye every\nday for years. And so to protect themselves people say \"I can't.\"Another related line you often hear is that not everyone can do\nwork they love—that someone has to do the unpleasant jobs. Really?\nHow do you make them? In the US the only mechanism for forcing\npeople to do unpleasant jobs is the draft, and that hasn't been\ninvoked for over 30 years. All we can do is encourage people to\ndo unpleasant work, with money and prestige.If there's something people still won't do, it seems as if society\njust has to make do without. That's what happened with domestic\nservants. For millennia that was the canonical example of a job\n\"someone had to do.\" And yet in the mid twentieth century servants\npractically disappeared in rich countries, and the rich have just\nhad to do without.So while there may be some things someone has to do, there's a good\nchance anyone saying that about any particular job is mistaken.\nMost unpleasant jobs would either get automated or go undone if no\none were willing to do them.Two RoutesThere's another sense of \"not everyone can do work they love\"\nthat's all too true, however. One has to make a living, and it's\nhard to get paid for doing work you love. There are two routes to\nthat destination:\n\n The organic route: as you become more eminent, gradually to\n increase the parts of your job that you like at the expense of\n those you don't.The two-job route: to work at things you don't like to get money\n to work on things you do.\n\nThe organic route is more common. It happens naturally to anyone\nwho does good work. A young architect has to take whatever work\nhe can get, but if he does well he'll gradually be in a position\nto pick and choose among projects. The disadvantage of this route\nis that it's slow and uncertain. Even tenure is not real freedom.The two-job route has several variants depending on how long you\nwork for money at a time. At one extreme is the \"day job,\" where\nyou work regular hours at one job to make money, and work on what\nyou love in your spare time. At the other extreme you work at\nsomething till you make enough not to \nhave to work for money again.The two-job route is less common than the organic route, because\nit requires a deliberate choice. It's also more dangerous. Life\ntends to get more expensive as you get older, so it's easy to get\nsucked into working longer than you expected at the money job.\nWorse still, anything you work on changes you. If you work too\nlong on tedious stuff, it will rot your brain. And the best paying\njobs are most dangerous, because they require your full attention.The advantage of the two-job route is that it lets you jump over\nobstacles. The landscape of possible jobs isn't flat; there are\nwalls of varying heights between different kinds of work. \n[7]\nThe trick of maximizing the parts of your job that you like can get you\nfrom architecture to product design, but not, probably, to music.\nIf you make money doing one thing and then work on another, you\nhave more freedom of choice.Which route should you take? That depends on how sure you are of\nwhat you want to do, how good you are at taking orders, how much\nrisk you can stand, and the odds that anyone will pay (in your\nlifetime) for what you want to do. If you're sure of the general\narea you want to work in and it's something people are likely to\npay you for, then you should probably take the organic route. But\nif you don't know what you want to work on, or don't like to take\norders, you may want to take the two-job route, if you can stand\nthe risk.Don't decide too soon. Kids who know early what they want to do\nseem impressive, as if they got the answer to some math question\nbefore the other kids. They have an answer, certainly, but odds\nare it's wrong.A friend of mine who is a quite successful doctor complains constantly\nabout her job. When people applying to medical school ask her for\nadvice, she wants to shake them and yell \"Don't do it!\" (But she\nnever does.) How did she get into this fix? In high school she\nalready wanted to be a doctor. And she is so ambitious and determined\nthat she overcame every obstacle along the way—including,\nunfortunately, not liking it.Now she has a life chosen for her by a high-school kid.When you're young, you're given the impression that you'll get\nenough information to make each choice before you need to make it.\nBut this is certainly not so with work. When you're deciding what\nto do, you have to operate on ridiculously incomplete information.\nEven in college you get little idea what various types of work are\nlike. At best you may have a couple internships, but not all jobs\noffer internships, and those that do don't teach you much more about\nthe work than being a batboy teaches you about playing baseball.In the design of lives, as in the design of most other things, you\nget better results if you use flexible media. So unless you're\nfairly sure what you want to do, your best bet may be to choose a\ntype of work that could turn into either an organic or two-job\ncareer. That was probably part of the reason I chose computers.\nYou can be a professor, or make a lot of money, or morph it into\nany number of other kinds of work.It's also wise, early on, to seek jobs that let you do many different\nthings, so you can learn faster what various kinds of work are like.\nConversely, the extreme version of the two-job route is dangerous\nbecause it teaches you so little about what you like. If you work\nhard at being a bond trader for ten years, thinking that you'll\nquit and write novels when you have enough money, what happens when\nyou quit and then discover that you don't actually like writing\nnovels?Most people would say, I'd take that problem. Give me a million\ndollars and I'll figure out what to do. But it's harder than it\nlooks. Constraints give your life shape. Remove them and most\npeople have no idea what to do: look at what happens to those who\nwin lotteries or inherit money. Much as everyone thinks they want\nfinancial security, the happiest people are not those who have it,\nbut those who like what they do. So a plan that promises freedom\nat the expense of knowing what to do with it may not be as good as\nit seems.Whichever route you take, expect a struggle. Finding work you love\nis very difficult. Most people fail. Even if you succeed, it's\nrare to be free to work on what you want till your thirties or\nforties. But if you have the destination in sight you'll be more\nlikely to arrive at it. If you know you can love work, you're in\nthe home stretch, and if you know what work you love, you're\npractically there.Notes[1]\nCurrently we do the opposite: when we make kids do boring work,\nlike arithmetic drills, instead of admitting frankly that it's\nboring, we try to disguise it with superficial decorations.[2]\nOne father told me about a related phenomenon: he found himself\nconcealing from his family how much he liked his work. When he\nwanted to go to work on a saturday, he found it easier to say that\nit was because he \"had to\" for some reason, rather than admitting\nhe preferred to work than stay home with them.[3]\nSomething similar happens with suburbs. Parents move to suburbs\nto raise their kids in a safe environment, but suburbs are so dull\nand artificial that by the time they're fifteen the kids are convinced\nthe whole world is boring.[4]\nI'm not saying friends should be the only audience for your\nwork. The more people you can help, the better. But friends should\nbe your compass.[5]\nDonald Hall said young would-be poets were mistaken to be so\nobsessed with being published. But you can imagine what it would\ndo for a 24 year old to get a poem published in The New Yorker.\nNow to people he meets at parties he's a real poet. Actually he's\nno better or worse than he was before, but to a clueless audience\nlike that, the approval of an official authority makes all the\ndifference. So it's a harder problem than Hall realizes. The\nreason the young care so much about prestige is that the people\nthey want to impress are not very discerning.[6]\nThis is isomorphic to the principle that you should prevent\nyour beliefs about how things are from being contaminated by how\nyou wish they were. Most people let them mix pretty promiscuously.\nThe continuing popularity of religion is the most visible index of\nthat.[7]\nA more accurate metaphor would be to say that the graph of jobs\nis not very well connected.Thanks to Trevor Blackwell, Dan Friedman, Sarah Harlin,\nJessica Livingston, Jackie McDonough, Robert Morris, Peter Norvig, \nDavid Sloo, and Aaron Swartz\nfor reading drafts of this." }, { "path": "data/PaulGrahamEssays/lwba.txt", "content": "\nAfter a link to \nBeating the Averages was posted on slashdot, \nsome readers wanted to hear in more detail \nabout the specific technical advantages we got from using\nLisp in Viaweb. For those who are interested,\nhere are some excerpts from a talk I gave in April 2001 at\nBBN Labs in Cambridge, MA." }, { "path": "data/PaulGrahamEssays/mac.txt", "content": "March 2005All the best hackers \nI know are gradually switching to Macs. My\nfriend Robert said his whole research group at MIT recently bought\nthemselves Powerbooks. These guys are not the graphic designers\nand grandmas who were buying Macs at Apple's low point in the\nmid 1990s. They're about as hardcore OS hackers as you can get.The reason, of course, is OS X. Powerbooks are beautifully designed\nand run FreeBSD. What more do you need to know?I got a Powerbook at the end of last year. When my IBM Thinkpad's\nhard disk died soon after, it became my only laptop. And when my\nfriend Trevor showed up at my house recently, he was carrying a\nPowerbook identical to mine.For most of us, it's not a switch to Apple, but a return. Hard as\nthis was to believe in the mid 90s, the Mac was in its time the\ncanonical hacker's computer.In the fall of 1983,\nthe professor in one of my college CS classes got up and announced,\nlike a prophet, that there would soon be a computer with half a MIPS\nof processing power that would fit under an airline seat and cost\nso little that we could save enough to buy one from a summer job.\nThe whole room gasped.\nAnd when the Mac appeared, it was even better than we'd hoped. It\nwas small and powerful and cheap, as promised. But it was also\nsomething we'd never considered a computer could be: fabulously\nwell designed.I had to have one. And I wasn't alone. In the mid to late 1980s,\nall the hackers I knew were either writing software for the Mac,\nor wanted to. Every futon sofa in Cambridge seemed to have the\nsame fat white book lying open on it. If you turned it over, it\nsaid \"Inside Macintosh.\" Then came Linux and FreeBSD, and hackers, who follow the most\npowerful OS wherever it leads, found themselves switching to Intel\nboxes. If you cared about design, you could buy a Thinkpad, which\nwas at least not actively repellent, if you could get the Intel and\nMicrosoft stickers \noff the front. [1]With OS X, the hackers are back. When I walked into the Apple store\nin Cambridge, it was like coming home. Much\nwas changed, but there was still that Apple coolness in the air,\nthat feeling that the show was being run by someone who really\ncared, instead of random corporate deal-makers.So what, the business world may say. Who cares if hackers like Apple\nagain? How big is the hacker market, after all?Quite small, but important out of proportion to its size. When it\ncomes to computers, what hackers are doing now, everyone will be\ndoing in ten years. Almost all technology, from Unix to bitmapped\ndisplays to the Web, became popular first within CS departments and\nresearch labs, and gradually spread to the rest of the world.I remember telling my father back in 1986 that there was a new kind\nof computer called a Sun that was a serious Unix machine, but\nso small and cheap that you could\nhave one of your own to sit in front of, instead of sitting in front\nof a VT100 connected to a single central Vax. Maybe, I suggested,\nhe should buy some stock in this company. I think he really wishes\nhe'd listened.In 1994 my friend Koling wanted to talk to his girlfriend in Taiwan,\nand to save long-distance bills he wrote some software that would \nconvert sound to data packets that could be sent over the Internet.\nWe weren't sure at the time whether this was a proper use of the \nInternet, which was still then a quasi-government entity. What he\nwas doing is now called VoIP, and it is a huge and rapidly growing\nbusiness.If you want to know what ordinary people will be doing with computers\nin ten years, just walk around the CS department at a good university.\nWhatever they're doing, you'll be doing.In the matter of \"platforms\" this tendency is even more pronounced,\nbecause novel software originates with \ngreat hackers, and they tend\nto write it first for whatever computer they personally use. And\nsoftware sells hardware. Many if not most of the initial sales of\nthe Apple II came from people who bought one to run VisiCalc. And\nwhy did Bricklin and Frankston write VisiCalc for the Apple II?\nBecause they personally liked it. They could have chosen any machine\nto make into a star.If you want to attract hackers to write software that will sell\nyour hardware, you have to make it something that they themselves\nuse. It's not enough to make it \"open.\" It has to be open and\ngood.And open and good is what Macs are again, finally. The intervening\nyears have created a situation that is, as far as I know, without\nprecedent: Apple is popular at the low end and the high end, but\nnot in the middle. My seventy year old mother has a Mac laptop.\nMy friends with PhDs in computer science have Mac laptops. [2] And yet \nApple's overall market share is still small.Though unprecedented, I predict this situation is also temporary.So Dad, there's this company called Apple. They make a new kind of\ncomputer that's as well designed as a Bang & Olufsen stereo system,\nand underneath is the best Unix machine you can buy. Yes, the price\nto earnings ratio is kind of high, but I think a lot of people are\ngoing to want these.\nNotes[1] These horrible stickers are much like the intrusive ads popular\non pre-Google search engines. They say to the customer: you are\nunimportant. We care about Intel and Microsoft, not you.[2] Y Combinator\nis (we hope) visited mostly by\nhackers. The proportions of OSes are: \nWindows 66.4%, Macintosh 18.8%, Linux 11.4%, and FreeBSD 1.5%.\nThe Mac number is\na big change from what it would have been five years ago." }, { "path": "data/PaulGrahamEssays/makersschedule.txt", "content": "\n\n\n\n\n\"...the mere consciousness of an engagement will sometimes worry a whole day.\"– Charles Dickens\n\n\n\n\nJuly 2009One reason programmers dislike meetings so much is that they're on\na different type of schedule from other people. Meetings cost them\nmore.There are two types of schedule, which I'll call the manager's\nschedule and the maker's schedule. The manager's schedule is for\nbosses. It's embodied in the traditional appointment book, with\neach day cut into one hour intervals. You can block off several\nhours for a single task if you need to, but by default you change\nwhat you're doing every hour.When you use time that way, it's merely a practical problem to meet\nwith someone. Find an open slot in your schedule, book them, and\nyou're done.Most powerful people are on the manager's schedule. It's the\nschedule of command. But there's another way of using time that's\ncommon among people who make things, like programmers and writers.\nThey generally prefer to use time in units of half a day at least.\nYou can't write or program well in units of an hour. That's barely\nenough time to get started.When you're operating on the maker's schedule, meetings are a\ndisaster. A single meeting can blow a whole afternoon, by breaking\nit into two pieces each too small to do anything hard in. Plus you\nhave to remember to go to the meeting. That's no problem for someone\non the manager's schedule. There's always something coming on the\nnext hour; the only question is what. But when someone on the\nmaker's schedule has a meeting, they have to think about it.For someone on the maker's schedule, having a meeting is like\nthrowing an exception. It doesn't merely cause you to switch from\none task to another; it changes the mode in which you work.I find one meeting can sometimes affect a whole day. A meeting\ncommonly blows at least half a day, by breaking up a morning or\nafternoon. But in addition there's sometimes a cascading effect.\nIf I know the afternoon is going to be broken up, I'm slightly less\nlikely to start something ambitious in the morning. I know this\nmay sound oversensitive, but if you're a maker, think of your own\ncase. Don't your spirits rise at the thought of having an entire\nday free to work, with no appointments at all? Well, that means\nyour spirits are correspondingly depressed when you don't. And\nambitious projects are by definition close to the limits of your\ncapacity. A small decrease in morale is enough to kill them off.Each type of schedule works fine by itself. Problems arise when\nthey meet. Since most powerful people operate on the manager's\nschedule, they're in a position to make everyone resonate at their\nfrequency if they want to. But the smarter ones restrain themselves,\nif they know that some of the people working for them need long\nchunks of time to work in.Our case is an unusual one. Nearly all investors, including all\nVCs I know, operate on the manager's schedule. But \nY Combinator\nruns on the maker's schedule. Rtm and Trevor and I do because we\nalways have, and Jessica does too, mostly, because she's gotten\ninto sync with us.I wouldn't be surprised if there start to be more companies like\nus. I suspect founders may increasingly be able to resist, or at\nleast postpone, turning into managers, just as a few decades ago\nthey started to be able to resist switching from jeans\nto suits.How do we manage to advise so many startups on the maker's schedule?\nBy using the classic device for simulating the manager's schedule\nwithin the maker's: office hours. Several times a week I set aside\na chunk of time to meet founders we've funded. These chunks of\ntime are at the end of my working day, and I wrote a signup program\nthat ensures all the appointments within a given set of office hours\nare clustered at the end. Because they come at the end of my day\nthese meetings are never an interruption. (Unless their working\nday ends at the same time as mine, the meeting presumably interrupts\ntheirs, but since they made the appointment it must be worth it to\nthem.) During busy periods, office hours sometimes get long enough\nthat they compress the day, but they never interrupt it.\nWhen we were working on our own startup, back in the 90s, I evolved\nanother trick for partitioning the day. I used to program from\ndinner till about 3 am every day, because at night no one could\ninterrupt me. Then I'd sleep till about 11 am, and come in and\nwork until dinner on what I called \"business stuff.\" I never thought\nof it in these terms, but in effect I had two workdays each day,\none on the manager's schedule and one on the maker's.When you're operating on the manager's schedule you can do something\nyou'd never want to do on the maker's: you can have speculative\nmeetings. You can meet someone just to get to know one another.\nIf you have an empty slot in your schedule, why not? Maybe it will\nturn out you can help one another in some way.Business people in Silicon Valley (and the whole world, for that\nmatter) have speculative meetings all the time. They're effectively\nfree if you're on the manager's schedule. They're so common that\nthere's distinctive language for proposing them: saying that you\nwant to \"grab coffee,\" for example.Speculative meetings are terribly costly if you're on the maker's\nschedule, though. Which puts us in something of a bind. Everyone\nassumes that, like other investors, we run on the manager's schedule.\nSo they introduce us to someone they think we ought to meet, or\nsend us an email proposing we grab coffee. At this point we have\ntwo options, neither of them good: we can meet with them, and lose\nhalf a day's work; or we can try to avoid meeting them, and probably\noffend them.Till recently we weren't clear in our own minds about the source\nof the problem. We just took it for granted that we had to either\nblow our schedules or offend people. But now that I've realized\nwhat's going on, perhaps there's a third option: to write something\nexplaining the two types of schedule. Maybe eventually, if the\nconflict between the manager's schedule and the maker's schedule\nstarts to be more widely understood, it will become less of a\nproblem.Those of us on the maker's schedule are willing to compromise. We\nknow we have to have some number of meetings. All we ask from those\non the manager's schedule is that they understand the cost.\nThanks to Sam Altman, Trevor Blackwell, Paul Buchheit, Jessica Livingston,\nand Robert Morris for reading drafts of this.Related:" }, { "path": "data/PaulGrahamEssays/marginal.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nJune 2006(This essay is derived from talks at Usenix 2006 and\nRailsconf 2006.)A couple years ago my friend Trevor and I went to look at the Apple\ngarage. As we stood there, he said that as a kid growing up in\nSaskatchewan he'd been amazed at the dedication Jobs and Wozniak\nmust have had to work in a garage.\"Those guys must have been\nfreezing!\"That's one of California's hidden advantages: the mild climate means\nthere's lots of marginal space. In cold places that margin gets\ntrimmed off. There's a sharper line between outside and inside,\nand only projects that are officially sanctioned — by organizations,\nor parents, or wives, or at least by oneself — get proper indoor\nspace. That raises the activation energy for new ideas. You can't\njust tinker. You have to justify.Some of Silicon Valley's most famous companies began in garages:\nHewlett-Packard in 1938, Apple in 1976, Google in 1998. In Apple's\ncase the garage story is a bit of an urban legend. Woz says all\nthey did there was assemble some computers, and that he did all the\nactual design of the Apple I and Apple II in his apartment or his\ncube at HP. \n[1]\nThis was apparently too marginal even for Apple's PR\npeople.By conventional standards, Jobs and Wozniak were marginal people\ntoo. Obviously they were smart, but they can't have looked good\non paper. They were at the time a pair of college dropouts with\nabout three years of school between them, and hippies to boot.\nTheir previous business experience consisted of making \"blue boxes\"\nto hack into the phone system, a business with the rare distinction\nof being both illegal and unprofitable.OutsidersNow a startup operating out of a garage in Silicon Valley would\nfeel part of an exalted tradition, like the poet in his garret, or\nthe painter who can't afford to heat his studio and thus has to\nwear a beret indoors. But in 1976 it didn't seem so cool. The\nworld hadn't yet realized that starting a computer company was in\nthe same category as being a writer or a painter. It hadn't been\nfor long. Only in the preceding couple years had the dramatic fall\nin the cost of hardware allowed outsiders to compete.In 1976, everyone looked down on a company operating out of a garage,\nincluding the founders. One of the first things Jobs did when they\ngot some money was to rent office space. He wanted Apple to seem\nlike a real company.They already had something few real companies ever have: a fabulously well\ndesigned product. You'd think they'd have had more confidence.\nBut I've talked to a lot of startup founders, and it's always this\nway. They've built something that's going to change the world, and\nthey're worried about some nit like not having proper business\ncards.That's the paradox I want to explore: great new things often come\nfrom the margins, and yet the people who discover them are looked\ndown on by everyone, including themselves.It's an old idea that new things come from the margins. I want to\nexamine its internal structure. Why do great ideas come from the\nmargins? What kind of ideas? And is there anything we can do to\nencourage the process?InsidersOne reason so many good ideas come from the margin is simply that\nthere's so much of it. There have to be more outsiders than insiders,\nif insider means anything. If the number of outsiders is huge it\nwill always seem as if a lot of ideas come from them, even if few\ndo per capita. But I think there's more going on than this. There\nare real disadvantages to being an insider, and in some kinds of\nwork they can outweigh the advantages.Imagine, for example, what would happen if the government decided\nto commission someone to write an official Great American Novel.\nFirst there'd be a huge ideological squabble over who to choose.\nMost of the best writers would be excluded for having offended one\nside or the other. Of the remainder, the smart ones would refuse\nsuch a job, leaving only a few with the wrong sort of ambition.\nThe committee would choose one at the height of his career — that\nis, someone whose best work was behind him — and hand over the\nproject with copious free advice about how the book should show in\npositive terms the strength and diversity of the American people,\netc, etc.The unfortunate writer would then sit down to work with a huge\nweight of expectation on his shoulders. Not wanting to blow such\na public commission, he'd play it safe. This book had better command\nrespect, and the way to ensure that would be to make it a tragedy.\nAudiences have to be enticed to laugh, but if you kill people they\nfeel obliged to take you seriously. As everyone knows, America\nplus tragedy equals the Civil War, so that's what it would have to\nbe about. When finally\ncompleted twelve years later, the book would be a 900-page pastiche\nof existing popular novels — roughly Gone with the Wind plus\nRoots. But its bulk and celebrity would make it a bestseller\nfor a few months, until blown out of the water by a talk-show host's\nautobiography. The book would be made into a movie and thereupon\nforgotten, except by the more waspish sort of reviewers, among whom\nit would be a byword for bogusness like Milli Vanilli or Battlefield\nEarth.Maybe I got a little carried away with this example. And yet is\nthis not at each point the way such a project would play out? The\ngovernment knows better than to get into the novel business, but\nin other fields where they have a natural monopoly, like nuclear\nwaste dumps, aircraft carriers, and regime change, you'd find plenty\nof projects isomorphic to this one — and indeed, plenty that were\nless successful.This little thought experiment suggests a few of the disadvantages\nof insider projects: the selection of the wrong kind of people, the\nexcessive scope, the inability to take risks, the need to seem\nserious, the weight of expectations, the power of vested interests,\nthe undiscerning audience, and perhaps most dangerous, the tendency\nof such work to become a duty rather than a pleasure.TestsA world with outsiders and insiders implies some kind of test for\ndistinguishing between them. And the trouble with most tests for\nselecting elites is that there are two ways to pass them: to be\ngood at what they try to measure, and to be good at hacking the\ntest itself.So the first question to ask about a field is how honest its tests\nare, because this tells you what it means to be an outsider. This\ntells you how much to trust your instincts when you disagree with\nauthorities, whether it's worth going through the usual channels\nto become one yourself, and perhaps whether you want to work in\nthis field at all.Tests are least hackable when there are consistent standards for\nquality, and the people running the test really care about its\nintegrity. Admissions to PhD programs in the hard sciences are\nfairly honest, for example. The professors will get whoever they\nadmit as their own grad students, so they try hard to choose well,\nand they have a fair amount of data to go on. Whereas undergraduate\nadmissions seem to be much more hackable.One way to tell whether a field has consistent standards is the\noverlap between the leading practitioners and the people who teach\nthe subject in universities. At one end of the scale you have\nfields like math and physics, where nearly all the teachers are\namong the best practitioners. In the middle are medicine, law,\nhistory, architecture, and computer science, where many are. At\nthe bottom are business, literature, and the visual arts, where\nthere's almost no overlap between the teachers and the leading\npractitioners. It's this end that gives rise to phrases like \"those\nwho can't do, teach.\"Incidentally, this scale might be helpful in deciding what to study\nin college. When I was in college the rule seemed to be that you\nshould study whatever you were most interested in. But in retrospect\nyou're probably better off studying something moderately interesting\nwith someone who's good at it than something very interesting with\nsomeone who isn't. You often hear people say that you shouldn't\nmajor in business in college, but this is actually an instance of\na more general rule: don't learn things from teachers who are bad\nat them.How much you should worry about being an outsider depends on the\nquality of the insiders. If you're an amateur mathematician and\nthink you've solved a famous open problem, better go back and check.\nWhen I was in grad school, a friend in the math department had the\njob of replying to people who sent in proofs of Fermat's last theorem\nand so on, and it did not seem as if he saw it as a valuable source\nof tips — more like manning a mental health hotline. Whereas if\nthe stuff you're writing seems different from what English professors\nare interested in, that's not necessarily a problem.Anti-TestsWhere the method of selecting the elite is thoroughly corrupt, most\nof the good people will be outsiders. In art, for example, the\nimage of the poor, misunderstood genius is not just one possible\nimage of a great artist: it's the standard image. I'm not\nsaying it's correct, incidentally, but it is telling how well this\nimage has stuck. You couldn't make a rap like that stick to math\nor medicine. \n[2]If it's corrupt enough, a test becomes an anti-test, filtering out\nthe people it should select by making them to do things only the\nwrong people would do. Popularity in high school\nseems to be such a test. There are plenty of similar ones in the grownup\nworld. For example, rising up through the hierarchy of the average\nbig company demands an attention to politics few thoughtful people\ncould spare.\n[3]\nSomeone like Bill Gates can grow a company under\nhim, but it's hard to imagine him having the patience to climb the\ncorporate ladder at General Electric — or Microsoft, actually.It's kind of strange when you think about it, because lord-of-the-flies\nschools and bureaucratic companies are both the default. There are\nprobably a lot of people who go from one to the other and never\nrealize the whole world doesn't work this way.I think that's one reason big companies are so often blindsided by\nstartups. \nPeople at big companies don't realize the extent to which\nthey live in an environment that is one large, ongoing test for the\nwrong qualities.If you're an outsider, your best chances for beating insiders are\nobviously in fields where corrupt tests select a lame elite. But\nthere's a catch: if the tests are corrupt, your victory won't be\nrecognized, at least in your lifetime. You may feel you don't need\nthat, but history suggests it's dangerous to work in fields with\ncorrupt tests. You may beat the insiders, and yet not do as good\nwork, on an absolute scale, as you would in a field that was more\nhonest.Standards in art, for example, were almost as corrupt in the first\nhalf of the eighteenth century as they are today. This was the era\nof those fluffy idealized portraits of countesses with their lapdogs.\nChardin \ndecided to skip all that and paint ordinary things as he\nsaw them. He's now considered the best of that period — and yet\nnot the equal of Leonardo or Bellini or Memling, who all had the\nadditional encouragement of honest standards.It can be worth participating in a corrupt contest, however, if\nit's followed by another that isn't corrupt. For example, it would\nbe worth competing with a company that can spend more than you on\nmarketing, as long as you can survive to the next round, when\ncustomers compare your actual products. Similarly, you shouldn't\nbe discouraged by the comparatively corrupt test of college admissions,\nbecause it's followed immediately by less hackable tests.\n[4]RiskEven in a field with honest tests, there are still advantages to\nbeing an outsider. The most obvious is that outsiders have nothing\nto lose. They can do risky things, and if they fail, so what? Few\nwill even notice.The eminent, on the other hand, are weighed down by their eminence.\nEminence is like a suit: it impresses the wrong people, and it\nconstrains the wearer.Outsiders should realize the advantage they have here. Being able\nto take risks is hugely valuable. Everyone values safety too much,\nboth the obscure and the eminent. No one wants to look like a fool.\nBut it's very useful to be able to. If most of your ideas aren't\nstupid, you're probably being too conservative. You're not bracketing\nthe problem.Lord Acton said we should judge talent at its best and character\nat its worst. For example, if you write one great book and ten bad\nones, you still count as a great writer — or at least, a better\nwriter than someone who wrote eleven that were merely good. Whereas\nif you're a quiet, law-abiding citizen most of the time but\noccasionally cut someone up and bury them in your backyard, you're\na bad guy.Almost everyone makes the mistake of treating ideas as if they were\nindications of character rather than talent — as if having a stupid\nidea made you stupid. There's a huge weight of tradition advising\nus to play it safe. \"Even a fool is thought wise if he keeps\nsilent,\" says the Old Testament (Proverbs 17:28).Well, that may be fine advice for a bunch of goatherds in Bronze\nAge Palestine. There conservatism would be the order of the day.\nBut times have changed. It might still be reasonable to stick with\nthe Old Testament in political questions, but materially the world\nnow has a lot more state. Tradition is less of a guide, not just\nbecause things change faster, but because the space of possibilities\nis so large. The more complicated the world gets, the more valuable\nit is to be willing to look like a fool.DelegationAnd yet the more successful people become, the more heat they get\nif they screw up — or even seem to screw up. In this respect, as\nin many others, the eminent are prisoners of their own success. So\nthe best way to understand the advantages of being an outsider may\nbe to look at the disadvantages of being an insider.If you ask eminent people what's wrong with their lives, the first\nthing they'll complain about is the lack of time. A friend of mine\nat Google is fairly high up in the company and went to work for\nthem long before they went public. In other words, he's now rich\nenough not to have to work. I asked him if he could still endure\nthe annoyances of having a job, now that he didn't have to. And\nhe said that there weren't really any annoyances, except — and he\ngot a wistful look when he said this — that he got so much\nemail.The eminent feel like everyone wants to take a bite out of them.\nThe problem is so widespread that people pretending to be eminent\ndo it by pretending to be overstretched.The lives of the eminent become scheduled, and that's not good for\nthinking. One of the great advantages of being an outsider is long,\nuninterrupted blocks of time. That's what I remember about grad\nschool: apparently endless supplies of time, which I spent worrying\nabout, but not writing, my dissertation. Obscurity is like health\nfood — unpleasant, perhaps, but good for you. Whereas fame tends\nto be like the alcohol produced by fermentation. When it reaches\na certain concentration, it kills off the yeast that produced it.The eminent generally respond to the shortage of time by turning\ninto managers. They don't have time to work. They're surrounded\nby junior people they're supposed to help or supervise. The obvious\nsolution is to have the junior people do the work. Some good\nstuff happens this way, but there are problems it doesn't work so\nwell for: the kind where it helps to have everything in one head.For example, it recently emerged that the famous glass artist Dale\nChihuly hasn't actually blown glass for 27 years. He has assistants\ndo the work for him. But one of the most valuable sources of ideas\nin the visual arts is the resistance of the medium. That's why oil\npaintings look so different from watercolors. In principle you\ncould make any mark in any medium; in practice the medium steers\nyou. And if you're no longer doing the work yourself, you stop\nlearning from this.So if you want to beat those eminent enough to delegate, one way\nto do it is to take advantage of direct contact with the medium.\nIn the arts it's obvious how: blow your own glass, edit your own\nfilms, stage your own plays. And in the process pay close attention\nto accidents and to new ideas you have on the fly. This technique\ncan be generalized to any sort of work: if you're an outsider, don't\nbe ruled by plans. Planning is often just a weakness forced on\nthose who delegate.Is there a general rule for finding problems best solved in one\nhead? Well, you can manufacture them by taking any project usually\ndone by multiple people and trying to do it all yourself. Wozniak's\nwork was a classic example: he did everything himself, hardware and\nsoftware, and the result was miraculous. He claims not one bug was\never found in the Apple II, in either hardware or software.Another way to find good problems to solve in one head is to focus\non the grooves in the chocolate bar — the places where tasks are\ndivided when they're split between several people. If you want to\nbeat delegation, focus on a vertical slice: for example, be both\nwriter and editor, or both design buildings and construct them.One especially good groove to span is the one between tools and\nthings made with them. For example, programming languages and\napplications are usually written by different people, and this is\nresponsible for a lot of the worst flaws in \nprogramming languages.\nI think every language should be designed simultaneously with a\nlarge application written in it, the way C was with Unix.Techniques for competing with delegation translate well into business,\nbecause delegation is endemic there. Instead of avoiding it as a\ndrawback of senility, many companies embrace it as a sign of maturity.\nIn big companies software is often designed, implemented, and sold\nby three separate types of people. In startups one person may have\nto do all three. And though this feels stressful, it's one reason\nstartups win. The needs of customers and the means of satisfying\nthem are all in one head.FocusThe very skill of insiders can be a weakness. Once someone is good\nat something, they tend to spend all their time doing that. This\nkind of focus is very valuable, actually. Much of the skill of\nexperts is the ability to ignore false trails. But focus has\ndrawbacks: you don't learn from other fields, and when a new approach\narrives, you may be the last to notice.For outsiders this translates into two ways to win. One is to work\non a variety of things. Since you can't derive as much benefit\n(yet) from a narrow focus, you may as well cast a wider net and\nderive what benefit you can from similarities between fields. Just\nas you can compete with delegation by working on larger vertical\nslices, you can compete with specialization by working on larger\nhorizontal slices — by both writing and illustrating your book, for\nexample.The second way to compete with focus is to see what focus overlooks.\nIn particular, new things. So if you're not good at anything yet,\nconsider working on something so new that no one else is either.\nIt won't have any prestige yet, if no one is good at it, but you'll\nhave it all to yourself.The potential of a new medium is usually underestimated, precisely\nbecause no one has yet explored its possibilities. Before \nDurer\ntried making engravings, no one took them very seriously. Engraving\nwas for making little devotional images — basically fifteenth century\nbaseball cards of saints. Trying to make masterpieces in this\nmedium must have seemed to Durer's contemporaries the way that,\nsay, making masterpieces in \ncomics \nmight seem to the average person\ntoday.In the computer world we get not new mediums but new platforms: the\nminicomputer, the microprocessor, the web-based application. At\nfirst they're always dismissed as being unsuitable for real work.\nAnd yet someone always decides to try anyway, and it turns out you\ncan do more than anyone expected. So in the future when you hear\npeople say of a new platform: yeah, it's popular and cheap, but not\nready yet for real work, jump on it.As well as being more comfortable working on established lines,\ninsiders generally have a vested interest in perpetuating them.\nThe professor who made his reputation by discovering some new idea\nis not likely to be the one to discover its replacement. This is\nparticularly true with companies, who have not only skill and pride\nanchoring them to the status quo, but money as well. The Achilles\nheel of successful companies is their inability to cannibalize\nthemselves. Many innovations consist of replacing something with\na cheaper alternative, and companies just don't want to see a path\nwhose immediate effect is to cut an existing source of revenue.So if you're an outsider you should actively seek out contrarian\nprojects. Instead of working on things the eminent have made\nprestigious, work on things that could steal that prestige.The really juicy new approaches are not the ones insiders reject\nas impossible, but those they ignore as undignified. For example,\nafter Wozniak designed the Apple II he offered it first to his\nemployer, HP. They passed. One of the reasons was that, to save\nmoney, he'd designed the Apple II to use a TV as a monitor, and HP\nfelt they couldn't produce anything so declasse.LessWozniak used a TV as a monitor for the simple reason that he couldn't\nafford a monitor. Outsiders are not merely free but compelled to\nmake things that are cheap and lightweight. And both are good bets\nfor growth: cheap things spread faster, and lightweight things\nevolve faster.The eminent, on the other hand, are almost forced to work on a large\nscale. Instead of garden sheds they must design huge art museums.\nOne reason they work on big things is that they can: like our\nhypothetical novelist, they're flattered by such opportunities.\nThey also know that big projects will by their sheer bulk impress\nthe audience. A garden shed, however lovely, would be easy to\nignore; a few might even snicker at it. You can't snicker at a\ngiant museum, no matter how much you dislike it. And finally, there\nare all those people the eminent have working for them; they have\nto choose projects that can keep them all busy.Outsiders are free of all this. They can work on small things, and\nthere's something very pleasing about small things. Small things\ncan be perfect; big ones always have something wrong with them.\nBut there's a \nmagic \nin small things that goes beyond such rational\nexplanations. All kids know it. Small things have more personality.Plus making them is more fun. You can do what you want; you don't\nhave to satisfy committees. And perhaps most important, small\nthings can be done fast. The prospect of seeing the finished project\nhangs in the air like the smell of dinner cooking. If you work\nfast, maybe you could have it done tonight.Working on small things is also a good way to learn. The most\nimportant kinds of learning happen one project at a time. (\"Next\ntime, I won't...\") The faster you cycle through projects, the\nfaster you'll evolve.Plain materials have a charm like small scale. And in addition\nthere's the challenge of making do with less. Every designer's\nears perk up at the mention of that game, because it's a game you\ncan't lose. Like the JV playing the varsity, if you even tie, you\nwin. So paradoxically there are cases where fewer resources yield\nbetter results, because the designers' pleasure at their own ingenuity\nmore than compensates.\n[5]So if you're an outsider, take advantage of your ability to make\nsmall and inexpensive things. Cultivate the pleasure and simplicity\nof that kind of work; one day you'll miss it.ResponsibilityWhen you're old and eminent, what will you miss about being young\nand obscure? What people seem to miss most is the lack of\nresponsibilities.Responsibility is an occupational disease of eminence. In principle\nyou could avoid it, just as in principle you could avoid getting\nfat as you get old, but few do. I sometimes suspect that responsibility\nis a trap and that the most virtuous route would be to shirk it,\nbut regardless it's certainly constraining.When you're an outsider you're constrained too, of course. You're\nshort of money, for example. But that constrains you in different\nways. How does responsibility constrain you? The worst thing is\nthat it allows you not to focus on real work. Just as the most\ndangerous forms of \nprocrastination \nare those that seem like work,\nthe danger of responsibilities is not just that they can consume a\nwhole day, but that they can do it without setting off the\nkind of alarms you'd set off if you spent a whole day sitting on a\npark bench.A lot of the pain of being an outsider is being aware of one's own\nprocrastination. But this is actually a good thing. You're at\nleast close enough to work that the smell of it makes you hungry.As an outsider, you're just one step away from getting things done.\nA huge step, admittedly, and one that most people never seem to\nmake, but only one step. If you can summon up the energy to get\nstarted, you can work on projects with an intensity (in both senses)\nthat few insiders can match. For insiders work turns into a duty,\nladen with responsibilities and expectations. It's never so pure\nas it was when they were young.Work like a dog being taken for a walk, instead of an ox being yoked\nto the plow. That's what they miss.AudienceA lot of outsiders make the mistake of doing the opposite; they\nadmire the eminent so much that they copy even their flaws. Copying\nis a good way to learn, but copy the right things. When I was in\ncollege I imitated the pompous diction of famous professors. But\nthis wasn't what made them eminent — it was more a flaw their\neminence had allowed them to sink into. Imitating it was like\npretending to have gout in order to seem rich.Half the distinguishing qualities of the eminent are actually\ndisadvantages. Imitating these is not only a waste of time, but\nwill make you seem a fool to your models, who are often well aware\nof it.What are the genuine advantages of being an insider? The greatest\nis an audience. It often seems to outsiders that the great advantage\nof insiders is money — that they have the resources to do what they\nwant. But so do people who inherit money, and that doesn't seem\nto help, not as much as an audience. It's good for morale to know\npeople want to see what you're making; it draws work out of you.If I'm right that the defining advantage of insiders is an audience,\nthen we live in exciting times, because just in the last ten years\nthe Internet has made audiences a lot more liquid. Outsiders don't\nhave to content themselves anymore with a proxy audience of a few\nsmart friends. Now, thanks to the Internet, they can start to grow\nthemselves actual audiences. This is great news for the marginal,\nwho retain the advantages of outsiders while increasingly being\nable to siphon off what had till recently been the prerogative of\nthe elite.Though the Web has been around for more than ten years, I think\nwe're just beginning to see its democratizing effects. Outsiders\nare still learning how to steal audiences. But more importantly,\naudiences are still learning how to be stolen — they're still just\nbeginning to realize how much \ndeeper bloggers can dig than\njournalists, how much\nmore interesting \na democratic news site can be than a\nfront page controlled by editors, and how much\nfunnier\na bunch of kids\nwith webcams can be than mass-produced sitcoms.The big media companies shouldn't worry that people will post their\ncopyrighted material on YouTube. They should worry that people\nwill post their own stuff on YouTube, and audiences will watch that\ninstead.HackingIf I had to condense the power of the marginal into one sentence\nit would be: just try hacking something together. That phrase draws\nin most threads I've mentioned here. Hacking something together\nmeans deciding what to do as you're doing it, not a subordinate\nexecuting the vision of his boss. It implies the result won't\nbe pretty, because it will be made quickly out of inadequate\nmaterials. It may work, but it won't be the sort of thing the\neminent would want to put their name on. Something hacked together\nmeans something that barely solves the problem, or maybe doesn't\nsolve the problem at all, but another you discovered en route. But\nthat's ok, because the main value of that initial version is not the\nthing itself, but what it leads to. Insiders who daren't walk\nthrough the mud in their nice clothes will never make it to the\nsolid ground on the other side.The word \"try\" is an especially valuable component. I disagree\nhere with Yoda, who said there is no try. There is try. It implies\nthere's no punishment if you fail. You're driven by curiosity\ninstead of duty. That means the wind of procrastination will be\nin your favor: instead of avoiding this work, this will be what you\ndo as a way of avoiding other work. And when you do it, you'll be\nin a better mood. The more the work depends on imagination, the\nmore that matters, because most people have more ideas when they're\nhappy.If I could go back and redo my twenties, that would be one thing\nI'd do more of: just try hacking things together. Like many people\nthat age, I spent a lot of time worrying about what I should do.\nI also spent some time trying to build stuff. I should have spent\nless time worrying and more time building. If you're not sure what\nto do, make something.Raymond Chandler's advice to thriller writers was \"When in doubt,\nhave a man come through a door with a gun in his hand.\" He followed\nthat advice. Judging from his books, he was often in doubt. But\nthough the result is occasionally cheesy, it's never boring. In\nlife, as in books, action is underrated.Fortunately the number of things you can just hack together keeps\nincreasing. People fifty years ago would be astonished that one\ncould just hack together a movie, for example. Now you can even\nhack together distribution. Just make stuff and put it online.InappropriateIf you really want to score big, the place to focus is the margin\nof the margin: the territories only recently captured from the\ninsiders. That's where you'll find the juiciest projects still\nundone, either because they seemed too risky, or simply because\nthere were too few insiders to explore everything.This is why I spend most of my time writing \nessays lately. The\nwriting of essays used to be limited to those who could get them\npublished. In principle you could have written them and just shown\nthem to your friends; in practice that didn't work. \n[6]\nAn\nessayist needs the resistance of an audience, just as an engraver\nneeds the resistance of the plate.Up till a few years ago, writing essays was the ultimate insider's\ngame. Domain experts were allowed to publish essays about their\nfield, but the pool allowed to write on general topics was about\neight people who went to the right parties in New York. Now the\nreconquista has overrun this territory, and, not surprisingly, found\nit sparsely cultivated. There are so many essays yet unwritten.\nThey tend to be the naughtier ones; the insiders have pretty much\nexhausted the motherhood and apple pie topics.This leads to my final suggestion: a technique for determining when\nyou're on the right track. You're on the right track when people\ncomplain that you're unqualified, or that you've done something\ninappropriate. If people are complaining, that means you're doing\nsomething rather than sitting around, which is the first step. And\nif they're driven to such empty forms of complaint, that means\nyou've probably done something good.If you make something and people complain that it doesn't work,\nthat's a problem. But if the worst thing they can hit you with is\nyour own status as an outsider, that implies that in every other\nrespect you've succeeded. Pointing out that someone is unqualified\nis as desperate as resorting to racial slurs. It's just a legitimate\nsounding way of saying: we don't like your type around here.But the best thing of all is when people call what you're doing\ninappropriate. I've been hearing this word all my life and I only\nrecently realized that it is, in fact, the sound of the homing\nbeacon. \"Inappropriate\" is the null criticism. It's merely the\nadjective form of \"I don't like it.\"So that, I think, should be the highest goal for the marginal. Be\ninappropriate. When you hear people saying that, you're golden.\nAnd they, incidentally, are busted.Notes[1]\nThe facts about Apple's early history are from an interview \nwith Steve \nWozniak in Jessica Livingston's \nFounders at Work.[2]\nAs usual the popular image is several decades behind reality.\nNow the misunderstood artist is not a chain-smoking drunk who pours\nhis soul into big, messy canvases that philistines see and say\n\"that's not art\" because it isn't a picture of anything. The\nphilistines have now been trained that anything hung on a wall\nis art. Now the misunderstood artist is a coffee-drinking vegan\ncartoonist whose work they see and say \"that's not art\" because it\nlooks like stuff they've seen in the Sunday paper.[3]\nIn fact this would do fairly well as a definition of politics:\nwhat determines rank in the absence of objective tests.[4]\nIn high school you're led to believe your whole future depends\non where you go to college, but it turns out only to buy you a couple\nyears. By your mid-twenties the people worth impressing\nalready judge you more by what\nyou've done than where you went to school.[5]\nManagers are presumably wondering, how can I make this miracle\nhappen? How can I make the people working for me do more with less?\nUnfortunately the constraint probably has to be self-imposed. If\nyou're expected to do more with less, then you're being\nstarved, not eating virtuously.[6]\nWithout the prospect of publication, the closest most people\ncome to writing essays is to write in a journal. I find I never\nget as deeply into subjects as I do in proper essays. As the name\nimplies, you don't go back and rewrite journal entries over\nand over for two weeks.Thanks to Sam Altman, Trevor Blackwell, Paul Buchheit, Sarah\nHarlin, Jessica Livingston, Jackie McDonough, Robert Morris, Olin\nShivers, and Chris Small for reading drafts of this, and to Chris\nSmall and Chad Fowler for inviting me to speak.\n" }, { "path": "data/PaulGrahamEssays/maybe.txt", "content": "February 2009A lot of cities look at Silicon Valley and ask \"How could we make\nsomething like that happen here?\" The \norganic way to do it is to\nestablish a first-rate university in a place where rich people want\nto live. That's how Silicon Valley happened. But could you shortcut\nthe process by funding startups?Possibly. Let's consider what it would take.The first thing to understand is that encouraging startups is a\ndifferent problem from encouraging startups in a particular city.\nThe latter is much more expensive.People sometimes think they could improve the startup scene in their\ntown by starting something like Y \nCombinator there, but in fact it\nwill have near zero effect. I know because Y Combinator itself had\nnear zero effect on Boston when we were based there half the year.\nThe people we funded came from all over the country (indeed, the\nworld) and afterward they went wherever they could get more\nfunding—which generally meant Silicon Valley.The seed funding business is not a regional business, because at\nthat stage startups are mobile. They're just a couple founders with\nlaptops. \n[1]If you want to encourage startups in a particular city, you have\nto fund startups that won't leave. There are two ways to do that:\nhave rules preventing them from leaving, or fund them at the point\nin their life when they naturally take root. The first approach\nis a mistake, because it becomes a filter for selecting bad startups.\nIf your terms force startups to do things they don't want to, only\nthe desperate ones will take your money.Good startups will move to another city as a condition of funding.\nWhat they won't do is agree not to move the next time they need\nfunding. So the only way to get them to stay is to give them enough\nthat they never need to leave.___How much would that take? If you want to keep startups from leaving\nyour town, you have to give them enough that they're not tempted\nby an offer from Silicon Valley VCs that requires them to move. A\nstartup would be able to refuse such an offer if they had grown to\nthe point where they were (a) rooted in your town and/or (b) so\nsuccessful that VCs would fund them even if they didn't move.How much would it cost to grow a startup to that point? A minimum\nof several hundred thousand dollars. Wufoo \nseem to have rooted\nthemselves in Tampa on $118k, but they're an extreme case. On\naverage it would take at least half a million.So if it seems too good to be true to think you could grow a local\nsilicon valley by giving startups $15-20k each like Y Combinator,\nthat's because it is. To make them stick around you'd have to give\nthem at least 20 times that much.However, even that is an interesting prospect. Suppose to be on\nthe safe side it would cost a million dollars per startup. If you\ncould get startups to stick to your town for a million apiece, then\nfor a billion dollars you could bring in a thousand startups. That probably wouldn't push you past Silicon Valley itself, \nbut it might get you second place.For the price of a football stadium, any town that was decent to\nlive in could make itself one of the biggest startup hubs in the\nworld.What's more, it wouldn't take very long. You could probably do\nit in five years. During the term of one mayor. And it would get\neasier over time, because the more startups you had in town, the\nless it would take to get new ones to move there. By the time you\nhad a thousand startups in town, the VCs wouldn't be trying so hard\nto get them to move to Silicon Valley; instead they'd be opening\nlocal offices. Then you'd really be in good shape. You'd have\nstarted a self-sustaining chain reaction like the one that drives\nthe Valley.___But now comes the hard part. You have to pick the startups. How\ndo you do that? Picking startups is a rare and valuable skill, and\nthe handful of people who have it are not readily hireable. And\nthis skill is so hard to measure that if a government did try to\nhire people with it, they'd almost certainly get the wrong ones.For example, a city could give money to a VC fund to establish a\nlocal branch, and let them make the choices. But only a bad VC\nfund would take that deal. They wouldn't seem bad to the city\nofficials. They'd seem very impressive. But they'd be bad at\npicking startups. That's the characteristic failure mode of VCs.\nAll VCs look impressive to limited partners. The difference between\nthe good ones and the bad ones only becomes visible in the other\nhalf of their jobs: choosing and advising startups.\n[2]What you really want is a pool of local angel investors—people\ninvesting money they made from their own startups. But unfortunately\nyou run into a chicken and egg problem here. If your city isn't\nalready a startup hub, there won't be people there who got rich\nfrom startups. And there is no way I can think of that a city could\nattract angels from outside. By definition they're rich. There's\nno incentive that would make them move.\n[3]However, a city could select startups by piggybacking on the expertise\nof investors who weren't local. It would be pretty straightforward\nto make a list of the most eminent Silicon Valley angels and from\nthat to generate a list of all the startups they'd invested in. If\na city offered these companies a million dollars each to move, a\nlot of the earlier stage ones would probably take it.Preposterous as this plan sounds, it's probably the most efficient\nway a city could select good startups.It would hurt the startups somewhat to be separated from their\noriginal investors. On the other hand, the extra million dollars\nwould give them a lot more runway.___Would the transplanted startups survive? Quite possibly. The only\nway to find out would be to try it. It would be a pretty cheap\nexperiment, as civil expenditures go. Pick 30 startups that eminent\nangels have recently invested in, give them each a million dollars\nif they'll relocate to your city, and see what happens after a year.\nIf they seem to be thriving, you can try importing startups on a\nlarger scale.Don't be too legalistic about the conditions under which they're\nallowed to leave. Just have a gentlemen's agreement.Don't try to do it on the cheap and pick only 10 for the initial\nexperiment. If you do this on too small a scale you'll just guarantee\nfailure. Startups need to be around other startups. 30 would be\nenough to feel like a community.Don't try to make them all work in some renovated warehouse you've\nmade into an \"incubator.\" Real startups prefer to work in their\nown spaces.In fact, don't impose any restrictions on the startups at all.\nStartup founders are mostly hackers, \nand hackers are much more\nconstrained by gentlemen's agreements than regulations. If they\nshake your hand on a promise, they'll keep it. But show them a\nlock and their first thought is how to pick it.Interestingly, the 30-startup experiment could be done by any\nsufficiently rich private citizen. And what pressure it would \nput on the city if it worked.\n[4]___Should the city take stock in return for the money?\nIn principle they're entitled to, but how would they choose valuations\nfor the startups? You couldn't just give them all the same valuation:\nthat would be too low for some (who'd turn you down) and too high\nfor others (because it might make their next round a \"down round\").\nAnd since we're assuming we're doing this without being able to\npick startups, we also have to assume we can't value them, since\nthat's practically the same thing.Another reason not to take stock in the startups is that startups\nare often involved in disreputable things. So are established\ncompanies, but they don't get blamed for it. If someone gets\nmurdered by someone they met on Facebook, the press will treat the\nstory as if it were about Facebook. If someone gets murdered by\nsomeone they met at a supermarket, the press will just treat it as\na story about a murder. So understand that if you invest in startups,\nthey might build things that get used for pornography, or file-sharing,\nor the expression of unfashionable opinions. You should probably\nsponsor this project jointly with your political opponents, so they\ncan't use whatever the startups do as a club to beat you with.It would be too much of a political liability just to give\nthe startups the money, though. So the best plan would be to \nmake it convertible debt, but which didn't convert except in\na really big round, like $20 million.___How well this scheme worked would depend on the \ncity. There are\nsome towns, like Portland, that would be easy to turn into startup\nhubs, and others, like Detroit, where it would really be an uphill\nbattle. So be honest with yourself about the sort of town you have\nbefore you try this.It will be easier in proportion to how much your town resembles San\nFrancisco. Do you have good weather? Do people live downtown, or\nhave they abandoned the center for the suburbs? Would the city be\ndescribed as \"hip\" and \"tolerant,\" or as reflecting \"traditional\nvalues?\" Are there good universities nearby? Are there walkable\nneighborhoods? Would nerds feel at home? If you answered yes to\nall these questions, you might be able not only to pull off this\nscheme, but to do it for less than a million per startup.I realize the chance of any city having\nthe political will to carry out this plan is microscopically\nsmall. I just wanted to explore what it would take if one did.\nHow hard would it be to jumpstart a silicon valley? It's\nfascinating to think this prize might be within\nthe reach of so many cities. So even though they'll all still\nspend the money on the stadium, at least now someone can ask them:\nwhy did you choose to do that instead of becoming a serious\nrival to Silicon Valley?\nNotes[1]\nWhat people who start these supposedly local seed firms always\nfind is that (a) their applicants come from all over, not just the\nlocal area, and (b) the local startups also apply to the other seed\nfirms. So what ends up happening is that the applicant pool gets\npartitioned by quality rather than geography.[2]\nInterestingly, the bad VCs fail by choosing startups run by\npeople like them—people who are good presenters, but have no\nreal substance. It's a case of the fake leading the fake. And\nsince everyone involved is so plausible, the LPs who invest in these\nfunds have no idea what's happening till they measure their returns.[3]\nNot even being a tax haven, I suspect. That makes some rich\npeople move, but not the type who would make good angel investors\nin startups.[4]\nThanks to Michael Keenan for pointing this out.Thanks to Trevor Blackwell, Jessica Livingston, Robert\nMorris, and Fred Wilson for reading drafts of this." }, { "path": "data/PaulGrahamEssays/mean.txt", "content": "November 2014It struck me recently how few of the most successful people I know\nare mean. There are exceptions, but remarkably few.Meanness isn't rare. In fact, one of the things the internet has\nshown us is how mean people can be. A few decades ago, only famous\npeople and professional writers got to publish their opinions. Now\neveryone can, and we can all see the long tail of\nmeanness that had previously been hidden.And yet while there are clearly a lot of mean people out there,\nthere are next to none among the most successful people I know.\nWhat's going on here? Are meanness and success inversely correlated?Part of what's going on, of course, is selection bias. I only know\npeople who work in certain fields: startup founders, programmers,\nprofessors. I'm willing to believe that successful people in other\nfields are mean. Maybe successful hedge fund managers are mean; I\ndon't know enough to say. It seems quite likely that most successful\ndrug lords are mean. But there are at least big chunks of the world\nthat mean people don't rule, and that territory seems to be growing.My wife and Y Combinator cofounder Jessica is one of those rare\npeople who have x-ray vision for character. Being married to her\nis like standing next to an airport baggage scanner. She came to\nthe startup world from investment banking, and she has always been\nstruck both by how consistently successful startup founders turn\nout to be good people, and how consistently bad people fail as\nstartup founders.Why? I think there are several reasons. One is that being mean\nmakes you stupid. That's why I hate fights. You never do your best\nwork in a fight, because fights are not sufficiently general.\nWinning is always a function of the situation and the people involved.\nYou don't win fights by thinking of big ideas but by thinking of\ntricks that work in one particular case. And yet fighting is just\nas much work as thinking about real problems. Which is particularly\npainful to someone who cares how their brain is used: your brain\ngoes fast but you get nowhere, like a car spinning its wheels.Startups don't win by attacking. They win by transcending. There\nare exceptions of course, but usually the way to win is to race\nahead, not to stop and fight.Another reason mean founders lose is that they can't get the best\npeople to work for them. They can hire people who will put up with\nthem because they need a job. But the best people have other options.\nA mean person can't convince the best people to work for him unless\nhe is super convincing. And while having the best people helps any\norganization, it's critical for startups.There is also a complementary force at work: if you want to build\ngreat things, it helps to be driven by a spirit of benevolence. The startup founders who end up\nrichest are not the ones driven by money. The ones driven by money\ntake the big acquisition offer that nearly every successful startup\ngets en route.\n[1]\nThe ones who keep going are driven by something\nelse. They may not say so explicitly, but they're usually trying\nto improve the world. Which means people with a desire to improve\nthe world have a natural advantage.\n[2]The exciting thing is that startups are not just one random type\nof work in which meanness and success are inversely correlated.\nThis kind of work is the future.For most of history success meant control of scarce resources. One\ngot that by fighting, whether literally in the case of pastoral\nnomads driving hunter-gatherers into marginal lands, or metaphorically\nin the case of Gilded Age financiers contending with one another\nto assemble railroad monopolies. For most of history, success meant\nsuccess at zero-sum games. And in most of them meanness was not a\nhandicap but probably an advantage.That is changing. Increasingly the games that matter are not zero-sum.\nIncreasingly you win not by fighting to get control of a scarce\nresource, but by having new ideas and building new things.\n[3]There have long been games where you won by having new ideas. In\nthe third century BC, Archimedes won by doing that. At least until\nan invading Roman army killed him. Which illustrates why\nthis change is happening: for new ideas to matter, you need a certain\ndegree of civil order. And not just not being at war. You also\nneed to prevent the sort of economic violence that nineteenth century\nmagnates practiced against one another and communist countries\npracticed against their citizens. People need to feel that what\nthey create can't be stolen.\n[4]That has always been the case for thinkers, which is why this trend\nbegan with them. When you think of successful people from history\nwho weren't ruthless, you get mathematicians and writers and artists.\nThe exciting thing is that their m.o. seems to be spreading. The\ngames played by intellectuals are leaking into the real world, and\nthis is reversing the historical polarity of the relationship between\nmeanness and success.So I'm really glad I stopped to think about this. Jessica and I\nhave always worked hard to teach our kids not to be mean. We\ntolerate noise and mess and junk food, but not meanness. And now\nI have both an additional reason to crack down on it, and an\nadditional argument to use when I do: that being mean makes you\nfail.\nNotes[1]\nI'm not saying all founders who take big acquisition offers\nare driven only by money, but rather that those who don't aren't.\nPlus one can have benevolent motives for being driven by money — for \nexample, to take care of one's family, or to be free to work\non projects that improve the world.[2]\nIt's unlikely that every successful startup improves the\nworld. But their founders, like parents, truly believe they do.\nSuccessful founders are in love with their companies. And while\nthis sort of love is as blind as the love people have for one\nanother, it is genuine.[3]\nPeter \nThiel would point out that successful founders still\nget rich from controlling monopolies, just monopolies they create\nrather than ones they capture. And while this is largely true, it\nmeans a big change in the sort of person who wins.[4]\nTo be fair, the Romans didn't mean to kill Archimedes. The\nRoman commander specifically ordered that he be spared. But he got\nkilled in the chaos anyway.In sufficiently disordered times, even thinking requires\ncontrol of scarce resources, because living at all is a scarce\nresource.Thanks to Sam Altman, Ron Conway, Daniel Gackle, Jessica Livingston, Robert Morris,\nGeoff Ralston, and Fred Wilson for reading drafts of this." }, { "path": "data/PaulGrahamEssays/microsoft.txt", "content": "April 2007A few days ago I suddenly realized Microsoft was dead. I was talking\nto a young startup founder about how Google was different from\nYahoo. I said that Yahoo had been warped from the start by\ntheir fear of Microsoft. That was why they'd positioned themselves\nas a \"media company\" instead of a technology company. Then I looked\nat his face and realized he didn't understand. It was as if I'd\ntold him how much girls liked Barry Manilow in the mid\n80s. Barry who?Microsoft? He didn't say anything, but I could tell he didn't quite\nbelieve anyone would be frightened of them.Microsoft cast\na shadow over the software world for almost 20 years\nstarting in the late 80s.\nI can remember when it was IBM before them. I mostly ignored this\nshadow. I never used Microsoft software, so it only affected me\nindirectly—for example, in the spam I got from botnets. And\nbecause I wasn't paying attention, I didn't notice when the shadow\ndisappeared.But it's gone now. I can sense that. No one is even afraid of\nMicrosoft anymore. They still make a lot of money—so does IBM,\nfor that matter. But they're not dangerous.When did Microsoft die, and of what? I know they seemed dangerous\nas late as 2001, because I wrote an essay then \nabout how they were\nless dangerous than they seemed. I'd guess they were dead by 2005.\nI know when we started Y Combinator we didn't worry about Microsoft\nas competition for the startups we funded. In fact, we've never\neven invited them to the demo days we organize for startups to\npresent to investors. We invite Yahoo and Google and some other\nInternet companies, but we've never bothered to invite Microsoft.\nNor has anyone there ever even sent us an email. They're in a\ndifferent world.What killed them? Four things, I think, all of them occurring\nsimultaneously in the mid 2000s.The most obvious is Google. There can only be one big man in town,\nand they're clearly it. Google is the most dangerous company\nnow by far, in both the good and bad senses of the word. Microsoft\ncan at best limp along afterward.When did Google take the lead? There will be a tendency to push\nit back to their IPO in August 2004, but they weren't setting the\nterms of the debate then. I'd say they took the lead in\n2005. Gmail was one of the things that put them over the edge.\nGmail showed they could do more than search.Gmail also showed how much you could do with web-based software,\nif you took advantage of what later came to be called \"Ajax.\" And\nthat was the second cause of Microsoft's death: everyone can see the\ndesktop is over. It now seems inevitable that applications will\nlive on the web—not just email, but everything, right up to\nPhotoshop. Even Microsoft sees that now.Ironically, Microsoft unintentionally helped create Ajax. The x\nin Ajax is from the XMLHttpRequest object, which lets the browser\ncommunicate with the server in the background while displaying a page.\n(Originally the only way to communicate with the server was to \nask for a new page.) XMLHttpRequest was created by Microsoft in the late 90s\nbecause they needed it for Outlook. What they didn't realize was\nthat it would be useful to a lot of other people too—in fact, to\nanyone who wanted to make web apps work like desktop ones.The other critical component of Ajax is Javascript, the programming\nlanguage that runs in the browser. Microsoft saw the danger of\nJavascript and tried to keep it broken for as long as they could.\n[1] \nBut eventually the open source world won, by producing\nJavascript libraries that grew over the brokenness of Explorer\nthe way a tree grows over barbed wire.The third cause of Microsoft's death was broadband Internet. Anyone\nwho cares can have fast Internet access\nnow. And the bigger the pipe to the server, the less you need the\ndesktop.The last nail in the coffin came, of all places, from Apple. \nThanks to OS X, Apple has come back from the dead in a way\nthat is extremely rare in technology.\n[2]\nTheir victory is so complete that I'm now surprised when I come across\na computer running Windows. Nearly all the people we fund at Y\nCombinator use Apple laptops. It was the same in the audience at \nstartup\nschool. All the computer people use Macs or Linux now. Windows is for\ngrandmas, like Macs used to be in the 90s. So not only does the\ndesktop no longer matter, no one who cares about computers uses\nMicrosoft's anyway.And of course Apple has Microsoft on the run in music\ntoo, with TV and phones on the way.I'm glad Microsoft is dead. They were like Nero or \nCommodus—evil\nin the way only inherited power can make you. Because remember,\nthe Microsoft monopoly didn't begin with Microsoft. They got it\nfrom IBM. The software business was overhung by a\nmonopoly from about the mid-1950s to about 2005. For practically\nits whole existence, that is. One of the reasons \"Web 2.0\" has\nsuch an air of euphoria about it is the feeling, conscious or not,\nthat this era of monopoly may finally be over.Of course, as a hacker I can't help thinking about how something\nbroken could be fixed. Is there some way Microsoft could come back?\nIn principle, yes. To see how, envision two things: (a) the amount\nof cash Microsoft now has on hand, and (b) Larry and Sergey making\nthe rounds of all the search engines ten years ago trying to sell\nthe idea for Google for a million dollars, and being turned down\nby everyone.The surprising fact is, brilliant hackers—dangerously brilliant\nhackers—can be had very cheaply, by the standards of a\ncompany as rich as Microsoft. They can't \nhire smart people anymore,\nbut they could buy as many as they wanted for only an order of magnitude \nmore. So if they wanted to be a contender\nagain, this is how they could do it:\n\n Buy all the good \"Web 2.0\" startups. They could get substantially\n all of them for less than they'd have to pay for Facebook. Put them all in a building in Silicon Valley, surrounded by\n lead shielding to protect them from any contact with Redmond.\n\nI feel safe suggesting this, because they'd never do it. Microsoft's\nbiggest weakness is that they still don't realize how much they\nsuck. They still think they can write software in house. Maybe they\ncan, by the standards of the desktop world. But that world ended\na few years ago.I already know what the reaction to this essay will be. Half the\nreaders will say that Microsoft is still an enormously profitable\ncompany, and that I should be more\ncareful about drawing conclusions based on what a few people think\nin our insular little \"Web 2.0\" bubble. The other half, the younger\nhalf, will complain that this is old news.See also: Microsoft is Dead: the Cliffs NotesNotes[1]\nIt doesn't take a conscious effort to make software incompatible.\nAll you have to do is not work too hard at fixing bugs—which, if\nyou're a big company, you produce in copious quantities. The\nsituation is analogous to the writing of \"literary\ntheorists.\" Most don't try to be obscure; they just don't make an\neffort to be clear. It wouldn't pay.[2]\nIn part because Steve Jobs got pushed out by John Sculley in\na way that's rare among technology companies. If Apple's board\nhadn't made that blunder, they wouldn't have had to bounce back." }, { "path": "data/PaulGrahamEssays/mit.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nOctober 2006(This essay is derived from a talk at MIT.)Till recently graduating seniors had two choices: get a job or go\nto grad school. I think there will increasingly be a third option:\nto start your own startup. But how common will that be?I'm sure the default will always be to get a job, but starting a\nstartup could well become as popular as grad school. In the late\n90s my professor friends used to complain that they couldn't get\ngrad students, because all the undergrads were going to work for\nstartups. I wouldn't be surprised if that situation returns, but\nwith one difference: this time they'll be starting their own\ninstead of going to work for other people's.The most ambitious students will at this point be asking: Why wait\ntill you graduate? Why not start a startup while you're in college?\nIn fact, why go to college at all? Why not start a startup instead?A year and a half ago I gave a talk \nwhere I said that the average age of the founders of\nYahoo, Google, and Microsoft was 24, and that if grad students could\nstart startups, why not undergrads? I'm glad I phrased that as a\nquestion, because now I can pretend it wasn't merely a rhetorical\none. At the time I couldn't imagine why there should be any lower\nlimit for the age of startup founders. Graduation is a bureaucratic\nchange, not a biological one. And certainly there are undergrads\nas competent technically as most grad students. So why shouldn't\nundergrads be able to start startups as well as grad students?I now realize that something does change at graduation: you lose a\nhuge excuse for failing. Regardless of how complex your life is,\nyou'll find that everyone else, including your family and friends,\nwill discard all the low bits and regard you as having a single\noccupation at any given time. If you're in college and have a\nsummer job writing software, you still read as a student. Whereas\nif you graduate and get a job programming, you'll be instantly\nregarded by everyone as a programmer.The problem with starting a startup while you're still in school\nis that there's a built-in escape hatch. If you start a startup\nin the summer between your junior and senior year, it reads to\neveryone as a summer job.\nSo if it goes nowhere, big deal; you return to school in the\nfall with all the other seniors; no one regards you as a failure,\nbecause your occupation is student, and you didn't fail at that.\nWhereas if you start a startup just one year later, after you\ngraduate, as long as you're not accepted to grad school in the fall\nthe startup reads to everyone as your occupation. You're\nnow a startup founder, so you have to do well at that.For nearly everyone, the opinion of one's peers is the most powerful\nmotivator of all—more powerful even than the nominal goal of most\nstartup founders, getting rich. \n[1]\nAbout a month into each funding\ncycle we have an event called Prototype Day where each startup\npresents to the others what they've got so far. You might think\nthey wouldn't need any more motivation. They're working on their\ncool new idea; they have funding for the immediate future; and\nthey're playing a game with only two outcomes: wealth or failure.\nYou'd think that would be motivation enough. And yet the prospect\nof a demo pushes most of them into a\nrush of activity.Even if you start a startup explicitly to get rich, the money you\nmight get seems pretty theoretical most of the time. What drives\nyou day to day is not wanting to look bad.You probably can't change that. Even if you could, I don't think\nyou'd want to; someone who really, truly doesn't care what his peers\nthink of him is probably a psychopath. So the best you can do is\nconsider this force like a wind, and set up your boat accordingly.\nIf you know your peers are going to push you in some direction,\nchoose good peers, and position yourself so they push you in a\ndirection you like.Graduation changes the prevailing winds, and those make a difference.\nStarting a startup is so hard\nthat it's a close call even for the ones that succeed. However\nhigh a startup may be flying now, it probably has a few leaves stuck\nin the landing gear from those trees it barely cleared at the end\nof the runway. In such a close game, the smallest increase in the\nforces against you can be enough to flick you over the edge into\nfailure.When we first started Y Combinator \nwe encouraged people to start\nstartups while they were still in college. That's partly because\nY Combinator began as a kind of summer program. We've kept the\nprogram shape—all of us having dinner together once a week turns\nout to be a good idea—but we've decided now\nthat the party line should be to tell people to wait till they\ngraduate.Does that mean you can't start a startup in college? Not at all.\nSam Altman, the co-founder of Loopt,\nhad just finished his sophomore year when we funded them, and Loopt\nis probably the most promising of all the startups we've funded so\nfar. But Sam Altman is a very unusual guy. Within about three\nminutes of meeting him, I remember thinking \"Ah, so this is what\nBill Gates must have been like when he was 19.\"If it can work to start a startup during college, why do\nwe tell people not to? For the same reason that the probably\napocryphal violinist, whenever he was asked to judge someone's\nplaying, would always say they didn't have enough talent to make\nit as a pro. Succeeding as a musician takes determination as well\nas talent, so this answer works out to be the right advice for\neveryone. The ones who are uncertain believe it and give up, and\nthe ones who are sufficiently determined think \"screw that, I'll\nsucceed anyway.\"So our official policy now is only to fund undergrads we can't talk\nout of it. And frankly, if you're not certain, you should wait.\nIt's not as if all the opportunities to start companies are going\nto be gone if you don't do it now. Maybe the window will close on\nsome idea you're working on, but that won't be the last idea you'll\nhave. For every idea that times out, new ones become feasible.\nHistorically the opportunities to start startups have only increased\nwith time.In that case, you might ask, why not wait longer? Why not go work\nfor a while, or go to grad school, and then start a startup? And\nindeed, that might be a good idea. If I had to pick the sweet spot\nfor startup founders, based on who we're most excited to see\napplications from, I'd say it's probably the mid-twenties. Why?\nWhat advantages does someone in their mid-twenties have over someone\nwho's 21? And why isn't it older? What can 25 year olds do that\n32 year olds can't? Those turn out to be questions worth examining.PlusIf you start a startup soon after college, you'll be a young founder\nby present standards, so you should know what the relative advantages\nof young founders are. They're not what you might think. As a\nyoung founder your strengths are: stamina, poverty, rootlessness,\ncolleagues, and ignorance.The importance of stamina shouldn't be surprising. If you've heard\nanything about startups you've probably heard about the long hours.\nAs far as I can tell these are universal. I can't think of any\nsuccessful startups whose founders worked 9 to 5. And it's\nparticularly necessary for younger founders to work long hours\nbecause they're probably not as efficient as they'll be later.Your second advantage, poverty, might not sound like an advantage,\nbut it is a huge one. Poverty implies you can live cheaply,\nand this is critically important for startups. Nearly every startup\nthat fails, fails by running out of money. It's a little misleading\nto put it this way, because there's usually some other underlying\ncause. But regardless of the source of your problems, a low burn\nrate gives you more opportunity to recover from them. And since\nmost startups make all kinds of mistakes at first, room to recover\nfrom mistakes is a valuable thing to have.Most startups end up doing something different than they planned.\nThe way the successful ones find something that works is by trying\nthings that don't. So the worst thing you can do in a startup is\nto have a rigid, pre-ordained plan and then start spending a lot\nof money to implement it. Better to operate cheaply and give your\nideas time to evolve.Recent grads can live on practically nothing, and this gives you\nan edge over older founders, because the main cost in software\nstartups is people. The guys with kids and mortgages are at a\nreal disadvantage. This is one reason I'd bet on the 25 year old\nover the 32 year old. The 32 year old probably is a better programmer,\nbut probably also has a much more expensive life. Whereas a 25\nyear old has some work experience (more on that later) but can live\nas cheaply as an undergrad.Robert Morris and I were 29 and 30 respectively when we started\nViaweb, but fortunately we still lived like 23 year olds. We both had\nroughly zero assets. I would have loved to have a mortgage,\nsince that would have meant I had a house. But in retrospect\nhaving nothing turned out to be convenient. I wasn't tied down and\nI was used to living cheaply.Even more important than living cheaply, though, is thinking cheaply.\nOne reason the Apple II was so popular was that it was cheap. The\ncomputer itself was cheap, and it used cheap, off-the-shelf peripherals\nlike a cassette tape recorder for data storage and a TV as a monitor.\nAnd you know why? Because Woz designed this computer for himself,\nand he couldn't afford anything more.We benefitted from the same phenomenon. Our prices were\ndaringly low for the time. The top level of service was\n$300 a month, which was an order of magnitude below the norm. In\nretrospect this was a smart move, but we didn't do it because we\nwere smart. $300 a month seemed like a lot of money to us. Like\nApple, we created something inexpensive, and therefore popular,\nsimply because we were poor.A lot of startups have that form: someone comes along and makes\nsomething for a tenth or a hundredth of what it used to cost, and\nthe existing players can't follow because they don't even want to\nthink about a world in which that's possible. Traditional long\ndistance carriers, for example, didn't even want to think about\nVoIP. (It was coming, all the same.) Being poor helps in this\ngame, because your own personal bias points in the same direction\ntechnology evolves in.The advantages of rootlessness are similar to those of poverty.\nWhen you're young you're more mobile—not just because you don't\nhave a house or much stuff, but also because you're less likely to\nhave serious relationships. This turns out to be important, because\na lot of startups involve someone moving.The founders of Kiko, for example, are now en route to the Bay Area\nto start their next startup. It's a better place for what they\nwant to do. And it was easy for them to decide to go, because\nneither as far as I know has a serious girlfriend, and everything\nthey own will fit in one car—or more precisely, will either fit\nin one car or is crappy enough that they don't mind leaving it\nbehind.They at least were in Boston. What if they'd been in Nebraska,\nlike Evan Williams was at their age? Someone wrote recently that\nthe drawback of Y Combinator was that you had to move to participate.\nIt couldn't be any other way. The kind of conversations we have\nwith founders, we have to have in person. We fund a dozen startups\nat a time, and we can't be in a dozen places at once. But even if\nwe could somehow magically save people from moving, we wouldn't.\nWe wouldn't be doing founders a favor by letting them stay in\nNebraska. Places that aren't \nstartup hubs are toxic to startups.\nYou can tell that from indirect evidence. You can tell how hard\nit must be to start a startup in Houston or Chicago or Miami from\nthe microscopically small number, per capita, that succeed \nthere. I don't know exactly what's suppressing all the startups in these\ntowns—probably a hundred subtle little things—but something\nmust be.\n[2]Maybe this will change. Maybe the increasing cheapness of startups\nwill mean they'll be able to survive anywhere, instead of only in\nthe most hospitable environments. Maybe 37signals is the pattern\nfor the future. But maybe not. Historically there have always\nbeen certain towns that were centers for certain industries, and\nif you weren't in one of them you were at a disadvantage. So my\nguess is that 37signals is an anomaly. We're looking at a pattern\nmuch older than \"Web 2.0\" here.Perhaps the reason more startups per capita happen in the Bay Area\nthan Miami is simply that there are more founder-type people there.\nSuccessful startups are almost never started by one person. Usually\nthey begin with a conversation in which someone mentions that\nsomething would be a good idea for a company, and his friend says,\n\"Yeah, that is a good idea, let's try it.\" If you're missing that\nsecond person who says \"let's try it,\" the startup never happens.\nAnd that is another area where undergrads have an edge. They're\nsurrounded by people willing to say that. At a good college you're\nconcentrated together with a lot of other ambitious and technically\nminded people—probably more concentrated than you'll ever be\nagain. If your nucleus spits out a neutron, there's a good chance\nit will hit another nucleus.The number one question people ask us at Y Combinator is: Where can\nI find a co-founder? That's the biggest problem for someone starting\na startup at 30. When they were in school they knew a lot of good\nco-founders, but by 30 they've either lost touch with them or these\npeople are tied down by jobs they don't want to leave.Viaweb was an anomaly in this respect too. Though we were comparatively\nold, we weren't tied down by impressive jobs. I was trying to be\nan artist, which is not very constraining, and Robert, though 29,\nwas still in grad school due to a little interruption in his academic\ncareer back in 1988. So arguably the Worm made Viaweb possible.\nOtherwise Robert would have been a junior professor at that age,\nand he wouldn't have had time to work on crazy speculative projects\nwith me.Most of the questions people ask Y Combinator we have some kind of\nanswer for, but not the co-founder question. There is no good\nanswer. Co-founders really should be people you already know. And\nby far the best place to meet them is school. You have a large\nsample of smart people; you get to compare how they all perform on\nidentical tasks; and everyone's life is pretty fluid. A lot of\nstartups grow out of schools for this reason. Google, Yahoo, and\nMicrosoft, among others, were all founded by people who met in\nschool. (In Microsoft's case, it was high school.)Many students feel they should wait and get a little more experience\nbefore they start a company. All other things being equal, they\nshould. But all other things are not quite as equal as they look.\nMost students don't realize how rich they are in the scarcest\ningredient in startups, co-founders. If you wait too long, you may\nfind that your friends are now involved in some project they don't\nwant to abandon. The better they are, the more likely this is to\nhappen.One way to mitigate this problem might be to actively plan your\nstartup while you're getting those n years of experience. Sure,\ngo off and get jobs or go to grad school or whatever, but get\ntogether regularly to scheme, so the idea of starting a startup\nstays alive in everyone's brain. I don't know if this works, but\nit can't hurt to try.It would be helpful just to realize what an advantage you have as\nstudents. Some of your classmates are probably going to be successful\nstartup founders; at a great technical university, that is a near\ncertainty. So which ones? If I were you I'd look for the people\nwho are not just smart, but incurable \nbuilders. \nLook\nfor the people who keep starting projects, and finish at least some\nof them. That's what we look for. Above all else, above academic\ncredentials and even the idea you apply with, we look for people\nwho build things.The other place co-founders meet is at work. Fewer do than at\nschool, but there are things you can do to improve the odds. The\nmost important, obviously, is to work somewhere that has a lot of\nsmart, young people. Another is to work for a company located in\na startup hub. It will be easier to talk a co-worker into quitting\nwith you in a place where startups are happening all around you.You might also want to look at the employment agreement you sign\nwhen you get hired. Most will say that any ideas you think of while\nyou're employed by the company belong to them. In practice it's\nhard for anyone to prove what ideas you had when, so the line gets\ndrawn at code. If you're going to start a startup, don't write any\nof the code while you're still employed. Or at least discard any\ncode you wrote while still employed and start over. It's not so\nmuch that your employer will find out and sue you. It won't come\nto that; investors or acquirers or (if you're so lucky) underwriters\nwill nail you first. Between t = 0 and when you buy that yacht,\nsomeone is going to ask if any of your code legally belongs\nto anyone else, and you need to be able to say no.\n[3]The most overreaching employee agreement I've seen so far is Amazon's.\nIn addition to the usual clauses about owning your ideas, you also\ncan't be a founder of a startup that has another founder who worked\nat Amazon—even if you didn't know them or even work there at the\nsame time. I suspect they'd have a hard time enforcing this, but\nit's a bad sign they even try. There are plenty of other places\nto work; you may as well choose one that keeps more of your options\nopen.Speaking of cool places to work, there is of course Google. But I\nnotice something slightly frightening about Google: zero startups\ncome out of there. In that respect it's a black hole. People seem\nto like working at Google too much to leave. So if you hope to start\na startup one day, the evidence so far suggests you shouldn't work\nthere.I realize this seems odd advice. If they make your life so good\nthat you don't want to leave, why not work there? Because, in\neffect, you're probably getting a local maximum. You need a certain\nactivation energy to start a startup. So an employer who's fairly\npleasant to work for can lull you into staying indefinitely, even\nif it would be a net win for you to leave.\n[4]The best place to work, if you want to start a startup, is probably\na startup. In addition to being the right sort of experience, one\nway or another it will be over quickly. You'll either end up rich,\nin which case problem solved, or the startup will get bought, in\nwhich case it it will start to suck to work there and it will be\neasy to leave, or most likely, the thing will blow up and you'll\nbe free again.Your final advantage, ignorance, may not sound very useful. I\ndeliberately used a controversial word for it; you might equally\ncall it innocence. But it seems to be a powerful force. My Y\nCombinator co-founder Jessica Livingston is just about to publish\na book of interviews\nwith startup founders, and I noticed a remarkable pattern in them.\nOne after another said that if they'd known how hard it would be,\nthey would have been too intimidated to start.Ignorance can be useful when it's a counterweight to other forms\nof stupidity. It's useful in starting startups because you're\ncapable of more than you realize. Starting startups is harder than\nyou expect, but you're also capable of more than you expect, so\nthey balance out.Most people look at a company like Apple and think, how could I\never make such a thing? Apple is an institution, and I'm just a\nperson. But every institution was at one point just a handful of\npeople in a room deciding to start something. Institutions are\nmade up, and made up by people no different from you.I'm not saying everyone could start a startup. I'm sure most people\ncouldn't; I don't know much about the population at large. When\nyou get to groups I know well, like hackers, I can say more precisely.\nAt the top schools, I'd guess as many as a quarter of the CS majors\ncould make it as startup founders if they wanted.That \"if they wanted\" is an important qualification—so important\nthat it's almost cheating to append it like that—because once you\nget over a certain threshold of intelligence, which most CS majors\nat top schools are past, the deciding factor in whether you succeed\nas a founder is how much you want to. You don't have to be that\nsmart. If you're not a genius, just start a startup in some unsexy\nfield where you'll have less competition, like software for human\nresources departments. I picked that example at random, but I feel\nsafe in predicting that whatever they have now, it wouldn't take\ngenius to do better. There are a lot of people out there working\non boring stuff who are desperately in need of better software, so\nhowever short you think you fall of Larry and Sergey, you can ratchet\ndown the coolness of the idea far enough to compensate.As well as preventing you from being intimidated, ignorance can\nsometimes help you discover new ideas. Steve Wozniak\nput this very strongly:\n\n All the best things that I did at Apple came from (a) not having\n money and (b) not having done it before, ever. Every single thing\n that we came out with that was really great, I'd never once done\n that thing in my life.\n\nWhen you know nothing, you have to reinvent stuff for yourself, and\nif you're smart your reinventions may be better than what preceded\nthem. This is especially true in fields where the rules change.\nAll our ideas about software were developed in a time when processors\nwere slow, and memories and disks were tiny. Who knows what obsolete\nassumptions are embedded in the conventional wisdom? And the way\nthese assumptions are going to get fixed is not by explicitly\ndeallocating them, but by something more akin to garbage collection.\nSomeone ignorant but smart will come along and reinvent everything,\nand in the process simply fail to reproduce certain existing ideas.MinusSo much for the advantages of young founders. What about the\ndisadvantages? I'm going to start with what goes wrong and try to\ntrace it back to the root causes.What goes wrong with young founders is that they build stuff that\nlooks like class projects. It was only recently that we figured\nthis out ourselves. We noticed a lot of similarities between the\nstartups that seemed to be falling behind, but we couldn't figure\nout how to put it into words. Then finally we realized what it\nwas: they were building class projects.But what does that really mean? What's wrong with class projects?\nWhat's the difference between a class project and a real startup?\nIf we could answer that question it would be useful not just to\nwould-be startup founders but to students in general, because we'd\nbe a long way toward explaining the mystery of the so-called real\nworld.There seem to be two big things missing in class projects: (1) an\niterative definition of a real problem and (2) intensity.The first is probably unavoidable. Class projects will inevitably\nsolve fake problems. For one thing, real problems are rare and\nvaluable. If a professor wanted to have students solve real problems,\nhe'd face the same paradox as someone trying to give an example of\nwhatever \"paradigm\" might succeed the Standard Model of physics.\nThere may well be something that does, but if you could think of\nan example you'd be entitled to the Nobel Prize. Similarly, good\nnew problems are not to be had for the asking.In technology the difficulty is compounded by the fact that real\nstartups tend to discover the problem they're solving by a process\nof evolution. Someone has an idea for something; they build it;\nand in doing so (and probably only by doing so) they realize\nthe problem they should be solving is another one. Even if the\nprofessor let you change your project description on the fly, there\nisn't time enough to do that in a college class, or a market to\nsupply evolutionary pressures. So class\nprojects are mostly about implementation, which is the least\nof your problems in a startup.It's not just that in a startup you work on the idea as well as\nimplementation. The very implementation is different. Its main\npurpose is to refine the idea. Often the only value of most of the\nstuff you build in the first six months is that it proves your\ninitial idea was mistaken. And that's extremely valuable. If\nyou're free of a misconception that everyone else still shares,\nyou're in a powerful position. But you're not thinking that way\nabout a class project. Proving your initial plan was mistaken would\njust get you a bad grade. Instead of building stuff to throw away,\nyou tend to want every line of code to go toward that final goal\nof showing you did a lot of work.That leads to our second difference: the way class projects are\nmeasured. Professors will tend to judge you by the distance between\nthe starting point and where you are now. If someone has achieved\na lot, they should get a good grade. But customers will judge you\nfrom the other direction: the distance remaining between where you\nare now and the features they need. The market doesn't give a shit\nhow hard you worked. Users just want your software to do what they\nneed, and you get a zero otherwise. That is one of the most\ndistinctive differences between school and the real world: there\nis no reward for putting in a good effort. In fact, the whole\nconcept of a \"good effort\" is a fake idea adults invented to encourage\nkids. It is not found in nature.Such lies seem to be helpful to kids. But unfortunately when you\ngraduate they don't give you a list of all the lies they told you\nduring your education. You have to get them beaten out of you by\ncontact with the real world. And this is why so many jobs want\nwork experience. I couldn't understand that when I was in college.\nI knew how to program. In fact, I could tell I knew how to program\nbetter than most people doing it for a living. So what was this\nmysterious \"work experience\" and why did I need it?Now I know what it is, and part of the confusion is grammatical.\nDescribing it as \"work experience\" implies it's like experience\noperating a certain kind of machine, or using a certain programming\nlanguage. But really what work experience refers to is not some\nspecific expertise, but the elimination of certain habits left over\nfrom childhood.One of the defining qualities of kids is that they flake. When\nyou're a kid and you face some hard test, you can cry and say \"I\ncan't\" and they won't make you do it. Of course, no one can make\nyou do anything in the grownup world either. What they do instead\nis fire you. And when motivated by that\nyou find you can do a lot more than you realized. So one of the\nthings employers expect from someone with \"work experience\" is the\nelimination of the flake reflex—the ability to get things done,\nwith no excuses.The other thing you get from work experience is an understanding\nof what work is, and in particular, how intrinsically horrible it\nis. Fundamentally the equation is a brutal one: you have to spend\nmost of your waking hours doing stuff someone else wants, or starve.\nThere are a few places where the work is so interesting that this\nis concealed, because what other people want done happens to coincide\nwith what you want to work on. But you only have to imagine what\nwould happen if they diverged to see the underlying reality.It's not so much that adults lie to kids about this as never explain\nit. They never explain what the deal is with money. You know from\nan early age that you'll have some sort of job, because everyone\nasks what you're going to \"be\" when you grow up. What they\ndon't tell you is that as a kid you're sitting on the shoulders of\nsomeone else who's treading water, and that starting working means\nyou get thrown into the water on your own, and have to start treading\nwater yourself or sink. \"Being\" something is incidental; the\nimmediate problem is not to drown.The relationship between work and money tends to dawn on you only\ngradually. At least it did for me. One's first thought tends to\nbe simply \"This sucks. I'm in debt. Plus I have to get up on monday\nand go to work.\" Gradually you realize that these two things are\nas tightly connected as only a market can make them.So the most important advantage 24 year old founders have over 20\nyear old founders is that they know what they're trying to avoid.\nTo the average undergrad the idea of getting rich translates into\nbuying Ferraris, or being admired. To someone who has learned from\nexperience about the relationship between money and work, it\ntranslates to something way more important: it means you get to opt\nout of the brutal equation that governs the lives of 99.9% of people.\nGetting rich means you can stop treading water.Someone who gets this will work much harder at making a startup\nsucceed—with the proverbial energy of a drowning man, in fact.\nBut understanding the relationship between money and work also\nchanges the way you work. You don't get money just for working,\nbut for doing things other people want. Someone who's figured that\nout will automatically focus more on the user. And that cures the\nother half of the class-project syndrome. After you've been working\nfor a while, you yourself tend to measure what you've done the same\nway the market does.Of course, you don't have to spend years working to learn this\nstuff. If you're sufficiently perceptive you can grasp these things\nwhile you're still in school. Sam Altman did. He must have, because\nLoopt is no class project. And as his example suggests, this can\nbe valuable knowledge. At a minimum, if you get this stuff, you\nalready have most of what you gain from the \"work experience\"\nemployers consider so desirable. But of course if you really get\nit, you can use this information in a way that's more valuable to\nyou than that.NowSo suppose you think you might start a startup at some point, either\nwhen you graduate or a few years after. What should you do now?\nFor both jobs and grad school, there are ways to prepare while\nyou're in college. If you want to get a job when you graduate, you\nshould get summer jobs at places you'd like to work. If you want\nto go to grad school, it will help to work on research projects as\nan undergrad. What's the equivalent for startups? How do you keep\nyour options maximally open?One thing you can do while you're still in school is to learn how\nstartups work. Unfortunately that's not easy. Few if any colleges\nhave classes about startups. There may be business school classes\non entrepreneurship, as they call it over there, but these are\nlikely to be a waste of time. Business schools like to talk about\nstartups, but philosophically they're at the opposite end of the\nspectrum. Most books on startups also seem to be useless. I've\nlooked at a few and none get it right. Books in most fields are\nwritten by people who know the subject from experience, but for\nstartups there's a unique problem: by definition the founders of\nsuccessful startups don't need to write books to make money. As a\nresult most books on the subject end up being written by people who\ndon't understand it.So I'd be skeptical of classes and books. The way to learn about\nstartups is by watching them in action, preferably by working at\none. How do you do that as an undergrad? Probably by sneaking in\nthrough the back door. Just hang around a lot and gradually start\ndoing things for them. Most startups are (or should be) very\ncautious about hiring. Every hire increases the burn rate, and bad\nhires early on are hard to recover from. However, startups usually\nhave a fairly informal atmosphere, and there's always a lot that\nneeds to be done. If you just start doing stuff for them, many\nwill be too busy to shoo you away. You can thus gradually work\nyour way into their confidence, and maybe turn it into an official\njob later, or not, whichever you prefer. This won't work for all\nstartups, but it would work for most I've known.Number two, make the most of the great advantage of school: the\nwealth of co-founders. Look at the people around you and ask\nyourself which you'd like to work with. When you apply that test,\nyou may find you get surprising results. You may find you'd prefer\nthe quiet guy you've mostly ignored to someone who seems impressive\nbut has an attitude to match. I'm not suggesting you suck up to\npeople you don't really like because you think one day they'll be\nsuccessful. Exactly the opposite, in fact: you should only start\na startup with someone you like, because a startup will put your\nfriendship through a stress test. I'm just saying you should think\nabout who you really admire and hang out with them, instead of\nwhoever circumstances throw you together with.Another thing you can do is learn skills that will be useful to you\nin a startup. These may be different from the skills you'd learn\nto get a job. For example, thinking about getting a job will make\nyou want to learn programming languages you think employers want,\nlike Java and C++. Whereas if you start a startup, you get to pick\nthe language, so you have to think about which will actually let\nyou get the most done. If you use that test you might end up\nlearning Ruby or Python instead.\nBut the most important skill for a startup founder isn't a programming\ntechnique. It's a knack for understanding users and figuring out\nhow to give them what they want. I know I repeat this, but that's\nbecause it's so important. And it's a skill you can learn, though\nperhaps habit might be a better word. Get into the habit of thinking\nof software as having users. What do those users want? What would\nmake them say wow?This is particularly valuable for undergrads, because the concept\nof users is missing from most college programming classes. The way\nyou get taught programming in college would be like teaching writing\nas grammar, without mentioning that its purpose is to communicate\nsomething to an audience. Fortunately an audience for software is\nnow only an http request away. So in addition to the programming\nyou do for your classes, why not build some kind of website people\nwill find useful? At the very least it will teach you how to write\nsoftware with users. In the best case, it might not just be\npreparation for a startup, but the startup itself, like it was for\nYahoo and Google.Notes[1]\nEven the desire to protect one's children seems weaker, judging\nfrom things people have historically done to their kids\nrather than risk their community's disapproval. (I assume we still\ndo things that will be regarded in the future as barbaric, but\nhistorical abuses are easier for us to see.)[2]\nWorrying that Y Combinator makes founders move for 3 months\nalso suggests one underestimates how hard it is to start a startup.\nYou're going to have to put up with much greater inconveniences than\nthat.[3]\nMost employee agreements\nsay that any idea relating to the company's present or potential\nfuture business belongs to them. Often as not the second clause could\ninclude any possible startup, and anyone doing due diligence for an \ninvestor or acquirer will assume the worst.To be safe either (a) don't use code written while you\nwere still employed in your previous job, or (b) get your employer to\nrenounce, in writing, any claim to the code you write for your side \nproject. Many will consent to (b) rather than\nlose a prized employee. The downside is that you'll have to tell them\nexactly what your project does.[4]\nGeshke and Warnock only founded Adobe because Xerox ignored\nthem. If Xerox had used what they built, they would probably \nnever have left PARC.Thanks to Jessica Livingston and Robert Morris for reading\ndrafts of this, and to Jeff Arnold and the SIPB for inviting me to\nspeak.\n\nComment on this essay." }, { "path": "data/PaulGrahamEssays/mod.txt", "content": "December 2019There are two distinct ways to be politically moderate: on purpose\nand by accident. Intentional moderates are trimmers, deliberately\nchoosing a position mid-way between the extremes of right and left.\nAccidental moderates end up in the middle, on average, because they\nmake up their own minds about each question, and the far right and\nfar left are roughly equally wrong.You can distinguish intentional from accidental moderates by the\ndistribution of their opinions. If the far left opinion on some\nmatter is 0 and the far right opinion 100, an intentional moderate's\nopinion on every question will be near 50. Whereas an accidental\nmoderate's opinions will be scattered over a broad range, but will,\nlike those of the intentional moderate, average to about 50.Intentional moderates are similar to those on the far left and the\nfar right in that their opinions are, in a sense, not their own.\nThe defining quality of an ideologue, whether on the left or the\nright, is to acquire one's opinions in bulk. You don't get to pick\nand choose. Your opinions about taxation can be predicted from your\nopinions about sex. And although intentional moderates\nmight seem to be the opposite of ideologues, their beliefs (though\nin their case the word \"positions\" might be more accurate) are also\nacquired in bulk. If the median opinion shifts to the right or left,\nthe intentional moderate must shift with it. Otherwise they stop\nbeing moderate.Accidental moderates, on the other hand, not only choose their own\nanswers, but choose their own questions. They may not care at all\nabout questions that the left and right both think are terribly\nimportant. So you can only even measure the politics of an accidental\nmoderate from the intersection of the questions they care about and\nthose the left and right care about, and this can\nsometimes be vanishingly small.It is not merely a manipulative rhetorical trick to say \"if you're\nnot with us, you're against us,\" but often simply false.Moderates are sometimes derided as cowards, particularly by \nthe extreme left. But while it may be accurate to call intentional\nmoderates cowards, openly being an accidental moderate requires the\nmost courage of all, because you get attacked from both right and\nleft, and you don't have the comfort of being an orthodox member\nof a large group to sustain you.Nearly all the most impressive people I know are accidental moderates.\nIf I knew a lot of professional athletes, or people in the entertainment\nbusiness, that might be different. Being on the far left or far\nright doesn't affect how fast you run or how well you sing. But\nsomeone who works with ideas has to be independent-minded to do it\nwell.Or more precisely, you have to be independent-minded about the ideas\nyou work with. You could be mindlessly doctrinaire in your politics\nand still be a good mathematician. In the 20th century, a lot of\nvery smart people were Marxists — just no one who was smart about\nthe subjects Marxism involves. But if the ideas you use in your\nwork intersect with the politics of your time, you have two choices:\nbe an accidental moderate, or be mediocre.Notes[1] It's possible in theory for one side to be entirely right and\nthe other to be entirely wrong. Indeed, ideologues must always\nbelieve this is the case. But historically it rarely has been.[2] For some reason the far right tend to ignore moderates rather\nthan despise them as backsliders. I'm not sure why. Perhaps it\nmeans that the far right is less ideological than the far left. Or\nperhaps that they are more confident, or more resigned, or simply\nmore disorganized. I just don't know.[3] Having heretical opinions doesn't mean you have to express\nthem openly. It may be\neasier to have them if you don't.\nThanks to Austen Allred, Trevor Blackwell, Patrick Collison, Jessica Livingston,\nAmjad Masad, Ryan Petersen, and Harj Taggar for reading drafts of this." }, { "path": "data/PaulGrahamEssays/name.txt", "content": "August 2015If you have a US startup called X and you don't have x.com, you\nshould probably change your name.The reason is not just that people can't find you. For companies\nwith mobile apps, especially, having the right domain name is not\nas critical as it used to be for getting users. The problem with\nnot having the .com of your name is that it signals weakness. Unless\nyou're so big that your reputation precedes you, a marginal domain\nsuggests you're a marginal company. Whereas\n(as Stripe shows)\nhaving x.com signals strength even if it has no relation to what you\ndo.Even good founders can be in denial about this. Their denial derives\nfrom two very powerful forces: identity, and lack of imagination.X is what we are, founders think. There's no other name as good.\nBoth of which are false.You can fix the first by stepping back from the problem. Imagine\nyou'd called your company something else. If you had, surely you'd\nbe just as attached to that name as you are to your current one.\nThe idea of switching to your current name would seem repellent.\n[1]There's nothing intrinsically great about your current name. Nearly\nall your attachment to it comes from it being attached to you.\n[2]The way to neutralize the second source of denial, your inability\nto think of other potential names, is to acknowledge that you're\nbad at naming. Naming is a completely separate skill from those\nyou need to be a good founder. You can be a great startup founder\nbut hopeless at thinking of names for your company.Once you acknowledge that, you stop believing there is nothing else\nyou could be called. There are lots of other potential names that\nare as good or better; you just can't think of them.How do you find them? One answer is the default way to solve\nproblems you're bad at: find someone else who can think of names.\nBut with company names there is another possible\napproach. It turns out almost any word or word pair that is not\nan obviously bad name is a sufficiently good one, and the number\nof such domains is so large that you can find plenty that are cheap\nor even untaken. So make a list and try to buy some. That's what\nStripe \ndid. (Their search also turned up parse.com, which their\nfriends at Parse took.)The reason I know that naming companies is a distinct skill orthogonal\nto the others you need in a startup is that I happen to have it.\nBack when I was running YC and did more office hours with startups,\nI would often help them find new names. 80% of the time we could\nfind at least one good name in a 20 minute office hour slot.Now when I do office hours I have to focus on more important\nquestions, like what the company is doing. I tell them when they\nneed to change their name. But I know the power of the forces that\nhave them in their grip, so I know most won't listen. \n[3]There are of course examples of startups that have succeeded without\nhaving the .com of their name. There are startups that have succeeded despite any\nnumber of different mistakes. But this mistake is less excusable\nthan most. It's something that can be fixed in a couple days if\nyou have sufficient discipline to acknowledge the problem.100% of the top 20 YC companies by valuation have the .com of their\nname. 94% of the top 50 do. But only 66% of companies in the current\nbatch have the .com of their name. Which suggests there are lessons\nahead for most of the rest, one way or another.\nNotes[1]\nIncidentally, this thought experiment works for\nnationality and religion too.[2]\nThe liking you have for a name that has become part of your\nidentity manifests itself not directly, which would be easy to\ndiscount, but as a collection of specious beliefs about its intrinsic\nqualities. (This too is true of nationality and religion as well.)[3]\nSometimes founders know it's a problem that they don't have\nthe .com of their name, but delusion strikes a step later in the belief that they'll\nbe able to buy it despite having no evidence it's for sale. Don't\nbelieve a domain is for sale unless the owner has already told you\nan asking price.\nThanks to Sam Altman, Jessica Livingston, and Geoff Ralston\nfor reading drafts of this." }, { "path": "data/PaulGrahamEssays/nerds.txt", "content": "February 2003When we were in junior high school, my friend Rich and I made a map\nof the school lunch tables according to popularity. This was easy\nto do, because kids only ate lunch with others of about the same\npopularity. We graded them from A to E. A tables were full of\nfootball players and cheerleaders and so on. E tables contained the\nkids with mild cases of Down's Syndrome, what in the language of\nthe time we called \"retards.\"We sat at a D table, as low as you could get without looking\nphysically different. We were not being especially candid to grade\nourselves as D. It would have taken a deliberate lie to say otherwise.\nEveryone in the school knew exactly how popular everyone else was,\nincluding us.My stock gradually rose during high school. Puberty finally arrived;\nI became a decent soccer player; I started a scandalous underground\nnewspaper. So I've seen a good part of the popularity landscape.I know a lot of people who were nerds in school, and they all tell\nthe same story: there is a strong correlation between being smart\nand being a nerd, and an even stronger inverse correlation between\nbeing a nerd and being popular. Being smart seems to make you\nunpopular.Why? To someone in school now, that may seem an odd question to\nask. The mere fact is so overwhelming that it may seem strange to\nimagine that it could be any other way. But it could. Being smart\ndoesn't make you an outcast in elementary school. Nor does it harm\nyou in the real world. Nor, as far as I can tell, is the problem\nso bad in most other countries. But in a typical American secondary\nschool, being smart is likely to make your life difficult. Why?\nThe key to this mystery is to rephrase the question slightly. Why\ndon't smart kids make themselves popular? If they're so smart, why\ndon't they figure out how popularity works and beat the system,\njust as they do for standardized tests?One argument says that this would be impossible, that the smart\nkids are unpopular because the other kids envy them for being smart,\nand nothing they could do could make them popular. I wish. If the\nother kids in junior high school envied me, they did a great job\nof concealing it. And in any case, if being smart were really an\nenviable quality, the girls would have broken ranks. The guys that\nguys envy, girls like.In the schools I went to, being smart just didn't matter much. Kids\ndidn't admire it or despise it. All other things being equal, they\nwould have preferred to be on the smart side of average rather than the\ndumb side, but intelligence counted far less than, say, physical\nappearance, charisma, or athletic ability.So if intelligence in itself is not a factor in popularity, why are\nsmart kids so consistently unpopular? The answer, I think, is that\nthey don't really want to be popular.If someone had told me that at the time, I would have laughed at\nhim. Being unpopular in school makes kids miserable, some of them\nso miserable that they commit suicide. Telling me that I didn't\nwant to be popular would have seemed like telling someone dying of\nthirst in a desert that he didn't want a glass of water. Of course\nI wanted to be popular.But in fact I didn't, not enough. There was something else I wanted\nmore: to be smart. Not simply to do well in school, though that\ncounted for something, but to design beautiful rockets, or to write\nwell, or to understand how to program computers. In general, to\nmake great things.At the time I never tried to separate my wants and weigh them\nagainst one another. If I had, I would have seen that being smart\nwas more important. If someone had offered me the chance to be\nthe most popular kid in school, but only at the price of being of\naverage intelligence (humor me here), I wouldn't have taken it.Much as they suffer from their unpopularity, I don't think many\nnerds would. To them the thought of average intelligence is unbearable.\nBut most kids would take that deal. For half of them, it would be\na step up. Even for someone in the eightieth percentile (assuming,\nas everyone seemed to then, that intelligence is a scalar), who\nwouldn't drop thirty points in exchange for being loved and admired\nby everyone?And that, I think, is the root of the problem. Nerds serve two\nmasters. They want to be popular, certainly, but they want even\nmore to be smart. And popularity is not something you can do in\nyour spare time, not in the fiercely competitive environment of an\nAmerican secondary school.\nAlberti, arguably the archetype of the Renaissance Man, writes that\n\"no art, however minor, demands less than total dedication if you\nwant to excel in it.\"\nI wonder if anyone in the world works harder\nat anything than American school kids work at popularity. Navy SEALs\nand neurosurgery residents seem slackers by comparison. They\noccasionally take vacations; some even have hobbies. An American\nteenager may work at being popular every waking hour, 365 days a\nyear.I don't mean to suggest they do this consciously. Some of them truly\nare little Machiavellis, but what I really mean here is that teenagers\nare always on duty as conformists.For example, teenage kids pay a great deal of attention to clothes.\nThey don't consciously dress to be popular. They dress to look good.\nBut to who? To the other kids. Other kids' opinions become their\ndefinition of right, not just for clothes, but for almost everything\nthey do, right down to the way they walk. And so every effort they\nmake to do things \"right\" is also, consciously or not, an effort\nto be more popular.Nerds don't realize this. They don't realize that it takes work to\nbe popular. In general, people outside some very demanding field\ndon't realize the extent to which success depends on constant (though\noften unconscious) effort. For example, most people seem to consider\nthe ability to draw as some kind of innate quality, like being tall.\nIn fact, most people who \"can draw\" like drawing, and have spent\nmany hours doing it; that's why they're good at it. Likewise, popular\nisn't just something you are or you aren't, but something you make\nyourself.The main reason nerds are unpopular is that they have other things\nto think about. Their attention is drawn to books or the natural\nworld, not fashions and parties. They're like someone trying to\nplay soccer while balancing a glass of water on his head. Other\nplayers who can focus their whole attention on the game beat them\neffortlessly, and wonder why they seem so incapable.Even if nerds cared as much as other kids about popularity, being\npopular would be more work for them. The popular kids learned to\nbe popular, and to want to be popular, the same way the nerds learned\nto be smart, and to want to be smart: from their parents. While the\nnerds were being trained to get the right answers, the popular kids\nwere being trained to please.\nSo far I've been finessing the relationship between smart and nerd,\nusing them as if they were interchangeable. In fact it's only the\ncontext that makes them so. A nerd is someone who isn't socially\nadept enough. But \"enough\" depends on where you are. In a typical\nAmerican school, standards for coolness are so high (or at least,\nso specific) that you don't have to be especially awkward to look\nawkward by comparison.Few smart kids can spare the attention that popularity requires.\nUnless they also happen to be good-looking, natural athletes, or\nsiblings of popular kids, they'll tend to become nerds. And that's\nwhy smart people's lives are worst between, say, the ages of eleven\nand seventeen. Life at that age revolves far more around popularity\nthan before or after.Before that, kids' lives are dominated by their parents, not by\nother kids. Kids do care what their peers think in elementary school,\nbut this isn't their whole life, as it later becomes.Around the age of eleven, though, kids seem to start treating their\nfamily as a day job. They create a new world among themselves, and\nstanding in this world is what matters, not standing in their family.\nIndeed, being in trouble in their family can win them points in the\nworld they care about.The problem is, the world these kids create for themselves is at\nfirst a very crude one. If you leave a bunch of eleven-year-olds\nto their own devices, what you get is Lord of the Flies. Like\na lot of American kids, I read this book in school. Presumably it\nwas not a coincidence. Presumably someone wanted to point out to\nus that we were savages, and that we had made ourselves a cruel and\nstupid world. This was too subtle for me. While the book seemed\nentirely believable, I didn't get the additional message. I wish\nthey had just told us outright that we were savages and our world\nwas stupid.\nNerds would find their unpopularity more bearable if it merely\ncaused them to be ignored. Unfortunately, to be unpopular in school\nis to be actively persecuted.Why? Once again, anyone currently in school might think this a\nstrange question to ask. How could things be any other way? But\nthey could be. Adults don't normally persecute nerds. Why do teenage\nkids do it?Partly because teenagers are still half children, and many\nchildren are just intrinsically cruel. Some torture nerds for the\nsame reason they pull the legs off spiders. Before you develop a\nconscience, torture is amusing.Another reason kids persecute nerds is to make themselves feel\nbetter. When you tread water, you lift yourself up by pushing water\ndown. Likewise, in any social hierarchy, people unsure of their own\nposition will try to emphasize it by maltreating those they think\nrank below. I've read that this is why poor whites in the United\nStates are the group most hostile to blacks.But I think the main reason other kids persecute nerds is that it's\npart of the mechanism of popularity. Popularity is only partially\nabout individual attractiveness. It's much more about alliances.\nTo become more popular, you need to be constantly doing things that\nbring you close to other popular people, and nothing brings people\ncloser than a common enemy.Like a politician who wants to distract voters from bad times at\nhome, you can create an enemy if there isn't a real one. By singling\nout and persecuting a nerd, a group of kids from higher in the\nhierarchy create bonds between themselves. Attacking an outsider\nmakes them all insiders. This is why the worst cases of bullying\nhappen with groups. Ask any nerd: you get much worse treatment from\na group of kids than from any individual bully, however sadistic.If it's any consolation to the nerds, it's nothing personal. The\ngroup of kids who band together to pick on you are doing the same\nthing, and for the same reason, as a bunch of guys who get together\nto go hunting. They don't actually hate you. They just need something\nto chase.Because they're at the bottom of the scale, nerds are a safe target\nfor the entire school. If I remember correctly, the most popular\nkids don't persecute nerds; they don't need to stoop to such things.\nMost of the persecution comes from kids lower down, the nervous\nmiddle classes.The trouble is, there are a lot of them. The distribution of\npopularity is not a pyramid, but tapers at the bottom like a pear.\nThe least popular group is quite small. (I believe we were the only\nD table in our cafeteria map.) So there are more people who want\nto pick on nerds than there are nerds.As well as gaining points by distancing oneself from unpopular kids,\none loses points by being close to them. A woman I know says that\nin high school she liked nerds, but was afraid to be seen talking\nto them because the other girls would make fun of her. Unpopularity\nis a communicable disease; kids too nice to pick on nerds will still\nostracize them in self-defense.It's no wonder, then, that smart kids tend to be unhappy in middle\nschool and high school. Their other interests leave them little\nattention to spare for popularity, and since popularity resembles\na zero-sum game, this in turn makes them targets for the whole\nschool. And the strange thing is, this nightmare scenario happens\nwithout any conscious malice, merely because of the shape of the\nsituation.\nFor me the worst stretch was junior high, when kid culture was new\nand harsh, and the specialization that would later gradually separate\nthe smarter kids had barely begun. Nearly everyone I've talked to\nagrees: the nadir is somewhere between eleven and fourteen.In our school it was eighth grade, which was ages twelve and thirteen\nfor me. There was a brief sensation that year when one of our\nteachers overheard a group of girls waiting for the school bus, and\nwas so shocked that the next day she devoted the whole class to an\neloquent plea not to be so cruel to one another.It didn't have any noticeable effect. What struck me at the time\nwas that she was surprised. You mean she doesn't know the kind of\nthings they say to one another? You mean this isn't normal?It's important to realize that, no, the adults don't know what the\nkids are doing to one another. They know, in the abstract, that\nkids are monstrously cruel to one another, just as we know in the\nabstract that people get tortured in poorer countries. But, like\nus, they don't like to dwell on this depressing fact, and they don't\nsee evidence of specific abuses unless they go looking for it.Public school teachers are in much the same position as prison\nwardens. Wardens' main concern is to keep the prisoners on the\npremises. They also need to keep them fed, and as far as possible\nprevent them from killing one another. Beyond that, they want to\nhave as little to do with the prisoners as possible, so they leave\nthem to create whatever social organization they want. From what\nI've read, the society that the prisoners create is warped, savage,\nand pervasive, and it is no fun to be at the bottom of it.In outline, it was the same at the schools I went to. The most\nimportant thing was to stay on the premises. While there, the\nauthorities fed you, prevented overt violence, and made some effort\nto teach you something. But beyond that they didn't want to have\ntoo much to do with the kids. Like prison wardens, the teachers\nmostly left us to ourselves. And, like prisoners, the culture we\ncreated was barbaric.\nWhy is the real world more hospitable to nerds? It might seem that\nthe answer is simply that it's populated by adults, who are too\nmature to pick on one another. But I don't think this is true.\nAdults in prison certainly pick on one another. And so, apparently,\ndo society wives; in some parts of Manhattan, life for women sounds\nlike a continuation of high school, with all the same petty intrigues.I think the important thing about the real world is not that it's\npopulated by adults, but that it's very large, and the things you\ndo have real effects. That's what school, prison, and ladies-who-lunch\nall lack. The inhabitants of all those worlds are trapped in little\nbubbles where nothing they do can have more than a local effect.\nNaturally these societies degenerate into savagery. They have no\nfunction for their form to follow.When the things you do have real effects, it's no longer enough\njust to be pleasing. It starts to be important to get the right\nanswers, and that's where nerds show to advantage. Bill Gates will\nof course come to mind. Though notoriously lacking in social skills,\nhe gets the right answers, at least as measured in revenue.The other thing that's different about the real world is that it's\nmuch larger. In a large enough pool, even the smallest minorities\ncan achieve a critical mass if they clump together. Out in the real\nworld, nerds collect in certain places and form their own societies\nwhere intelligence is the most important thing. Sometimes the current\neven starts to flow in the other direction: sometimes, particularly\nin university math and science departments, nerds deliberately\nexaggerate their awkwardness in order to seem smarter. John Nash\nso admired Norbert Wiener that he adopted his habit of touching the\nwall as he walked down a corridor.\nAs a thirteen-year-old kid, I didn't have much more experience of\nthe world than what I saw immediately around me. The warped little\nworld we lived in was, I thought, the world. The world seemed cruel\nand boring, and I'm not sure which was worse.Because I didn't fit into this world, I thought that something must\nbe wrong with me. I didn't realize that the reason we nerds didn't\nfit in was that in some ways\nwe were a step ahead. We were already thinking about\nthe kind of things that matter in the real world, instead of spending\nall our time playing an exacting but mostly pointless game like the\nothers.We were a bit like an adult would be if he were thrust back into\nmiddle school. He wouldn't know the right clothes to wear, the right\nmusic to like, the right slang to use. He'd seem to the kids a\ncomplete alien. The thing is, he'd know enough not to care what\nthey thought. We had no such confidence.A lot of people seem to think it's good for smart kids to be thrown\ntogether with \"normal\" kids at this stage of their lives. Perhaps.\nBut in at least some cases the reason the nerds don't fit in really\nis that everyone else is crazy. I remember sitting in the audience\nat a \"pep rally\" at my high school, watching as the cheerleaders\nthrew an effigy of an opposing player into the audience to be torn\nto pieces. I felt like an explorer witnessing some bizarre tribal\nritual.\nIf I could go back and give my thirteen year old self some advice,\nthe main thing I'd tell him would be to stick his head up and look\naround. I didn't really grasp it at the time, but the whole world\nwe lived in was as fake as a Twinkie. Not just school, but the\nentire town. Why do people move to suburbia? To have kids! So no\nwonder it seemed boring and sterile. The whole place was a giant\nnursery, an artificial town created explicitly for the purpose of\nbreeding children.Where I grew up, it felt as if there was nowhere to go, and nothing\nto do. This was no accident. Suburbs are deliberately designed to\nexclude the outside world, because it contains things that could\nendanger children.And as for the schools, they were just holding pens within this\nfake world. Officially the purpose of schools is to teach kids. In\nfact their primary purpose is to keep kids locked up in one\nplace for a big chunk of the day so adults can get things done. And\nI have no problem with this: in a specialized industrial society,\nit would be a disaster to have kids running around loose.What bothers me is not that the kids are kept in prisons, but that\n(a) they aren't told about it, and (b) the prisons are run mostly\nby the inmates. Kids are sent off to spend six years memorizing\nmeaningless facts in a world ruled by a caste of giants who run\nafter an oblong brown ball, as if this were the most natural thing\nin the world. And if they balk at this surreal cocktail, they're\ncalled misfits.\nLife in this twisted world is stressful for the kids. And not just\nfor the nerds. Like any war, it's damaging even to the winners.Adults can't avoid seeing that teenage kids are tormented. So why\ndon't they do something about it? Because they blame it on puberty.\nThe reason kids are so unhappy, adults tell themselves, is that\nmonstrous new chemicals, hormones, are now coursing through their\nbloodstream and messing up everything. There's nothing wrong with\nthe system; it's just inevitable that kids will be miserable at\nthat age.This idea is so pervasive that even the kids believe it, which\nprobably doesn't help. Someone who thinks his feet naturally hurt\nis not going to stop to consider the possibility that he is wearing\nthe wrong size shoes.I'm suspicious of this theory that thirteen-year-old kids are\nintrinsically messed up. If it's physiological, it should be\nuniversal. Are Mongol nomads all nihilists at thirteen? I've read\na lot of history, and I have not seen a single reference\nto this supposedly universal fact before the twentieth century.\nTeenage apprentices in the Renaissance seem to have been cheerful\nand eager. They got in fights and played tricks on one another of\ncourse (Michelangelo had his nose broken by a bully), but they\nweren't crazy.As far as I can tell, the concept of the hormone-crazed teenager\nis coeval with suburbia. I don't think this is a coincidence. I\nthink teenagers are driven crazy by the life they're made to lead.\nTeenage apprentices in the Renaissance were working dogs. Teenagers\nnow are neurotic lapdogs. Their craziness is the craziness of the\nidle everywhere.\nWhen I was in school, suicide was a constant topic among the smarter\nkids. No one I knew did it, but several planned to, and\nsome may have tried. Mostly this was just a pose. Like other\nteenagers, we loved the dramatic, and suicide seemed very dramatic.\nBut partly it was because our lives were at times genuinely miserable.Bullying was only part of the problem. Another problem, and possibly\nan even worse one, was that we never had anything real to work on.\nHumans like to work; in most of the world, your work is your identity.\nAnd all the work we did was \npointless, or seemed so at the time.At best it was practice for real work we might do far in the future,\nso far that we didn't even know at the time what we were practicing\nfor. More often it was just an arbitrary series of hoops to jump\nthrough, words without content designed mainly for testability.\n(The three main causes of the Civil War were....\nTest: List the three main causes of the Civil War.)And there was no way to opt out. The adults had agreed among\nthemselves that this was to be the route to college. The only way\nto escape this empty life was to submit to it.\nTeenage kids used to have a more active role in society. In\npre-industrial times, they were all apprentices of one sort or\nanother, whether in shops or on farms or even on warships. They\nweren't left to create their own societies. They were junior members\nof adult societies.Teenagers seem to have respected adults more then, because\nthe adults were the visible experts in the skills they were trying\nto learn. Now most kids have little idea what their parents do in\ntheir distant offices, and see no connection (indeed, there is\nprecious little) between schoolwork and the work they'll do as\nadults.And if teenagers respected adults more, adults also had more use\nfor teenagers. After a couple years' training, an apprentice could\nbe a real help. Even the newest apprentice could be made to carry\nmessages or sweep the workshop.Now adults have no immediate use for teenagers. They would be in\nthe way in an office. So they drop them off at school on their way\nto work, much as they might drop the dog off at a kennel if they \nwere going away for the weekend.What happened? We're up against a hard one here. The cause of this\nproblem is the same as the cause of so many present ills: specialization.\nAs jobs become more specialized, we have to train longer for them.\nKids in pre-industrial times started working at about 14 at\nthe latest; kids on farms, where most people lived, began far \nearlier. Now kids who go to college don't start working full-time \ntill 21 or 22. With some degrees, like MDs and PhDs, you may not\nfinish your training till 30.Teenagers now are useless, except as cheap labor in industries like\nfast food, which evolved to exploit precisely this fact. In almost\nany other kind of work, they'd be a net loss. But they're also too \nyoung to be left unsupervised. Someone has to watch over them, and\nthe most efficient way to do this is to collect them together in\none place. Then a few adults can watch all of them.If you stop there, what you're describing is literally a prison,\nalbeit a part-time one. The problem is, many schools practically\ndo stop there. The stated purpose of schools is to educate the kids.\nBut there is no external pressure to do this well. And so most\nschools do such a bad job of teaching that the kids don't really\ntake it seriously-- not even the smart kids. Much of the time we\nwere all, students and teachers both, just going through the motions.In my high school French class we were supposed to read Hugo's Les\nMiserables. I don't think any of us knew French well enough to make\nour way through this enormous book. Like the rest of the class, I \njust skimmed the Cliff's Notes. When we were given a test on the\nbook, I noticed that the questions sounded odd. They were full of \nlong words that our teacher wouldn't have used. Where had these \nquestions come from? From the Cliff's Notes, it turned out. The \nteacher was using them too. We were all just pretending.There are certainly great public school teachers. The energy and \nimagination of my fourth grade teacher, Mr. Mihalko, made that \nyear something his students still talk about, thirty years later.\nBut teachers like him were individuals swimming\nupstream. They couldn't fix the system.\nIn almost any group of people you'll find hierarchy.\nWhen groups of adults form in the real world, it's generally for \nsome common purpose, and the leaders end up being those who are best\nat it. The problem with most schools is, they have no purpose. \nBut hierarchy there must be.\nAnd so the kids make one out of nothing.We have a phrase to describe what happens when rankings have to be\ncreated without any meaningful criteria. We say that the situation\ndegenerates into a popularity contest. And that's exactly what\nhappens in most American schools.\nInstead of depending on some real test, one's rank\ndepends mostly on one's ability to increase one's rank. It's\nlike the court of Louis XIV. There is no external opponent, so the\nkids become one another's opponents.When there is some real external test of skill, it isn't painful\nto be at the bottom of the hierarchy. A rookie on a football team\ndoesn't resent the skill of the veteran; he hopes to be like him\none day and is happy to have the chance to learn from him.\nThe veteran may in turn feel a sense of\nnoblesse oblige.\nAnd most importantly, their status depends on how well they\ndo against opponents, not on whether they can push the other down.Court hierarchies are another thing entirely. This type of society\ndebases anyone who enters it. There is neither admiration at the \nbottom, nor noblesse oblige at the top. It's kill or be killed.This is the sort of society that gets created\nin American\nsecondary schools. And it happens because these schools have no\nreal purpose beyond keeping the kids all in one place for a certain\nnumber of hours each day. What I didn't realize at the time, and\nin fact didn't realize till very recently, is that the twin horrors\nof school life, the cruelty and the boredom, both have the same \ncause.\nThe mediocrity of American public schools has worse consequences\nthan just making kids unhappy for six years. It breeds a rebelliousness\nthat actively drives kids away from the things they're supposed to\nbe learning.Like many nerds, probably, it was years after high school before I\ncould bring myself to read anything we'd been assigned then.\nAnd I lost more than books. I mistrusted words like \"character\" and \n\"integrity\" because they had been so debased by adults. As they\nwere used then, these words all seemed to mean the same thing:\nobedience. The kids who got praised for these qualities tended to \nbe at best dull-witted prize bulls, and at worst facile schmoozers.\nIf that was what character and integrity were, I wanted no part of\nthem.The word I most misunderstood was \"tact.\" As used by adults, it\nseemed to mean keeping your mouth shut.\nI assumed it was derived from the same root as\n\"tacit\" and \"taciturn,\" and that it literally meant being quiet. I\nvowed that I would never be tactful; they were never going to shut\nme up. In fact, it's derived from the same root as \"tactile,\" and\nwhat it means is to have a deft touch. Tactful is the opposite of\nclumsy. I don't think I learned this until college.Nerds aren't the only losers in the popularity rat race. Nerds are\nunpopular because they're distracted. There are other kids who\ndeliberately opt out because they're so disgusted with the whole \nprocess.Teenage kids, even rebels, don't like to be alone, so when kids opt\nout of the system, they tend to do it as a group. At the schools I\nwent to, the focus of rebellion was drug use, specifically marijuana.\nThe kids in this tribe wore black concert t-shirts and were called\n\"freaks.\"Freaks and nerds were allies, and there was a good deal of overlap\nbetween them. Freaks were on the whole smarter than other kids,\nthough never studying (or at least never appearing to) was an \nimportant tribal value. I was more in the nerd camp, but I was\nfriends with a lot of freaks.They used drugs, at least at first, for the social bonds they\ncreated. It was something to do together, and because the drugs \nwere illegal, it was a shared badge of rebellion.I'm not claiming that bad schools are the whole reason kids get\ninto trouble with drugs. After a while, drugs have their own momentum.\nNo doubt some of the freaks ultimately used drugs to escape from \nother problems-- trouble at home, for example. But, in my school\nat least, the reason most kids started using drugs was rebellion.\nFourteen-year-olds didn't start smoking pot because they'd heard\nit would help them forget their problems. They started because they\nwanted to join a different tribe.Misrule breeds rebellion; this is not a new idea. And yet the\nauthorities still for the most part act as if drugs were themselves\nthe cause of the problem.\nThe real problem is the emptiness of school life. We won't see\nsolutions till adults realize that. The adults who\nmay realize it first are the ones who were themselves nerds in \nschool. Do you want your kids to be as unhappy in eighth grade as\nyou were? I wouldn't. Well, then, is there anything we can do to\nfix things? Almost certainly. There is nothing inevitable about the\ncurrent system. It has come about mostly by default.Adults, though, are busy. Showing up for school plays is one thing.\nTaking on the educational bureaucracy is another. Perhaps a few\nwill have the energy to try to change things. I suspect the hardest \npart is realizing that you can.Nerds still in school should not hold their breath. Maybe one day\na heavily armed force of adults will show up in helicopters to \nrescue you, but they probably won't be coming this month. Any \nimmediate improvement in nerds' lives is probably going to have to\ncome from the nerds themselves.Merely understanding the situation they're in should make it less \npainful. Nerds aren't losers. They're just playing a different game,\nand a game much closer to the one played in the real world. Adults\nknow this. It's hard to find successful adults now who don't claim\nto have been nerds in high school.It's important for nerds to realize, too, that school is not life.\nSchool is a strange, artificial thing, half sterile and half feral.\nIt's all-encompassing, like life, but it isn't the real thing. It's\nonly temporary, and if you look, you can see beyond it even while\nyou're still in it.If life seems awful to kids, it's neither because hormones are \nturning you all into monsters (as your parents believe), nor because\nlife actually is awful (as you believe). It's because the adults,\nwho no longer have any economic use for you, have abandoned you to\nspend years cooped up together with nothing real to do. Any society\nof that type is awful to live in.\nYou don't have\nto look any further to explain why teenage kids are unhappy.I've said some harsh things in this essay, but really the thesis\nis an optimistic one-- that several problems we take for granted\nare in fact not insoluble after all. Teenage kids are not inherently\nunhappy monsters. That should be encouraging news to kids and adults\nboth.\nThanks to Sarah Harlin, Trevor Blackwell, Robert Morris,\nEric Raymond, and Jackie Weicker for reading drafts of this essay,\nand Maria Daniels for scanning photos." }, { "path": "data/PaulGrahamEssays/newideas.txt", "content": "May 2021There's one kind of opinion I'd be very afraid to express publicly.\nIf someone I knew to be both a domain expert and a reasonable person\nproposed an idea that sounded preposterous, I'd be very reluctant\nto say \"That will never work.\"Anyone who has studied the history of ideas, and especially the\nhistory of science, knows that's how big things start. Someone\nproposes an idea that sounds crazy, most people dismiss it, then\nit gradually takes over the world.Most implausible-sounding ideas are in fact bad and could be safely\ndismissed. But not when they're proposed by reasonable domain\nexperts. If the person proposing the idea is reasonable, then they\nknow how implausible it sounds. And yet they're proposing it anyway.\nThat suggests they know something you don't. And if they have deep\ndomain expertise, that's probably the source of it.\n[1]Such ideas are not merely unsafe to dismiss, but disproportionately\nlikely to be interesting. When the average person proposes an\nimplausible-sounding idea, its implausibility is evidence of their\nincompetence. But when a reasonable domain expert does it, the\nsituation is reversed. There's something like an efficient market\nhere: on average the ideas that seem craziest will, if correct,\nhave the biggest effect. So if you can eliminate the theory that\nthe person proposing an implausible-sounding idea is incompetent,\nits implausibility switches from evidence that it's boring to\nevidence that it's exciting.\n[2]Such ideas are not guaranteed to work. But they don't have to be.\nThey just have to be sufficiently good bets — to have sufficiently\nhigh expected value. And I think on average they do. I think if you\nbet on the entire set of implausible-sounding ideas proposed by\nreasonable domain experts, you'd end up net ahead.The reason is that everyone is too conservative. The word \"paradigm\"\nis overused, but this is a case where it's warranted. Everyone is\ntoo much in the grip of the current paradigm. Even the people who\nhave the new ideas undervalue them initially. Which means that\nbefore they reach the stage of proposing them publicly, they've\nalready subjected them to an excessively strict filter.\n[3]The wise response to such an idea is not to make statements, but\nto ask questions, because there's a real mystery here. Why has this\nsmart and reasonable person proposed an idea that seems so wrong?\nAre they mistaken, or are you? One of you has to be. If you're the\none who's mistaken, that would be good to know, because it means\nthere's a hole in your model of the world. But even if they're\nmistaken, it should be interesting to learn why. A trap that an\nexpert falls into is one you have to worry about too.This all seems pretty obvious. And yet there are clearly a lot of\npeople who don't share my fear of dismissing new ideas. Why do they\ndo it? Why risk looking like a jerk now and a fool later, instead\nof just reserving judgement?One reason they do it is envy. If you propose a radical new idea\nand it succeeds, your reputation (and perhaps also your wealth)\nwill increase proportionally. Some people would be envious if that\nhappened, and this potential envy propagates back into a conviction\nthat you must be wrong.Another reason people dismiss new ideas is that it's an easy way\nto seem sophisticated. When a new idea first emerges, it usually\nseems pretty feeble. It's a mere hatchling. Received wisdom is a\nfull-grown eagle by comparison. So it's easy to launch a devastating\nattack on a new idea, and anyone who does will seem clever to those\nwho don't understand this asymmetry.This phenomenon is exacerbated by the difference between how those\nworking on new ideas and those attacking them are rewarded. The\nrewards for working on new ideas are weighted by the value of the\noutcome. So it's worth working on something that only has a 10%\nchance of succeeding if it would make things more than 10x better.\nWhereas the rewards for attacking new ideas are roughly constant;\nsuch attacks seem roughly equally clever regardless of the target.People will also attack new ideas when they have a vested interest\nin the old ones. It's not surprising, for example, that some of\nDarwin's harshest critics were churchmen. People build whole careers\non some ideas. When someone claims they're false or obsolete, they\nfeel threatened.The lowest form of dismissal is mere factionalism: to automatically\ndismiss any idea associated with the opposing faction. The lowest\nform of all is to dismiss an idea because of who proposed it.But the main thing that leads reasonable people to dismiss new ideas\nis the same thing that holds people back from proposing them: the\nsheer pervasiveness of the current paradigm. It doesn't just affect\nthe way we think; it is the Lego blocks we build thoughts out of.\nPopping out of the current paradigm is something only a few people\ncan do. And even they usually have to suppress their intuitions at\nfirst, like a pilot flying through cloud who has to trust his\ninstruments over his sense of balance.\n[4]Paradigms don't just define our present thinking. They also vacuum\nup the trail of crumbs that led to them, making our standards for\nnew ideas impossibly high. The current paradigm seems so perfect\nto us, its offspring, that we imagine it must have been accepted\ncompletely as soon as it was discovered — that whatever the church thought\nof the heliocentric model, astronomers must have been convinced as\nsoon as Copernicus proposed it. Far, in fact, from it. Copernicus\npublished the heliocentric model in 1532, but it wasn't till the\nmid seventeenth century that the balance of scientific opinion\nshifted in its favor.\n[5]Few understand how feeble new ideas look when they first appear.\nSo if you want to have new ideas yourself, one of the most valuable\nthings you can do is to learn what they look like when they're born.\nRead about how new ideas happened, and try to get yourself into the\nheads of people at the time. How did things look to them, when the\nnew idea was only half-finished, and even the person who had it was\nonly half-convinced it was right?But you don't have to stop at history. You can observe big new ideas\nbeing born all around you right now. Just look for a reasonable\ndomain expert proposing something that sounds wrong.If you're nice, as well as wise, you won't merely resist attacking\nsuch people, but encourage them. Having new ideas is a lonely\nbusiness. Only those who've tried it know how lonely. These people\nneed your help. And if you help them, you'll probably learn something\nin the process.Notes[1]\nThis domain expertise could be in another field. Indeed,\nsuch crossovers tend to be particularly promising.[2]\nI'm not claiming this principle extends much beyond math,\nengineering, and the hard sciences. In politics, for example,\ncrazy-sounding ideas generally are as bad as they sound. Though\narguably this is not an exception, because the people who propose\nthem are not in fact domain experts; politicians are domain experts\nin political tactics, like how to get elected and how to get\nlegislation passed, but not in the world that policy acts upon.\nPerhaps no one could be.[3]\nThis sense of \"paradigm\" was defined by Thomas Kuhn in his\nStructure of Scientific Revolutions, but I also recommend his\nCopernican Revolution, where you can see him at work developing the\nidea.[4]\nThis is one reason people with a touch of Asperger's may have\nan advantage in discovering new ideas. They're always flying on\ninstruments.[5]\nHall, Rupert. From Galileo to Newton. Collins, 1963. This\nbook is particularly good at getting into contemporaries' heads.Thanks to Trevor Blackwell, Patrick Collison, Suhail Doshi, Daniel\nGackle, Jessica Livingston, and Robert Morris for reading drafts of this." }, { "path": "data/PaulGrahamEssays/newthings.txt", "content": "February 2008The fiery reaction to the release of Arc had\nan unexpected consequence: it made me realize I had a design\nphilosophy. The main complaint of the more articulate critics was\nthat Arc seemed so flimsy. After years of working on it, all I had\nto show for myself were a few thousand lines of macros? Why hadn't\nI worked on more substantial problems?As I was mulling over these remarks it struck me how familiar they\nseemed. This was exactly the kind of thing people said at first\nabout Viaweb, and Y Combinator, and most of my essays.When we launched Viaweb, it seemed laughable to VCs and e-commerce\n\"experts.\" We were just a couple guys in an apartment,\nwhich did not seem cool in 1995 the way it does now. And the thing\nwe'd built, as far as they could tell, wasn't even software.\nSoftware, to them, equalled big, honking Windows apps. Since Viaweb\nwas the first web-based app \nthey'd seen, it seemed to be nothing\nmore than a website. They were even more contemptuous when they\ndiscovered that Viaweb didn't process credit card transactions (we\ndidn't for the whole first year). Transaction processing seemed\nto them what e-commerce was all about. It sounded serious and\ndifficult.And yet, mysteriously, Viaweb ended up crushing all its competitors.The initial reaction to \nY Combinator was almost identical. It\nseemed laughably lightweight. Startup funding meant series A rounds:\nmillions of dollars given to a small number of startups founded by\npeople with established credentials after months of serious,\nbusinesslike meetings, on terms described in a document a foot\nthick. Y Combinator seemed inconsequential. It's too early to say\nyet whether Y Combinator will turn out like Viaweb, but judging\nfrom the number of imitations, a lot of people seem to think we're\non to something.I can't measure whether my essays are successful, except in page\nviews, but the reaction to them is at least different from when I\nstarted. At first the default reaction of the Slashdot trolls was\n(translated into articulate terms): \"Who is this guy and what\nauthority does he have to write about these topics? I haven't read\nthe essay, but there's no way anything so short and written in such\nan informal style could have anything useful to say about such and\nsuch topic, when people with degrees in the subject have already\nwritten many thick books about it.\" Now there's a new generation\nof trolls on a new generation of sites, but they have at least\nstarted to omit the initial \"Who is this guy?\"Now people are saying the same things about Arc that they said at\nfirst about Viaweb and Y Combinator and most of my essays. Why the\npattern? The answer, I realized, is that my m.o. for all four has\nbeen the same.Here it is: I like to find (a) simple solutions (b) to overlooked\nproblems (c) that actually need to be solved, and (d) deliver them\nas informally as possible, (e) starting with a very crude version\n1, then (f) iterating rapidly.When I first laid out these principles explicitly, I noticed something\nstriking: this is practically a recipe for generating a contemptuous\ninitial reaction. Though simple solutions are better, they don't\nseem as impressive as complex ones. Overlooked problems are by\ndefinition problems that most people think don't matter. Delivering\nsolutions in an informal way means that instead of judging something\nby the way it's presented, people have to actually understand it,\nwhich is more work. And starting with a crude version 1 means your\ninitial effort is always small and incomplete.I'd noticed, of course, that people never seemed to grasp new ideas\nat first. I thought it was just because most people were stupid.\nNow I see there's more to it than that. Like a\ncontrarian investment fund, someone following this strategy will\nalmost always be doing things that seem wrong to the average person.As with contrarian investment strategies, that's exactly the point.\nThis technique is successful (in the long term) because it gives you\nall the advantages other people forgo by trying to seem legit. If\nyou work on overlooked problems, you're more likely to discover new\nthings, because you have less competition. If you deliver solutions\ninformally, you (a) save all the effort you would have had to expend\nto make them look impressive, and (b) avoid the danger of fooling\nyourself as well as your audience. And if you release a crude\nversion 1 then iterate, your solution can benefit from the imagination\nof nature, which, as Feynman pointed out, is more powerful than\nyour own.In the case of Viaweb, the simple solution was to make the software\nrun on the server. The overlooked problem was to generate web sites\nautomatically; in 1995, online stores were all made by hand by human\ndesigners, but we knew this wouldn't scale. The part that actually\nmattered was graphic design, not transaction processing.\nThe informal delivery mechanism was me, showing up in jeans and a\nt-shirt at some retailer's office. And the crude version 1 was,\nif I remember correctly, less than 10,000 lines of code when we\nlaunched.The power of this technique extends beyond startups and programming\nlanguages and essays. It probably extends to any kind of creative\nwork. Certainly it can be used in painting: this is exactly \nwhat Cezanne and Klee did.At Y Combinator we bet money on it, in the sense that we encourage\nthe startups we fund to work this way. There are always new ideas\nright under your nose. So look for simple things that other people\nhave overlooked—things people will later claim were \n\"obvious\"—especially when they've been led astray by obsolete \nconventions,\nor by trying to do things that are superficially impressive. Figure\nout what the real problem is, and make sure you solve that. Don't\nworry about trying to look corporate; the product is what wins in\nthe long term. And launch as soon as you can, so you start learning\nfrom users what you should have been making.Reddit is a classic example of \nthis approach. When Reddit first\nlaunched, it seemed like there was nothing to it. To the graphically\nunsophisticated its deliberately minimal design seemed like no\ndesign at all. But Reddit solved the real problem, which was to\ntell people what was new and otherwise stay out of the way. As a\nresult it became massively successful. Now that conventional ideas\nhave caught up with it, it seems obvious. People look at Reddit\nand think the founders were lucky. Like all such things, it was\nharder than it looked. The Reddits pushed so hard against the\ncurrent that they reversed it; now it looks like they're merely\nfloating downstream.So when you look at something like Reddit and think \"I wish I could\nthink of an idea like that,\" remember: ideas like that are all\naround you. But you ignore them because they look wrong." }, { "path": "data/PaulGrahamEssays/nft.txt", "content": "May 2021Noora Health, a nonprofit I've \nsupported for years, just launched\na new NFT. It has a dramatic name, Save Thousands of Lives,\nbecause that's what the proceeds will do.Noora has been saving lives for 7 years. They run programs in\nhospitals in South Asia to teach new mothers how to take care of\ntheir babies once they get home. They're in 165 hospitals now. And\nbecause they know the numbers before and after they start at a new\nhospital, they can measure the impact they have. It is massive.\nFor every 1000 live births, they save 9 babies.This number comes from a study\nof 133,733 families at 28 different\nhospitals that Noora conducted in collaboration with the Better\nBirth team at Ariadne Labs, a joint center for health systems\ninnovation at Brigham and Women’s Hospital and Harvard T.H. Chan\nSchool of Public Health.Noora is so effective that even if you measure their costs in the\nmost conservative way, by dividing their entire budget by the number\nof lives saved, the cost of saving a life is the lowest I've seen.\n$1,235.For this NFT, they're going to issue a public report tracking how\nthis specific tranche of money is spent, and estimating the number\nof lives saved as a result.NFTs are a new territory, and this way of using them is especially\nnew, but I'm excited about its potential. And I'm excited to see\nwhat happens with this particular auction, because unlike an NFT\nrepresenting something that has already happened,\nthis NFT gets better as the price gets higher.The reserve price was about $2.5 million, because that's what it\ntakes for the name to be accurate: that's what it costs to save\n2000 lives. But the higher the price of this NFT goes, the more\nlives will be saved. What a sentence to be able to write." }, { "path": "data/PaulGrahamEssays/noob.txt", "content": "January 2020When I was young, I thought old people had everything figured out.\nNow that I'm old, I know this isn't true.I constantly feel like a noob. It seems like I'm always talking to\nsome startup working in a new field I know nothing about, or reading\na book about a topic I don't understand well enough, or visiting some new\ncountry where I don't know how things work.It's not pleasant to feel like a noob. And the word \"noob\" is\ncertainly not a compliment. And yet today I realized something\nencouraging about being a noob: the more of a noob you are locally,\nthe less of a noob you are globally.For example, if you stay in your home country, you'll feel less\nof a noob than if you move to Farawavia, where everything works\ndifferently. And yet you'll know more if you move.\nSo the feeling of being a noob is inversely correlated with actual\nignorance.But if the feeling of being a noob is good for us, why do we dislike\nit? What evolutionary purpose could such an aversion serve?I think the answer is that there are two sources of feeling like a\nnoob: being stupid, and doing something novel. Our dislike of feeling\nlike a noob is our brain telling us \"Come on, come on, figure this\nout.\" Which was the right thing to be thinking for most of human\nhistory. The life of hunter-gatherers was complex, but it didn't\nchange as much as life does now. They didn't suddenly have to figure\nout what to do about cryptocurrency. So it made sense to be biased\ntoward competence at existing problems over the discovery of new\nones. It made sense for humans to dislike the feeling of being a\nnoob, just as, in a world where food was scarce, it made sense for\nthem to dislike the feeling of being hungry.Now that too much food is more of a problem than too little, our\ndislike of feeling hungry leads us astray. And I think our dislike\nof feeling like a noob does too.Though it feels unpleasant, and people will sometimes ridicule you\nfor it, the more you feel like a noob, the better." }, { "path": "data/PaulGrahamEssays/noop.txt", "content": "\nThere is a kind of mania for object-oriented programming at the moment, but\n\nsome of the smartest programmers I know are some of the least excited about it.My own feeling is that object-oriented\nprogramming is a useful technique in some\ncases, but it isn't something that has to pervade every program you\nwrite. You should be able to define new types,\nbut you shouldn't have to express every program as the\ndefinition of new types.I think there are five reasons people like object-oriented \nprogramming, and three and a half of them are bad:\n Object-oriented programming is exciting \nif you have a statically-typed language without \nlexical closures or macros. To some degree, it offers a way around these\nlimitations. (See Greenspun's Tenth Rule.) Object-oriented programming is popular in big companies,\nbecause it suits the way they write software. At big companies,\nsoftware tends to be written by large (and frequently changing) \nteams of\nmediocre programmers. Object-oriented programming imposes a\ndiscipline on these programmers that prevents any one of them\nfrom doing too much damage. The price is that the resulting\ncode is bloated with protocols and full of duplication. \nThis is not too high a price for big companies, because their\nsoftware is probably going to be bloated and full of \nduplication anyway. Object-oriented\nprogramming generates a lot of what looks like work.\nBack in the days of fanfold, there was a type of programmer who\nwould only put five or ten lines of code on a page, preceded\nby twenty lines of elaborately formatted comments. \nObject-oriented programming is like crack for these people: it lets\nyou incorporate all this scaffolding right into your source\ncode. Something that a Lisp hacker might handle by pushing\na symbol onto a list becomes a whole file of classes and\nmethods. So it is a good tool if you want to convince yourself,\nor someone else, that you are doing a lot of work. If a language is itself an object-oriented program, it can\nbe extended by users. Well, maybe. Or maybe you can do\neven better by offering the sub-concepts\nof object-oriented programming a la carte. Overloading, \nfor example, is not intrinsically tied to classes. We'll see. Object-oriented abstractions map neatly onto the domains\nof certain specific kinds of programs, like simulations and CAD\nsystems. \n\n\nI personally have never needed object-oriented abstractions.\nCommon Lisp has an enormously powerful object system and I've\nnever used it once. I've done a lot of things (e.g. making \nhash tables full of closures) that would have required \nobject-oriented techniques to do in wimpier languages, but\nI have never had to use CLOS.Maybe I'm just stupid, or have worked on some limited subset\nof applications. There is a danger in designing a language\nbased on one's own experience of programming. But it seems\nmore dangerous to put stuff in that you've never needed \nbecause it's thought to be a good idea." }, { "path": "data/PaulGrahamEssays/notnot.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nMarch 2007(This essay is derived from talks at the 2007 \nStartup School and the Berkeley CSUA.)We've now been doing Y Combinator long enough to have some data\nabout success rates. Our first batch, in the summer of 2005, had\neight startups in it. Of those eight, it now looks as if at least\nfour succeeded. Three have been acquired: \nReddit was a merger of\ntwo, Reddit and Infogami, and a third was acquired that we can't\ntalk about yet. Another from that batch was \nLoopt, which is doing\nso well they could probably be acquired in about ten minutes if\nthey wanted to.So about half the founders from that first summer, less than two\nyears ago, are now rich, at least by their standards. (One thing\nyou learn when you get rich is that there are many degrees of it.)I'm not ready to predict our success rate will stay as high as 50%.\nThat first batch could have been an anomaly. But we should be able\nto do better than the oft-quoted (and probably made\nup) standard figure of 10%. I'd feel safe aiming at 25%.Even the founders who fail don't seem to have such a bad time. Of\nthose first eight startups, three are now probably dead. In two\ncases the founders just went on to do other things at the end of\nthe summer. I don't think they were traumatized by the experience.\nThe closest to a traumatic failure was Kiko, whose founders kept\nworking on their startup for a whole year before being squashed by\nGoogle Calendar. But they ended up happy. They sold their software\non eBay for a quarter of a million dollars. After they paid back\ntheir angel investors, they had about a year's salary each. \n[1]\nThen they immediately went on to start a new and much more exciting\nstartup, Justin.TV.So here is an even more striking statistic: 0% of that first batch\nhad a terrible experience. They had ups and downs, like every\nstartup, but I don't think any would have traded it for a job in a\ncubicle. And that statistic is probably not an anomaly. Whatever\nour long-term success rate ends up being, I think the rate of people\nwho wish they'd gotten a regular job will stay close to 0%.The big mystery to me is: why don't more people start startups? If\nnearly everyone who does it prefers it to a regular job, and a\nsignificant percentage get rich, why doesn't everyone want to do\nthis? A lot of people think we get thousands of applications for\neach funding cycle. In fact we usually only get several hundred.\nWhy don't more people apply? And while it must seem to anyone\nwatching this world that startups are popping up like crazy, the\nnumber is small compared to the number of people with the necessary\nskills. The great majority of programmers still go straight from\ncollege to cubicle, and stay there.It seems like people are not acting in their own interest. What's\ngoing on? Well, I can answer that. Because of Y Combinator's\nposition at the very start of the venture funding process, we're\nprobably the world's leading experts on the psychology of people\nwho aren't sure if they want to start a company.There's nothing wrong with being unsure. If you're a hacker thinking\nabout starting a startup and hesitating before taking the leap,\nyou're part of a grand tradition. Larry and Sergey seem to have\nfelt the same before they started Google, and so did Jerry and Filo\nbefore they started Yahoo. In fact, I'd guess the most successful\nstartups are the ones started by uncertain hackers rather than\ngung-ho business guys.We have some evidence to support this. Several of the most successful\nstartups we've funded told us later that they only decided to apply\nat the last moment. Some decided only hours before the deadline.The way to deal with uncertainty is to analyze it into components.\nMost people who are reluctant to do something have about eight\ndifferent reasons mixed together in their heads, and don't know\nthemselves which are biggest. Some will be justified and some\nbogus, but unless you know the relative proportion of each, you\ndon't know whether your overall uncertainty is mostly justified or\nmostly bogus.So I'm going to list all the components of people's reluctance to\nstart startups, and explain which are real. Then would-be founders\ncan use this as a checklist to examine their own feelings.I admit my goal is to increase your self-confidence. But there are\ntwo things different here from the usual confidence-building exercise.\nOne is that I'm motivated to be honest. Most people in the\nconfidence-building business have already achieved their goal when\nyou buy the book or pay to attend the seminar where they tell you\nhow great you are. Whereas if I encourage people to start startups\nwho shouldn't, I make my own life worse. If I encourage too many\npeople to apply to Y Combinator, it just means more work for me,\nbecause I have to read all the applications.The other thing that's going to be different is my approach. Instead\nof being positive, I'm going to be negative. Instead of telling\nyou \"come on, you can do it\" I'm going to consider all the reasons\nyou aren't doing it, and show why most (but not all) should be\nignored. We'll start with the one everyone's born with.1. Too youngA lot of people think they're too young to start a startup. Many\nare right. The median age worldwide is about 27, so probably a\nthird of the population can truthfully say they're too young.What's too young? One of our goals with Y Combinator was to discover\nthe lower bound on the age of startup founders. It always seemed\nto us that investors were too conservative here—that they wanted\nto fund professors, when really they should be funding grad students\nor even undergrads.The main thing we've discovered from pushing the edge of this\nenvelope is not where the edge is, but how fuzzy it is. The outer\nlimit may be as low as 16. We don't look beyond 18 because people\nyounger than that can't legally enter into contracts. But the most\nsuccessful founder we've funded so far, Sam Altman, was 19 at the\ntime.Sam Altman, however, is an outlying data point. When he was 19,\nhe seemed like he had a 40 year old inside him. There are other\n19 year olds who are 12 inside.There's a reason we have a distinct word \"adult\" for people over a\ncertain age. There is a threshold you cross. It's conventionally\nfixed at 21, but different people cross it at greatly varying ages.\nYou're old enough to start a startup if you've crossed this threshold,\nwhatever your age.How do you tell? There are a couple tests adults use. I realized\nthese tests existed after meeting Sam Altman, actually. I noticed\nthat I felt like I was talking to someone much older. Afterward I\nwondered, what am I even measuring? What made him seem older?One test adults use is whether you still have the kid flake reflex.\nWhen you're a little kid and you're asked to do something hard, you\ncan cry and say \"I can't do it\" and the adults will probably let\nyou off. As a kid there's a magic button you can press by saying\n\"I'm just a kid\" that will get you out of most difficult situations.\nWhereas adults, by definition, are not allowed to flake. They still\ndo, of course, but when they do they're ruthlessly pruned.The other way to tell an adult is by how they react to a challenge.\nSomeone who's not yet an adult will tend to respond to a challenge\nfrom an adult in a way that acknowledges their dominance. If an\nadult says \"that's a stupid idea,\" a kid will either crawl away\nwith his tail between his legs, or rebel. But rebelling presumes\ninferiority as much as submission. The adult response to\n\"that's a stupid idea,\" is simply to look the other person in the\neye and say \"Really? Why do you think so?\"There are a lot of adults who still react childishly to challenges,\nof course. What you don't often find are kids who react to challenges\nlike adults. When you do, you've found an adult, whatever their\nage.2. Too inexperiencedI once wrote that startup founders should be at least 23, and that\npeople should work for another company for a few years before\nstarting their own. I no longer believe that, and what changed my\nmind is the example of the startups we've funded.I still think 23 is a better age than 21. But the best way to get\nexperience if you're 21 is to start a startup. So, paradoxically,\nif you're too inexperienced to start a startup, what you should do\nis start one. That's a way more efficient cure for inexperience\nthan a normal job. In fact, getting a normal job may actually make\nyou less able to start a startup, by turning you into a tame animal\nwho thinks he needs an office to work in and a product manager to\ntell him what software to write.What really convinced me of this was the Kikos. They started a\nstartup right out of college. Their inexperience caused them to\nmake a lot of mistakes. But by the time we funded their second\nstartup, a year later, they had become extremely formidable. They\nwere certainly not tame animals. And there is no way they'd have\ngrown so much if they'd spent that year working at Microsoft, or\neven Google. They'd still have been diffident junior programmers.So now I'd advise people to go ahead and start startups right out\nof college. There's no better time to take risks than when you're\nyoung. Sure, you'll probably fail. But even failure will get you\nto the ultimate goal faster than getting a job.It worries me a bit to be saying this, because in effect we're\nadvising people to educate themselves by failing at our expense,\nbut it's the truth.3. Not determined enoughYou need a lot of determination to succeed as a startup founder.\nIt's probably the single best predictor of success.Some people may not be determined enough to make it. It's\nhard for me to say for sure, because I'm so determined that I can't\nimagine what's going on in the heads of people who aren't. But I\nknow they exist.Most hackers probably underestimate their determination. I've seen\na lot become visibly more determined as they get used to running a \nstartup. I can think of\nseveral we've funded who would have been delighted at first to be\nbought for $2 million, but are now set on world domination.How can you tell if you're determined enough, when Larry and Sergey\nthemselves were unsure at first about starting a company? I'm\nguessing here, but I'd say the test is whether you're sufficiently\ndriven to work on your own projects. Though they may have been\nunsure whether they wanted to start a company, it doesn't seem as\nif Larry and Sergey were meek little research assistants, obediently\ndoing their advisors' bidding. They started projects of their own.\n4. Not smart enoughYou may need to be moderately smart to succeed as a startup founder.\nBut if you're worried about this, you're probably mistaken. If\nyou're smart enough to worry that you might not be smart enough to\nstart a startup, you probably are.And in any case, starting a startup just doesn't require that much\nintelligence. Some startups do. You have to be good at math to\nwrite Mathematica. But most companies do more mundane stuff where\nthe decisive factor is effort, not brains. Silicon Valley can warp\nyour perspective on this, because there's a cult of smartness here.\nPeople who aren't smart at least try to act that way. But if you\nthink it takes a lot of intelligence to get rich, try spending a\ncouple days in some of the fancier bits of New York or LA.If you don't think you're smart enough to start a startup doing\nsomething technically difficult, just write enterprise software.\nEnterprise software companies aren't technology companies, they're\nsales companies, and sales depends mostly on effort.5. Know nothing about businessThis is another variable whose coefficient should be zero. You\ndon't need to know anything about business to start a startup. The\ninitial focus should be the product. All you need to know in this\nphase is how to build things people want. If you succeed, you'll\nhave to think about how to make money from it. But this is so easy\nyou can pick it up on the fly.I get a fair amount of flak for telling founders just to make\nsomething great and not worry too much about making money. And yet\nall the empirical evidence points that way: pretty much 100% of\nstartups that make something popular manage to make money from it.\nAnd acquirers tell me privately that revenue is not what they buy\nstartups for, but their strategic value. Which means, because they\nmade something people want. Acquirers know the rule holds for them\ntoo: if users love you, you can always make money from that somehow,\nand if they don't, the cleverest business model in the world won't\nsave you.So why do so many people argue with me? I think one reason is that\nthey hate the idea that a bunch of twenty year olds could get rich\nfrom building something cool that doesn't make any money. They\njust don't want that to be possible. But how possible it is doesn't\ndepend on how much they want it to be.For a while it annoyed me to hear myself described as some kind of\nirresponsible pied piper, leading impressionable young hackers down\nthe road to ruin. But now I realize this kind of controversy is a\nsign of a good idea.The most valuable truths are the ones most people don't believe.\nThey're like undervalued stocks. If you start with them, you'll\nhave the whole field to yourself. So when you find an idea you\nknow is good but most people disagree with, you should not\nmerely ignore their objections, but push aggressively in that\ndirection. In this case, that means you should seek out ideas that\nwould be popular but seem hard to make money from.We'll bet a seed round you can't make something popular that we\ncan't figure out how to make money from.6. No cofounderNot having a cofounder is a real problem. A startup is too much\nfor one person to bear. And though we differ from other investors\non a lot of questions, we all agree on this. All investors, without\nexception, are more likely to fund you with a cofounder than without.We've funded two single founders, but in both cases we suggested\ntheir first priority should be to find a cofounder. Both did. But\nwe'd have preferred them to have cofounders before they applied.\nIt's not super hard to get a cofounder for a project that's just\nbeen funded, and we'd rather have cofounders committed enough to\nsign up for something super hard.If you don't have a cofounder, what should you do? Get one. It's\nmore important than anything else. If there's no one where you\nlive who wants to start a startup with you, move where there are\npeople who do. If no one wants to work with you on your current\nidea, switch to an idea people want to work on.If you're still in school, you're surrounded by potential cofounders.\nA few years out it gets harder to find them. Not only do you have\na smaller pool to draw from, but most already have jobs, and perhaps\neven families to support. So if you had friends in college you\nused to scheme about startups with, stay in touch with them as well\nas you can. That may help keep the dream alive.It's possible you could meet a cofounder through something like a\nuser's group or a conference. But I wouldn't be too optimistic.\nYou need to work with someone to know whether you want them as a\ncofounder. \n[2]The real lesson to draw from this is not how to find a cofounder,\nbut that you should start startups when you're young and there are\nlots of them around.7. No ideaIn a sense, it's not a problem if you don't have a good idea, because\nmost startups change their idea anyway. In the average Y Combinator\nstartup, I'd guess 70% of the idea is new at the end of the\nfirst three months. Sometimes it's 100%.In fact, we're so sure the founders are more important than the\ninitial idea that we're going to try something new this funding\ncycle. We're going to let people apply with no idea at all. If you\nwant, you can answer the question on the application form that asks\nwhat you're going to do with \"We have no idea.\" If you seem really\ngood we'll accept you anyway. We're confident we can sit down with\nyou and cook up some promising project.Really this just codifies what we do already. We put little weight\non the idea. We ask mainly out of politeness. The kind of question\non the application form that we really care about is the one where\nwe ask what cool things you've made. If what you've made is version\none of a promising startup, so much the better, but the main thing\nwe care about is whether you're good at making things. Being lead\ndeveloper of a popular open source project counts almost as much.That solves the problem if you get funded by Y Combinator. What\nabout in the general case? Because in another sense, it is a problem\nif you don't have an idea. If you start a startup with no idea,\nwhat do you do next?So here's the brief recipe for getting startup ideas. Find something\nthat's missing in your own life, and supply that need—no matter\nhow specific to you it seems. Steve Wozniak built himself a computer;\nwho knew so many other people would want them? A need that's narrow\nbut genuine is a better starting point than one that's broad but\nhypothetical. So even if the problem is simply that you don't have\na date on Saturday night, if you can think of a way to fix that by\nwriting software, you're onto something, because a lot of other\npeople have the same problem.8. No room for more startupsA lot of people look at the ever-increasing number of startups and\nthink \"this can't continue.\" Implicit in their thinking is a\nfallacy: that there is some limit on the number of startups there\ncould be. But this is false. No one claims there's any limit on\nthe number of people who can work for salary at 1000-person companies.\nWhy should there be any limit on the number who can work for equity\nat 5-person companies? \n[3]Nearly everyone who works is satisfying some kind of need. Breaking\nup companies into smaller units doesn't make those needs go away.\nExisting needs would probably get satisfied more efficiently by a\nnetwork of startups than by a few giant, hierarchical organizations,\nbut I don't think that would mean less opportunity, because satisfying\ncurrent needs would lead to more. Certainly this tends to be the\ncase in individuals. Nor is there anything wrong with that. We\ntake for granted things that medieval kings would have considered\neffeminate luxuries, like whole buildings heated to spring temperatures\nyear round. And if things go well, our descendants will take for\ngranted things we would consider shockingly luxurious. There is\nno absolute standard for material wealth. Health care is a component\nof it, and that alone is a black hole. For the foreseeable future,\npeople will want ever more material wealth, so there is no limit\nto the amount of work available for companies, and for startups in\nparticular.Usually the limited-room fallacy is not expressed directly. Usually\nit's implicit in statements like \"there are only so many startups\nGoogle, Microsoft, and Yahoo can buy.\" Maybe, though the list of\nacquirers is a lot longer than that. And whatever you think of\nother acquirers, Google is not stupid. The reason big companies\nbuy startups is that they've created something valuable. And why\nshould there be any limit to the number of valuable startups companies\ncan acquire, any more than there is a limit to the amount of wealth\nindividual people want? Maybe there would be practical limits on\nthe number of startups any one acquirer could assimilate, but if\nthere is value to be had, in the form of upside that founders are\nwilling to forgo in return for an immediate payment, acquirers will\nevolve to consume it. Markets are pretty smart that way.9. Family to supportThis one is real. I wouldn't advise anyone with a family to start\na startup. I'm not saying it's a bad idea, just that I don't want\nto take responsibility for advising it. I'm willing to take\nresponsibility for telling 22 year olds to start startups. So what\nif they fail? They'll learn a lot, and that job at Microsoft will\nstill be waiting for them if they need it. But I'm not prepared\nto cross moms.What you can do, if you have a family and want to start a startup,\nis start a consulting business you can then gradually turn into a\nproduct business. Empirically the chances of pulling that off seem\nvery small. You're never going to produce Google this way. But at\nleast you'll never be without an income.Another way to decrease the risk is to join an existing startup\ninstead of starting your own. Being one of the first employees of\na startup is a lot like being a founder, in both the good ways and\nthe bad. You'll be roughly 1/n^2 founder, where n is your employee\nnumber.As with the question of cofounders, the real lesson here is to start\nstartups when you're young.10. Independently wealthyThis is my excuse for not starting a startup. Startups are stressful.\nWhy do it if you don't need the money? For every \"serial entrepreneur,\"\nthere are probably twenty sane ones who think \"Start another\ncompany? Are you crazy?\"I've come close to starting new startups a couple times, but I\nalways pull back because I don't want four years of my life to be\nconsumed by random schleps. I know this business well enough to\nknow you can't do it half-heartedly. What makes a good startup\nfounder so dangerous is his willingness to endure infinite schleps.There is a bit of a problem with retirement, though. Like a lot\nof people, I like to work. And one of the many weird little problems\nyou discover when you get rich is that a lot of the interesting\npeople you'd like to work with are not rich. They need to work at\nsomething that pays the bills. Which means if you want to have\nthem as colleagues, you have to work at something that pays the\nbills too, even though you don't need to. I think this is what\ndrives a lot of serial entrepreneurs, actually.That's why I love working on Y Combinator so much. It's an excuse\nto work on something interesting with people I like.11. Not ready for commitmentThis was my reason for not starting a startup for most of my twenties.\nLike a lot of people that age, I valued freedom most of all. I was\nreluctant to do anything that required a commitment of more than a\nfew months. Nor would I have wanted to do anything that completely\ntook over my life the way a startup does. And that's fine. If you\nwant to spend your time travelling around, or playing in a band,\nor whatever, that's a perfectly legitimate reason not to start a\ncompany.If you start a startup that succeeds, it's going to consume at least\nthree or four years. (If it fails, you'll be done a lot quicker.)\nSo you shouldn't do it if you're not ready for commitments on that\nscale. Be aware, though, that if you get a regular job, you'll\nprobably end up working there for as long as a startup would take,\nand you'll find you have much less spare time than you might expect.\nSo if you're ready to clip on that ID badge and go to that orientation\nsession, you may also be ready to start that startup.12. Need for structureI'm told there are people who need structure in their lives. This\nseems to be a nice way of saying they need someone to tell them\nwhat to do. I believe such people exist. There's plenty of empirical\nevidence: armies, religious cults, and so on. They may even be the\nmajority.If you're one of these people, you probably shouldn't start a\nstartup. In fact, you probably shouldn't even go to work for one.\nIn a good startup, you don't get told what to do very much. There\nmay be one person whose job title is CEO, but till the company has\nabout twelve people no one should be telling anyone what to do.\nThat's too inefficient. Each person should just do what they need\nto without anyone telling them.If that sounds like a recipe for chaos, think about a soccer team.\nEleven people manage to work together in quite complicated ways,\nand yet only in occasional emergencies does anyone tell anyone else\nwhat to do. A reporter once asked David Beckham if there were any\nlanguage problems at Real Madrid, since the players were from about\neight different countries. He said it was never an issue, because\neveryone was so good they never had to talk. They all just did the\nright thing.How do you tell if you're independent-minded enough to start a\nstartup? If you'd bristle at the suggestion that you aren't, then\nyou probably are.13. Fear of uncertaintyPerhaps some people are deterred from starting startups because\nthey don't like the uncertainty. If you go to work for Microsoft,\nyou can predict fairly accurately what the next few years will be\nlike—all too accurately, in fact. If you start a startup, anything\nmight happen.Well, if you're troubled by uncertainty, I can solve that problem\nfor you: if you start a startup, it will probably fail. Seriously, \nthough, this is not a bad way to think\nabout the whole experience. Hope for the best, but expect the\nworst. In the worst case, it will at least be interesting. In the\nbest case you might get rich.No one will blame you if the startup tanks, so long as you made a\nserious effort. There may once have been a time when employers\nwould regard that as a mark against you, but they wouldn't now. I\nasked managers at big companies, and they all said they'd prefer\nto hire someone who'd tried to start a startup and failed over\nsomeone who'd spent the same time working at a big company.Nor will investors hold it against you, as long as you didn't fail\nout of laziness or incurable stupidity. I'm told there's a lot\nof stigma attached to failing in other places—in Europe, for\nexample. Not here. In America, companies, like practically\neverything else, are disposable.14. Don't realize what you're avoidingOne reason people who've been out in the world for a year or two\nmake better founders than people straight from college is that they\nknow what they're avoiding. If their startup fails, they'll have\nto get a job, and they know how much jobs suck.If you've had summer jobs in college, you may think you know what\njobs are like, but you probably don't. Summer jobs at technology\ncompanies are not real jobs. If you get a summer job as a waiter,\nthat's a real job. Then you have to carry your weight. But software\ncompanies don't hire students for the summer as a source of cheap\nlabor. They do it in the hope of recruiting them when they graduate.\nSo while they're happy if you produce, they don't expect you to.That will change if you get a real job after you graduate. Then\nyou'll have to earn your keep. And since most of what big companies\ndo is boring, you're going to have to work on boring stuff. Easy,\ncompared to college, but boring. At first it may seem cool to get\npaid for doing easy stuff, after paying to do hard stuff in college.\nBut that wears off after a few months. Eventually it gets demoralizing\nto work on dumb stuff, even if it's easy and you get paid a lot.And that's not the worst of it. The thing that really sucks about\nhaving a regular job is the expectation that you're supposed to be\nthere at certain times. Even Google is afflicted with this,\napparently. And what this means, as everyone who's had a regular\njob can tell you, is that there are going to be times when you have\nabsolutely no desire to work on anything, and you're going to have\nto go to work anyway and sit in front of your screen and pretend\nto. To someone who likes work, as most good hackers do, this is\ntorture.In a startup, you skip all that. There's no concept of office hours\nin most startups. Work and life just get mixed together. But the\ngood thing about that is that no one minds if you have a life at\nwork. In a startup you can do whatever you want most of the time.\nIf you're a founder, what you want to do most of the time is work.\nBut you never have to pretend to.If you took a nap in your office in a big company, it would seem\nunprofessional. But if you're starting a startup and you fall\nasleep in the middle of the day, your cofounders will just assume\nyou were tired.15. Parents want you to be a doctorA significant number of would-be startup founders are probably\ndissuaded from doing it by their parents. I'm not going to say you\nshouldn't listen to them. Families are entitled to their own\ntraditions, and who am I to argue with them? But I will give you\na couple reasons why a safe career might not be what your parents\nreally want for you.One is that parents tend to be more conservative for their kids\nthan they would be for themselves. This is actually a rational\nresponse to their situation. Parents end up sharing more of their\nkids' ill fortune than good fortune. Most parents don't mind this;\nit's part of the job; but it does tend to make them excessively\nconservative. And erring on the side of conservatism is still\nerring. In almost everything, reward is proportionate to risk. So\nby protecting their kids from risk, parents are, without realizing\nit, also protecting them from rewards. If they saw that, they'd\nwant you to take more risks.The other reason parents may be mistaken is that, like generals,\nthey're always fighting the last war. If they want you to be a\ndoctor, odds are it's not just because they want you to help the\nsick, but also because it's a prestigious and lucrative career.\n[4]\nBut not so lucrative or prestigious as it was when their\nopinions were formed. When I was a kid in the seventies, a doctor\nwas the thing to be. There was a sort of golden triangle involving\ndoctors, Mercedes 450SLs, and tennis. All three vertices now seem\npretty dated.The parents who want you to be a doctor may simply not realize how\nmuch things have changed. Would they be that unhappy if you were\nSteve Jobs instead? So I think the way to deal with your parents'\nopinions about what you should do is to treat them like feature\nrequests. Even if your only goal is to please them, the way to do\nthat is not simply to give them what they ask for. Instead think\nabout why they're asking for something, and see if there's a better\nway to give them what they need.16. A job is the defaultThis leads us to the last and probably most powerful reason people\nget regular jobs: it's the default thing to do. Defaults are\nenormously powerful, precisely because they operate without any\nconscious choice.To almost everyone except criminals, it seems an axiom that if you\nneed money, you should get a job. Actually this tradition is not\nmuch more than a hundred years old. Before that, the default way\nto make a living was by farming. It's a bad plan to treat something\nonly a hundred years old as an axiom. By historical standards,\nthat's something that's changing pretty rapidly.We may be seeing another such change right now. I've read a lot\nof economic history, and I understand the startup world pretty well,\nand it now seems to me fairly likely that we're seeing the beginning\nof a change like the one from farming to manufacturing.And you know what? If you'd been around when that change began\n(around 1000 in Europe) it would have seemed to nearly everyone\nthat running off to the city to make your fortune was a crazy thing\nto do. Though serfs were in principle forbidden to leave their\nmanors, it can't have been that hard to run away to a city. There\nwere no guards patrolling the perimeter of the village. What\nprevented most serfs from leaving was that it seemed insanely risky.\nLeave one's plot of land? Leave the people you'd spent your whole\nlife with, to live in a giant city of three or four thousand complete\nstrangers? How would you live? How would you get food, if you\ndidn't grow it?Frightening as it seemed to them, it's now the default with us to\nlive by our wits. So if it seems risky to you to start a startup,\nthink how risky it once seemed to your ancestors to live as we do\nnow. Oddly enough, the people who know this best are the very ones\ntrying to get you to stick to the old model. How can Larry and\nSergey say you should come work as their employee, when they didn't\nget jobs themselves?Now we look back on medieval peasants and wonder how they stood it.\nHow grim it must have been to till the same fields your whole life\nwith no hope of anything better, under the thumb of lords and priests\nyou had to give all your surplus to and acknowledge as your masters.\nI wouldn't be surprised if one day people look back on what we\nconsider a normal job in the same way. How grim it would be to\ncommute every day to a cubicle in some soulless office complex, and\nbe told what to do by someone you had to acknowledge as a boss—someone \nwho could call you into their office and say \"take a seat,\"\nand you'd sit! Imagine having to ask permission to release\nsoftware to users. Imagine being sad on Sunday afternoons because\nthe weekend was almost over, and tomorrow you'd have to get up and\ngo to work. How did they stand it?It's exciting to think we may be on the cusp of another shift like\nthe one from farming to manufacturing. That's why I care about\nstartups. Startups aren't interesting just because they're a way\nto make a lot of money. I couldn't care less about other ways to\ndo that, like speculating in securities. At most those are interesting\nthe way puzzles are. There's more going on with startups. They\nmay represent one of those rare, historic shifts in the way \nwealth is created.That's ultimately what drives us to work on Y Combinator. We want\nto make money, if only so we don't have to stop doing it, but that's\nnot the main goal. There have only been a handful of these great\neconomic shifts in human history. It would be an amazing hack to\nmake one happen faster.\nNotes[1]\nThe only people who lost were us. The angels had convertible\ndebt, so they had first claim on the proceeds of the auction. Y\nCombinator only got 38 cents on the dollar.[2]\nThe best kind of organization for that might be an open source\nproject, but those don't involve a lot of face to face meetings.\nMaybe it would be worth starting one that did.[3]\nThere need to be some number of big companies to acquire the\nstartups, so the number of big companies couldn't decrease to zero.[4]\nThought experiment: If doctors did the same work, but as\nimpoverished outcasts, which parents would still want their kids\nto be doctors?Thanks to Trevor Blackwell, Jessica Livingston, and Robert\nMorris for reading drafts of this, to the founders of Zenter\nfor letting me use their web-based PowerPoint killer even though \nit isn't launched yet, and to Ming-Hay Luk\nof the Berkeley CSUA for inviting me to speak.\nComment on this essay." }, { "path": "data/PaulGrahamEssays/nov.txt", "content": "November 2019If you discover something new, there's a significant chance you'll be\naccused of some form of heresy.To discover new things, you have\nto work on ideas that are good but non-obvious; if an idea is\nobviously good, other people are probably already working on it.\nOne common way for a good idea to be non-obvious is for it to be hidden in the\nshadow of some mistaken assumption that people are very attached to.\nBut anything you discover from working on such an idea will tend to\ncontradict the mistaken assumption that was concealing it. And you\nwill thus get a lot of heat from people attached to the mistaken\nassumption. Galileo and Darwin are famous examples of this phenomenon,\nbut it's probably always an ingredient in the resistance to new\nideas.So it's particularly dangerous for an organization or society to\nhave a culture of pouncing on heresy. When you suppress heresies,\nyou don't just prevent people from contradicting the mistaken\nassumption you're trying to protect. You also suppress any idea\nthat implies indirectly that it's false.\nEvery cherished mistaken assumption has\na dead zone of unexplored ideas around it. And the more preposterous\nthe assumption, the bigger the dead zone it creates.There is a positive side to this phenomenon though. If you're\nlooking for new ideas, one way to find them is by looking for\nheresies. When you look at the question this way, the depressingly\nlarge dead zones around mistaken assumptions become excitingly large\nmines of new ideas." }, { "path": "data/PaulGrahamEssays/nthings.txt", "content": "September 2009I bet you the current issue of Cosmopolitan has an article\nwhose title begins with a number. \"7 Things He Won't Tell You about\nSex,\" or something like that. Some popular magazines\nfeature articles of this type on the cover of every\nissue. That can't be happening by accident. Editors must know\nthey attract readers.Why do readers like the list of n things so much? Mainly because\nit's easier to read than a regular article. \n[1]\nStructurally, the list of n things is a degenerate case of essay.\nAn essay can go anywhere the writer wants. In a list of n things\nthe writer agrees to constrain himself to a collection of points\nof roughly equal importance, and he tells the reader explicitly\nwhat they are.Some of the work of reading an article is understanding its\nstructure—figuring out what in high school we'd have called\nits \"outline.\" Not explicitly, of course, but someone who really\nunderstands an article probably has something in his brain afterward\nthat corresponds to such an outline. In a list of n things, this\nwork is done for you. Its structure is an exoskeleton.As well as being explicit, the structure is guaranteed to be of the\nsimplest possible type: a few main points with few to no subordinate\nones, and no particular connection between them.Because the main points are unconnected, the list of n things is\nrandom access. There's no thread of reasoning you have to follow. You could\nread the list in any order. And because the points are independent\nof one another, they work like watertight compartments in an\nunsinkable ship. If you get bored with, or can't understand, or\ndon't agree with one point, you don't have to give up on the article.\nYou can just abandon that one and skip to the next. A list of n\nthings is parallel and therefore fault tolerant.There are times when this format is what a writer wants. One, obviously,\nis when what you have to say actually is a list of n\nthings. I once wrote an essay about the mistakes that kill startups, and a few people made fun of me\nfor writing something whose title began with a number. But in that\ncase I really was trying to make a complete catalog of a number of\nindependent things. In fact, one of the questions I was trying to\nanswer was how many there were.There are other less legitimate reasons for using this format. For\nexample, I use it when I get close to a deadline. If I have to\ngive a talk and I haven't started it a few days beforehand, I'll\nsometimes play it safe and make the talk a list of n things.The list of n things is easier for writers as well as readers. When\nyou're writing a real essay, there's always a chance you'll hit a\ndead end. A real essay is a train of thought, and some trains of\nthought just peter out. That's an alarming possibility when you\nhave to give a talk in a few days. What if you run out of ideas?\nThe compartmentalized structure of the list of n things protects\nthe writer from his own stupidity in much the same way it protects\nthe reader. If you run out of ideas on one point, no problem: it\nwon't kill the essay. You can take out the whole point if you need\nto, and the essay will still survive.Writing a list of n things is so relaxing. You think of n/2 of\nthem in the first 5 minutes. So bang, there's the structure, and\nyou just have to fill it in. As you think of more points, you just\nadd them to the end. Maybe you take out or rearrange or combine a\nfew, but at every stage you have a valid (though initially low-res)\nlist of n things. It's like the sort of programming where you write\na version 1 very quickly and then gradually modify it, but at every\npoint have working code—or the style of painting where you begin\nwith a complete but very blurry sketch done in an hour, then spend\na week cranking up the resolution.Because the list of n things is easier for writers too, it's not\nalways a damning sign when readers prefer it. It's not necessarily\nevidence readers are lazy; it could also mean they don't have\nmuch confidence in the writer. The list of n things is in that\nrespect the cheeseburger of essay forms. If you're eating at a\nrestaurant you suspect is bad, your best bet is to order the\ncheeseburger. Even a bad cook can make a decent cheeseburger. And\nthere are pretty strict conventions about what a cheeseburger should\nlook like. You can assume the cook isn't going to try something\nweird and artistic. The list of n things similarly limits the\ndamage that can be done by a bad writer. You know it's going to\nbe about whatever the title says, and the format prevents the writer\nfrom indulging in any flights of fancy.Because the list of n things is the easiest essay form, it should\nbe a good one for beginning writers. And in fact it is what most\nbeginning writers are taught. The classic 5 paragraph essay is\nreally a list of n things for n = 3. But the students writing them\ndon't realize they're using the same structure as the articles they\nread in Cosmopolitan. They're not allowed to include the numbers,\nand they're expected to spackle over the gaps with gratuitous\ntransitions (\"Furthermore...\") and cap the thing at either end with\nintroductory and concluding paragraphs so it will look superficially\nlike a real essay.\n[2]It seems a fine plan to start students off with the list of n things.\nIt's the easiest form. But if we're going to do that, why not do\nit openly? Let them write lists of n things like the pros, with\nnumbers and no transitions or \"conclusion.\"There is one case where the list of n things is a dishonest format:\nwhen you use it to attract attention by falsely claiming the list\nis an exhaustive one. I.e. if you write an article that purports\nto be about the 7 secrets of success. That kind of title is the\nsame sort of reflexive challenge as a whodunit. You have to at least\nlook at the article to check whether they're the same 7 you'd list.\nAre you overlooking one of the secrets of success? Better check.It's fine to put \"The\" before the number if you really believe\nyou've made an exhaustive list. But evidence suggests most things\nwith titles like this are linkbait.The greatest weakness of the list of n things is that there's so\nlittle room for new thought. The main point of essay writing, when\ndone right, is the new ideas you have while doing it. A real essay,\nas the name implies, is \ndynamic: you don't know what you're going\nto write when you start. It will be about whatever you discover\nin the course of writing it.This can only happen in a very limited way in a list of n things.\nYou make the title first, and that's what it's going to be about.\nYou can't have more new ideas in the writing than will fit in the\nwatertight compartments you set up initially. And your brain seems\nto know this: because you don't have room for new ideas, you don't\nhave them.Another advantage of admitting to beginning writers that the 5\nparagraph essay is really a list of n things is that we can warn\nthem about this. It only lets you experience the defining\ncharacteristic of essay writing on a small scale: in thoughts of a\nsentence or two. And it's particularly dangerous that the 5 paragraph\nessay buries the list of n things within something that looks like\na more sophisticated type of essay. If you don't know you're using\nthis form, you don't know you need to escape it.Notes[1]\nArticles of this type are also startlingly popular on Delicious,\nbut I think that's because \ndelicious/popular \nis driven by bookmarking,\nnot because Delicious users are stupid. Delicious users are\ncollectors, and a list of n things seems particularly collectible\nbecause it's a collection itself.[2]\nMost \"word problems\" in school math textbooks are similarly\nmisleading. They look superficially like the application of math\nto real problems, but they're not. So if anything they reinforce\nthe impression that math is merely a complicated but pointless\ncollection of stuff to be memorized." }, { "path": "data/PaulGrahamEssays/opensource.txt", "content": "August 2005(This essay is derived from a talk at Oscon 2005.)Lately companies have been paying more attention to open source.\nTen years ago there seemed a real danger Microsoft would extend its\nmonopoly to servers. It seems safe to say now that open source has\nprevented that. A recent survey found 52% of companies are replacing\nWindows servers with Linux servers.\n[1]More significant, I think, is which 52% they are. At this point,\nanyone proposing to run Windows on servers should be prepared to\nexplain what they know about servers that Google, Yahoo, and Amazon\ndon't.But the biggest thing business has to learn from open source is not\nabout Linux or Firefox, but about the forces that produced them.\nUltimately these will affect a lot more than what software you use.We may be able to get a fix on these underlying forces by triangulating\nfrom open source and blogging. As you've probably noticed, they\nhave a lot in common.Like open source, blogging is something people do themselves, for\nfree, because they enjoy it. Like open source hackers, bloggers\ncompete with people working for money, and often win. The method\nof ensuring quality is also the same: Darwinian. Companies ensure\nquality through rules to prevent employees from screwing up. But\nyou don't need that when the audience can communicate with one\nanother. People just produce whatever they want; the good stuff\nspreads, and the bad gets ignored. And in both cases, feedback\nfrom the audience improves the best work.Another thing blogging and open source have in common is the Web.\nPeople have always been willing to do great work\nfor free, but before the Web it was harder to reach an audience\nor collaborate on projects.AmateursI think the most important of the new principles business has to learn is\nthat people work a lot harder on stuff they like. Well, that's\nnews to no one. So how can I claim business has to learn it? When\nI say business doesn't know this, I mean the structure of business\ndoesn't reflect it.Business still reflects an older model, exemplified by the French\nword for working: travailler. It has an English cousin, travail,\nand what it means is torture.\n[2]This turns out not to be the last word on work, however.\nAs societies get richer, they learn something about\nwork that's a lot like what they learn about diet. We know now that the\nhealthiest diet is the one our peasant ancestors were forced to\neat because they were poor. Like rich food, idleness\nonly seems desirable when you don't get enough of it. I think we were\ndesigned to work, just as we were designed to eat a certain amount\nof fiber, and we feel bad if we don't.There's a name for people who work for the love of it: amateurs.\nThe word now has such bad connotations that we forget its etymology,\nthough it's staring us in the face. \"Amateur\" was originally rather\na complimentary word. But the thing to be in the twentieth century\nwas professional, which amateurs, by definition, are not.That's why the business world was so surprised by one lesson from\nopen source: that people working for love often surpass those working\nfor money. Users don't switch from Explorer to Firefox because\nthey want to hack the source. They switch because it's a better\nbrowser.It's not that Microsoft isn't trying. They know controlling the\nbrowser is one of the keys to retaining their monopoly. The problem\nis the same they face in operating systems: they can't pay people\nenough to build something better than a group of inspired hackers\nwill build for free.I suspect professionalism was always overrated-- not just in the\nliteral sense of working for money, but also connotations like\nformality and detachment. Inconceivable as it would have seemed\nin, say, 1970, I think professionalism was largely a fashion,\ndriven by conditions that happened to exist in the twentieth century.One of the most powerful of those was the existence of \"channels.\" Revealingly,\nthe same term was used for both products and information: there\nwere distribution channels, and TV and radio channels.It was the narrowness of such channels that made professionals\nseem so superior to amateurs. There were only a few jobs as\nprofessional journalists, for example, so competition ensured the\naverage journalist was fairly good. Whereas anyone can express\nopinions about current events in a bar. And so the average person\nexpressing his opinions in a bar sounds like an idiot compared to\na journalist writing about the subject.On the Web, the barrier for publishing your ideas is even lower.\nYou don't have to buy a drink, and they even let kids in.\nMillions of people are publishing online, and the average\nlevel of what they're writing, as you might expect, is not very\ngood. This has led some in the media to conclude that blogs don't\npresent much of a threat-- that blogs are just a fad.Actually, the fad is the word \"blog,\" at least the way the print\nmedia now use it. What they mean by \"blogger\" is not someone who\npublishes in a weblog format, but anyone who publishes online.\nThat's going to become a problem as the Web becomes the default\nmedium for publication. So I'd\nlike to suggest an alternative word for someone who publishes online.\nHow about \"writer?\"Those in the print media who dismiss the writing online because of\nits low average quality are missing an important point: no one reads\nthe average blog. In the old world of channels, it meant something\nto talk about average quality, because that's what you were getting\nwhether you liked it or not.\nBut now you can read any writer you want. So the average\nquality of writing online isn't what the print media are competing\nagainst. They're competing against the best writing online. And, \nlike Microsoft, they're losing.I know that from my own experience as a reader. Though most print\npublications are online, I probably\nread two or three articles on individual people's sites for every\none I read on the site of a newspaper or magazine.And when I read, say, New York Times stories, I never reach\nthem through the Times front page. Most I find through aggregators\nlike Google News or Slashdot or Delicious. Aggregators show how\nmuch better \nyou can do than the channel. The New York Times front page is\na list of articles written by people who work for the New York Times. Delicious\nis a list of articles that are interesting. And it's only now that\nyou can see the two side by side that you notice how little overlap there is.Most articles in the print media are boring. For example, the\npresident notices that a majority of voters now think invading Iraq\nwas a mistake, so he makes an address to the nation to drum up\nsupport. Where is the man bites dog in that? I didn't hear the\nspeech, but I could probably tell you exactly what he said. A\nspeech like that is, in the most literal sense, not news: there is\nnothing new in it.\n[3]Nor is there anything new, except the names and places, in most\n\"news\" about things going wrong. A child is abducted; there's a\ntornado; a ferry sinks; someone gets bitten by a shark; a small\nplane crashes. And what do you learn about the world from these\nstories? Absolutely nothing. They're outlying data points; what\nmakes them gripping also makes them irrelevant.As in software, when professionals produce such crap, it's not\nsurprising if amateurs can do better. Live by the channel, die by\nthe channel: if you depend on an oligopoly, you sink into bad habits\nthat are hard to overcome when you suddenly get competition.\n[4]WorkplacesAnother thing blogs and open source software have in common is that\nthey're often made by people working at home. That may not seem\nsurprising. But it should be. It's the architectural equivalent\nof a home-made aircraft shooting down an F-18. Companies spend\nmillions to build office buildings for a single purpose: to be a\nplace to work. And yet people working in their own homes,\nwhich aren't even designed to be workplaces, end up\nbeing more productive.This proves something a lot of us have suspected. The average\noffice is a miserable place to get work done. And a lot of what\nmakes offices bad are the very qualities we associate with\nprofessionalism. The sterility\nof offices is supposed to suggest efficiency. But suggesting\nefficiency is a different thing from actually being efficient.The atmosphere of the average workplace is to productivity what\nflames painted on the side of a car are to speed. And it's not\njust the way offices look that's bleak. The way people act is just\nas bad.Things are different in a startup. Often as not a startup begins\nin an apartment. Instead of matching beige cubicles\nthey have an assortment of furniture they bought used. They work\nodd hours, wearing the most casual of clothing. They look at\nwhatever they want online without worrying whether it's \"work safe.\"\nThe cheery, bland language of the office is replaced by wicked humor. And\nyou know what? The company at this stage is probably the most\nproductive it's ever going to be.Maybe it's not a coincidence. Maybe some aspects of professionalism\nare actually a net lose.To me the most demoralizing aspect of the traditional office is\nthat you're supposed to be there at certain times. There are usually\na few people in a company who really have to, but the reason most\nemployees work fixed hours is that the company can't measure their\nproductivity.The basic idea behind office hours is that if you can't make people\nwork, you can at least prevent them from having fun. If employees\nhave to be in the building a certain number of hours a day, and are\nforbidden to do non-work things while there, then they must be\nworking. In theory. In practice they spend a lot of their time\nin a no-man's land, where they're neither working nor having fun.If you could measure how much work people did, many companies\nwouldn't need any fixed workday. You could just say: this is what\nyou have to do. Do it whenever you like, wherever you like. If\nyour work requires you to talk to other people in the company, then\nyou may need to be here a certain amount. Otherwise we don't care.That may seem utopian, but it's what we told people who came to\nwork for our company. There were no fixed office hours. I never\nshowed up before 11 in the morning. But we weren't saying this to\nbe benevolent. We were saying: if you work here we expect you to\nget a lot done. Don't try to fool us just by being here a lot.The problem with the facetime model is not just that it's demoralizing, but\nthat the people pretending to work interrupt\nthe ones actually working. I'm convinced the facetime model\nis the main reason large organizations have so many meetings.\nPer capita, large organizations accomplish very little.\nAnd yet all those people have to be on site at least eight hours a\nday. When so much time goes in one end and so little achievement\ncomes out the other, something has to give. And meetings are the\nmain mechanism for taking up the slack.For one year I worked at a regular nine to five job, and I remember\nwell the strange, cozy feeling that comes over one during meetings.\nI was very aware, because of the novelty, that I was being paid for\nprogramming. It seemed just amazing, as if there was a machine on\nmy desk that spat out a dollar bill every two minutes no matter\nwhat I did. Even while I was in the bathroom! But because the\nimaginary machine was always running, I felt I always ought to be\nworking. And so meetings felt wonderfully relaxing. They\ncounted as work, just like programming, but they were so much easier.\nAll you had to do was sit and look attentive.Meetings are like an opiate with a network effect. So is email,\non a smaller scale. And in addition to the direct cost in time,\nthere's the cost in fragmentation-- breaking people's day up into\nbits too small to be useful.You can see how dependent you've become on something by removing\nit suddenly. So for big companies I propose the following experiment.\nSet aside one day where meetings are forbidden-- where everyone has to\nsit at their desk all day and work without interruption on\nthings they can do without talking to anyone else.\nSome amount of communication is necessary in most jobs, but I'm\nsure many employees could find eight hours worth of stuff they could\ndo by themselves. You could call it \"Work Day.\"The other problem with pretend work\nis that it often looks better than real work. When I'm\nwriting or hacking I spend as much time just thinking as I do\nactually typing. Half the time I'm sitting drinking a cup of tea,\nor walking around the neighborhood. This is a critical phase--\nthis is where ideas come from-- and yet I'd feel guilty doing this\nin most offices, with everyone else looking busy.It's hard to see how bad some practice is till you have something\nto compare it to. And that's one reason open source, and even blogging\nin some cases, are so important. They show us what real work looks like.We're funding eight new startups at the moment. A friend asked\nwhat they were doing for office space, and seemed surprised when I\nsaid we expected them to work out of whatever apartments they found\nto live in. But we didn't propose that to save money. We did it\nbecause we want their software to be good. Working in crappy\ninformal spaces is one of the things startups do right without\nrealizing it. As soon as you get into an office, work and life\nstart to drift apart.That is one of the key tenets of professionalism. Work and life\nare supposed to be separate. But that part, I'm convinced, is a \nmistake.Bottom-UpThe third big lesson we can learn from open source and\nblogging is that ideas can bubble up from the bottom, instead of\nflowing down from the top. Open source and blogging both work\nbottom-up: people make what they want, and the best stuff\nprevails.Does this sound familiar? It's the principle of a market economy.\nIronically, though open source and blogs are done for free, those\nworlds resemble market economies, while most companies, for all\ntheir talk about the value of free markets, are run internally like\ncommunist states.There are two forces that together steer design: ideas about\nwhat to do next, and the enforcement of quality. In the channel\nera, both flowed down from the top. For example, newspaper editors\nassigned stories to reporters, then edited what they wrote.Open source and blogging show us things don't have to work that\nway. Ideas and even the enforcement of quality can flow bottom-up.\nAnd in both cases the results are not merely acceptable, but better.\nFor example, open source software is more reliable precisely because\nit's open source; anyone can find mistakes.The same happens with writing. As we got close to publication, I\nfound I was very worried about the essays in \nHackers\n& Painters\nthat hadn't been online. Once an essay has had a couple thousand\npage views I feel reasonably confident about it. But these had had \nliterally orders of magnitude less scrutiny. It felt like\nreleasing software without testing it.That's what all publishing used to be like. If\nyou got ten people to read a manuscript, you were lucky. But I'd\nbecome so used to publishing online that the old method now seemed\nalarmingly unreliable, like navigating by dead reckoning once you'd\ngotten used to a GPS.The other thing I like about publishing online is that you can write\nwhat you want and publish when you want. Earlier this year I wrote\nsomething that seemed suitable for a magazine, so\nI sent it to an editor I know.\nAs I was waiting to hear back, I found to my surprise that I was\nhoping they'd reject it. Then I could put it online right away.\nIf they accepted it, it wouldn't be read by anyone for months, and\nin the meantime I'd have to fight word-by-word to save it from being\nmangled by some twenty five year old copy editor.\n[5]Many employees would like to build great things for the companies\nthey work for, but more often than not management won't let them.\nHow many of us have heard stories of employees going to management\nand saying, please let us build this thing to make money for you--\nand the company saying no? The most famous example is probably Steve Wozniak,\nwho originally wanted to build microcomputers for his then-employer, HP.\nAnd they turned him down. On the blunderometer, this episode ranks\nwith IBM accepting a non-exclusive license for DOS. But I think this\nhappens all the time. We just don't hear about it usually,\nbecause to prove yourself right you have to quit\nand start your own company, like Wozniak did.StartupsSo these, I think, are the three big lessons open source and blogging\nhave to teach business: (1) that people work harder on stuff they\nlike, (2) that the standard office environment is very unproductive,\nand (3) that bottom-up often works better than top-down.I can imagine managers at this point saying: what is this guy talking\nabout? What good does it do me to know that my programmers\nwould be more productive\nworking at home on their own projects? I need their asses in here\nworking on version 3.2 of our software, or we're never going to\nmake the release date.And it's true, the benefit that specific manager could derive from\nthe forces I've described is near zero. When I say business can\nlearn from open source, I don't mean any specific business can. I\nmean business can learn about new conditions the same way a gene\npool does. I'm not claiming companies can get smarter, just that\ndumb ones will die.So what will business look like when it has assimilated the lessons\nof open source and blogging? I think the big obstacle preventing\nus from seeing the future of business is the assumption that people\nworking for you have to be employees. But think about what's going\non underneath: the company has some money, and they pay it to the\nemployee in the hope that he'll make something worth more than they\npaid him. Well, there are other ways to arrange that relationship.\nInstead of paying the guy money as a salary, why not give it to him\nas investment? Then instead of coming to your office to work on\nyour projects, he can work wherever he wants on projects of his own.Because few of us know any alternative, we have no idea how much\nbetter we could do than the traditional employer-employee relationship.\nSuch customs evolve with glacial slowness. Our \nemployer-employee relationship still retains a big chunk of\nmaster-servant DNA.\n[6]I dislike being on either end of it.\nI'll work my ass off for a customer, but I resent being told what\nto do by a boss. And being a boss is also horribly frustrating; \nhalf the time it's easier just to do stuff yourself than to get\nsomeone else to do it for you.\nI'd rather do almost anything than give or receive a\nperformance review.On top of its unpromising origins, employment\nhas accumulated a lot of cruft over the years. The list of what\nyou can't ask in job interviews is now so long that for convenience\nI assume it's infinite. Within the\noffice you now have to walk on eggshells lest anyone \nsay or do\nsomething that makes the company prey to a lawsuit. And God help\nyou if you fire anyone.Nothing shows more clearly that employment is not an ordinary economic\nrelationship than companies being sued for firing people. In any\npurely economic relationship you're free to do what you want. If\nyou want to stop buying steel pipe from one supplier and start\nbuying it from another, you don't have to explain why. No one can\naccuse you of unjustly switching pipe suppliers. Justice implies\nsome kind of paternal obligation that isn't there in\ntransactions between equals.Most of the legal restrictions on employers are intended to protect\nemployees. But you can't have action without an equal and opposite\nreaction. You can't expect employers to have some kind of paternal\nresponsibility toward employees without putting employees in the\nposition of children. And that seems a bad road to go down.Next time you're in a moderately large city, drop by the main post\noffice and watch the body language of the people working there.\nThey have the same sullen resentment as children made to do\nsomething they don't want to. Their union has exacted pay\nincreases and work restrictions that would have been the envy of\nprevious generations of postal workers, and yet they don't seem any\nhappier for it. It's demoralizing\nto be on the receiving end of a paternalistic relationship, no\nmatter how cozy the terms. Just ask any teenager.I see the disadvantages of the employer-employee relationship because\nI've been on both sides of a better one: the investor-founder relationship.\nI wouldn't claim it's painless. When I was running a\nstartup, the thought of our investors used to keep me up at night.\nAnd now that I'm an investor,\nthe thought of our startups keeps me\nup at night. All the pain of whatever problem you're trying to\nsolve is still there.\nBut the pain hurts less when it isn't\nmixed with resentment.I had the misfortune to participate in what amounted to a controlled\nexperiment to prove that. After Yahoo bought our startup I went\nto work for them. I was doing exactly the same work, except with\nbosses. And to my horror I started acting like a child. The \nsituation pushed buttons I'd forgotten\nI had.The big advantage of investment over employment, as the examples of open\nsource and blogging suggest, is that people working on projects of\ntheir own are enormously more productive. And a\nstartup is a project\nof one's own in two senses, both of them important: it's creatively\none's own, and also economically ones's own.Google is a rare example of a big company in tune with the forces\nI've described. They've tried hard to make their offices less sterile\nthan the usual cube farm. They give employees who do great work\nlarge grants of stock to simulate the rewards of a startup. They\neven let hackers spend 20% of their time on their own projects.Why not let people spend 100% of their time on their own projects,\nand instead of trying to approximate the value of what they create,\ngive them the actual market value? Impossible? That is in fact\nwhat venture capitalists do.So am I claiming that no one is going to be an employee anymore--\nthat everyone should go and start a startup? Of course not.\nBut more people could do it than do it now.\nAt the moment, even the smartest students leave school thinking\nthey have to get a job. \nActually what they need to do is make\nsomething valuable. A job is one way to do that, but the more\nambitious ones will ordinarily be better off taking money from an\ninvestor than an employer.Hackers tend to think business is for MBAs. But business\nadministration is not what you're doing in a startup. What you're\ndoing is business creation. And the first phase of that\nis mostly product creation-- that is, hacking. That's the\nhard part. It's a lot harder to create something people love than\nto take something people love and figure out how to make money from\nit.Another thing that keeps people away from starting startups is the\nrisk. Someone with kids and a mortgage should think twice before\ndoing it. But most young hackers have neither.And as the example of open source and blogging suggests, you'll\nenjoy it more, even if you fail. You'll be working on your own\nthing, instead of going to some office and doing what you're told.\nThere may be more pain in your own company, but it won't hurt as\nmuch.That may be the greatest effect, in the long run, of the forces \nunderlying open source and blogging: finally ditching the old\npaternalistic employer-employee relationship, and replacing it with\na purely economic one, between equals.\nNotes[1]\nSurvey by Forrester Research reported in the cover story of\nBusiness Week, 31 Jan 2005. Apparently someone believed you have to\nreplace the actual server in order to switch the operating system.[2]\nIt derives from the late Latin tripalium,\na torture device so called because it consisted of three stakes.\nI don't know how the stakes were used. \"Travel\" has the same root.[3]\nIt would be much bigger news, in that sense, if the president\nfaced unscripted questions by giving a press conference.[4]\nOne measure of the incompetence of newspapers is that so many\nstill make you register to read stories. I have yet to find a blog\nthat tried that.[5]\nThey accepted the article, but I took so long to\nsend them the final version that by the time I did the section of\nthe magazine they'd accepted it for had disappeared in a reorganization.[6]\nThe word \"boss\" is derived from the Dutch baas, meaning\n\"master.\"Thanks to Sarah Harlin, Jessica Livingston, and Robert Morris for reading drafts of this." }, { "path": "data/PaulGrahamEssays/organic.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nApril 2010The best way to come up with startup ideas is to ask yourself the\nquestion: what do you wish someone would make for you?There are two types of startup ideas: those that grow organically\nout of your own life, and those that you decide, from afar, are\ngoing to be necessary to some class of users other than you. Apple\nwas the first type. Apple happened because Steve Wozniak wanted a\ncomputer. Unlike most people who wanted computers, he could design\none, so he did. And since lots of other people wanted the same\nthing, Apple was able to sell enough of them to get the company\nrolling. They still rely on this principle today, incidentally.\nThe iPhone is the phone Steve Jobs wants.\n[1]Our own startup, Viaweb, was of the second type. We made software\nfor building online stores. We didn't need this software ourselves.\nWe weren't direct marketers. We didn't even know when we started\nthat our users were called \"direct marketers.\" But we were\ncomparatively old when we started the company (I was 30 and Robert\nMorris was 29), so we'd seen enough to know users would need this\ntype of software.\n[2]There is no sharp line between the two types of ideas, but\nthe most successful startups seem to be closer to the Apple type\nthan the Viaweb type. When he was writing that first Basic interpreter\nfor the Altair, Bill Gates was writing something he would use, as\nwere Larry and Sergey when they wrote the first versions of Google.Organic ideas are generally preferable to the made up kind, but\nparticularly so when the founders are young. It takes experience\nto predict what other people will want. The worst ideas we see at\nY Combinator are from young founders making things they think other\npeople will want.So if you want to start a startup and don't know yet what you're\ngoing to do, I'd encourage you to focus initially on organic ideas.\nWhat's missing or broken in your daily life? Sometimes if you just\nask that question you'll get immediate answers. It must have seemed\nobviously broken to Bill Gates that you could only program the\nAltair in machine language.You may need to stand outside yourself a bit to see brokenness,\nbecause you tend to get used to it and take it for granted. You\ncan be sure it's there, though. There are always great ideas sitting\nright under our noses. In 2004 it was ridiculous that Harvard\nundergrads were still using a Facebook printed on paper. Surely\nthat sort of thing should have been online.There are ideas that obvious lying around now. The reason you're\noverlooking them is the same reason you'd have overlooked the idea\nof building Facebook in 2004: organic startup ideas usually don't\nseem like startup ideas at first. We know now that Facebook was\nvery successful, but put yourself back in 2004. Putting undergraduates'\nprofiles online wouldn't have seemed like much of a startup idea.\nAnd in fact, it wasn't initially a startup idea. When Mark spoke\nat a YC dinner this winter he said he wasn't trying to start a\ncompany when he wrote the first version of Facebook. It was just\na project. So was the Apple I when Woz first started working on\nit. He didn't think he was starting a company. If these guys had\nthought they were starting companies, they might have been tempted\nto do something more \"serious,\" and that would have been a mistake.So if you want to come up with organic startup ideas, I'd encourage\nyou to focus more on the idea part and less on the startup part.\nJust fix things that seem broken, regardless of whether it seems\nlike the problem is important enough to build a company on. If you\nkeep pursuing such threads it would be hard not to end up making\nsomething of value to a lot of people, and when you do, surprise,\nyou've got a company.\n[3]Don't be discouraged if what you produce initially is something\nother people dismiss as a toy. In fact, that's a good sign.\nThat's probably why everyone else has been overlooking the idea. The first\nmicrocomputers were dismissed as toys. And the first planes, and\nthe first cars. At this point, when someone comes to us with\nsomething that users like but that we could envision forum trolls\ndismissing as a toy, it makes us especially likely to invest.While young founders are at a disadvantage when coming up with\nmade-up ideas, they're the best source of organic ones, because\nthey're at the forefront of technology. They use the latest stuff.\nThey only just decided what to use, so why wouldn't they? And\nbecause they use the latest stuff, they're in a position to discover\nvaluable types of fixable brokenness first.There's nothing more valuable than an unmet need that is just\nbecoming fixable. If you find something broken that you can fix\nfor a lot of people, you've found a gold mine. As with an actual\ngold mine, you still have to work hard to get the gold out of it.\nBut at least you know where the seam is, and that's the hard part.Notes[1]\nThis suggests a way to predict areas where Apple will be weak:\nthings Steve Jobs doesn't use. E.g. I doubt he is much into gaming.\n[2]\nIn retrospect, we should have become direct marketers. If\nI were doing Viaweb again, I'd open our own online store. If we\nhad, we'd have understood users a lot better. I'd encourage anyone\nstarting a startup to become one of its users, however unnatural it\nseems.[3]\nPossible exception: It's hard to compete directly with open source software.\nYou can build things for programmers, but there has to be some part\nyou can charge for.Thanks to Sam Altman, Trevor Blackwell, and Jessica Livingston\nfor reading drafts of this." }, { "path": "data/PaulGrahamEssays/orth.txt", "content": "July 2020\n\n\n\n\"Few people are capable of expressing with equanimity opinions which differ from the prejudices of their social environment. Most people are even incapable of forming such opinions.\"— Einstein\n\n\n\nThere has been a lot of talk about privilege lately. Although the\nconcept is overused, there is something to it, and in particular\nto the idea that privilege makes you blind — that you can't see\nthings that are visible to someone whose life is very different\nfrom yours.But one of the most pervasive examples of this kind of blindness\nis one that I haven't seen mentioned explicitly. I'm going to call\nit orthodox privilege: The more conventional-minded someone is, the\nmore it seems to them that it's safe for everyone to express their\nopinions.It's safe for them to express their opinions, because the source\nof their opinions is whatever it's currently acceptable to believe.\nSo it seems to them that it must be safe for everyone. They literally\ncan't imagine a true statement that would get them in trouble.And yet at every point in history, there were true things that would\nget you in terrible trouble to say. \nIs ours the first where this\nisn't so? What an amazing coincidence that would be.Surely it should at least be the default assumption that our time\nis not unique, and that there are true things you can't say now,\njust as there have always been. You would think. But even in the\nface of such overwhelming historical evidence, most people will go\nwith their gut on this one.The spectral signature of orthodox privilege is \"Why don't you just\nsay it?\" The more extreme will even\naccuse you of specific heresies they imagine you must have in mind,\nthough if there's more than one heresy current in your time, these\naccusations will tend to be nondeterministic: you must either be\nan xist or a yist.Frustrating as it is to deal with these people, it's important to\nrealize that they're in earnest. They're not pretending they think\nit's impossible for an idea to be both unorthodox and true. The\nworld really looks that way to them.How do you respond to orthodox privilege? Merely giving it a name\nmay help somewhat, because it will remind you, when you encounter it,\nwhy the people you're talking to seem so strangely unreasonable.\nBecause this is a uniquely tenacious form of privilege. People can\novercome the blindness induced by most forms of privilege by learning\nmore about whatever they're not. But they can't overcome orthodox\nprivilege just by learning more. They'd have to become more\nindependent-minded. If that happens at all, it doesn't happen on\nthe time scale of one conversation.It may be possible to convince some people that orthodox privilege\nmust exist even though they can't sense it, just as one can with,\nsay, dark matter. There may be some who could be convinced, for\nexample, that it's very unlikely that this is the first point in\nhistory at which there's nothing true you can't say, even if they\ncan't imagine specific examples.But except with these people, I don't think it will work to say\n\"check your privilege\" about this type of privilege, because those\nin its demographic don't realize they're in it. It doesn't seem to\nconventional-minded people that they're conventional-minded. It\njust seems to them that they're right. Indeed, they tend to be\nparticularly sure of it.Perhaps the solution is to appeal to politeness. If someone says\nthey can hear a high-pitched noise that you can't, it's only polite\nto take them at their word, instead of demanding evidence that's\nimpossible to produce, or simply denying that they hear anything.\nImagine how rude that would seem. Similarly, if someone says they\ncan think of things that are true but that cannot be said, it's\nonly polite to take them at their word, even if you can't think of\nany yourself.Once you realize that orthodox privilege exists, a lot of other\nthings become clearer. For example, how can it be that a large\nnumber of reasonable, intelligent people worry about something they\ncall \"cancel culture,\" while other reasonable, intelligent people\ndeny that it's a problem? Once you understand the concept of orthodox\nprivilege, it's easy to see the source of this disagreement. If\nyou believe there's nothing true that you can't say, then anyone\nwho gets in trouble for something they say must deserve it.Thanks to Sam Altman, Trevor Blackwell, Patrick Collison, Antonio Garcia-Martinez,\nJessica Livingston, Robert Morris, Michael Nielsen, Geoff Ralston, Max Roser, and\nHarj Taggar for reading drafts of this." }, { "path": "data/PaulGrahamEssays/own.txt", "content": "June 2021A few days ago, on the way home from school, my nine year old son\ntold me he couldn't wait to get home to write more of the story he\nwas working on. This made me as happy as anything I've heard him\nsay — not just because he was excited about his story, but because\nhe'd discovered this way of working. Working on a project of your\nown is as different from ordinary work as skating is from walking.\nIt's more fun, but also much more productive.What proportion of great work has been done by people who were\nskating in this sense? If not all of it, certainly a lot.There is something special about working on a project of your own.\nI wouldn't say exactly that you're happier. A better word would be\nexcited, or engaged. You're happy when things are going well, but\noften they aren't. When I'm writing an essay, most of the time I'm\nworried and puzzled: worried that the essay will turn out badly,\nand puzzled because I'm groping for some idea that I can't see\nclearly enough. Will I be able to pin it down with words? In the\nend I usually can, if I take long enough, but I'm never sure; the\nfirst few attempts often fail.You have moments of happiness when things work out, but they don't\nlast long, because then you're on to the next problem. So why do\nit at all? Because to the kind of people who like working this way,\nnothing else feels as right. You feel as if you're an animal in its\nnatural habitat, doing what you were meant to do — not always\nhappy, maybe, but awake and alive.Many kids experience the excitement of working on projects of their\nown. The hard part is making this converge with the work you do as\nan adult. And our customs make it harder. We treat \"playing\" and\n\"hobbies\" as qualitatively different from \"work\". It's not clear\nto a kid building a treehouse that there's a direct (though long)\nroute from that to architecture or engineering. And instead of\npointing out the route, we conceal it, by implicitly treating the\nstuff kids do as different from real work.\n[1]Instead of telling kids that their treehouses could be on the path\nto the work they do as adults, we tell them the path goes through\nschool. And unfortunately schoolwork tends to be very different from\nworking on projects of one's own. It's usually neither a project,\nnor one's own. So as school gets more serious, working on projects\nof one's own is something that survives, if at all, as a thin thread\noff to the side.It's a bit sad to think of all the high school kids turning their\nbacks on building treehouses and sitting in class dutifully learning\nabout Darwin or Newton to pass some exam, when the work that made\nDarwin and Newton famous was actually closer in spirit to building\ntreehouses than studying for exams.If I had to choose between my kids getting good grades and \nworking on ambitious projects of their own, I'd pick\nthe projects. And not because I'm an indulgent parent, but because\nI've been on the other end and I know which has more predictive\nvalue. When I was picking startups for Y Combinator, I didn't care\nabout applicants' grades. But if they'd worked on projects of their\nown, I wanted to hear all about those.\n[2]It may be inevitable that school is the way it is. I'm not saying\nwe have to redesign it (though I'm not saying we don't), just that\nwe should understand what it does to our attitudes to work — that\nit steers us toward the dutiful plodding kind of work, often using\ncompetition as bait, and away from skating.There are occasionally times when schoolwork becomes a project of\none's own. Whenever I had to write a paper, that would become a\nproject of my own — except in English classes, ironically, because\nthe things one has to write in English classes are so \nbogus. And\nwhen I got to college and started taking CS classes, the programs\nI had to write became projects of my own. Whenever I was writing\nor programming, I was usually skating, and that has been true ever\nsince.So where exactly is the edge of projects of one's own? That's an\ninteresting question, partly because the answer is so complicated,\nand partly because there's so much at stake. There turn out to be\ntwo senses in which work can be one's own: 1) that you're doing it\nvoluntarily, rather than merely because someone told you to, and\n2) that you're doing it by yourself.The edge of the former is quite sharp. People who care a lot about\ntheir work are usually very sensitive to the difference between\npulling, and being pushed, and work tends to fall into one category\nor the other. But the test isn't simply whether you're told to do\nsomething. You can choose to do something you're told to do. Indeed,\nyou can own it far more thoroughly than the person who told you to\ndo it.For example, math homework is for most people something they're\ntold to do. But for my father, who was a mathematician, it wasn't.\nMost of us think of the problems in a math book as a way to test\nor develop our knowledge of the material explained in each section.\nBut to my father the problems were the part that mattered, and the\ntext was merely a sort of annotation. Whenever he got a new math\nbook it was to him like being given a puzzle: here was a new set\nof problems to solve, and he'd immediately set about solving all\nof them.The other sense of a project being one's own — working on it by\noneself — has a much softer edge. It shades gradually into\ncollaboration. And interestingly, it shades into collaboration in\ntwo different ways. One way to collaborate is to share a single\nproject. For example, when two mathematicians collaborate on a proof\nthat takes shape in the course of a conversation between them. The\nother way is when multiple people work on separate projects of their\nown that fit together like a jigsaw puzzle. For example, when one\nperson writes the text of a book and another does the graphic design.\n[3]These two paths into collaboration can of course be combined. But\nunder the right conditions, the excitement of working on a project\nof one's own can be preserved for quite a while before disintegrating\ninto the turbulent flow of work in a large organization. Indeed,\nthe history of successful organizations is partly the history of\ntechniques for preserving that excitement.\n[4]The team that made the original Macintosh were a great example of\nthis phenomenon. People like Burrell Smith and Andy Hertzfeld and\nBill Atkinson and Susan Kare were not just following orders. They\nwere not tennis balls hit by Steve Jobs, but rockets let loose by\nSteve Jobs. There was a lot of collaboration between them, but\nthey all seem to have individually felt the excitement of\nworking on a project of one's own.In Andy Hertzfeld's book on the Macintosh, he describes how they'd\ncome back into the office after dinner and work late into the night.\nPeople who've never experienced the thrill of working on a project\nthey're excited about can't distinguish this kind of working long\nhours from the kind that happens in sweatshops and boiler rooms,\nbut they're at opposite ends of the spectrum. That's why it's a\nmistake to insist dogmatically on \"work/life balance.\" Indeed, the\nmere expression \"work/life\" embodies a mistake: it assumes work and\nlife are distinct. For those to whom the word \"work\" automatically\nimplies the dutiful plodding kind, they are. But for the skaters,\nthe relationship between work and life would be better represented\nby a dash than a slash. I wouldn't want to work on anything that I didn't\nwant to take over my life.Of course, it's easier to achieve this level of motivation when\nyou're making something like the Macintosh. It's easy for something\nnew to feel like a project of your own. That's one of the reasons\nfor the tendency programmers have to rewrite things that don't need\nrewriting, and to write their own versions of things that already\nexist. This sometimes alarms managers, and measured by total number\nof characters typed, it's rarely the optimal solution. But it's not\nalways driven simply by arrogance or cluelessness.\nWriting code from scratch is also much more rewarding — so much\nmore rewarding that a good programmer can end up net ahead, despite\nthe shocking waste of characters. Indeed, it may be one of the\nadvantages of capitalism that it encourages such rewriting. A company\nthat needs software to do something can't use the software already\nwritten to do it at another company, and thus has to write their\nown, which often turns out better.\n[5]The natural alignment between skating and solving new problems is\none of the reasons the payoffs from startups are so high. Not only\nis the market price of unsolved problems higher, you also get a\ndiscount on productivity when you work on them. In fact, you get a\ndouble increase in productivity: when you're doing a clean-sheet\ndesign, it's easier to recruit skaters, and they get to spend all\ntheir time skating.Steve Jobs knew a thing or two about skaters from having watched\nSteve Wozniak. If you can find the right people, you only have to\ntell them what to do at the highest level. They'll handle the\ndetails. Indeed, they insist on it. For a project to feel like your\nown, you must have sufficient autonomy. You can't be working to\norder, or slowed down \nby bureaucracy.One way to ensure autonomy is not to have a boss at all. There are\ntwo ways to do that: to be the boss yourself, and to work on projects\noutside of work. Though they're at opposite ends of the scale\nfinancially, startups and open source projects have a lot in common,\nincluding the fact that they're often run by skaters. And indeed,\nthere's a wormhole from one end of the scale to the other: one of\nthe best ways to discover \nstartup ideas is to work on a project\njust for fun.If your projects are the kind that make money, it's easy to work\non them. It's harder when they're not. And the hardest part, usually,\nis morale. That's where adults have it harder than kids. Kids just\nplunge in and build their treehouse without worrying about whether\nthey're wasting their time, or how it compares to other treehouses.\nAnd frankly we could learn a lot from kids here. The high standards\nmost grownups have for \"real\" work do not always serve us well.The most important phase in a project of one's own is at the\nbeginning: when you go from thinking it might be cool to do x to\nactually doing x. And at that point high standards are not merely\nuseless but positively harmful. There are a few people who start\ntoo many new projects, but far more, I suspect, who are deterred\nby fear of failure from starting projects that would have succeeded\nif they had.But if we couldn't benefit as kids from the knowledge that our\ntreehouses were on the path to grownup projects, we can at least\nbenefit as grownups from knowing that our projects are on a path\nthat stretches back to treehouses. Remember that careless confidence\nyou had as a kid when starting something new? That would be a\npowerful thing to recapture.If it's harder as adults to retain that kind of confidence, we at\nleast tend to be more aware of what we're doing. Kids bounce, or\nare herded, from one kind of work to the next, barely realizing\nwhat's happening to them. Whereas we know more about different types\nof work and have more control over which we do. Ideally we can have\nthe best of both worlds: to be deliberate in choosing to work on\nprojects of our own, and carelessly confident in starting new ones.\nNotes[1]\n\"Hobby\" is a curious word. Now it means work that isn't real\nwork — work that one is not to be judged by — but originally it just\nmeant an obsession in a fairly general sense (even a political\nopinion, for example) that one metaphorically rode as a child rides\na hobby-horse. It's hard to say if its recent, narrower meaning is\na change for the better or the worse. For sure there are lots of\nfalse positives — lots of projects that end up being important but\nare dismissed initially as mere hobbies. But on the other hand, the\nconcept provides valuable cover for projects in the early, ugly\nduckling phase.[2]\nTiger parents, as parents so often do, are fighting the last\nwar. Grades mattered more in the old days when the route to success\nwas to acquire \ncredentials \nwhile ascending some predefined ladder.\nBut it's just as well that their tactics are focused on grades. How\nawful it would be if they invaded the territory of projects, and\nthereby gave their kids a distaste for this kind of work by forcing\nthem to do it. Grades are already a grim, fake world, and aren't\nharmed much by parental interference, but working on one's own\nprojects is a more delicate, private thing that could be damaged\nvery easily.[3]\nThe complicated, gradual edge between working on one's own\nprojects and collaborating with others is one reason there is so\nmuch disagreement about the idea of the \"lone genius.\" In practice\npeople collaborate (or not) in all kinds of different ways, but the\nidea of the lone genius is definitely not a myth. There's a core\nof truth to it that goes with a certain way of working.[4]\nCollaboration is powerful too. The optimal organization would\ncombine collaboration and ownership in such a way as to do the least\ndamage to each. Interestingly, companies and university departments\napproach this ideal from opposite directions: companies insist on\ncollaboration, and occasionally also manage both to recruit skaters\nand allow them to skate, and university departments insist on the\nability to do independent research (which is by custom treated as\nskating, whether it is or not), and the people they hire collaborate\nas much as they choose.[5]\nIf a company could design its software in such a way that the\nbest newly arrived programmers always got a clean sheet, it could\nhave a kind of eternal youth. That might not be impossible. If you\nhad a software backbone defining a game with sufficiently clear\nrules, individual programmers could write their own players.\nThanks to Trevor Blackwell, Paul Buchheit, Andy Hertzfeld, Jessica\nLivingston, and Peter Norvig for reading drafts of this." }, { "path": "data/PaulGrahamEssays/patentpledge.txt", "content": "August 2011I realized recently that we may be able to solve part of the patent\nproblem without waiting for the government.I've never been 100% sure whether patents help or hinder technological\nprogress. When I was a kid I thought they helped. I thought they\nprotected inventors from having their ideas stolen by big companies.\nMaybe that was truer in the past, when more things were physical.\nBut regardless of whether patents are in general a good thing, there\ndo seem to be bad ways of using them. And since bad uses of patents\nseem to be increasing, there is an increasing call for patent reform.The problem with patent reform is that it has to go through the\ngovernment. That tends to be slow. But recently I realized we can\nalso attack the problem downstream. As well as pinching off the\nstream of patents at the point where they're issued, we may in some\ncases be able to pinch it off at the point where they're used.One way of using patents that clearly does not encourage innovation\nis when established companies with bad products use patents to\nsuppress small competitors with good products. This is the type\nof abuse we may be able to decrease without having to go through\nthe government.The way to do it is to get the companies that are above pulling\nthis sort of trick to pledge publicly not to. Then the ones that\nwon't make such a pledge will be very conspicuous. Potential\nemployees won't want to work for them. And investors, too, will\nbe able to see that they're the sort of company that competes by\nlitigation rather than by making good products.Here's the pledge:\n\n No first use of software patents against companies with less \n than 25 people.\n\nI've deliberately traded precision for brevity. The patent pledge\nis not legally binding. It's like Google's \"Don't be evil.\" They\ndon't define what evil is, but by publicly saying that, they're\nsaying they're willing to be held to a standard that, say, Altria\nis not. And though constraining, \"Don't be evil\" has been good for\nGoogle. Technology companies win by attracting the most productive\npeople, and the most productive people are attracted to employers\nwho hold themselves to a higher standard than the law requires.\n[1]The patent pledge is in effect a narrower but open source \"Don't\nbe evil.\" I encourage every technology company to adopt it. If\nyou want to help fix patents, encourage your employer to.Already most technology companies wouldn't sink to using patents\non startups. You don't see Google or Facebook suing startups for\npatent infringement. They don't need to. So for the better technology\ncompanies, the patent pledge requires no change in behavior. They're\njust promising to do what they'd do anyway. And when all the\ncompanies that won't use patents on startups have said so, the\nholdouts will be very conspicuous.The patent pledge doesn't fix every problem with patents. It won't\nstop patent trolls, for example; they're already pariahs. But the\nproblem the patent pledge does fix may be more serious than the\nproblem of patent trolls. Patent trolls are just parasites. A\nclumsy parasite may occasionally kill the host, but that's not its\ngoal. Whereas companies that sue startups for patent infringement\ngenerally do it with explicit goal of keeping their product off the\nmarket.Companies that use patents on startups are attacking innovation at\nthe root. Now there's something any individual can do about this\nproblem, without waiting for the government: ask companies where\nthey stand.\nPatent Pledge Site\nNotes:[1]\nBecause the pledge is deliberately vague, we're going to need\ncommon sense when intepreting it. And even more vice versa: the\npledge is vague in order to make people use common sense when\ninterpreting it.So for example I've deliberately avoided saying whether the 25\npeople have to be employees, or whether contractors count too. If\na company has to split hairs that fine about whether a suit would\nviolate the patent pledge, it's probably still a dick move." }, { "path": "data/PaulGrahamEssays/pgh.txt", "content": "April 2016(This is a talk I gave at an event called Opt412 in Pittsburgh.\nMuch of it will apply to other towns. But not all, because\nas I say in the talk, Pittsburgh has some important advantages over\nmost would-be startup hubs.)What would it take to make Pittsburgh into a startup hub, like\nSilicon Valley? I understand Pittsburgh pretty well,\nbecause I grew up here, in Monroeville. And I understand Silicon\nValley pretty well because that's where I live now. Could you get\nthat kind of startup ecosystem going here?When I agreed to speak here, I didn't think I'd be able to give a\nvery optimistic talk. I thought I'd be talking about what Pittsburgh\ncould do to become a startup hub, very much in the subjunctive.\nInstead I'm going to talk about what Pittsburgh can do.What changed my mind was an article I read in, of all places, the New\nYork Times food section. The title was \"Pittsburgh's Youth-Driven\nFood Boom.\" To most people that might not even sound interesting,\nlet alone something related to startups. But it was electrifying\nto me to read that title. I don't think I could pick a more promising\none if I tried. And when I read the article I got even more excited.\nIt said \"people ages 25 to 29 now make up 7.6 percent of all\nresidents, up from 7 percent about a decade ago.\" Wow, I thought,\nPittsburgh could be the next Portland. It could become the cool\nplace all the people in their twenties want to go live.When I got here a couple days ago, I could feel the difference. I\nlived here from 1968 to 1984. I didn't realize it at the time, but\nduring that whole period the city was in free fall. On top of the\nflight to the suburbs that happened everywhere, the steel and nuclear\nbusinesses were both dying. Boy are things different now. It's not\njust that downtown seems a lot more prosperous. There is an energy\nhere that was not here when I was a kid.When I was a kid, this was a place young people left. Now it's a\nplace that attracts them.What does that have to do with startups? Startups are made\nof people, and the average age of the people in a typical startup\nis right in that 25 to 29 bracket.I've seen how powerful it is for a city to have those people. Five\nyears ago they shifted the center of gravity of Silicon Valley from\nthe peninsula to San Francisco. Google and Facebook are on the\npeninsula, but the next generation of big winners are all in SF.\nThe reason the center of gravity shifted was the talent war, for\nprogrammers especially. Most 25 to 29 year olds want to live in\nthe city, not down in the boring suburbs. So whether they like it\nor not, founders know they have to be in the city. I know multiple\nfounders who would have preferred to live down in the Valley proper,\nbut who made themselves move to SF because they knew otherwise\nthey'd lose the talent war.So being a magnet for people in their twenties is a very promising\nthing to be. It's hard to imagine a place becoming a startup hub\nwithout also being that. When I read that statistic about the\nincreasing percentage of 25 to 29 year olds, I had exactly the same\nfeeling of excitement I get when I see a startup's graphs start to\ncreep upward off the x axis.Nationally the percentage of 25 to 29 year olds is 6.8%. That means\nyou're .8% ahead. The population is 306,000, so we're talking about\na surplus of about 2500 people. That's the population of a small\ntown, and that's just the surplus. So you have a toehold. Now you\njust have to expand it.And though \"youth-driven food boom\" may sound frivolous, it is\nanything but. Restaurants and cafes are a big part of the personality\nof a city. Imagine walking down a street in Paris. What are you\nwalking past? Little restaurants and cafes. Imagine driving through\nsome depressing random exurb. What are you driving past? Starbucks\nand McDonalds and Pizza Hut. As Gertrude Stein said, there is no\nthere there. You could be anywhere.These independent restaurants and cafes are not just feeding people.\nThey're making there be a there here.So here is my first concrete recommendation for turning Pittsburgh\ninto the next Silicon Valley: do everything you can to encourage\nthis youth-driven food boom. What could the city do? Treat the\npeople starting these little restaurants and cafes as your users,\nand go ask them what they want. I can guess at least one thing\nthey might want: a fast permit process. San Francisco has left you\na huge amount of room to beat them in that department.I know restaurants aren't the prime mover though. The prime mover,\nas the Times article said, is cheap housing. That's a big advantage.\nBut that phrase \"cheap housing\" is a bit misleading. There are\nplenty of places that are cheaper. What's special about Pittsburgh\nis not that it's cheap, but that it's a cheap place you'd actually\nwant to live.Part of that is the buildings themselves. I realized a long time\nago, back when I was a poor twenty-something myself, that the best\ndeals were places that had once been rich, and then became poor.\nIf a place has always been rich, it's nice but too expensive. If\na place has always been poor, it's cheap but grim. But if a place\nwas once rich and then got poor, you can find palaces for cheap.\nAnd that's what's bringing people here. When Pittsburgh was rich,\na hundred years ago, the people who lived here built big solid\nbuildings. Not always in the best taste, but definitely solid. So\nhere is another piece of advice for becoming a startup hub: don't\ndestroy the buildings that are bringing people here. When cities\nare on the way back up, like Pittsburgh is now, developers race to\ntear down the old buildings. Don't let that happen. Focus on\nhistoric preservation. Big real estate development projects are\nnot what's bringing the twenty-somethings here. They're the opposite\nof the new restaurants and cafes; they subtract personality from\nthe city.The empirical evidence suggests you cannot be too strict about\nhistoric preservation. The tougher cities are about it, the better\nthey seem to do.But the appeal of Pittsburgh is not just the buildings themselves.\nIt's the neighborhoods they're in. Like San Francisco and New York,\nPittsburgh is fortunate in being a pre-car city. It's not too\nspread out. Because those 25 to 29 year olds do not like driving.\nThey prefer walking, or bicycling, or taking public transport. If\nyou've been to San Francisco recently you can't help noticing the\nhuge number of bicyclists. And this is not just a fad that the\ntwenty-somethings have adopted. In this respect they have discovered\na better way to live. The beards will go, but not the bikes. Cities\nwhere you can get around without driving are just better period.\nSo I would suggest you do everything you can to capitalize on this.\nAs with historic preservation, it seems impossible to go too far.Why not make Pittsburgh the most bicycle and pedestrian friendly\ncity in the country? See if you can go so far that you make San\nFrancisco seem backward by comparison. If you do, it's very unlikely\nyou'll regret it. The city will seem like a paradise to the young\npeople you want to attract. If they do leave to get jobs elsewhere,\nit will be with regret at leaving behind such a place. And what's\nthe downside? Can you imagine a headline \"City ruined by becoming\ntoo bicycle-friendly?\" It just doesn't happen.So suppose cool old neighborhoods and cool little restaurants make\nthis the next Portland. Will that be enough? It will put you in\na way better position than Portland itself, because Pittsburgh has\nsomething Portland lacks: a first-rate research university. CMU\nplus little cafes means you have more than hipsters drinking lattes.\nIt means you have hipsters drinking lattes while talking about\ndistributed systems. Now you're getting really close to San\nFrancisco.In fact you're better off than San Francisco in one way, because\nCMU is downtown, but Stanford and Berkeley are out in the suburbs.What can CMU do to help Pittsburgh become a startup hub? Be an\neven better research university. CMU is one of the best universities\nin the world, but imagine what things would be like if it were the\nvery best, and everyone knew it. There are a lot of ambitious\npeople who must go to the best place, wherever it is. If CMU were it, they would all come here. There would be\nkids in Kazakhstan dreaming of one day living in Pittsburgh.Being that kind of talent magnet is the most important contribution\nuniversities can make toward making their city a startup hub. In\nfact it is practically the only contribution they can make.But wait, shouldn't universities be setting up programs with words\nlike \"innovation\" and \"entrepreneurship\" in their names? No, they\nshould not. These kind of things almost always turn out to be\ndisappointments. They're pursuing the wrong targets. The way to\nget innovation is not to aim for innovation but to aim for something\nmore specific, like better batteries or better 3D printing. And\nthe way to learn about entrepreneurship is to do it, which you \ncan't\nin school.I know it may disappoint some administrators to hear that the best\nthing a university can do to encourage startups is to be a great\nuniversity. It's like telling people who want to lose weight that\nthe way to do it is to eat less.But if you want to know where startups come from, look at the\nempirical evidence. Look at the histories of the most successful\nstartups, and you'll find they grow organically out of a couple of\nfounders building something that starts as an interesting side\nproject. Universities are great at bringing together founders, but\nbeyond that the best thing they can do is get out of the way. For\nexample, by not claiming ownership of \"intellectual property\" that\nstudents and faculty develop, and by having liberal rules about\ndeferred admission and leaves of absence.In fact, one of the most effective things a university could do to\nencourage startups is an elaborate form of getting out of the way\ninvented by Harvard. Harvard used to have exams for the fall\nsemester after Christmas. At the beginning of January they had\nsomething called \"Reading Period\" when you were supposed to be\nstudying for exams. And Microsoft and Facebook have something in\ncommon that few people realize: they were both started during Reading\nPeriod. It's the perfect situation for producing the sort of side\nprojects that turn into startups. The students are all on campus,\nbut they don't have to do anything because they're supposed to be\nstudying for exams.Harvard may have closed this window, because a few years ago they\nmoved exams before Christmas and shortened reading period from 11\ndays to 7. But if a university really wanted to help its students\nstart startups, the empirical evidence, weighted by market cap,\nsuggests the best thing they can do is literally nothing.The culture of Pittsburgh is another of its strengths. It seems\nlike a city has to be socially liberal to be a startup hub,\nand it's pretty clear why. A city has to tolerate strangeness to\nbe a home for startups, because startups are so strange. And you\ncan't choose to allow just the forms of strangeness that will turn\ninto big startups, because they're all intermingled. You have to\ntolerate all strangeness.That immediately rules out big chunks of the US. I'm optimistic\nit doesn't rule out Pittsburgh. One of the things I remember from\ngrowing up here, though I didn't realize at the time that there was\nanything unusual about it, is how well people got along. I'm still\nnot sure why. Maybe one reason was that everyone felt like an\nimmigrant. When I was a kid in Monroeville, people didn't call\nthemselves American. They called themselves Italian or Serbian or\nUkranian. Just imagine what it must have been like here a hundred\nyears ago, when people were pouring in from twenty different\ncountries. Tolerance was the only option.What I remember about the culture of Pittsburgh is that it was\nboth tolerant and pragmatic. That's how I'd describe the culture\nof Silicon Valley too. And it's not a coincidence, because Pittsburgh\nwas the Silicon Valley of its time. This was a city where people\nbuilt new things. And while the things people build have changed,\nthe spirit you need to do that kind of work is the same.So although an influx of latte-swilling hipsters may be annoying\nin some ways, I would go out of my way to encourage them. And more\ngenerally to tolerate strangeness, even unto the degree wacko\nCalifornians do. For Pittsburgh that is a conservative choice:\nit's a return to the city's roots.Unfortunately I saved the toughest part for last. There is one more\nthing you need to be a startup hub, and Pittsburgh hasn't got it:\ninvestors. Silicon Valley has a big investor community because\nit's had 50 years to grow one. New York has a big investor community\nbecause it's full of people who like money a lot and are quick to\nnotice new ways to get it. But Pittsburgh has neither of these.\nAnd the cheap housing that draws other people here has no effect\non investors.If an investor community grows up here, it will happen the same way\nit did in Silicon Valley: slowly and organically. So I would not\nbet on having a big investor community in the short term. But\nfortunately there are three trends that make that less necessary\nthan it used to be. One is that startups are increasingly cheap\nto start, so you just don't need as much outside money as you used\nto. The second is that thanks to things like Kickstarter, a startup\ncan get to revenue faster. You can put something on Kickstarter\nfrom anywhere. The third is programs like Y Combinator. A startup\nfrom anywhere in the world can go to YC for 3 months, pick up\nfunding, and then return home if they want.My advice is to make Pittsburgh a great place for startups, and\ngradually more of them will stick. Some of those will succeed;\nsome of their founders will become investors; and still more startups\nwill stick.This is not a fast path to becoming a startup hub. But it is at\nleast a path, which is something few other cities have. And it's\nnot as if you have to make painful sacrifices in the meantime.\nThink about what I've suggested you should do. Encourage local\nrestaurants, save old buildings, take advantage of density, make\nCMU the best, promote tolerance. These are the things that make\nPittsburgh good to live in now. All I'm saying is that you should\ndo even more of them.And that's an encouraging thought. If Pittsburgh's path to becoming\na startup hub is to be even more itself, then it has a good chance\nof succeeding. In fact it probably has the best chance of any city\nits size. It will take some effort, and a lot of time, but if any\ncity can do it, Pittsburgh can.Thanks to Charlie Cheever and Jessica Livingston for reading\ndrafts of this, and to Meg Cheever for organizing Opt412 and inviting\nme to speak." }, { "path": "data/PaulGrahamEssays/philosophy.txt", "content": "September 2007In high school I decided I was going to study philosophy in college.\nI had several motives, some more honorable than others. One of the\nless honorable was to shock people. College was regarded as job\ntraining where I grew up, so studying philosophy seemed an impressively\nimpractical thing to do. Sort of like slashing holes in your clothes\nor putting a safety pin through your ear, which were other forms\nof impressive impracticality then just coming into fashion.But I had some more honest motives as well. I thought studying\nphilosophy would be a shortcut straight to wisdom. All the people\nmajoring in other things would just end up with a bunch of domain\nknowledge. I would be learning what was really what.I'd tried to read a few philosophy books. Not recent ones; you\nwouldn't find those in our high school library. But I tried to\nread Plato and Aristotle. I doubt I believed I understood them,\nbut they sounded like they were talking about something important.\nI assumed I'd learn what in college.The summer before senior year I took some college classes. I learned\na lot in the calculus class, but I didn't learn much in Philosophy\n101. And yet my plan to study philosophy remained intact. It was\nmy fault I hadn't learned anything. I hadn't read the books we\nwere assigned carefully enough. I'd give Berkeley's Principles\nof Human Knowledge another shot in college. Anything so admired\nand so difficult to read must have something in it, if one could\nonly figure out what.Twenty-six years later, I still don't understand Berkeley. I have\na nice edition of his collected works. Will I ever read it? Seems\nunlikely.The difference between then and now is that now I understand why\nBerkeley is probably not worth trying to understand. I think I see\nnow what went wrong with philosophy, and how we might fix it.WordsI did end up being a philosophy major for most of college. It\ndidn't work out as I'd hoped. I didn't learn any magical truths\ncompared to which everything else was mere domain knowledge. But\nI do at least know now why I didn't. Philosophy doesn't really\nhave a subject matter in the way math or history or most other\nuniversity subjects do. There is no core of knowledge one must\nmaster. The closest you come to that is a knowledge of what various\nindividual philosophers have said about different topics over the\nyears. Few were sufficiently correct that people have forgotten\nwho discovered what they discovered.Formal logic has some subject matter. I took several classes in\nlogic. I don't know if I learned anything from them.\n[1]\nIt does seem to me very important to be able to flip ideas around in\none's head: to see when two ideas don't fully cover the space of\npossibilities, or when one idea is the same as another but with a\ncouple things changed. But did studying logic teach me the importance\nof thinking this way, or make me any better at it? I don't know.There are things I know I learned from studying philosophy. The\nmost dramatic I learned immediately, in the first semester of\nfreshman year, in a class taught by Sydney Shoemaker. I learned\nthat I don't exist. I am (and you are) a collection of cells that\nlurches around driven by various forces, and calls itself I. But\nthere's no central, indivisible thing that your identity goes with.\nYou could conceivably lose half your brain and live. Which means\nyour brain could conceivably be split into two halves and each\ntransplanted into different bodies. Imagine waking up after such\nan operation. You have to imagine being two people.The real lesson here is that the concepts we use in everyday life\nare fuzzy, and break down if pushed too hard. Even a concept as\ndear to us as I. It took me a while to grasp this, but when I\ndid it was fairly sudden, like someone in the nineteenth century\ngrasping evolution and realizing the story of creation they'd been\ntold as a child was all wrong. \n[2]\nOutside of math there's a limit\nto how far you can push words; in fact, it would not be a bad\ndefinition of math to call it the study of terms that have precise\nmeanings. Everyday words are inherently imprecise. They work well\nenough in everyday life that you don't notice. Words seem to work,\njust as Newtonian physics seems to. But you can always make them\nbreak if you push them far enough.I would say that this has been, unfortunately for philosophy, the\ncentral fact of philosophy. Most philosophical debates are not\nmerely afflicted by but driven by confusions over words. Do we\nhave free will? Depends what you mean by \"free.\" Do abstract ideas\nexist? Depends what you mean by \"exist.\"Wittgenstein is popularly credited with the idea that most philosophical\ncontroversies are due to confusions over language. I'm not sure\nhow much credit to give him. I suspect a lot of people realized\nthis, but reacted simply by not studying philosophy, rather than\nbecoming philosophy professors.How did things get this way? Can something people have spent\nthousands of years studying really be a waste of time? Those are\ninteresting questions. In fact, some of the most interesting\nquestions you can ask about philosophy. The most valuable way to\napproach the current philosophical tradition may be neither to get\nlost in pointless speculations like Berkeley, nor to shut them down\nlike Wittgenstein, but to study it as an example of reason gone\nwrong.HistoryWestern philosophy really begins with Socrates, Plato, and Aristotle.\nWhat we know of their predecessors comes from fragments and references\nin later works; their doctrines could be described as speculative\ncosmology that occasionally strays into analysis. Presumably they\nwere driven by whatever makes people in every other society invent\ncosmologies.\n[3]With Socrates, Plato, and particularly Aristotle, this tradition\nturned a corner. There started to be a lot more analysis. I suspect\nPlato and Aristotle were encouraged in this by progress in math.\nMathematicians had by then shown that you could figure things out\nin a much more conclusive way than by making up fine sounding stories\nabout them. \n[4]People talk so much about abstractions now that we don't realize\nwhat a leap it must have been when they first started to. It was\npresumably many thousands of years between when people first started\ndescribing things as hot or cold and when someone asked \"what is\nheat?\" No doubt it was a very gradual process. We don't know if\nPlato or Aristotle were the first to ask any of the questions they\ndid. But their works are the oldest we have that do this on a large\nscale, and there is a freshness (not to say naivete) about them\nthat suggests some of the questions they asked were new to them,\nat least.Aristotle in particular reminds me of the phenomenon that happens\nwhen people discover something new, and are so excited by it that\nthey race through a huge percentage of the newly discovered territory\nin one lifetime. If so, that's evidence of how new this kind of\nthinking was. \n[5]This is all to explain how Plato and Aristotle can be very impressive\nand yet naive and mistaken. It was impressive even to ask the\nquestions they did. That doesn't mean they always came up with\ngood answers. It's not considered insulting to say that ancient\nGreek mathematicians were naive in some respects, or at least lacked\nsome concepts that would have made their lives easier. So I hope\npeople will not be too offended if I propose that ancient philosophers\nwere similarly naive. In particular, they don't seem to have fully\ngrasped what I earlier called the central fact of philosophy: that\nwords break if you push them too far.\"Much to the surprise of the builders of the first digital computers,\"\nRod Brooks wrote, \"programs written for them usually did not work.\"\n[6]\nSomething similar happened when people first started trying\nto talk about abstractions. Much to their surprise, they didn't\narrive at answers they agreed upon. In fact, they rarely seemed\nto arrive at answers at all.They were in effect arguing about artifacts induced by sampling at\ntoo low a resolution.The proof of how useless some of their answers turned out to be is\nhow little effect they have. No one after reading Aristotle's\nMetaphysics does anything differently as a result.\n[7]Surely I'm not claiming that ideas have to have practical applications\nto be interesting? No, they may not have to. Hardy's boast that\nnumber theory had no use whatsoever wouldn't disqualify it. But\nhe turned out to be mistaken. In fact, it's suspiciously hard to\nfind a field of math that truly has no practical use. And Aristotle's\nexplanation of the ultimate goal of philosophy in Book A of the\nMetaphysics implies that philosophy should be useful too.Theoretical KnowledgeAristotle's goal was to find the most general of general principles.\nThe examples he gives are convincing: an ordinary worker builds\nthings a certain way out of habit; a master craftsman can do more\nbecause he grasps the underlying principles. The trend is clear:\nthe more general the knowledge, the more admirable it is. But then\nhe makes a mistake—possibly the most important mistake in the\nhistory of philosophy. He has noticed that theoretical knowledge\nis often acquired for its own sake, out of curiosity, rather than\nfor any practical need. So he proposes there are two kinds of\ntheoretical knowledge: some that's useful in practical matters and\nsome that isn't. Since people interested in the latter are interested\nin it for its own sake, it must be more noble. So he sets as his\ngoal in the Metaphysics the exploration of knowledge that has no\npractical use. Which means no alarms go off when he takes on grand\nbut vaguely understood questions and ends up getting lost in a sea\nof words.His mistake was to confuse motive and result. Certainly, people\nwho want a deep understanding of something are often driven by\ncuriosity rather than any practical need. But that doesn't mean\nwhat they end up learning is useless. It's very valuable in practice\nto have a deep understanding of what you're doing; even if you're\nnever called on to solve advanced problems, you can see shortcuts\nin the solution of simple ones, and your knowledge won't break down\nin edge cases, as it would if you were relying on formulas you\ndidn't understand. Knowledge is power. That's what makes theoretical\nknowledge prestigious. It's also what causes smart people to be\ncurious about certain things and not others; our DNA is not so\ndisinterested as we might think.So while ideas don't have to have immediate practical applications\nto be interesting, the kinds of things we find interesting will\nsurprisingly often turn out to have practical applications.The reason Aristotle didn't get anywhere in the Metaphysics was\npartly that he set off with contradictory aims: to explore the most\nabstract ideas, guided by the assumption that they were useless.\nHe was like an explorer looking for a territory to the north of\nhim, starting with the assumption that it was located to the south.And since his work became the map used by generations of future\nexplorers, he sent them off in the wrong direction as well. \n[8]\nPerhaps worst of all, he protected them from both the criticism of\noutsiders and the promptings of their own inner compass by establishing\nthe principle that the most noble sort of theoretical knowledge had\nto be useless.The Metaphysics is mostly a failed experiment. A few ideas from\nit turned out to be worth keeping; the bulk of it has had no effect\nat all. The Metaphysics is among the least read of all famous\nbooks. It's not hard to understand the way Newton's Principia\nis, but the way a garbled message is.Arguably it's an interesting failed experiment. But unfortunately\nthat was not the conclusion Aristotle's successors derived from\nworks like the Metaphysics. \n[9]\nSoon after, the western world\nfell on intellectual hard times. Instead of version 1s to be\nsuperseded, the works of Plato and Aristotle became revered texts\nto be mastered and discussed. And so things remained for a shockingly\nlong time. It was not till around 1600 (in Europe, where the center\nof gravity had shifted by then) that one found people confident\nenough to treat Aristotle's work as a catalog of mistakes. And\neven then they rarely said so outright.If it seems surprising that the gap was so long, consider how little\nprogress there was in math between Hellenistic times and the\nRenaissance.In the intervening years an unfortunate idea took hold: that it\nwas not only acceptable to produce works like the Metaphysics,\nbut that it was a particularly prestigious line of work, done by a\nclass of people called philosophers. No one thought to go back and\ndebug Aristotle's motivating argument. And so instead of correcting\nthe problem Aristotle discovered by falling into it—that you can\neasily get lost if you talk too loosely about very abstract ideas—they \ncontinued to fall into it.The SingularityCuriously, however, the works they produced continued to attract\nnew readers. Traditional philosophy occupies a kind of singularity\nin this respect. If you write in an unclear way about big ideas,\nyou produce something that seems tantalizingly attractive to\ninexperienced but intellectually ambitious students. Till one knows\nbetter, it's hard to distinguish something that's hard to understand\nbecause the writer was unclear in his own mind from something like\na mathematical proof that's hard to understand because the ideas\nit represents are hard to understand. To someone who hasn't learned\nthe difference, traditional philosophy seems extremely attractive:\nas hard (and therefore impressive) as math, yet broader in scope.\nThat was what lured me in as a high school student.This singularity is even more singular in having its own defense\nbuilt in. When things are hard to understand, people who suspect\nthey're nonsense generally keep quiet. There's no way to prove a\ntext is meaningless. The closest you can get is to show that the\nofficial judges of some class of texts can't distinguish them from\nplacebos. \n[10]And so instead of denouncing philosophy, most people who suspected\nit was a waste of time just studied other things. That alone is\nfairly damning evidence, considering philosophy's claims. It's\nsupposed to be about the ultimate truths. Surely all smart people\nwould be interested in it, if it delivered on that promise.Because philosophy's flaws turned away the sort of people who might\nhave corrected them, they tended to be self-perpetuating. Bertrand\nRussell wrote in a letter in 1912:\n\n Hitherto the people attracted to philosophy have been mostly those\n who loved the big generalizations, which were all wrong, so that\n few people with exact minds have taken up the subject.\n[11]\n\nHis response was to launch Wittgenstein at it, with dramatic results.I think Wittgenstein deserves to be famous not for the discovery\nthat most previous philosophy was a waste of time, which judging\nfrom the circumstantial evidence must have been made by every smart\nperson who studied a little philosophy and declined to pursue it\nfurther, but for how he acted in response.\n[12]\nInstead of quietly\nswitching to another field, he made a fuss, from inside. He was\nGorbachev.The field of philosophy is still shaken from the fright Wittgenstein\ngave it. \n[13]\nLater in life he spent a lot of time talking about\nhow words worked. Since that seems to be allowed, that's what a\nlot of philosophers do now. Meanwhile, sensing a vacuum in the\nmetaphysical speculation department, the people who used to do\nliterary criticism have been edging Kantward, under new names like\n\"literary theory,\" \"critical theory,\" and when they're feeling\nambitious, plain \"theory.\" The writing is the familiar word salad:\n\n Gender is not like some of the other grammatical modes which\n express precisely a mode of conception without any reality that\n corresponds to the conceptual mode, and consequently do not express\n precisely something in reality by which the intellect could be\n moved to conceive a thing the way it does, even where that motive\n is not something in the thing as such.\n [14]\n\nThe singularity I've described is not going away. There's a market\nfor writing that sounds impressive and can't be disproven. There\nwill always be both supply and demand. So if one group abandons\nthis territory, there will always be others ready to occupy it.A ProposalWe may be able to do better. Here's an intriguing possibility.\nPerhaps we should do what Aristotle meant to do, instead of what\nhe did. The goal he announces in the Metaphysics seems one worth\npursuing: to discover the most general truths. That sounds good.\nBut instead of trying to discover them because they're useless,\nlet's try to discover them because they're useful.I propose we try again, but that we use that heretofore despised\ncriterion, applicability, as a guide to keep us from wondering\noff into a swamp of abstractions. Instead of trying to answer the\nquestion:\n\n What are the most general truths?\n\nlet's try to answer the question\n\n Of all the useful things we can say, which are the most general?\n\nThe test of utility I propose is whether we cause people who read\nwhat we've written to do anything differently afterward. Knowing\nwe have to give definite (if implicit) advice will keep us from\nstraying beyond the resolution of the words we're using.The goal is the same as Aristotle's; we just approach it from a\ndifferent direction.As an example of a useful, general idea, consider that of the\ncontrolled experiment. There's an idea that has turned out to be\nwidely applicable. Some might say it's part of science, but it's\nnot part of any specific science; it's literally meta-physics (in\nour sense of \"meta\"). The idea of evolution is another. It turns\nout to have quite broad applications—for example, in genetic\nalgorithms and even product design. Frankfurt's distinction between\nlying and bullshitting seems a promising recent example.\n[15]These seem to me what philosophy should look like: quite general\nobservations that would cause someone who understood them to do\nsomething differently.Such observations will necessarily be about things that are imprecisely\ndefined. Once you start using words with precise meanings, you're\ndoing math. So starting from utility won't entirely solve the\nproblem I described above—it won't flush out the metaphysical\nsingularity. But it should help. It gives people with good\nintentions a new roadmap into abstraction. And they may thereby\nproduce things that make the writing of the people with bad intentions\nlook bad by comparison.One drawback of this approach is that it won't produce the sort of\nwriting that gets you tenure. And not just because it's not currently\nthe fashion. In order to get tenure in any field you must not\narrive at conclusions that members of tenure committees can disagree\nwith. In practice there are two kinds of solutions to this problem.\nIn math and the sciences, you can prove what you're saying, or at\nany rate adjust your conclusions so you're not claiming anything\nfalse (\"6 of 8 subjects had lower blood pressure after the treatment\").\nIn the humanities you can either avoid drawing any definite conclusions\n(e.g. conclude that an issue is a complex one), or draw conclusions\nso narrow that no one cares enough to disagree with you.The kind of philosophy I'm advocating won't be able to take either\nof these routes. At best you'll be able to achieve the essayist's\nstandard of proof, not the mathematician's or the experimentalist's.\nAnd yet you won't be able to meet the usefulness test without\nimplying definite and fairly broadly applicable conclusions. Worse\nstill, the usefulness test will tend to produce results that annoy\npeople: there's no use in telling people things they already believe,\nand people are often upset to be told things they don't.Here's the exciting thing, though. Anyone can do this. Getting\nto general plus useful by starting with useful and cranking up the\ngenerality may be unsuitable for junior professors trying to get\ntenure, but it's better for everyone else, including professors who\nalready have it. This side of the mountain is a nice gradual slope.\nYou can start by writing things that are useful but very specific,\nand then gradually make them more general. Joe's has good burritos.\nWhat makes a good burrito? What makes good food? What makes\nanything good? You can take as long as you want. You don't have\nto get all the way to the top of the mountain. You don't have to\ntell anyone you're doing philosophy.If it seems like a daunting task to do philosophy, here's an\nencouraging thought. The field is a lot younger than it seems.\nThough the first philosophers in the western tradition lived about\n2500 years ago, it would be misleading to say the field is 2500\nyears old, because for most of that time the leading practitioners\nweren't doing much more than writing commentaries on Plato or\nAristotle while watching over their shoulders for the next invading\narmy. In the times when they weren't, philosophy was hopelessly\nintermingled with religion. It didn't shake itself free till a\ncouple hundred years ago, and even then was afflicted by the\nstructural problems I've described above. If I say this, some will\nsay it's a ridiculously overbroad and uncharitable generalization,\nand others will say it's old news, but here goes: judging from their\nworks, most philosophers up to the present have been wasting their\ntime. So in a sense the field is still at the first step. \n[16]That sounds a preposterous claim to make. It won't seem so\npreposterous in 10,000 years. Civilization always seems old, because\nit's always the oldest it's ever been. The only way to say whether\nsomething is really old or not is by looking at structural evidence,\nand structurally philosophy is young; it's still reeling from the\nunexpected breakdown of words.Philosophy is as young now as math was in 1500. There is a lot\nmore to discover.Notes\n[1]\nIn practice formal logic is not much use, because despite\nsome progress in the last 150 years we're still only able to formalize\na small percentage of statements. We may never do that much better,\nfor the same reason 1980s-style \"knowledge representation\" could\nnever have worked; many statements may have no representation more\nconcise than a huge, analog brain state.[2]\nIt was harder for Darwin's contemporaries to grasp this than\nwe can easily imagine. The story of creation in the Bible is not\njust a Judeo-Christian concept; it's roughly what everyone must\nhave believed since before people were people. The hard part of\ngrasping evolution was to realize that species weren't, as they\nseem to be, unchanging, but had instead evolved from different,\nsimpler organisms over unimaginably long periods of time.Now we don't have to make that leap. No one in an industrialized\ncountry encounters the idea of evolution for the first time as an\nadult. Everyone's taught about it as a child, either as truth or\nheresy.[3]\nGreek philosophers before Plato wrote in verse. This must\nhave affected what they said. If you try to write about the nature\nof the world in verse, it inevitably turns into incantation. Prose\nlets you be more precise, and more tentative.[4]\nPhilosophy is like math's\nne'er-do-well brother. It was born when Plato and Aristotle looked\nat the works of their predecessors and said in effect \"why can't\nyou be more like your brother?\" Russell was still saying the same\nthing 2300 years later.Math is the precise half of the most abstract ideas, and philosophy\nthe imprecise half. It's probably inevitable that philosophy will\nsuffer by comparison, because there's no lower bound to its precision.\nBad math is merely boring, whereas bad philosophy is nonsense. And\nyet there are some good ideas in the imprecise half.[5]\nAristotle's best work was in logic and zoology, both of which\nhe can be said to have invented. But the most dramatic departure\nfrom his predecessors was a new, much more analytical style of\nthinking. He was arguably the first scientist.[6]\nBrooks, Rodney, Programming in Common Lisp, Wiley, 1985, p.\n94.[7]\nSome would say we depend on Aristotle more than we realize,\nbecause his ideas were one of the ingredients in our common culture.\nCertainly a lot of the words we use have a connection with Aristotle,\nbut it seems a bit much to suggest that we wouldn't have the concept\nof the essence of something or the distinction between matter and\nform if Aristotle hadn't written about them.One way to see how much we really depend on Aristotle would be to\ndiff European culture with Chinese: what ideas did European culture\nhave in 1800 that Chinese culture didn't, in virtue of Aristotle's\ncontribution?[8]\nThe meaning of the word \"philosophy\" has changed over time.\nIn ancient times it covered a broad range of topics, comparable in\nscope to our \"scholarship\" (though without the methodological\nimplications). Even as late as Newton's time it included what we\nnow call \"science.\" But core of the subject today is still what\nseemed to Aristotle the core: the attempt to discover the most\ngeneral truths.Aristotle didn't call this \"metaphysics.\" That name got assigned\nto it because the books we now call the Metaphysics came after\n(meta = after) the Physics in the standard edition of Aristotle's\nworks compiled by Andronicus of Rhodes three centuries later. What\nwe call \"metaphysics\" Aristotle called \"first philosophy.\"[9]\nSome of Aristotle's immediate successors may have realized\nthis, but it's hard to say because most of their works are lost.[10]\nSokal, Alan, \"Transgressing the Boundaries: Toward a Transformative\nHermeneutics of Quantum Gravity,\" Social Text 46/47, pp. 217-252.Abstract-sounding nonsense seems to be most attractive when it's\naligned with some axe the audience already has to grind. If this\nis so we should find it's most popular with groups that are (or\nfeel) weak. The powerful don't need its reassurance.[11]\nLetter to Ottoline Morrell, December 1912. Quoted in:Monk, Ray, Ludwig Wittgenstein: The Duty of Genius, Penguin, 1991,\np. 75.[12]\nA preliminary result, that all metaphysics between Aristotle\nand 1783 had been a waste of time, is due to I. Kant.[13]\nWittgenstein asserted a sort of mastery to which the inhabitants\nof early 20th century Cambridge seem to have been peculiarly\nvulnerable—perhaps partly because so many had been raised religious\nand then stopped believing, so had a vacant space in their heads\nfor someone to tell them what to do (others chose Marx or Cardinal\nNewman), and partly because a quiet, earnest place like Cambridge\nin that era had no natural immunity to messianic figures, just as\nEuropean politics then had no natural immunity to dictators.[14]\nThis is actually from the Ordinatio of Duns Scotus (ca.\n1300), with \"number\" replaced by \"gender.\" Plus ca change.Wolter, Allan (trans), Duns Scotus: Philosophical Writings, Nelson,\n1963, p. 92.[15]\nFrankfurt, Harry, On Bullshit, Princeton University Press,\n2005.[16]\nSome introductions to philosophy now take the line that\nphilosophy is worth studying as a process rather than for any\nparticular truths you'll learn. The philosophers whose works they\ncover would be rolling in their graves at that. They hoped they\nwere doing more than serving as examples of how to argue: they hoped\nthey were getting results. Most were wrong, but it doesn't seem\nan impossible hope.This argument seems to me like someone in 1500 looking at the lack\nof results achieved by alchemy and saying its value was as a process.\nNo, they were going about it wrong. It turns out it is possible\nto transmute lead into gold (though not economically at current\nenergy prices), but the route to that knowledge was to\nbacktrack and try another approach.Thanks to Trevor Blackwell, Paul Buchheit, Jessica Livingston, \nRobert Morris, Mark Nitzberg, and Peter Norvig for reading drafts of this." }, { "path": "data/PaulGrahamEssays/pinch.txt", "content": "December 2014Many startups go through a point a few months before they die where\nalthough they have a significant amount of money in the bank, they're\nalso losing a lot each month, and revenue growth is either nonexistent\nor mediocre. The company has, say, 6 months of runway. Or to put\nit more brutally, 6 months before they're out of business. They\nexpect to avoid that by raising more from investors.\n[1]That last sentence is the fatal one.There may be nothing founders are so prone to delude themselves\nabout as how interested investors will be in giving them additional\nfunding. It's hard to convince investors the first time too, but\nfounders expect that. What bites them the second time is a confluence\nof three forces:\n\n The company is spending more now than it did the first time\n it raised money. Investors have much higher standards for companies that have\n already raised money. The company is now starting to read as a failure. The first\n time it raised money, it was neither a success nor a failure; it\n was too early to ask. Now it's possible to ask that question, and\n the default answer is failure, because at this point that is the\n default outcome.\n\nI'm going to call the situation I described in the first paragraph \"the fatal pinch.\" I try to resist\ncoining phrases, but making up a name for this situation may snap\nfounders into realizing when they're in it.One of the things that makes the fatal pinch so dangerous is\nthat it's self-reinforcing. Founders overestimate their chances\nof raising more money, and so are slack about reaching\nprofitability, which further decreases their chances of raising\nmoney.Now that you know about the fatal pinch, how do you avoid it? Y Combinator tells\nfounders who raise money to act as if it's the last they'll ever\nget. Because the self-reinforcing nature of this situation works\nthe other way too: the less you need further investment, the easier\nit is to get.What do you do if you're already in the fatal pinch? The\nfirst step is to re-evaluate the probability of raising more money.\nI will now, by an amazing feat of clairvoyance, do this for you:\nthe probability is zero. \n[2]Three options remain: you can shut down the company, you can increase\nhow much you make, and you can decrease how much you spend.You should shut down the company if you're certain it will\nfail no matter what you do. Then at least you can give back the\nmoney you have left, and save yourself however many months you would\nhave spent riding it down.Companies rarely have to fail though. What I'm really doing\nhere is giving you the option of admitting you've already given up.If you don't want to shut down the company, that leaves increasing\nrevenues and decreasing expenses. In most startups, expenses =\npeople, and decreasing expenses = firing people.\n[3]\nDeciding to\nfire people is usually hard, but there's one case in which it\nshouldn't be: when there are people you already know you should\nfire but you're in denial about it. If so, now's the time.If that makes you profitable, or will enable you to make it to\nprofitability on the money you have left, you've avoided the immediate\ndanger.Otherwise you have three options: you either have to fire good\npeople, get some or all of the employees to take less salary for a\nwhile, or increase revenues.Getting people to take less salary is a weak solution that will\nonly work when the problem isn't too bad. If your current trajectory\nwon't quite get you to profitability but you can get over the threshold\nby cutting salaries a little,\nyou might be able to make the case to everyone for doing it.\nOtherwise you're probably just postponing the problem, and that\nwill be obvious to the people whose salaries you're proposing to\ncut.\n[4]Which leaves two options, firing good people and making more money.\nWhile trying to balance them, keep in mind the eventual goal: to be\na successful product company in the sense of having a single thing\nlots of people use.You should lean more toward firing people if the source of your\ntrouble is overhiring. If you went out and hired 15 people before\nyou even knew what you were building, you've created a broken\ncompany. You need to figure out what you're building, and it will\nprobably be easier to do that with a handful of people than 15.\nPlus those 15 people might not even be the ones you need for whatever\nyou end up building. So the solution may be to shrink and then\nfigure out what direction to grow in. After all, you're not doing\nthose 15 people any favors if you fly the company into ground with\nthem aboard. They'll all lose their jobs eventually, along with\nall the time they expended on this doomed company.Whereas if you only have a handful of people, it may be better to\nfocus on trying to make more money. It may seem facile to suggest\na startup make more money, as if that could be done for the asking.\nUsually a startup is already trying as hard as it can to sell\nwhatever it sells. What I'm suggesting here is not so much to try\nharder to make money but to try to make money in a different way.\nFor example, if you have only one person selling while the rest are\nwriting code, consider having everyone work on selling. What good\nwill more code do you when you're out of business? \nIf you have to write code to close a certain deal, go ahead;\nthat follows from everyone working on selling. But only work on\nwhatever will get you the most revenue the soonest.Another way to make money differently is to sell different things,\nand in particular to do more consultingish work. I say consultingish\nbecause there is a long slippery slope from making products to pure\nconsulting, and you don't have to go far down it before you start\nto offer something really attractive to customers. Although your\nproduct may not be very appealing yet, if you're a startup your\nprogrammers will often be way better than the ones your customers\nhave. Or you may have expertise in some new field they\ndon't understand. So if you change your sales conversations\njust a little from \"do you want to buy our product?\" to \"what do\nyou need that you'd pay a lot for?\" you may find it's suddenly a\nlot easier to extract money from customers.Be ruthlessly mercenary when you start doing this, though. You're\ntrying to save your company from death here, so make customers pay\na lot, quickly. And to the extent you can, try to avoid the\nworst pitfalls of consulting. The ideal thing might be if you built\na precisely defined derivative version of your product for the\ncustomer, and it was otherwise a straight product sale. You keep\nthe IP and no billing by the hour.In the best case, this consultingish work may not be just something\nyou do to survive, but may turn out to be the thing-that-doesn't-scale that defines your\ncompany. Don't expect it to be, but as you dive into individual\nusers' needs, keep your eyes open for narrow openings that have\nwide vistas beyond.There is usually so much demand for custom work that unless you're\nreally incompetent there has to be some point down the slope of\nconsulting at which you can survive. But I didn't use the term\nslippery slope by accident; customers' insatiable demand for custom\nwork will always be pushing you toward the bottom. So while you'll\nprobably survive, the problem now becomes to survive with the least\ndamage and distraction.The good news is, plenty of successful startups have passed through\nnear-death experiences and gone on to flourish. You just have to\nrealize in time that you're near death. And if you're in the fatal pinch,\nyou are.\nNotes[1]\nThere are a handful of companies that can't reasonably expect\nto make money for the first year or two, because what they're\nbuilding takes so long. For these companies substitute \"progress\"\nfor \"revenue growth.\" You're not one of these companies unless\nyour initial investors agreed in advance that you were. And frankly\neven these companies wish they weren't, because the illiquidity of\n\"progress\" puts them at the mercy of investors.[2]\nThere's a variant of the fatal pinch where your existing\ninvestors help you along by promising to invest more. Or rather,\nwhere you read them as promising to invest more, while they think\nthey're just mentioning the possibility. The way to solve this\nproblem, if you have 8 months of runway or less, is to try to get\nthe money right now. Then you'll either get the money, in which\ncase (immediate) problem solved, or at least prevent your investors\nfrom helping you to remain in denial about your fundraising prospects.[3]\nObviously, if you have significant expenses other than salaries\nthat you can eliminate, do it now.[4]\nUnless of course the source of the problem is that you're paying\nyourselves high salaries. If by cutting the founders' salaries to\nthe minimum you need, you can make it to profitability, you should.\nBut it's a bad sign if you needed to read this to realize that.\nThanks to Sam Altman, Paul Buchheit, Jessica Livingston, and\nGeoff Ralston for reading drafts of this." }, { "path": "data/PaulGrahamEssays/polls.txt", "content": "November 2004\nA lot of people are writing now about \nwhy Kerry lost. Here I want to\nexamine a more specific question: why were the exit polls so \nwrong?In Ohio, which Kerry ultimately\nlost 49-51, exit polls gave him a 52-48 victory. And this wasn't just\nrandom error. In every swing state they overestimated the Kerry vote.\nIn Florida, which Bush ultimately won 52-47, exit polls predicted\na dead heat.(These are not early numbers. They're from about midnight eastern time, \nlong after polls closed in Ohio and Florida. And yet by the\nnext afternoon the exit poll numbers online corresponded to the returns. \nThe only way I can imagine this happening is if those in\ncharge of the exit polls cooked the books after seeing the actual\nreturns. But that's another issue.)What happened? The source of the problem may be a variant of\nthe Bradley Effect. \nThis term\nwas invented after Tom Bradley, the black mayor of Los Angeles, \nlost an election for governor of California despite a comfortable\nlead in the polls. Apparently voters were afraid to say \nthey planned to vote against him, lest their motives be\n(perhaps correctly) suspected.It seems likely that something similar happened in exit polls this year.\nIn theory, exit polls ought to be very accurate. \nYou're not asking people what they would do. You're\nasking what they just did.How can you get errors asking that? Because some people don't\nrespond. To get a truly random sample, pollsters ask, say, every\n20th person leaving the polling place who they voted for. But not\neveryone wants to answer. And the pollsters can't simply ignore\nthose who won't, or their sample isn't random anymore. So what\nthey do, apparently, is note down the age and race and sex of the\nperson, and guess from that who they voted for.This works so long as there is no correlation between who people\nvote for and whether they're willing to talk about it. But this\nyear there may have been. It may be that a significant number of \nthose who voted for\nBush didn't want to say so.Why not? Because people in the US are more conservative than they're\nwilling to admit. The values of the elite in this country, at least\nat the moment, are NPR values. The average person, as I think both\nRepublicans and Democrats would agree, is more socially conservative. \nBut while some openly flaunt the fact that they don't share the\nopinions of the elite, others feel a little nervous about it, as \nif they had bad table manners.For example, according to current NPR values, you \ncan't say anything that might be \nperceived as disparaging towards homosexuals. To do \nso is \"homophobic.\" And yet a large number of Americans are deeply\nreligious, and the Bible is quite explicit on the subject of\nhomosexuality. What are they to do? I think what many do is keep \ntheir opinions, but keep them to themselves.They know what they believe, but they also know what they're supposed\nto believe.\nAnd so when a stranger (for example, a pollster) asks\nthem their opinion about something like gay marriage, they will not\nalways say what they really think.When the values of the elite are liberal, polls will tend to\nunderestimate the conservativeness of ordinary voters. This seems\nto me the leading theory to explain why the exit polls were so \nfar off this year. NPR values \nsaid one ought to vote for Kerry. So all the people who voted for\nKerry felt virtuous for doing so, and were eager to tell pollsters\nthey had. No one who voted for Kerry did it as an act of quiet\ndefiance." }, { "path": "data/PaulGrahamEssays/popular.txt", "content": "May 2001(This article was written as a kind of business plan for a\nnew language.\nSo it is missing (because it takes for granted) the most important\nfeature of a good programming language: very powerful abstractions.)A friend of mine once told an eminent operating systems\nexpert that he wanted to design a really good\nprogramming language. The expert told him that it would be a\nwaste of time, that programming languages don't become popular\nor unpopular based on their merits, and so no matter how\ngood his language was, no one would use it. At least, that\nwas what had happened to the language he had designed.What does make a language popular? Do popular\nlanguages deserve their popularity? Is it worth trying to\ndefine a good programming language? How would you do it?I think the answers to these questions can be found by looking \nat hackers, and learning what they want. Programming\nlanguages are for hackers, and a programming language\nis good as a programming language (rather than, say, an\nexercise in denotational semantics or compiler design)\nif and only if hackers like it.1 The Mechanics of PopularityIt's true, certainly, that most people don't choose programming\nlanguages simply based on their merits. Most programmers are told\nwhat language to use by someone else. And yet I think the effect\nof such external factors on the popularity of programming languages\nis not as great as it's sometimes thought to be. I think a bigger\nproblem is that a hacker's idea of a good programming language is\nnot the same as most language designers'.Between the two, the hacker's opinion is the one that matters.\nProgramming languages are not theorems. They're tools, designed\nfor people, and they have to be designed to suit human strengths\nand weaknesses as much as shoes have to be designed for human feet.\nIf a shoe pinches when you put it on, it's a bad shoe, however\nelegant it may be as a piece of sculpture.It may be that the majority of programmers can't tell a good language\nfrom a bad one. But that's no different with any other tool. It\ndoesn't mean that it's a waste of time to try designing a good\nlanguage. Expert hackers \ncan tell a good language when they see\none, and they'll use it. Expert hackers are a tiny minority,\nadmittedly, but that tiny minority write all the good software,\nand their influence is such that the rest of the programmers will\ntend to use whatever language they use. Often, indeed, it is not\nmerely influence but command: often the expert hackers are the very\npeople who, as their bosses or faculty advisors, tell the other\nprogrammers what language to use.The opinion of expert hackers is not the only force that determines\nthe relative popularity of programming languages — legacy software\n(Cobol) and hype (Ada, Java) also play a role — but I think it is\nthe most powerful force over the long term. Given an initial critical\nmass and enough time, a programming language probably becomes about\nas popular as it deserves to be. And popularity further separates\ngood languages from bad ones, because feedback from real live users\nalways leads to improvements. Look at how much any popular language\nhas changed during its life. Perl and Fortran are extreme cases,\nbut even Lisp has changed a lot. Lisp 1.5 didn't have macros, for\nexample; these evolved later, after hackers at MIT had spent a\ncouple years using Lisp to write real programs. [1]So whether or not a language has to be good to be popular, I think\na language has to be popular to be good. And it has to stay popular\nto stay good. The state of the art in programming languages doesn't\nstand still. And yet the Lisps we have today are still pretty much\nwhat they had at MIT in the mid-1980s, because that's the last time\nLisp had a sufficiently large and demanding user base.Of course, hackers have to know about a language before they can\nuse it. How are they to hear? From other hackers. But there has to\nbe some initial group of hackers using the language for others even\nto hear about it. I wonder how large this group has to be; how many\nusers make a critical mass? Off the top of my head, I'd say twenty.\nIf a language had twenty separate users, meaning twenty users who\ndecided on their own to use it, I'd consider it to be real.Getting there can't be easy. I would not be surprised if it is\nharder to get from zero to twenty than from twenty to a thousand.\nThe best way to get those initial twenty users is probably to use\na trojan horse: to give people an application they want, which\nhappens to be written in the new language.2 External FactorsLet's start by acknowledging one external factor that does affect\nthe popularity of a programming language. To become popular, a\nprogramming language has to be the scripting language of a popular\nsystem. Fortran and Cobol were the scripting languages of early\nIBM mainframes. C was the scripting language of Unix, and so, later,\nwas Perl. Tcl is the scripting language of Tk. Java and Javascript\nare intended to be the scripting languages of web browsers.Lisp is not a massively popular language because it is not the\nscripting language of a massively popular system. What popularity\nit retains dates back to the 1960s and 1970s, when it was the\nscripting language of MIT. A lot of the great programmers of the\nday were associated with MIT at some point. And in the early 1970s,\nbefore C, MIT's dialect of Lisp, called MacLisp, was one of the\nonly programming languages a serious hacker would want to use.Today Lisp is the scripting language of two moderately popular\nsystems, Emacs and Autocad, and for that reason I suspect that most\nof the Lisp programming done today is done in Emacs Lisp or AutoLisp.Programming languages don't exist in isolation. To hack is a\ntransitive verb — hackers are usually hacking something — and in\npractice languages are judged relative to whatever they're used to\nhack. So if you want to design a popular language, you either have\nto supply more than a language, or you have to design your language\nto replace the scripting language of some existing system.Common Lisp is unpopular partly because it's an orphan. It did\noriginally come with a system to hack: the Lisp Machine. But Lisp\nMachines (along with parallel computers) were steamrollered by the\nincreasing power of general purpose processors in the 1980s. Common\nLisp might have remained popular if it had been a good scripting\nlanguage for Unix. It is, alas, an atrociously bad one.One way to describe this situation is to say that a language isn't\njudged on its own merits. Another view is that a programming language\nreally isn't a programming language unless it's also the scripting\nlanguage of something. This only seems unfair if it comes as a\nsurprise. I think it's no more unfair than expecting a programming\nlanguage to have, say, an implementation. It's just part of what\na programming language is.A programming language does need a good implementation, of course,\nand this must be free. Companies will pay for software, but individual\nhackers won't, and it's the hackers you need to attract.A language also needs to have a book about it. The book should be\nthin, well-written, and full of good examples. K&R is the ideal\nhere. At the moment I'd almost say that a language has to have a\nbook published by O'Reilly. That's becoming the test of mattering\nto hackers.There should be online documentation as well. In fact, the book\ncan start as online documentation. But I don't think that physical\nbooks are outmoded yet. Their format is convenient, and the de\nfacto censorship imposed by publishers is a useful if imperfect\nfilter. Bookstores are one of the most important places for learning\nabout new languages.3 BrevityGiven that you can supply the three things any language needs — a\nfree implementation, a book, and something to hack — how do you\nmake a language that hackers will like?One thing hackers like is brevity. Hackers are lazy, in the same\nway that mathematicians and modernist architects are lazy: they\nhate anything extraneous. It would not be far from the truth to\nsay that a hacker about to write a program decides what language\nto use, at least subconsciously, based on the total number of\ncharacters he'll have to type. If this isn't precisely how hackers\nthink, a language designer would do well to act as if it were.It is a mistake to try to baby the user with long-winded expressions\nthat are meant to resemble English. Cobol is notorious for this\nflaw. A hacker would consider being asked to writeadd x to y giving zinstead ofz = x+yas something between an insult to his intelligence and a sin against\nGod.It has sometimes been said that Lisp should use first and rest\ninstead of car and cdr, because it would make programs easier to\nread. Maybe for the first couple hours. But a hacker can learn\nquickly enough that car means the first element of a list and cdr\nmeans the rest. Using first and rest means 50% more typing. And\nthey are also different lengths, meaning that the arguments won't\nline up when they're called, as car and cdr often are, in successive\nlines. I've found that it matters a lot how code lines up on the\npage. I can barely read Lisp code when it is set in a variable-width\nfont, and friends say this is true for other languages too.Brevity is one place where strongly typed languages lose. All other\nthings being equal, no one wants to begin a program with a bunch\nof declarations. Anything that can be implicit, should be.The individual tokens should be short as well. Perl and Common Lisp\noccupy opposite poles on this question. Perl programs can be almost\ncryptically dense, while the names of built-in Common Lisp operators\nare comically long. The designers of Common Lisp probably expected\nusers to have text editors that would type these long names for\nthem. But the cost of a long name is not just the cost of typing\nit. There is also the cost of reading it, and the cost of the space\nit takes up on your screen.4 HackabilityThere is one thing more important than brevity to a hacker: being\nable to do what you want. In the history of programming languages\na surprising amount of effort has gone into preventing programmers\nfrom doing things considered to be improper. This is a dangerously\npresumptuous plan. How can the language designer know what the\nprogrammer is going to need to do? I think language designers would\ndo better to consider their target user to be a genius who will\nneed to do things they never anticipated, rather than a bumbler\nwho needs to be protected from himself. The bumbler will shoot\nhimself in the foot anyway. You may save him from referring to\nvariables in another package, but you can't save him from writing\na badly designed program to solve the wrong problem, and taking\nforever to do it.Good programmers often want to do dangerous and unsavory things.\nBy unsavory I mean things that go behind whatever semantic facade\nthe language is trying to present: getting hold of the internal\nrepresentation of some high-level abstraction, for example. Hackers\nlike to hack, and hacking means getting inside things and second\nguessing the original designer.Let yourself be second guessed. When you make any tool, people use\nit in ways you didn't intend, and this is especially true of a\nhighly articulated tool like a programming language. Many a hacker\nwill want to tweak your semantic model in a way that you never\nimagined. I say, let them; give the programmer access to as much\ninternal stuff as you can without endangering runtime systems like\nthe garbage collector.In Common Lisp I have often wanted to iterate through the fields\nof a struct — to comb out references to a deleted object, for example,\nor find fields that are uninitialized. I know the structs are just\nvectors underneath. And yet I can't write a general purpose function\nthat I can call on any struct. I can only access the fields by\nname, because that's what a struct is supposed to mean.A hacker may only want to subvert the intended model of things once\nor twice in a big program. But what a difference it makes to be\nable to. And it may be more than a question of just solving a\nproblem. There is a kind of pleasure here too. Hackers share the\nsurgeon's secret pleasure in poking about in gross innards, the\nteenager's secret pleasure in popping zits. [2] For boys, at least,\ncertain kinds of horrors are fascinating. Maxim magazine publishes\nan annual volume of photographs, containing a mix of pin-ups and\ngrisly accidents. They know their audience.Historically, Lisp has been good at letting hackers have their way.\nThe political correctness of Common Lisp is an aberration. Early\nLisps let you get your hands on everything. A good deal of that\nspirit is, fortunately, preserved in macros. What a wonderful thing,\nto be able to make arbitrary transformations on the source code.Classic macros are a real hacker's tool — simple, powerful, and\ndangerous. It's so easy to understand what they do: you call a\nfunction on the macro's arguments, and whatever it returns gets\ninserted in place of the macro call. Hygienic macros embody the\nopposite principle. They try to protect you from understanding what\nthey're doing. I have never heard hygienic macros explained in one\nsentence. And they are a classic example of the dangers of deciding\nwhat programmers are allowed to want. Hygienic macros are intended\nto protect me from variable capture, among other things, but variable\ncapture is exactly what I want in some macros.A really good language should be both clean and dirty: cleanly\ndesigned, with a small core of well understood and highly orthogonal\noperators, but dirty in the sense that it lets hackers have their\nway with it. C is like this. So were the early Lisps. A real hacker's\nlanguage will always have a slightly raffish character.A good programming language should have features that make the kind\nof people who use the phrase \"software engineering\" shake their\nheads disapprovingly. At the other end of the continuum are languages\nlike Ada and Pascal, models of propriety that are good for teaching\nand not much else.5 Throwaway ProgramsTo be attractive to hackers, a language must be good for writing\nthe kinds of programs they want to write. And that means, perhaps\nsurprisingly, that it has to be good for writing throwaway programs.A throwaway program is a program you write quickly for some limited\ntask: a program to automate some system administration task, or\ngenerate test data for a simulation, or convert data from one format\nto another. The surprising thing about throwaway programs is that,\nlike the \"temporary\" buildings built at so many American universities\nduring World War II, they often don't get thrown away. Many evolve\ninto real programs, with real features and real users.I have a hunch that the best big programs begin life this way,\nrather than being designed big from the start, like the Hoover Dam.\nIt's terrifying to build something big from scratch. When people\ntake on a project that's too big, they become overwhelmed. The\nproject either gets bogged down, or the result is sterile and\nwooden: a shopping mall rather than a real downtown, Brasilia rather\nthan Rome, Ada rather than C.Another way to get a big program is to start with a throwaway\nprogram and keep improving it. This approach is less daunting, and\nthe design of the program benefits from evolution. I think, if one\nlooked, that this would turn out to be the way most big programs\nwere developed. And those that did evolve this way are probably\nstill written in whatever language they were first written in,\nbecause it's rare for a program to be ported, except for political\nreasons. And so, paradoxically, if you want to make a language that\nis used for big systems, you have to make it good for writing\nthrowaway programs, because that's where big systems come from.Perl is a striking example of this idea. It was not only designed\nfor writing throwaway programs, but was pretty much a throwaway\nprogram itself. Perl began life as a collection of utilities for\ngenerating reports, and only evolved into a programming language\nas the throwaway programs people wrote in it grew larger. It was\nnot until Perl 5 (if then) that the language was suitable for\nwriting serious programs, and yet it was already massively popular.What makes a language good for throwaway programs? To start with,\nit must be readily available. A throwaway program is something that\nyou expect to write in an hour. So the language probably must\nalready be installed on the computer you're using. It can't be\nsomething you have to install before you use it. It has to be there.\nC was there because it came with the operating system. Perl was\nthere because it was originally a tool for system administrators,\nand yours had already installed it.Being available means more than being installed, though. An\ninteractive language, with a command-line interface, is more\navailable than one that you have to compile and run separately. A\npopular programming language should be interactive, and start up\nfast.Another thing you want in a throwaway program is brevity. Brevity\nis always attractive to hackers, and never more so than in a program\nthey expect to turn out in an hour.6 LibrariesOf course the ultimate in brevity is to have the program already\nwritten for you, and merely to call it. And this brings us to what\nI think will be an increasingly important feature of programming\nlanguages: library functions. Perl wins because it has large\nlibraries for manipulating strings. This class of library functions\nare especially important for throwaway programs, which are often\noriginally written for converting or extracting data. Many Perl\nprograms probably begin as just a couple library calls stuck\ntogether.I think a lot of the advances that happen in programming languages\nin the next fifty years will have to do with library functions. I\nthink future programming languages will have libraries that are as\ncarefully designed as the core language. Programming language design\nwill not be about whether to make your language strongly or weakly\ntyped, or object oriented, or functional, or whatever, but about\nhow to design great libraries. The kind of language designers who\nlike to think about how to design type systems may shudder at this.\nIt's almost like writing applications! Too bad. Languages are for\nprogrammers, and libraries are what programmers need.It's hard to design good libraries. It's not simply a matter of\nwriting a lot of code. Once the libraries get too big, it can\nsometimes take longer to find the function you need than to write\nthe code yourself. Libraries need to be designed using a small set\nof orthogonal operators, just like the core language. It ought to\nbe possible for the programmer to guess what library call will do\nwhat he needs.Libraries are one place Common Lisp falls short. There are only\nrudimentary libraries for manipulating strings, and almost none\nfor talking to the operating system. For historical reasons, Common\nLisp tries to pretend that the OS doesn't exist. And because you\ncan't talk to the OS, you're unlikely to be able to write a serious\nprogram using only the built-in operators in Common Lisp. You have\nto use some implementation-specific hacks as well, and in practice\nthese tend not to give you everything you want. Hackers would think\na lot more highly of Lisp if Common Lisp had powerful string\nlibraries and good OS support.7 SyntaxCould a language with Lisp's syntax, or more precisely, lack of\nsyntax, ever become popular? I don't know the answer to this\nquestion. I do think that syntax is not the main reason Lisp isn't\ncurrently popular. Common Lisp has worse problems than unfamiliar\nsyntax. I know several programmers who are comfortable with prefix\nsyntax and yet use Perl by default, because it has powerful string\nlibraries and can talk to the os.There are two possible problems with prefix notation: that it is\nunfamiliar to programmers, and that it is not dense enough. The\nconventional wisdom in the Lisp world is that the first problem is\nthe real one. I'm not so sure. Yes, prefix notation makes ordinary\nprogrammers panic. But I don't think ordinary programmers' opinions\nmatter. Languages become popular or unpopular based on what expert\nhackers think of them, and I think expert hackers might be able to\ndeal with prefix notation. Perl syntax can be pretty incomprehensible,\nbut that has not stood in the way of Perl's popularity. If anything\nit may have helped foster a Perl cult.A more serious problem is the diffuseness of prefix notation. For\nexpert hackers, that really is a problem. No one wants to write\n(aref a x y) when they could write a[x,y].In this particular case there is a way to finesse our way out of\nthe problem. If we treat data structures as if they were functions\non indexes, we could write (a x y) instead, which is even shorter\nthan the Perl form. Similar tricks may shorten other types of\nexpressions.We can get rid of (or make optional) a lot of parentheses by making\nindentation significant. That's how programmers read code anyway:\nwhen indentation says one thing and delimiters say another, we go\nby the indentation. Treating indentation as significant would\neliminate this common source of bugs as well as making programs\nshorter.Sometimes infix syntax is easier to read. This is especially true\nfor math expressions. I've used Lisp my whole programming life and\nI still don't find prefix math expressions natural. And yet it is\nconvenient, especially when you're generating code, to have operators\nthat take any number of arguments. So if we do have infix syntax,\nit should probably be implemented as some kind of read-macro.I don't think we should be religiously opposed to introducing syntax\ninto Lisp, as long as it translates in a well-understood way into\nunderlying s-expressions. There is already a good deal of syntax\nin Lisp. It's not necessarily bad to introduce more, as long as no\none is forced to use it. In Common Lisp, some delimiters are reserved\nfor the language, suggesting that at least some of the designers\nintended to have more syntax in the future.One of the most egregiously unlispy pieces of syntax in Common Lisp\noccurs in format strings; format is a language in its own right,\nand that language is not Lisp. If there were a plan for introducing\nmore syntax into Lisp, format specifiers might be able to be included\nin it. It would be a good thing if macros could generate format\nspecifiers the way they generate any other kind of code.An eminent Lisp hacker told me that his copy of CLTL falls open to\nthe section format. Mine too. This probably indicates room for\nimprovement. It may also mean that programs do a lot of I/O.8 EfficiencyA good language, as everyone knows, should generate fast code. But\nin practice I don't think fast code comes primarily from things\nyou do in the design of the language. As Knuth pointed out long\nago, speed only matters in certain critical bottlenecks. And as\nmany programmers have observed since, one is very often mistaken\nabout where these bottlenecks are.So, in practice, the way to get fast code is to have a very good\nprofiler, rather than by, say, making the language strongly typed.\nYou don't need to know the type of every argument in every call in\nthe program. You do need to be able to declare the types of arguments\nin the bottlenecks. And even more, you need to be able to find out\nwhere the bottlenecks are.One complaint people have had with Lisp is that it's hard to tell\nwhat's expensive. This might be true. It might also be inevitable,\nif you want to have a very abstract language. And in any case I\nthink good profiling would go a long way toward fixing the problem:\nyou'd soon learn what was expensive.Part of the problem here is social. Language designers like to\nwrite fast compilers. That's how they measure their skill. They\nthink of the profiler as an add-on, at best. But in practice a good\nprofiler may do more to improve the speed of actual programs written\nin the language than a compiler that generates fast code. Here,\nagain, language designers are somewhat out of touch with their\nusers. They do a really good job of solving slightly the wrong\nproblem.It might be a good idea to have an active profiler — to push\nperformance data to the programmer instead of waiting for him to\ncome asking for it. For example, the editor could display bottlenecks\nin red when the programmer edits the source code. Another approach\nwould be to somehow represent what's happening in running programs.\nThis would be an especially big win in server-based applications,\nwhere you have lots of running programs to look at. An active\nprofiler could show graphically what's happening in memory as a\nprogram's running, or even make sounds that tell what's happening.Sound is a good cue to problems. In one place I worked, we had a\nbig board of dials showing what was happening to our web servers.\nThe hands were moved by little servomotors that made a slight noise\nwhen they turned. I couldn't see the board from my desk, but I\nfound that I could tell immediately, by the sound, when there was\na problem with a server.It might even be possible to write a profiler that would automatically\ndetect inefficient algorithms. I would not be surprised if certain\npatterns of memory access turned out to be sure signs of bad\nalgorithms. If there were a little guy running around inside the\ncomputer executing our programs, he would probably have as long\nand plaintive a tale to tell about his job as a federal government\nemployee. I often have a feeling that I'm sending the processor on\na lot of wild goose chases, but I've never had a good way to look\nat what it's doing.A number of Lisps now compile into byte code, which is then executed\nby an interpreter. This is usually done to make the implementation\neasier to port, but it could be a useful language feature. It might\nbe a good idea to make the byte code an official part of the\nlanguage, and to allow programmers to use inline byte code in\nbottlenecks. Then such optimizations would be portable too.The nature of speed, as perceived by the end-user, may be changing.\nWith the rise of server-based applications, more and more programs\nmay turn out to be i/o-bound. It will be worth making i/o fast.\nThe language can help with straightforward measures like simple,\nfast, formatted output functions, and also with deep structural\nchanges like caching and persistent objects.Users are interested in response time. But another kind of efficiency\nwill be increasingly important: the number of simultaneous users\nyou can support per processor. Many of the interesting applications\nwritten in the near future will be server-based, and the number of\nusers per server is the critical question for anyone hosting such\napplications. In the capital cost of a business offering a server-based\napplication, this is the divisor.For years, efficiency hasn't mattered much in most end-user\napplications. Developers have been able to assume that each user\nwould have an increasingly powerful processor sitting on their\ndesk. And by Parkinson's Law, software has expanded to use the\nresources available. That will change with server-based applications.\nIn that world, the hardware and software will be supplied together.\nFor companies that offer server-based applications, it will make\na very big difference to the bottom line how many users they can\nsupport per server.In some applications, the processor will be the limiting factor,\nand execution speed will be the most important thing to optimize.\nBut often memory will be the limit; the number of simultaneous\nusers will be determined by the amount of memory you need for each\nuser's data. The language can help here too. Good support for\nthreads will enable all the users to share a single heap. It may\nalso help to have persistent objects and/or language level support\nfor lazy loading.9 TimeThe last ingredient a popular language needs is time. No one wants\nto write programs in a language that might go away, as so many\nprogramming languages do. So most hackers will tend to wait until\na language has been around for a couple years before even considering\nusing it.Inventors of wonderful new things are often surprised to discover\nthis, but you need time to get any message through to people. A\nfriend of mine rarely does anything the first time someone asks\nhim. He knows that people sometimes ask for things that they turn\nout not to want. To avoid wasting his time, he waits till the third\nor fourth time he's asked to do something; by then, whoever's asking\nhim may be fairly annoyed, but at least they probably really do\nwant whatever they're asking for.Most people have learned to do a similar sort of filtering on new\nthings they hear about. They don't even start paying attention\nuntil they've heard about something ten times. They're perfectly\njustified: the majority of hot new whatevers do turn out to be a\nwaste of time, and eventually go away. By delaying learning VRML,\nI avoided having to learn it at all.So anyone who invents something new has to expect to keep repeating\ntheir message for years before people will start to get it. We\nwrote what was, as far as I know, the first web-server based\napplication, and it took us years to get it through to people that\nit didn't have to be downloaded. It wasn't that they were stupid.\nThey just had us tuned out.The good news is, simple repetition solves the problem. All you\nhave to do is keep telling your story, and eventually people will\nstart to hear. It's not when people notice you're there that they\npay attention; it's when they notice you're still there.It's just as well that it usually takes a while to gain momentum.\nMost technologies evolve a good deal even after they're first\nlaunched — programming languages especially. Nothing could be better,\nfor a new techology, than a few years of being used only by a small\nnumber of early adopters. Early adopters are sophisticated and\ndemanding, and quickly flush out whatever flaws remain in your\ntechnology. When you only have a few users you can be in close\ncontact with all of them. And early adopters are forgiving when\nyou improve your system, even if this causes some breakage.There are two ways new technology gets introduced: the organic\ngrowth method, and the big bang method. The organic growth method\nis exemplified by the classic seat-of-the-pants underfunded garage\nstartup. A couple guys, working in obscurity, develop some new\ntechnology. They launch it with no marketing and initially have\nonly a few (fanatically devoted) users. They continue to improve\nthe technology, and meanwhile their user base grows by word of\nmouth. Before they know it, they're big.The other approach, the big bang method, is exemplified by the\nVC-backed, heavily marketed startup. They rush to develop a product,\nlaunch it with great publicity, and immediately (they hope) have\na large user base.Generally, the garage guys envy the big bang guys. The big bang\nguys are smooth and confident and respected by the VCs. They can\nafford the best of everything, and the PR campaign surrounding the\nlaunch has the side effect of making them celebrities. The organic\ngrowth guys, sitting in their garage, feel poor and unloved. And\nyet I think they are often mistaken to feel sorry for themselves.\nOrganic growth seems to yield better technology and richer founders\nthan the big bang method. If you look at the dominant technologies\ntoday, you'll find that most of them grew organically.This pattern doesn't only apply to companies. You see it in sponsored\nresearch too. Multics and Common Lisp were big-bang projects, and\nUnix and MacLisp were organic growth projects.10 Redesign\"The best writing is rewriting,\" wrote E. B. White. Every good\nwriter knows this, and it's true for software too. The most important\npart of design is redesign. Programming languages, especially,\ndon't get redesigned enough.To write good software you must simultaneously keep two opposing\nideas in your head. You need the young hacker's naive faith in\nhis abilities, and at the same time the veteran's skepticism. You\nhave to be able to think \nhow hard can it be? with one half of\nyour brain while thinking \nit will never work with the other.The trick is to realize that there's no real contradiction here.\nYou want to be optimistic and skeptical about two different things.\nYou have to be optimistic about the possibility of solving the\nproblem, but skeptical about the value of whatever solution you've\ngot so far.People who do good work often think that whatever they're working\non is no good. Others see what they've done and are full of wonder,\nbut the creator is full of worry. This pattern is no coincidence:\nit is the worry that made the work good.If you can keep hope and worry balanced, they will drive a project\nforward the same way your two legs drive a bicycle forward. In the\nfirst phase of the two-cycle innovation engine, you work furiously\non some problem, inspired by your confidence that you'll be able\nto solve it. In the second phase, you look at what you've done in\nthe cold light of morning, and see all its flaws very clearly. But\nas long as your critical spirit doesn't outweigh your hope, you'll\nbe able to look at your admittedly incomplete system, and think,\nhow hard can it be to get the rest of the way?, thereby continuing\nthe cycle.It's tricky to keep the two forces balanced. In young hackers,\noptimism predominates. They produce something, are convinced it's\ngreat, and never improve it. In old hackers, skepticism predominates,\nand they won't even dare to take on ambitious projects.Anything you can do to keep the redesign cycle going is good. Prose\ncan be rewritten over and over until you're happy with it. But\nsoftware, as a rule, doesn't get redesigned enough. Prose has\nreaders, but software has users. If a writer rewrites an essay,\npeople who read the old version are unlikely to complain that their\nthoughts have been broken by some newly introduced incompatibility.Users are a double-edged sword. They can help you improve your\nlanguage, but they can also deter you from improving it. So choose\nyour users carefully, and be slow to grow their number. Having\nusers is like optimization: the wise course is to delay it. Also,\nas a general rule, you can at any given time get away with changing\nmore than you think. Introducing change is like pulling off a\nbandage: the pain is a memory almost as soon as you feel it.Everyone knows that it's not a good idea to have a language designed\nby a committee. Committees yield bad design. But I think the worst\ndanger of committees is that they interfere with redesign. It is\nso much work to introduce changes that no one wants to bother.\nWhatever a committee decides tends to stay that way, even if most\nof the members don't like it.Even a committee of two gets in the way of redesign. This happens\nparticularly in the interfaces between pieces of software written\nby two different people. To change the interface both have to agree\nto change it at once. And so interfaces tend not to change at all,\nwhich is a problem because they tend to be one of the most ad hoc\nparts of any system.One solution here might be to design systems so that interfaces\nare horizontal instead of vertical — so that modules are always\nvertically stacked strata of abstraction. Then the interface will\ntend to be owned by one of them. The lower of two levels will either\nbe a language in which the upper is written, in which case the\nlower level will own the interface, or it will be a slave, in which\ncase the interface can be dictated by the upper level.11 LispWhat all this implies is that there is hope for a new Lisp. There\nis hope for any language that gives hackers what they want, including\nLisp. I think we may have made a mistake in thinking that hackers\nare turned off by Lisp's strangeness. This comforting illusion may\nhave prevented us from seeing the real problem with Lisp, or at\nleast Common Lisp, which is that it sucks for doing what hackers\nwant to do. A hacker's language needs powerful libraries and\nsomething to hack. Common Lisp has neither. A hacker's language is\nterse and hackable. Common Lisp is not.The good news is, it's not Lisp that sucks, but Common Lisp. If we\ncan develop a new Lisp that is a real hacker's language, I think\nhackers will use it. They will use whatever language does the job.\nAll we have to do is make sure this new Lisp does some important\njob better than other languages.History offers some encouragement. Over time, successive new\nprogramming languages have taken more and more features from Lisp.\nThere is no longer much left to copy before the language you've\nmade is Lisp. The latest hot language, Python, is a watered-down\nLisp with infix syntax and no macros. A new Lisp would be a natural\nstep in this progression.I sometimes think that it would be a good marketing trick to call\nit an improved version of Python. That sounds hipper than Lisp. To\nmany people, Lisp is a slow AI language with a lot of parentheses.\nFritz Kunze's official biography carefully avoids mentioning the\nL-word. But my guess is that we shouldn't be afraid to call the\nnew Lisp Lisp. Lisp still has a lot of latent respect among the\nvery best hackers — the ones who took 6.001 and understood it, for\nexample. And those are the users you need to win.In \"How to Become a Hacker,\" Eric Raymond describes Lisp as something\nlike Latin or Greek — a language you should learn as an intellectual\nexercise, even though you won't actually use it:\n\n Lisp is worth learning for the profound enlightenment experience\n you will have when you finally get it; that experience will make\n you a better programmer for the rest of your days, even if you\n never actually use Lisp itself a lot.\n\nIf I didn't know Lisp, reading this would set me asking questions.\nA language that would make me a better programmer, if it means\nanything at all, means a language that would be better for programming.\nAnd that is in fact the implication of what Eric is saying.As long as that idea is still floating around, I think hackers will\nbe receptive enough to a new Lisp, even if it is called Lisp. But\nthis Lisp must be a hacker's language, like the classic Lisps of\nthe 1970s. It must be terse, simple, and hackable. And it must have\npowerful libraries for doing what hackers want to do now.In the matter of libraries I think there is room to beat languages\nlike Perl and Python at their own game. A lot of the new applications\nthat will need to be written in the coming years will be \nserver-based\napplications. There's no reason a new Lisp shouldn't have string\nlibraries as good as Perl, and if this new Lisp also had powerful\nlibraries for server-based applications, it could be very popular.\nReal hackers won't turn up their noses at a new tool that will let\nthem solve hard problems with a few library calls. Remember, hackers\nare lazy.It could be an even bigger win to have core language support for\nserver-based applications. For example, explicit support for programs\nwith multiple users, or data ownership at the level of type tags.Server-based applications also give us the answer to the question\nof what this new Lisp will be used to hack. It would not hurt to\nmake Lisp better as a scripting language for Unix. (It would be\nhard to make it worse.) But I think there are areas where existing\nlanguages would be easier to beat. I think it might be better to\nfollow the model of Tcl, and supply the Lisp together with a complete\nsystem for supporting server-based applications. Lisp is a natural\nfit for server-based applications. Lexical closures provide a way\nto get the effect of subroutines when the ui is just a series of\nweb pages. S-expressions map nicely onto html, and macros are good\nat generating it. There need to be better tools for writing\nserver-based applications, and there needs to be a new Lisp, and\nthe two would work very well together.12 The Dream LanguageBy way of summary, let's try describing the hacker's dream language.\nThe dream language is \nbeautiful, clean, and terse. It has an\ninteractive toplevel that starts up fast. You can write programs\nto solve common problems with very little code. Nearly all the\ncode in any program you write is code that's specific to your\napplication. Everything else has been done for you.The syntax of the language is brief to a fault. You never have to\ntype an unnecessary character, or even to use the shift key much.Using big abstractions you can write the first version of a program\nvery quickly. Later, when you want to optimize, there's a really\ngood profiler that tells you where to focus your attention. You\ncan make inner loops blindingly fast, even writing inline byte code\nif you need to.There are lots of good examples to learn from, and the language is\nintuitive enough that you can learn how to use it from examples in\na couple minutes. You don't need to look in the manual much. The\nmanual is thin, and has few warnings and qualifications.The language has a small core, and powerful, highly orthogonal\nlibraries that are as carefully designed as the core language. The\nlibraries all work well together; everything in the language fits\ntogether like the parts in a fine camera. Nothing is deprecated,\nor retained for compatibility. The source code of all the libraries\nis readily available. It's easy to talk to the operating system\nand to applications written in other languages.The language is built in layers. The higher-level abstractions are\nbuilt in a very transparent way out of lower-level abstractions,\nwhich you can get hold of if you want.Nothing is hidden from you that doesn't absolutely have to be. The\nlanguage offers abstractions only as a way of saving you work,\nrather than as a way of telling you what to do. In fact, the language\nencourages you to be an equal participant in its design. You can\nchange everything about it, including even its syntax, and anything\nyou write has, as much as possible, the same status as what comes\npredefined.Notes[1] Macros very close to the modern idea were proposed by Timothy\nHart in 1964, two years after Lisp 1.5 was released. What was\nmissing, initially, were ways to avoid variable capture and multiple\nevaluation; Hart's examples are subject to both.[2] In When the Air Hits Your Brain, neurosurgeon Frank Vertosick\nrecounts a conversation in which his chief resident, Gary, talks\nabout the difference between surgeons and internists (\"fleas\"):\n\n Gary and I ordered a large pizza and found an open booth. The\n chief lit a cigarette. \"Look at those goddamn fleas, jabbering\n about some disease they'll see once in their lifetimes. That's\n the trouble with fleas, they only like the bizarre stuff. They\n hate their bread and butter cases. That's the difference between\n us and the fucking fleas. See, we love big juicy lumbar disc\n herniations, but they hate hypertension....\"\n\nIt's hard to think of a lumbar disc herniation as juicy (except\nliterally). And yet I think I know what they mean. I've often had\na juicy bug to track down. Someone who's not a programmer would\nfind it hard to imagine that there could be pleasure in a bug.\nSurely it's better if everything just works. In one way, it is.\nAnd yet there is undeniably a grim satisfaction in hunting down\ncertain sorts of bugs." }, { "path": "data/PaulGrahamEssays/pow.txt", "content": "January 2017People who are powerful but uncharismatic will tend to be disliked.\nTheir power makes them a target for criticism that they don't have\nthe charisma to disarm. That was Hillary Clinton's problem. It also\ntends to be a problem for any CEO who is more of a builder than a\nschmoozer. And yet the builder-type CEO is (like Hillary) probably\nthe best person for the job.I don't think there is any solution to this problem. It's human\nnature. The best we can do is to recognize that it's happening, and\nto understand that being a magnet for criticism is sometimes a sign\nnot that someone is the wrong person for a job, but that they're\nthe right one." }, { "path": "data/PaulGrahamEssays/power.txt", "content": "May 2002\n\n\n\n\"The quantity of meaning compressed into a small space by \nalgebraic signs, is another circumstance that facilitates \nthe reasonings we are accustomed to carry on by their aid.\"- Charles Babbage, quoted in Iverson's Turing Award Lecture\n\n\n\nIn the discussion about issues raised by Revenge \nof the Nerds on the LL1 mailing list, Paul Prescod wrote\nsomething that stuck in my mind.\n\nPython's goal is regularity and readability, not succinctness.\n\nOn the face of it, this seems a rather damning thing to claim about a \nprogramming language. As far as I can tell, succinctness = power.\nIf so, then substituting, we get\n\nPython's goal is regularity and readability, not power.\n\nand this doesn't seem a tradeoff (if it is a tradeoff)\nthat you'd want to make. \nIt's not far from saying that Python's goal is not to be effective \nas a programming language.Does succinctness = power? This seems to me an important question,\nmaybe the most important question for anyone interested in\nlanguage design, and one that it would be useful to confront\ndirectly. I don't feel sure yet that the answer is a simple yes, but it seems \na good hypothesis to begin with.HypothesisMy hypothesis is that succinctness is power, or is close enough\nthat except in pathological examples you can treat them as \nidentical.It seems to me that succinctness is what programming languages are \nfor. Computers would be just as happy to be told what to\ndo directly in machine language. I think that the main\nreason we take the trouble to develop high-level languages is to\nget leverage, so that we can say (and more importantly, think)\nin 10 lines of a high-level language what would require 1000\nlines of machine language. In other words,\nthe main point of high-level languages is to make source code smaller.If smaller source code is the purpose of high-level languages, and\nthe power of something is how well it achieves its purpose, then\nthe measure of the power of a programming language is how small it\nmakes your programs.Conversely, a language that doesn't make your programs small is\ndoing a bad job of what programming languages are supposed to\ndo, like a knife that doesn't cut well, or printing that's illegible.\nMetricsSmall in what sense though? The most common measure of code size is\nlines of code. But I think that this metric is the most common because\nit is the easiest to measure. I don't think anyone really believes\nit is the true test of the length of a program. Different\nlanguages have different conventions for how much you should put\non a line; in C a lot of lines have nothing on them but a delimiter or two.Another easy test is the number of characters in a \nprogram, but this is not very good either; some languages (Perl,\nfor example) just\nuse shorter identifiers than others.I think a better measure of the size of a program would be the \nnumber of elements, where an element is anything that\nwould be a distinct node if you drew a tree representing the \nsource code. The name of\na variable or function is an element; \nan integer or a floating-point number is an element;\na segment of literal text is an element;\nan element of a pattern, or a format directive, is an element;\na new block is an element. There are borderline cases\n(is -5 two elements or one?) but I think most of them are the\nsame for every language, so they don't affect comparisons much.This metric needs fleshing out, and\nit could require interpretation in the case of specific languages,\nbut I think it tries to measure the right thing, which is the \nnumber of parts a program has. I think the tree you'd draw in this\nexercise is what you have to make in your head in order to\nconceive of the program, and so its size is proportionate to the\namount of work you have to do to write or read it.DesignThis kind of metric would allow us to compare different languages,\nbut that is not, at least for me, its main value. The main value\nof the succinctness test is as a guide in designing languages.\nThe most useful comparison between languages is between two\npotential variants of the same language. What can I do in the\nlanguage to make programs shorter?If the conceptual load of\na program is proportionate to its complexity, and a given programmer\ncan tolerate a fixed conceptual load, then this is the same as asking,\nwhat can I do to enable programmers to get the most done? And\nthat seems to me identical to asking, how can I design a good\nlanguage?(Incidentally, nothing makes it more patently obvious that the old\nchestnut \"all languages are equivalent\" is false than designing\nlanguages. When you are designing a new language, you're constantly\ncomparing two languages-- the language if I did x, and if I didn't-- to\ndecide which is better. If this were really a meaningless question,\nyou might as well flip a coin.)Aiming for succinctness seems a good way to find new ideas.\nIf you can do something that makes many\ndifferent programs shorter, it is probably not a coincidence: you have \nprobably discovered a useful new abstraction. You might even be\nable to write a program to help by searching\nsource code for repeated patterns. Among other languages, those\nwith a reputation for succinctness would be the ones to look to for\nnew ideas: Forth, Joy, Icon.ComparisonThe first person to write about these issues, as far as I know, was\nFred Brooks in the Mythical Man Month. He wrote\nthat programmers seemed to generate about the same\namount of code per day regardless of the language.\nWhen I first read this in my early twenties,\nit was a big surprise to me and seemed to have huge implications.\nIt meant that (a) the only way to get software written faster was to\nuse a more succinct language, and (b) someone who took the\ntrouble to do this could leave competitors who didn't in the dust.Brooks' hypothesis, if it's true, seems to be at the very heart of hacking.\nIn the years since, I've paid close attention to any evidence I could\nget on the question, from formal studies to anecdotes about individual\nprojects. I have seen nothing to contradict him.I have not yet seen evidence that seemed to me conclusive,\nand I don't expect to. Studies\nlike Lutz Prechelt's comparison of programming languages, while\ngenerating the kind of results I expected, tend to use problems that\nare too short to be meaningful tests. A better test of a language is\nwhat happens in programs that take a month to write. And the only\nreal test, if you believe as I do that the main purpose of a language\nis to be good to think in (rather than just to tell a computer what to\ndo once you've thought of it) is what new things you can write in it.\nSo any language comparison where\nyou have to meet a predefined spec is testing slightly the wrong\nthing.The true test of a language is how well you can discover\nand solve new problems, not\nhow well you can use it to solve a problem someone else has\nalready formulated. These two are quite different criteria.\nIn art, mediums like embroidery and mosaic work well if you\nknow beforehand what you want to make, but are absolutely lousy if\nyou don't. When you want to discover the image as you make it--\nas you have to do with anything as complex as an image of a\nperson, for example-- you need to use a more fluid medium like pencil or\nink wash or oil paint. And indeed, the way tapestries and mosaics are made in\npractice is to make a painting first, then copy it. (The word\n\"cartoon\" was originally used to describe a painting intended for\nthis purpose).What this means is that we are never likely to have accurate comparisons\nof the relative power of programming languages. We'll have precise\ncomparisons, but not accurate ones. In particular, explicit studies\nfor the purpose of comparing languages,\nbecause they will probably use small problems, and will necessarily use\npredefined problems, will tend to underestimate the power of the\nmore powerful languages.Reports from the field, though they will necessarily be less precise than\n\"scientific\" studies, are likely to be more meaningful. For example, \nUlf Wiger of Ericsson did a \nstudy that \nconcluded that Erlang was 4-10x\nmore succinct than C++, and proportionately faster to develop \nsoftware in:\n\nComparisons between Ericsson-internal development projects indicate\nsimilar line/hour productivity, including all phases of software development,\nrather independently of which language (Erlang, PLEX, C, C++, or Java)\nwas used. What differentiates the different languages then becomes source\ncode volume.\n\n The study also deals explictly with a point that was \nonly implicit in Brooks' book (since he measured lines of debugged code):\nprograms written in more powerful languages tend to have fewer bugs.\nThat becomes an end in itself, possibly more important than programmer\nproductivity, in applications like network switches.The Taste TestUltimately, I think you have to go with your gut. What does it feel\nlike to program in the language? I think the way to find (or design)\nthe best language is to become hypersensitive to how well a language\nlets you think, then choose/design the language that feels best. If\nsome language feature is awkward or restricting, don't worry, you'll\nknow about it.Such hypersensitivity will come at a cost. You'll find that you can't\nstand programming in clumsy languages. I find it unbearably\nrestrictive to program in languages without macros, just as someone used\nto dynamic typing finds it unbearably restrictive to have to go back to\nprogramming in a language where you have to declare the type of\nevery variable, and can't make a list of objects of different types.\nI'm not the only one. I know many Lisp hackers that this has happened\nto. In fact, the most accurate measure of the relative power of programming\nlanguages might be the percentage of people who know the language\nwho will take any job where they get to use that language, regardless\nof the application domain.RestrictivenessI think most hackers know what it means for a language to feel restrictive.\nWhat's happening when you feel that? I think it's the same feeling\nyou get when the street you want to take is blocked off, and you have to\ntake a long detour to get where you wanted to go. There is something\nyou want to say, and the language won't let you.What's really going on here, I think, is that a restrictive language is\none that isn't succinct enough. The problem is not simply that you can't\nsay what you planned to. It's that the detour the language makes you\ntake is longer. Try this thought experiment. Suppose there were\nsome program you wanted to write, and the language wouldn't let you\nexpress it the way you planned to, but instead forced you to write the\nprogram in some other way that was shorter. For me at least,\nthat wouldn't feel very restrictive. It would be like the street you\nwanted to take being blocked off, and the policeman at the \nintersection directing you to a shortcut instead of a detour. Great!I think most (ninety percent?) of \nthe feeling of restrictiveness comes from being forced to make the program\nyou write in the language longer than one you have in your head.\nRestrictiveness is mostly lack of succinctness.\nSo when a language feels restrictive, what that (mostly) means is that it isn't\nsuccinct enough, and when a language isn't succinct, it will\nfeel restrictive.ReadabilityThe quote I began with mentions two other qualities, regularity and\nreadability. I'm not sure what regularity is, or what advantage, \nif any, code that is regular and readable has over code that is merely\nreadable. But I think I know what is meant by readability, and I think\nit is also related to succinctness.We have to be careful here to distinguish between the readability of\nan individual line of code and the readability of the whole program.\nIt's the second that matters. I agree that a line of Basic is likely to be\nmore readable than a line of Lisp. But a program written in Basic is\nis going to have more lines than the same program written in\nLisp (especially once you cross over into Greenspunland). The\ntotal effort of reading the Basic program will surely be greater.\n\ntotal effort = effort per line x number of lines\n\nI'm not as sure that readability is directly proportionate to succinctness\nas I am that power is, but certainly succinctness is a factor \n(in the mathematical sense; see equation above) in readability.\nSo it may not even be meaningful to say that the goal of a language is\nreadability, not succinctness; it could be like saying the goal was readability,\nnot readability.What readability-per-line does mean, to the user encountering the language\nfor the first time, is that source code will look unthreatening. So\nreadability-per-line\ncould be a good marketing decision, even if it is a bad design\ndecision. It's isomorphic to the very successful technique of letting\npeople pay in installments: instead of frightening them with a high\nupfront price, you tell them the low monthly payment. Installment plans\nare a net lose for the buyer, though, as mere readability-per-line probably\nis for the programmer.\nThe buyer is going to make a lot of those low, low payments; and \nthe programmer is going to read a lot of those individually readable lines.This tradeoff predates programming languages. If you're used to reading\nnovels and newspaper articles, your first experience of reading a math\npaper can be dismaying. It could take half an hour to read a single page. \nAnd yet, I am pretty sure that the notation is not the problem, even though\nit may feel like it is. The math paper is hard to read \nbecause the ideas are hard. If you expressed the same ideas in prose\n(as mathematicians had to do before they evolved succinct notations),\nthey wouldn't be any easier to read, because the paper would grow to the\nsize of a book.To What Extent?A number of people have rejected\nthe idea that succinctness = power. I think it would be more useful, instead\nof simply arguing that they are the same or aren't, to ask:\nto what extent does succinctness = power?\nBecause clearly succinctness is\na large part of what higher-level languages are for. If it is not all they're\nfor, then what else are they for, and how important, relatively, are these\nother functions?I'm not proposing this just to make the debate more civilized. I really\nwant to know the answer. When, if ever, is a language too succinct for \nits own good?The hypothesis I began with was that, except in pathological examples,\nI thought succinctness could be considered identical with power. What\nI meant was that in any language anyone would design, they\nwould be identical, but that if someone wanted to design a language\nexplicitly to disprove this hyphothesis, they could probably do it. I'm\nnot even sure of that, actually.Languages, not ProgramsWe should be clear that we are talking about the succinctness\nof languages, not of individual programs.\nIt certainly is possible for individual programs to be written too densely.I wrote about this in On Lisp. A complex macro\nmay have to save many times its own length to be justified. If writing\nsome hairy macro could save you ten lines of code every time you use it,\nand the macro is itself ten lines of code, then you get a net saving in\nlines if you use it more than once. But that could still be a bad move,\nbecause macro definitions are harder to read than ordinary code. You \nmight have to use the macro ten or twenty times before it yielded a net\nimprovement in readability.I'm sure every language has such tradeoffs (though I suspect the stakes\nget higher as the language gets more powerful). Every programmer must\nhave seen code that some clever person has made marginally shorter\nby using dubious programming tricks.So there is no argument about that-- at least, not from me. Individual\nprograms can certainly be too succinct for their own good. The question\nis, can a language be? Can a language compel programmers to write\ncode that's short (in elements) at the expense of overall readability?One reason it's hard to imagine a language being too succinct is that if\nthere were some excessively compact way to phrase something, there would\nprobably also be a longer way. For example, if you felt Lisp programs using\na lot of macros or higher-order functions were too dense, you could, if you\npreferred, write code that was isomorphic to Pascal. If you\ndon't want to express factorial in Arc as a call to a higher-order function\n\n(rec zero 1 * 1-)\n\nyou can also write out a recursive definition:\n\n(rfn fact (x) (if (zero x) 1 (* x (fact (1- x)))))\n\nThough I can't off the top of my head think of any examples, I am interested\nin the question of whether a language could be too succinct. Are there languages \nthat force you to write code in a way that is crabbed and incomprehensible?\nIf anyone has examples, I would be very interested to see them.(Reminder: What I'm looking for are programs that are very dense according\nto the metric of \"elements\" sketched above, not merely programs that are\nshort because delimiters can be omitted and everything has a one-character name.)\n" }, { "path": "data/PaulGrahamEssays/prcmc.txt", "content": "July 2008At this year's startup school, David Heinemeier Hansson gave a\n talk\nin which he suggested that startup founders\nshould do things the old fashioned way. Instead of hoping to get\nrich by building a valuable company and then selling stock in a\n\"liquidity event,\" founders should start companies that make money\nand live off the revenues.Sounds like a good plan. Let's think about the optimal way to do\nthis.One disadvantage of living off the revenues of your company is that\nyou have to keep running it. And as anyone who runs their own\nbusiness can tell you, that requires your complete attention. You\ncan't just start a business and check out once things are going\nwell, or they stop going well surprisingly fast.The main economic motives of startup founders seem to be freedom\nand security. They want enough money that (a) they don't have to\nworry about running out of money and (b) they can spend their time\nhow they want. Running your own business offers neither. You\ncertainly don't have freedom: no boss is so demanding. Nor do you\nhave security, because if you stop paying attention to the company,\nits revenues go away, and with them your income.The best case, for most people, would be if you could hire someone\nto manage the company for you once you'd grown it to a certain size.\nSuppose you could find a really good manager. Then you would have\nboth freedom and security. You could pay as little attention to\nthe business as you wanted, knowing that your manager would keep\nthings running smoothly. And that being so, revenues would continue\nto flow in, so you'd have security as well.There will of course be some founders who wouldn't like that idea:\nthe ones who like running their company so much that there's nothing\nelse they'd rather do. But this group must be small. The way you\nsucceed in most businesses is to be fanatically attentive\nto customers' needs. What are the odds that your own desires would\ncoincide exactly with the demands of this powerful, external force?Sure, running your own company can be fairly interesting. Viaweb\nwas more interesting than any job I'd had before. And since I made\nmuch more money from it, it offered the highest ratio of income to\nboringness of anything I'd done, by orders of magnitude. But was\nit the most interesting work I could imagine doing? No.Whether the number of founders in the same position is asymptotic\nor merely large, there are certainly a lot of them. For them the\nright approach would be to hand the company over to a professional\nmanager eventually, if they could find one who was good enough._____So far so good. But what if your manager was hit by a bus? What\nyou really want is a management company to run your company for\nyou. Then you don't depend on any one person.If you own rental property, there are companies you can hire to\nmanage it for you. Some will do everything, from finding tenants\nto fixing leaks. Of course, running companies is a lot more\ncomplicated than managing rental property, but let's suppose there\nwere management companies that could do it for you. They'd charge\na lot, but wouldn't it be worth it? I'd sacrifice a large percentage\nof the income for the extra peace of mind.I realize what I'm describing already sounds too good to be true, but I\ncan think of a way to make it even more attractive. If\ncompany management companies existed, there would be an additional\nservice they could offer clients: they could let them insure their\nreturns by pooling their risk. After all, even a perfect manager can't save a company\nwhen, as sometimes happens, its whole market dies, just as property\nmanagers can't save you from the building burning down. But a\ncompany that managed a large enough number of companies could say\nto all its clients: we'll combine the revenues from all your\ncompanies, and pay you your proportionate share.If such management companies existed, they'd offer the maximum of\nfreedom and security. Someone would run your company for you, and\nyou'd be protected even if it happened to die.Let's think about how such a management company might be organized.\nThe simplest way would be to have a new kind of stock representing\nthe total pool of companies they were managing. When you signed\nup, you'd trade your company's stock for shares of this pool, in\nproportion to an estimate of your company's value that you'd both\nagreed upon. Then you'd automatically get your share of the returns\nof the whole pool.The catch is that because this kind of trade would be hard to undo,\nyou couldn't switch management companies. But there's a way they\ncould fix that: suppose all the company management companies got\ntogether and agreed to allow their clients to exchange shares in\nall their pools. Then you could, in effect, simultaneously choose\nall the management companies to run yours for you, in whatever\nproportion you wanted, and change your mind later as often as you\nwanted.If such pooled-risk company management companies existed, signing\nup with one would seem the ideal plan for most people following the\nroute David advocated.Good news: they do exist. What I've just\ndescribed is an acquisition by a public company._____Unfortunately, though public acquirers are structurally identical\nto pooled-risk company management companies, they don't think of\nthemselves that way. With a property management company, you can\njust walk in whenever you want and say \"manage my rental property\nfor me\" and they'll do it. Whereas acquirers are, as of this\nwriting, extremely fickle. Sometimes they're in a buying mood and\nthey'll overpay enormously; other times they're not interested.\nThey're like property management companies run by madmen. Or more\nprecisely, by Benjamin Graham's Mr. Market.So while on average public acquirers behave like pooled-risk company\nmanagers, you need a window of several years to get average case\nperformance. If you wait long enough (five years, say) you're\nlikely to hit an up cycle where some acquirer is hot to buy you.\nBut you can't choose when it happens.You can't assume investors will carry you for as long as you might\nhave to wait. Your company has to make money. Opinions are divided\nabout how early to focus on that. \nJoe Kraus says you should try\ncharging customers right away. And yet some of the most successful\nstartups, including Google, ignored revenue at first and concentrated\nexclusively on development. The answer probably depends on the\ntype of company you're starting. I can imagine some where trying\nto make sales would be a good heuristic for product design, and\nothers where it would just be a distraction. The test is probably\nwhether it helps you to understand your users.You can choose whichever revenue strategy you think is best for the\ntype of company you're starting, so long as you're profitable.\nBeing profitable ensures you'll get at least the average of the\nacquisition market—in which public companies do behave as pooled-risk\ncompany management companies.David isn't mistaken in saying you should start a company to live\noff its revenues. The mistake is thinking this is somehow opposed\nto starting a company and selling it. In fact, for most people the\nlatter is merely the optimal case of the former.Thanks to Trevor Blackwell, Jessica Livingston, Michael\nMandel, Robert Morris, and Fred Wilson for reading drafts of this.\n" }, { "path": "data/PaulGrahamEssays/procrastination.txt", "content": "December 2005The most impressive people I know are all terrible procrastinators.\nSo could it be that procrastination isn't always bad?Most people who write about procrastination write about how to cure\nit. But this is, strictly speaking, impossible. There are an\ninfinite number of things you could be doing. No matter what you\nwork on, you're not working on everything else. So the question\nis not how to avoid procrastination, but how to procrastinate well.There are three variants of procrastination, depending on what you\ndo instead of working on something: you could work on (a) nothing,\n(b) something less important, or (c) something more important. That\nlast type, I'd argue, is good procrastination.That's the \"absent-minded professor,\" who forgets to shave, or eat,\nor even perhaps look where he's going while he's thinking about\nsome interesting question. His mind is absent from the everyday\nworld because it's hard at work in another.That's the sense in which the most impressive people I know are all\nprocrastinators. They're type-C procrastinators: they put off\nworking on small stuff to work on big stuff.What's \"small stuff?\" Roughly, work that has zero chance of being\nmentioned in your obituary. It's hard to say at the time what will\nturn out to be your best work (will it be your magnum opus on\nSumerian temple architecture, or the detective thriller you wrote\nunder a pseudonym?), but there's a whole class of tasks you can\nsafely rule out: shaving, doing your laundry, cleaning the house,\nwriting thank-you notes—anything that might be called an errand.Good procrastination is avoiding errands to do real work.Good in a sense, at least. The people who want you to do the errands\nwon't think it's good. But you probably have to annoy them if you\nwant to get anything done. The mildest seeming people, if they\nwant to do real work, all have a certain degree of ruthlessness\nwhen it comes to avoiding errands.Some errands, like replying to letters, go away if you\nignore them (perhaps taking friends with them). Others, like mowing\nthe lawn, or filing tax returns, only get worse if you put them\noff. In principle it shouldn't work to put off the second kind of\nerrand. You're going to have to do whatever it is eventually. Why\nnot (as past-due notices are always saying) do it now?The reason it pays to put off even those errands is that real work\nneeds two things errands don't: big chunks of time, and the\nright mood. If you get inspired by some project, it can be a net\nwin to blow off everything you were supposed to do for the next few\ndays to work on it. Yes, those errands may cost you more time when\nyou finally get around to them. But if you get a lot done during\nthose few days, you will be net more productive.In fact, it may not be a difference in degree, but a difference in\nkind. There may be types of work that can only be done in long,\nuninterrupted stretches, when inspiration hits, rather than dutifully\nin scheduled little slices. Empirically it seems to be so. When\nI think of the people I know who've done great things, I don't\nimagine them dutifully crossing items off to-do lists. I imagine\nthem sneaking off to work on some new idea.Conversely, forcing someone to perform errands synchronously is\nbound to limit their productivity. The cost of an interruption is\nnot just the time it takes, but that it breaks the time on either\nside in half. You probably only have to interrupt someone a couple\ntimes a day before they're unable to work on hard problems at all.I've wondered a lot about why \nstartups are most productive at the\nvery beginning, when they're just a couple guys in an apartment.\nThe main reason may be that there's no one to interrupt them yet.\nIn theory it's good when the founders finally get enough money to\nhire people to do some of the work for them. But it may be better\nto be overworked than interrupted. Once you dilute a startup with\nordinary office workers—with type-B procrastinators—the whole\ncompany starts to resonate at their frequency. They're interrupt-driven,\nand soon you are too.Errands are so effective at killing great projects that a lot of\npeople use them for that purpose. Someone who has decided to write\na novel, for example, will suddenly find that the house needs\ncleaning. People who fail to write novels don't do it by sitting\nin front of a blank page for days without writing anything. They\ndo it by feeding the cat, going out to buy something they need for\ntheir apartment, meeting a friend for coffee, checking email. \"I\ndon't have time to work,\" they say. And they don't; they've made\nsure of that.(There's also a variant where one has no place to work. The cure\nis to visit the places where famous people worked, and see how\nunsuitable they were.)I've used both these excuses at one time or another. I've learned\na lot of tricks for making myself work over the last 20 years, but\neven now I don't win consistently. Some days I get real work done.\nOther days are eaten up by errands. And I know it's usually my\nfault: I let errands eat up the day, to avoid\nfacing some hard problem.The most dangerous form of procrastination is unacknowledged type-B\nprocrastination, because it doesn't feel like procrastination.\nYou're \"getting things done.\" Just the wrong things.Any advice about procrastination that concentrates on crossing\nthings off your to-do list is not only incomplete, but positively\nmisleading, if it doesn't consider the possibility that the to-do\nlist is itself a form of type-B procrastination. In fact, possibility\nis too weak a word. Nearly everyone's is. Unless you're working\non the biggest things you could be working on, you're type-B\nprocrastinating, no matter how much you're getting done.In his famous essay You and Your Research \n(which I recommend to\nanyone ambitious, no matter what they're working on), Richard Hamming\nsuggests that you ask yourself three questions:\n\n What are the most important problems in your field? Are you working on one of them? Why not?\n\nHamming was at Bell Labs when he started asking such questions. In\nprinciple anyone there ought to have been able to work on the most\nimportant problems in their field. Perhaps not everyone can make\nan equally dramatic mark on the world; I don't know; but whatever\nyour capacities, there are projects that stretch them. So Hamming's\nexercise can be generalized to:\n\n What's the best thing you could be working on, and why aren't\n you?\n\nMost people will shy away from this question. I shy away from it\nmyself; I see it there on the page and quickly move on to the next\nsentence. Hamming used to go around actually asking people this,\nand it didn't make him popular. But it's a question anyone ambitious\nshould face.The trouble is, you may end up hooking a very big fish with this\nbait. To do good work, you need to do more than find good projects.\nOnce you've found them, you have to get yourself to work on them,\nand that can be hard. The bigger the problem, the harder it is to\nget yourself to work on it.Of course, the main reason people find it difficult to work on a\nparticular problem is that they don't \nenjoy it. When you're young,\nespecially, you often find yourself working on stuff you don't\nreally like-- because it seems impressive, for example, or because\nyou've been assigned to work on it. Most grad students are stuck\nworking on big problems they don't really like, and grad school is\nthus synonymous with procrastination.But even when you like what you're working on, it's easier to get\nyourself to work on small problems than big ones. Why? Why is it\nso hard to work on big problems? One reason is that you may not\nget any reward in the forseeable future. If you work on something\nyou can finish in a day or two, you can expect to have a nice feeling\nof accomplishment fairly soon. If the reward is indefinitely far\nin the future, it seems less real.Another reason people don't work on big projects is, ironically,\nfear of wasting time. What if they fail? Then all the time they\nspent on it will be wasted. (In fact it probably won't be, because\nwork on hard projects almost always leads somewhere.)But the trouble with big problems can't be just that they promise\nno immediate reward and might cause you to waste a lot of time. If\nthat were all, they'd be no worse than going to visit your in-laws.\nThere's more to it than that. Big problems are terrifying.\nThere's an almost physical pain in facing them. It's like having\na vacuum cleaner hooked up to your imagination. All your initial\nideas get sucked out immediately, and you don't have any more, and\nyet the vacuum cleaner is still sucking.You can't look a big problem too directly in the eye. You have to\napproach it somewhat obliquely. But you have to adjust the angle\njust right: you have to be facing the big problem directly enough\nthat you catch some of the excitement radiating from it, but not\nso much that it paralyzes you. You can tighten the angle once you\nget going, just as a sailboat can sail closer to the wind once it\ngets underway.If you want to work on big things, you seem to have to trick yourself\ninto doing it. You have to work on small things that could grow\ninto big things, or work on successively larger things, or split\nthe moral load with collaborators. It's not a sign of weakness to\ndepend on such tricks. The very best work has been done this way.When I talk to people who've managed to make themselves work on big\nthings, I find that all blow off errands, and all feel guilty about\nit. I don't think they should feel guilty. There's more to do\nthan anyone could. So someone doing the best work they can is\ninevitably going to leave a lot of errands undone. It seems a\nmistake to feel bad about that.I think the way to \"solve\" the problem of procrastination is to let\ndelight pull you instead of making a to-do list push you. Work on\nan ambitious project you really enjoy, and sail as close to the\nwind as you can, and you'll leave the right things undone.Thanks to Trevor Blackwell, Jessica Livingston, and Robert\nMorris for reading drafts of this." }, { "path": "data/PaulGrahamEssays/progbot.txt", "content": "1993\n\n(This essay is from the introduction to On Lisp.)\nIt's a long-standing principle of programming style that the functional\nelements of a program should not be too large. If some component of a\nprogram grows beyond the stage where it's readily comprehensible,\nit becomes a mass of complexity which conceals errors as easily\nas a big city conceals fugitives. Such software will be\nhard to read, hard to test, and hard to debug.In accordance with this principle, a large program must be divided\ninto pieces, and the larger the program, the more it must be divided.\nHow do you divide a program? The traditional approach is\ncalled top-down design: you say \"the purpose of the\nprogram is to do these seven things, so I divide it into seven major\nsubroutines. The first subroutine has to do these four things, so\nit in turn will have four of its own subroutines,\" and so on.\nThis process continues until the whole program has the right level\nof granularity-- each part large enough to do something substantial,\nbut small enough to be understood as a single unit.Experienced Lisp programmers divide up their programs differently.\nAs well as top-down design, they follow a principle which\ncould be called bottom-up design-- changing the language\nto suit the problem.\nIn Lisp, you don't just write your program down toward the language,\nyou also build the language up toward your program. As you're\nwriting a program you may think \"I wish Lisp had such-and-such an\noperator.\" So you go and write it. Afterward\nyou realize that using the new operator would simplify the design \nof another part of the program, and so on.\nLanguage and program evolve together.\nLike the border between two warring states,\nthe boundary between language and program is drawn and redrawn,\nuntil eventually it comes to rest along the mountains and rivers,\nthe natural frontiers of your problem.\nIn the end your program will look as if the language had been\ndesigned for it.\nAnd when language and\nprogram fit one another well, you end up with code which is\nclear, small, and efficient.\nIt's worth emphasizing that bottom-up design doesn't mean\njust writing the same program in a different order. When you\nwork bottom-up, you usually end up with a different program.\nInstead of a single, monolithic program,\nyou will get a larger language with more abstract operators, \nand a smaller program written in it. Instead of a lintel,\nyou'll get an arch.\nIn typical code, once you abstract out the parts which are\nmerely bookkeeping, what's left is much shorter;\nthe higher you build up the language, the less distance you\nwill have to travel from the top down to it.\nThis brings several advantages:\n By making the language do more of the work, bottom-up design\nyields programs which are smaller and more agile. A shorter\nprogram doesn't have to be divided into so many components, and\nfewer components means programs which are easier to read or\nmodify. Fewer components also means fewer connections between \ncomponents, and thus less chance for errors there. As\nindustrial designers strive to reduce the number of moving parts\nin a machine, experienced Lisp programmers use bottom-up design\nto reduce the size and complexity of their programs. Bottom-up design promotes code re-use.\nWhen you write two\nor more programs, many of the utilities you wrote for the first\nprogram will also be useful in the succeeding ones. Once you've \nacquired a large substrate of utilities, writing a new program can\ntake only a fraction of the effort it would require if you had to \nstart with raw Lisp. Bottom-up design makes programs easier to read.\n\nAn instance of this type\nof abstraction asks the reader to understand a general-purpose operator;\nan instance of functional abstraction asks the reader to understand\na special-purpose subroutine. [1] Because it causes you always to be on the lookout for patterns\nin your code, working bottom-up helps to clarify your ideas about\nthe design of your program. If two distant components of a program\nare similar in form, you'll be led to notice the similarity and\nperhaps to redesign the program in a simpler way.\n\n\nBottom-up design is possible to a certain degree in languages\nother than Lisp. Whenever you see library functions,\nbottom-up design is happening. However, Lisp gives you much broader\npowers in this department, and augmenting the language plays a\nproportionately larger role in Lisp style-- so much so that\nLisp is not just a different language, but a whole different way\nof programming.It's true that this style of development is better suited to\nprograms which can be written by small groups. However, at the\nsame time, it extends the limits of what can be done by a small\ngroup. In The Mythical Man-Month,\nFrederick Brooks\nproposed that the productivity of a group of programmers\ndoes not grow linearly with its size. As the size of the\ngroup increases, the productivity of individual programmers\ngoes down. The experience of Lisp programming \nsuggests a more cheerful way\nto phrase this law: as the size of the group decreases, the\nproductivity of individual programmers goes up.\nA small group wins, relatively speaking, simply because it's\nsmaller. When a small group also takes advantage of the\ntechniques that Lisp makes possible, it can \nwin outright.New: Download On Lisp for Free.\n[1] \"But no one can read\nthe program without understanding all your new utilities.\"\nTo see why such statements are usually mistaken,\nsee Section 4.8." }, { "path": "data/PaulGrahamEssays/prop62.txt", "content": "November 2016If you're a California voter, there is an important proposition\non your ballot this year: Proposition 62, which bans the death\npenalty.When I was younger I used to think the debate about the death\npenalty was about when it's ok to take a human life. Is it ok\nto kill a killer?But that is not the issue here.The real world does not work like the version I was shown on TV growing up. The police \noften arrest the wrong person.\nDefendants' lawyers are often incompetent. And prosecutors\nare often motivated more by publicity than justice.In the real world, \nabout 4% of people sentenced to death\nare innocent.\nSo this is not about whether it's ok to kill killers. This\nis about whether it's ok to kill innocent people.A child could answer that one for you.This year, in California, you have a chance to end this, by\nvoting yes on Proposition 62. But beware, because there is another \nproposition, Proposition 66, whose goal is to make it \neasier to execute people. So yes on 62, no on 66.It's time." }, { "path": "data/PaulGrahamEssays/property.txt", "content": "March 2012As a child I read a book of stories about a famous judge in eighteenth\ncentury Japan called Ooka Tadasuke. One of the cases he decided\nwas brought by the owner of a food shop. A poor student who could\nafford only rice was eating his rice while enjoying the delicious\ncooking smells coming from the food shop. The owner wanted the\nstudent to pay for the smells he was enjoying.The student was\nstealing his smells!This story often comes to mind when I hear the RIAA and MPAA accusing\npeople of stealing music and movies.It sounds ridiculous to us to treat smells as property. But I can\nimagine scenarios in which one could charge for smells. Imagine\nwe were living on a moon base where we had to buy air by the\nliter. I could imagine air suppliers adding scents at an extra\ncharge.The reason it seems ridiculous to us to treat smells as property\nis that it wouldn't work to. It would work on a moon base, though.What counts as property depends on what works to treat as property.\nAnd that not only can change, but has changed. Humans may always\n(for some definition of human and always) have treated small items\ncarried on one's person as property. But hunter gatherers didn't\ntreat land, for example, as property in the way we do.\n[1]The reason so many people think of property as having a single\nunchanging definition is that its definition changes very slowly.\n[2]\nBut we are in the midst of such a change now. The record\nlabels and movie studios used to distribute what they made like air\nshipped through tubes on a moon base. But with the arrival of\nnetworks, it's as if we've moved to a planet with a breathable\natmosphere. Data moves like smells now. And through a combination\nof wishful thinking and short-term greed, the labels and studios\nhave put themselves in the position of the food shop owner, accusing\nus all of stealing their smells.(The reason I say short-term greed is that the underlying problem\nwith the labels and studios is that the people who run them are\ndriven by bonuses rather than equity. If they were driven by equity\nthey'd be looking for ways to take advantage of technological change\ninstead of fighting it. But building new things takes too long.\nTheir bonuses depend on this year's revenues, and the best way to\nincrease those is to extract more money from stuff they do already.)So what does this mean? Should people not be able to charge for\ncontent? There's not a single yes or no answer to that question.\nPeople should be able to charge for content when it works to charge\nfor content.But by \"works\" I mean something more subtle than \"when they can get\naway with it.\" I mean when people can charge for content without\nwarping society in order to do it. After all, the companies selling\nsmells on the moon base could continue to sell them on the Earth,\nif they lobbied successfully for laws requiring us all to continue\nto breathe through tubes down here too, even though we no longer\nneeded to.The crazy legal measures that the labels and studios have been\ntaking have a lot of that flavor. Newspapers and magazines are\njust as screwed, but they are at least declining gracefully. The\nRIAA and MPAA would make us breathe through tubes if they could.Ultimately it comes down to common sense. When you're abusing the\nlegal system by trying to use mass lawsuits against randomly chosen\npeople as a form of exemplary punishment, or lobbying for laws\nthat would break the Internet if they passed, that's ipso facto\nevidence you're using a definition of property that doesn't work.This is where it's helpful to have working democracies and multiple\nsovereign countries. If the world had a single, autocratic government,\nthe labels and studios could buy laws making the definition of\nproperty be whatever they wanted. But fortunately there are still\nsome countries that are not copyright colonies of the US, and even\nin the US, politicians\nstill seem to be afraid of actual voters, in sufficient numbers.\n[3]The people running the US may not like it when voters or other\ncountries refuse to bend to their will, but ultimately it's in all\nour interest that there's not a single point of attack for people\ntrying to warp the law to serve their own purposes. Private property\nis an extremely useful idea — arguably one of our greatest inventions.\nSo far, each new definition of it has brought us increasing material\nwealth.\n[4]\nIt seems reasonable to suppose the newest one will\ntoo. It would be a disaster if we all had to keep running an\nobsolete version just because a few powerful people were too lazy\nto upgrade.Notes[1]\nIf you want to learn more about hunter gatherers I strongly\nrecommend Elizabeth Marshall Thomas's The\nHarmless People and The\nOld Way.[2]\nChange in the definition of property is driven mostly by\ntechnological progress, however, and since technological progress\nis accelerating, so presumably will the rate of change in the\ndefinition of property. Which means it's all the more important\nfor societies to be able to respond gracefully to such changes,\nbecause they will come at an ever increasing rate.[3]\nAs far as I know, the term \"copyright colony\" was first used\nby Myles\nPeterson.[4]\nThe state of technology isn't simply a function of\nthe definition of property. They each constrain the other. But\nthat being so, you can't mess with the definition of property without\naffecting (and probably harming) the state of technology. The\nhistory of the USSR offers a vivid illustration of that.Thanks to Sam Altman and Geoff Ralston for reading drafts\nof this." }, { "path": "data/PaulGrahamEssays/publishing.txt", "content": "September 2009Publishers of all types, from news to music, are unhappy that\nconsumers won't pay for content anymore. At least, that's how they\nsee it.In fact consumers never really were paying for content, and publishers\nweren't really selling it either. If the content was what they\nwere selling, why has the price of books or music or movies always\ndepended mostly on the format? Why didn't better content cost more?\n[1]A copy of Time costs $5 for 58 pages, or 8.6 cents a page. \nThe Economist costs $7 for 86 pages, or 8.1 cents a page. Better\njournalism is actually slightly cheaper.Almost every form of publishing has been organized as if the medium\nwas what they were selling, and the content was irrelevant. Book\npublishers, for example, set prices based on the cost of producing\nand distributing books. They treat the words printed in the book\nthe same way a textile manufacturer treats the patterns printed on\nits fabrics.Economically, the print media are in the business of marking up\npaper. We can all imagine an old-style editor getting a scoop and\nsaying \"this will sell a lot of papers!\" Cross out that final S and\nyou're describing their business model. The reason they make less\nmoney now is that people don't need as much paper.A few months ago I ran into a friend in a cafe. I had a copy of\nthe New York Times, which I still occasionally buy on weekends. As\nI was leaving I offered it to him, as I've done countless times\nbefore in the same situation. But this time something new happened.\nI felt that sheepish feeling you get when you offer someone something\nworthless. \"Do you, er, want a printout of yesterday's news?\" I\nasked. (He didn't.)Now that the medium is evaporating, publishers have nothing left\nto sell. Some seem to think they're going to sell content—that\nthey were always in the content business, really. But they weren't,\nand it's unclear whether anyone could be.SellingThere have always been people in the business of selling information,\nbut that has historically been a distinct business from publishing.\nAnd the business of selling information to consumers has always\nbeen a marginal one. When I was a kid there were people who used\nto sell newsletters containing stock tips, printed on colored paper\nthat made them hard for the copiers of the day to reproduce. That\nis a different world, both culturally and economically, from the\none publishers currently inhabit.People will pay for information they think they can make money from.\nThat's why they paid for those stock tip newsletters, and why\ncompanies pay now for Bloomberg terminals and Economist Intelligence\nUnit reports. But will people pay for information otherwise?\nHistory offers little encouragement.If audiences were willing to pay more for better content, why wasn't\nanyone already selling it to them? There was no reason you couldn't\nhave done that in the era of physical media. So were the print\nmedia and the music labels simply overlooking this opportunity? Or\nis it, rather, nonexistent?What about iTunes? Doesn't that show people will pay for content?\nWell, not really. iTunes is more of a tollbooth than a store. Apple\ncontrols the default path onto the iPod. They offer a convenient\nlist of songs, and whenever you choose one they ding your credit\ncard for a small amount, just below the threshold of attention.\nBasically, iTunes makes money by taxing people, not selling them\nstuff. You can only do that if you own the channel, and even then\nyou don't make much from it, because a toll has to be ignorable to\nwork. Once a toll becomes painful, people start to find ways around\nit, and that's pretty easy with digital content.The situation is much the same with digital books. Whoever controls\nthe device sets the terms. It's in their interest for content to\nbe as cheap as possible, and since they own the channel, there's a\nlot they can do to drive prices down. Prices will fall even further\nonce writers realize they don't need publishers. Getting a book\nprinted and distributed is a daunting prospect for a writer, but\nmost can upload a file.Is software a counterexample? People pay a lot for desktop software,\nand that's just information. True, but I don't think publishers\ncan learn much from software. Software companies can charge a lot\nbecause (a) many of the customers are businesses, who get in \ntrouble\nif they use pirated versions, and (b) though in form merely\ninformation, software is treated by both maker and purchaser as a\ndifferent type of thing from a song or an article. A Photoshop\nuser needs Photoshop in a way that no one needs a particular song\nor article.That's why there's a separate word, \"content,\" for information\nthat's not software. Software is a different business. Software\nand content blur together in some of the most lightweight software,\nlike casual games. But those are usually free. To make money the\nway software companies do, publishers would have to become software\ncompanies, and being publishers gives them no particular head start\nin that domain. \n[2]The most promising countertrend is the premium cable channel. People\nstill pay for those. But broadcasting isn't publishing: you're not\nselling a copy of something. That's one reason the movie business\nhasn't seen their revenues decline the way the news and music\nbusinesses have. They only have one foot in publishing.To the extent the movie business can avoid becoming publishers,\nthey may avoid publishing's problems. But there are limits to how\nwell they'll be able to do that. Once publishing—giving people\ncopies—becomes the most natural way of distributing your content,\nit probably doesn't work to stick to old forms of distribution just\nbecause you make more that way. If free copies of your content are\navailable online, then you're competing with publishing's form of\ndistribution, and that's just as bad as being a publisher.Apparently some people in the music business hope to retroactively\nconvert it away from publishing, by getting listeners to pay for\nsubscriptions. It seems unlikely that will work if they're just\nstreaming the same files you can get as mp3s.NextWhat happens to publishing if you can't sell content? You have two\nchoices: give it away and make money from it indirectly, or find\nways to embody it in things people will pay for.The first is probably the future of most current media. \nGive music\naway and make money from concerts and t-shirts. Publish articles\nfor free and make money from one of a dozen permutations of\nadvertising. Both publishers and investors are down on advertising\nat the moment, but it has more potential than they realize.I'm not claiming that potential will be realized by the existing\nplayers. The optimal\nways to make money from the written word\nprobably require different words written by different people.It's harder to say what will happen to movies. They could evolve\ninto ads. Or they could return to their roots and make going to\nthe theater a treat. If they made the experience good enough,\naudiences might start to prefer it to watching pirated movies at\nhome. \n[3]\nOr maybe the movie business will dry up, and the people\nworking in it will go to work for game developers.I don't know how big embodying information in physical form will\nbe. It may be surprisingly large; people overvalue \nphysical stuff.\nThere should remain some market for printed books, at least.I can see the evolution of book publishing in the books on my\nshelves. Clearly at some point in the 1960s the big publishing\nhouses started to ask: how cheaply can we make books before people\nrefuse to buy them? The answer turned out to be one step short of\nphonebooks. As long as it isn't floppy, consumers still perceive\nit as a book.That worked as long as buying printed books was the only way to\nread them. If printed books are optional, publishers will have to\nwork harder to entice people to buy them. There should be some\nmarket, but it's hard to foresee how big, because its size will\ndepend not on macro trends like the amount people read, but on the\ningenuity of individual publishers. \n[4]Some magazines may thrive by focusing on the magazine as a physical\nobject. Fashion magazines could be made lush in a way that would\nbe hard to match digitally, at least for a while. But this is\nprobably not an option for most magazines.I don't know exactly what the future will look like, but I'm not\ntoo worried about it. This sort of change tends to create as many\ngood things as it kills. Indeed, the really interesting question is not\nwhat will happen to existing forms, but what new forms will appear.The reason I've been writing about existing forms is that I don't\nknow what new forms will appear. But though I can't predict\nspecific winners, I can offer a recipe for recognizing them. When\nyou see something that's taking advantage of new technology to give\npeople something they want that they couldn't have before, you're\nprobably looking at a winner. And when you see something that's\nmerely reacting to new technology in an attempt to preserve some\nexisting source of revenue, you're probably looking at a loser.\nNotes[1]\nI don't like the word \"content\" and tried for a while to avoid\nusing it, but I have to admit there's no other word that means the\nright thing. \"Information\" is too general.Ironically, the main reason I don't like \"content\" is the thesis\nof this essay. The word suggests an undifferentiated slurry, but\neconomically that's how both publishers and audiences treat it.\nContent is information you don't need.[2]\nSome types of publishers would be at a disadvantage trying\nto enter the software business. Record labels, for example, would\nprobably find it more natural to expand into casinos than software,\nbecause the kind of people who run them would be more at home at\nthe mafia end of the business spectrum than the don't-be-evil end.[3]\nI never watch movies in theaters anymore. The tipping point\nfor me was the ads they show first.[4]\nUnfortunately, making physically nice books will only be a\nniche within a niche. Publishers are more likely to resort to\nexpedients like selling autographed copies, or editions with the\nbuyer's picture on the cover.Thanks to Michael Arrington, Trevor Blackwell, Steven Levy, Robert\nMorris, and Geoff Ralston for reading drafts of this." }, { "path": "data/PaulGrahamEssays/pypar.txt", "content": "August 2004In a recent talk I said something that upset a lot of\npeople: that you could get smarter programmers to work on\na Python project than you could to work on a Java project.I didn't mean by this that Java programmers are dumb. I\nmeant that Python programmers are smart. It's a lot of\nwork to learn a new programming language. And people don't\nlearn Python because it will get them a job; they learn it\nbecause they genuinely like to program and aren't satisfied with the languages they\nalready know.Which makes them exactly the kind of programmers\ncompanies should want to hire. Hence what, for lack of a better\nname, I'll call the Python paradox: if a company chooses to write\nits software in a comparatively esoteric language, they'll be able \nto hire better programmers, because they'll attract only those\nwho cared enough to learn it. And for \nprogrammers the paradox is even more pronounced: the language\nto learn, if you want to get a good job, is a language that\npeople don't learn merely to get a job.Only a few companies have been smart enough to realize this \nso far. But there is a kind of selection going on here too: they're \nexactly the companies programmers would\nmost like to work for. Google, for example. When they \nadvertise Java programming jobs, they also want Python experience.A friend of mine who knows nearly all the widely used languages\nuses Python for most of his projects. He says the main reason\nis that he likes the way source code looks. That may seem\na frivolous reason to choose one language over another.\nBut it is not so frivolous as it sounds: when you program,\nyou spend more time reading code than writing it.\nYou push blobs of source code around the way a sculptor does\nblobs of clay. So a language that makes source code ugly is\nmaddening to an exacting programmer, as clay full of lumps\nwould be to a sculptor.At the mention of ugly source code, people will of course think\nof Perl. But the superficial ugliness of Perl is not the sort\nI mean. Real ugliness is not harsh-looking\nsyntax, but having to build programs out of the wrong\nconcepts. Perl may look like a cartoon character swearing,\nbut there are \ncases where it surpasses Python conceptually.So far, anyway. Both languages are of course \nmoving targets. But they\nshare, along with Ruby (and Icon, and Joy, and J, and Lisp,\nand Smalltalk) the fact that\nthey're created by, and used by, people who really care about\nprogramming. And those tend to be the ones who do it well." }, { "path": "data/PaulGrahamEssays/ramenprofitable.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nJuly 2009Now that the term \"ramen profitable\" has become widespread, I ought\nto explain precisely what the idea entails.Ramen profitable means a startup makes just enough to pay the\nfounders' living expenses. This is a different form of profitability\nthan startups have traditionally aimed for. Traditional profitability\nmeans a big bet is finally paying off, whereas the main importance\nof ramen profitability is that it buys you time.\n[1]In the past, a startup would usually become profitable only\nafter raising and spending quite a lot of money. A company making\ncomputer hardware might not become profitable for 5 years, during\nwhich they spent $50 million. But when they did\nthey might have revenues of $50 million a year. This kind of\nprofitability means the startup has succeeded.Ramen profitability is the other extreme: a startup that becomes\nprofitable after 2 months, even though its revenues are only $3000\na month, because the only employees are a couple 25 year old founders\nwho can live on practically nothing. Revenues of $3000 a month do\nnot mean the company has succeeded.\nBut it does share something with the one\nthat's profitable in the traditional way: they don't need to raise\nmoney to survive.Ramen profitability is an unfamiliar idea to most people because\nit only recently became feasible. It's still not feasible for a\nlot of startups; it would not be for most biotech startups, for\nexample; but it is for many software startups because they're now\nso cheap. For many, the only real cost is the founders'\nliving expenses.The main significance of this type of profitability is that you're\nno longer at the mercy of investors. If you're still losing money,\nthen eventually you'll either have to raise more\nor shut down. Once you're\nramen profitable this painful choice goes away.\nYou can still raise money, but you don't have to do it now.* * *The most obvious advantage of not needing money is that\nyou can get better terms. If investors know you need money, they'll\nsometimes take advantage of you. Some may even deliberately\nstall, because they know that as you run out of money you'll become\nincreasingly pliable.But there are also three less obvious advantages of ramen profitability.\nOne is that it makes you more attractive to investors. If you're\nalready profitable, on however small a scale, it shows that (a) you\ncan get at least someone to pay you, (b) you're serious about\nbuilding things people want, and (c) you're disciplined enough to\nkeep expenses low.This is reassuring to investors, because you've addressed three of\ntheir biggest worries. It's common for them to fund companies that\nhave smart founders and a big market, and yet still fail. When\nthese companies fail, it's usually because (a) people wouldn't pay\nfor what they made, e.g. because it was too hard to sell to them,\nor the market wasn't ready yet, (b) the founders solved the wrong\nproblem, instead of paying attention to what users needed, or (c)\nthe company spent too much and burned through their funding before\nthey started to make money. If you're ramen profitable, you're\nalready avoiding these mistakes.Another advantage of ramen profitability is that it's good for\nmorale. A company\ntends to feel rather theoretical when you first start it. It's\nlegally a company, but you feel like you're lying when you call it\none. When people start to pay you significant amounts, the company\nstarts to feel real. And your own living expenses are the milestone\nyou feel most, because at that point the future flips state. Now\nsurvival is the default, instead of dying.A morale boost on that scale is very valuable in a startup, because\nthe moral weight of running a startup is what makes it hard. Startups\nare still very rare. Why don't more people do it? The financial\nrisk? Plenty of 25 year olds save nothing anyway. The long hours?\nPlenty of people work just as long hours in regular jobs. What keeps\npeople from starting startups is the fear of having so much\nresponsibility. And this is not an irrational fear: it really is\nhard to bear. Anything that takes some of that weight off you will \ngreatly increase your chances of surviving.A startup that reaches ramen profitability may be more likely\nto succeed than not. Which is pretty exciting, considering the\nbimodal distribution of outcomes in startups: you either fail or\nmake a lot of money.The fourth advantage of ramen profitability is the least obvious\nbut may be the most important. If you don't need to raise money,\nyou don't have to interrupt working on the company to do it.Raising money is terribly distracting. \nYou're lucky if your\nproductivity is a third of what it was before. And it can last for\nmonths.I didn't understand (or rather, remember) precisely why raising\nmoney was so distracting till earlier this year. I'd noticed that\nstartups we funded would usually grind to a halt when they switched\nto raising money, but I didn't remember exactly why till YC raised\nmoney itself. We had a comparatively easy time of it; the first\npeople I asked said yes; but it took months to work out the\ndetails, and during that time I got hardly any real work done. Why?\nBecause I thought about it all the time.At any given time there tends to be one problem that's the most\nurgent for a startup. This is what you think about as you fall\nasleep at night and when you take a shower in the morning. And\nwhen you start raising money, that becomes the problem you think\nabout. You only take one shower in the morning, and if you're\nthinking about investors during it, then you're not thinking about\nthe product.Whereas if you can choose when you raise money, you can pick a time\nwhen you're not in the middle of something else, and you can probably\nalso insist that the round close fast. You may even be able to\navoid having the round occupy your thoughts, if you don't care\nwhether it closes.* * *Ramen profitable means no more than the definition implies. It\ndoes not, for example, imply that you're \"bootstrapping\" the\nstartup—that you're never going to take money from investors.\nEmpirically that doesn't seem to work very well. Few startups\nsucceed without taking investment. Maybe as startups get cheaper\nit will become more common. On the other hand, the money is there,\nwaiting to be invested. If startups need it less, they'll be able\nto get it on better terms, which will make them more inclined to\ntake it. That will tend to produce an equilibrium.\n[2]Another thing ramen profitability doesn't imply is Joe Kraus's idea\nthat you should put your \nbusiness model in beta when you put your\nproduct in beta. He believes you should get\npeople to pay you from the beginning. I think that's too constraining.\nFacebook didn't, and they've done better than most startups. Making\nmoney right away was not only unnecessary for them, but probably\nwould have been harmful. I do think Joe's rule could be useful for\nmany startups, though. When founders seem unfocused, I sometimes\nsuggest they try to get customers to pay them for something, in the\nhope that this constraint will prod them into action.The difference between Joe's idea and ramen profitability is that\na ramen profitable company doesn't have to be making money the way\nit ultimately will. It just has to be making money. The most\nfamous example is Google, which initially made money by licensing\nsearch to sites like Yahoo.Is there a downside to ramen profitability? Probably the biggest\ndanger is that it might turn you into a consulting firm. Startups\nhave to be product companies, in the sense of making a single thing\nthat everyone uses. The defining quality of startups is that they\ngrow fast, and consulting just can't scale the way a product can.\n[3]\nBut it's pretty easy to make $3000 a month consulting; in\nfact, that would be a low rate for contract programming. So there\ncould be a temptation to slide into consulting, and telling\nyourselves you're a ramen profitable startup, when in fact\nyou're not a startup at all.It's ok to do a little consulting-type work at first. Startups\nusually have to do something weird at first. But remember\nthat ramen profitability is not the destination. A startup's\ndestination is to grow really big; ramen profitability is a trick\nfor not dying en route.Notes[1]\nThe \"ramen\" in \"ramen profitable\" refers to instant ramen,\nwhich is just about the cheapest food available.Please do not take the term literally. Living on instant ramen\nwould be very unhealthy. Rice and beans are a better source of\nfood. Start by investing in a rice cooker, if you don't have one.Rice and Beans for 2n\n\n olive oil or butter\n n yellow onions\n other fresh vegetables; experiment\n 3n cloves garlic\n n 12-oz cans white, kidney, or black beans\n n cubes Knorr beef or vegetable bouillon\n n teaspoons freshly ground black pepper\n 3n teaspoons ground cumin\n n cups dry rice, preferably brown\n\nPut rice in rice cooker. Add water as specified on rice package.\n(Default: 2 cups water per cup of rice.) Turn on rice cooker and\nforget about it.Chop onions and other vegetables and fry in oil, over fairly low\nheat, till onions are glassy. Put in chopped garlic, pepper, cumin,\nand a little more fat, and stir. Keep heat low. Cook another 2 or\n3 minutes, then add beans (don't drain the beans), and stir. Throw\nin the bouillon cube(s), cover, and cook on lowish heat for at least\n10 minutes more. Stir vigilantly to avoid sticking.If you want to save money, buy beans in giant cans from discount\nstores. Spices are also much cheaper when bought in bulk.\nIf there's an Indian grocery store near you, they'll have big \nbags of cumin for the same price as the little jars in supermarkets.[2]\nThere's a good chance that a shift in power from investors\nto founders would actually increase the size of the venture business.\nI think investors currently err too far on the side of being harsh\nto founders. If they were forced to stop, the whole venture business\nwould work better, and you might see something like the increase\nin trade you always see when restrictive laws are removed.Investors\nare one of the biggest sources of pain for founders; if they stopped\ncausing so much pain, it would be better to be a founder; and if\nit were better to be a founder, more people would do it.[3]\nIt's conceivable that a startup could grow big by transforming\nconsulting into a form that would scale. But if they did that\nthey'd really be a product company.Thanks to Jessica Livingston for reading drafts of this." }, { "path": "data/PaulGrahamEssays/randomness.txt", "content": "April 2006, rev August 2009Plato quotes Socrates as saying \"the unexamined life is not worth\nliving.\" Part of what he meant was that the proper role of humans is to\nthink, just as the proper role of anteaters is to poke their noses\ninto anthills.A lot of ancient philosophy had the quality — and I\ndon't mean this in an insulting way — of the kind of conversations\nfreshmen have late at night in common rooms:\n\nWhat is our purpose? Well, we humans are\nas conspicuously different from other animals as the anteater.\nIn our case the distinguishing feature is the ability to reason.\nSo obviously that is what we should be doing, and a human who\ndoesn't is doing a bad job of being human — is no better than an\nanimal.\n\nNow we'd give a different answer. At least, someone Socrates's age\nwould. We'd ask why we even suppose we have a \"purpose\" in life.\nWe may be better adapted for some things than others; we\nmay be happier doing things we're adapted for; but why assume\npurpose?The history of ideas\nis a history of gradually discarding the assumption that it's all\nabout us. No, it turns out, the earth is not the center of the\nuniverse — not even the center of the solar system. No, it turns\nout, humans are not created by God in his own image; they're just\none species among many, descended not merely from apes, but from\nmicroorganisms. Even the concept of \"me\" turns out to be fuzzy\naround the edges if you examine it closely.The idea that we're the center of things is difficult to discard.\nSo difficult that there's probably room to discard more. Richard\nDawkins made another step in that direction only in the last several\ndecades, with the idea of the \nselfish gene. \nNo, it turns\nout, we're not even the protagonists: we're just the latest model\nvehicle our genes have constructed to travel around in. And having\nkids is our genes heading for the lifeboats. Reading\nthat book snapped my brain out of its previous way of thinking the\nway Darwin's must have when it first appeared.(Few people can experience now what Darwin's contemporaries did\nwhen The Origin of Species was first published, because everyone\nnow is raised either to take evolution for granted, or to regard\nit as a heresy. No one encounters the idea of natural selection for\nthe first time as an adult.)So if you want to discover things that have been overlooked till\nnow, one really good place to look is in our blind spot: in our\nnatural, naive belief that it's all about us. And expect to encounter\nferocious opposition if you do.Conversely, if you have to choose between two theories, prefer the\none that doesn't center on you.This principle isn't only for big ideas. It works in everyday life,\ntoo. For example, suppose you're saving a piece of cake in the fridge, and you\ncome home one day to find your housemate has eaten\nit. Two possible theories:\n\na) Your housemate did it deliberately to upset you. He knew\nyou were saving that piece of cake.b) Your housemate was hungry.\n\nI say pick b. No one knows who said \"never attribute to malice what\ncan be explained by incompetence,\" but it is a powerful idea.\nIts more general version is our answer to the Greeks:\nDon't see purpose where there isn't.\nOr better still, the positive version:\nSee randomness." }, { "path": "data/PaulGrahamEssays/re.txt", "content": "January 2016One advantage of being old is that you can see change happen in\nyour lifetime. A lot of the change I've seen is fragmentation. US\npolitics is much more polarized than it used to be. Culturally we\nhave ever less common ground. The creative class flocks to a handful\nof happy cities, abandoning the rest. And increasing economic\ninequality means the spread between rich and poor is growing too.\nI'd like to propose a hypothesis: that all these trends are instances\nof the same phenomenon. And moreover, that the cause is not some\nforce that's pulling us apart, but rather the erosion of forces\nthat had been pushing us together.Worse still, for those who worry about these trends, the forces\nthat were pushing us together were an anomaly, a one-time combination\nof circumstances that's unlikely to be repeated — and indeed, that\nwe would not want to repeat.The two forces were war (above all World War II), and the rise of\nlarge corporations.The effects of World War II were both economic and social.\nEconomically, it decreased variation in income. Like all modern\narmed forces, America's were socialist economically. From each\naccording to his ability, to each according to his need. More or\nless. Higher ranking members of the military got more (as higher\nranking members of socialist societies always do), but what they\ngot was fixed according to their rank. And the flattening effect\nwasn't limited to those under arms, because the US economy was\nconscripted too. Between 1942 and 1945 all wages were set by the\nNational War Labor Board. Like the military, they defaulted to\nflatness. And this national standardization of wages was so pervasive\nthat its effects could still be seen years after the war ended.\n[1]Business owners weren't supposed to be making money either. FDR\nsaid \"not a single war millionaire\" would be permitted. To ensure\nthat, any increase in a company's profits over prewar levels was\ntaxed at 85%. And when what was left after corporate taxes reached\nindividuals, it was taxed again at a marginal rate of 93%.\n[2]Socially too the war tended to decrease variation. Over 16 million\nmen and women from all sorts of different backgrounds were brought\ntogether in a way of life that was literally uniform. Service rates\nfor men born in the early 1920s approached 80%. And working toward\na common goal, often under stress, brought them still closer together.Though strictly speaking World War II lasted less than 4 years for\nthe US, its effects lasted longer. Wars make central governments\nmore powerful, and World War II was an extreme case of this. In\nthe US, as in all the other Allied countries, the federal government\nwas slow to give up the new powers it had acquired. Indeed, in\nsome respects the war didn't end in 1945; the enemy just switched\nto the Soviet Union. In tax rates, federal power, defense spending,\nconscription, and nationalism, the decades after the war looked more\nlike wartime than prewar peacetime.\n[3]\nAnd the social effects\nlasted too. The kid pulled into the army from behind a mule team\nin West Virginia didn't simply go back to the farm afterward.\nSomething else was waiting for him, something that looked a lot\nlike the army.If total war was the big political story of the 20th century, the\nbig economic story was the rise of a new kind of company. And this\ntoo tended to produce both social and economic cohesion.\n[4]The 20th century was the century of the big, national corporation.\nGeneral Electric, General Foods, General Motors. Developments in\nfinance, communications, transportation, and manufacturing enabled\na new type of company whose goal was above all scale. Version 1\nof this world was low-res: a Duplo world of a few giant companies\ndominating each big market.\n[5]The late 19th and early 20th centuries had been a time of consolidation,\nled especially by J. P. Morgan. Thousands of companies run by their\nfounders were merged into a couple hundred giant ones run by\nprofessional managers. Economies of scale ruled the day. It seemed\nto people at the time that this was the final state of things. John\nD. Rockefeller said in 1880\n\n The day of combination is here to stay. Individualism has gone,\n never to return.\n\nHe turned out to be mistaken, but he seemed right for the next\nhundred years.The consolidation that began in the late 19th century continued for\nmost of the 20th. By the end of World War II, as Michael Lind\nwrites, \"the major sectors of the economy were either organized\nas government-backed cartels or dominated by a few oligopolistic\ncorporations.\"For consumers this new world meant the same choices everywhere, but\nonly a few of them. When I grew up there were only 2 or 3 of most\nthings, and since they were all aiming at the middle of the market\nthere wasn't much to differentiate them.One of the most important instances of this phenomenon was in TV.\nHere there were 3 choices: NBC, CBS, and ABC. Plus public TV for\neggheads and communists. The programs that the 3 networks offered were\nindistinguishable. In fact, here there was a triple pressure toward\nthe center. If one show did try something daring, local affiliates\nin conservative markets would make them stop. Plus since TVs were\nexpensive, whole families watched the same shows together, so they\nhad to be suitable for everyone.And not only did everyone get the same thing, they got it at the\nsame time. It's difficult to imagine now, but every night tens of\nmillions of families would sit down together in front of their TV\nset watching the same show, at the same time, as their next door\nneighbors. What happens now with the Super Bowl used to happen\nevery night. We were literally in sync.\n[6]In a way mid-century TV culture was good. The view it gave of the\nworld was like you'd find in a children's book, and it probably had\nsomething of the effect that (parents hope) children's books have\nin making people behave better. But, like children's books, TV was\nalso misleading. Dangerously misleading, for adults. In his\nautobiography, Robert MacNeil talks of seeing gruesome images that\nhad just come in from Vietnam and thinking, we can't show these to\nfamilies while they're having dinner.I know how pervasive the common culture was, because I tried to opt\nout of it, and it was practically impossible to find alternatives.\nWhen I was 13 I realized, more from internal evidence than any\noutside source, that the ideas we were being fed on TV were crap,\nand I stopped watching it.\n[7]\nBut it wasn't just TV. It seemed\nlike everything around me was crap. The politicians all saying the\nsame things, the consumer brands making almost identical products\nwith different labels stuck on to indicate how prestigious they\nwere meant to be, the balloon-frame houses with fake \"colonial\"\nskins, the cars with several feet of gratuitous metal on each end\nthat started to fall apart after a couple years, the \"red delicious\"\napples that were red but only nominally \napples. And in retrospect, it was crap.\n[8]But when I went looking for alternatives to fill this void, I found\npractically nothing. There was no Internet then. The only place\nto look was in the chain bookstore in our local shopping mall. \n[9]\nThere I found a copy of The Atlantic. I wish I could say it became\na gateway into a wider world, but in fact I found it boring and\nincomprehensible. Like a kid tasting whisky for the first time and\npretending to like it, I preserved that magazine as carefully as\nif it had been a book. I'm sure I still have it somewhere. But\nthough it was evidence that there was, somewhere, a world that\nwasn't red delicious, I didn't find it till college.It wasn't just as consumers that the big companies made us similar.\nThey did as employers too. Within companies there were powerful\nforces pushing people toward a single model of how to look and act.\nIBM was particularly notorious for this, but they were only a little\nmore extreme than other big companies. And the models of how to\nlook and act varied little between companies. Meaning everyone\nwithin this world was expected to seem more or less the same. And\nnot just those in the corporate world, but also everyone who aspired\nto it — which in the middle of the 20th century meant most people\nwho weren't already in it. For most of the 20th century, working-class\npeople tried hard to look middle class. You can see it in old\nphotos. Few adults aspired to look dangerous in 1950.But the rise of national corporations didn't just compress us\nculturally. It compressed us economically too, and on both ends.Along with giant national corporations, we got giant national labor\nunions. And in the mid 20th century the corporations cut deals\nwith the unions where they paid over market price for labor. Partly\nbecause the unions were monopolies. \n[10]\nPartly because, as\ncomponents of oligopolies themselves, the corporations knew they\ncould safely pass the cost on to their customers, because their\ncompetitors would have to as well. And partly because in mid-century\nmost of the giant companies were still focused on finding new ways\nto milk economies of scale. Just as startups rightly pay AWS a\npremium over the cost of running their own servers so they can focus\non growth, many of the big national corporations were willing to\npay a premium for labor. \n[11]As well as pushing incomes up from the bottom, by overpaying unions,\nthe big companies of the 20th century also pushed incomes down at\nthe top, by underpaying their top management. Economist J. K.\nGalbraith wrote in 1967 that \"There are few corporations in which\nit would be suggested that executive salaries are at a maximum.\"\n[12]To some extent this was an illusion. Much of the de facto pay of\nexecutives never showed up on their income tax returns, because it\ntook the form of perks. The higher the rate of income tax, the\nmore pressure there was to pay employees upstream of it. (In the\nUK, where taxes were even higher than in the US, companies would\neven pay their kids' private school tuitions.) One of the most\nvaluable things the big companies of the mid 20th century gave their\nemployees was job security, and this too didn't show up in tax\nreturns or income statistics. So the nature of employment in these\norganizations tended to yield falsely low numbers about economic\ninequality. But even accounting for that, the big companies paid\ntheir best people less than market price. There was no market; the\nexpectation was that you'd work for the same company for decades\nif not your whole career. \n[13]Your work was so illiquid there was little chance of getting market\nprice. But that same illiquidity also encouraged you not to seek\nit. If the company promised to employ you till you retired and\ngive you a pension afterward, you didn't want to extract as much\nfrom it this year as you could. You needed to take care of the\ncompany so it could take care of you. Especially when you'd been\nworking with the same group of people for decades. If you tried\nto squeeze the company for more money, you were squeezing the\norganization that was going to take care of them. Plus if\nyou didn't put the company first you wouldn't be promoted, and if\nyou couldn't switch ladders, promotion on this one was the only way\nup. \n[14]To someone who'd spent several formative years in the armed forces,\nthis situation didn't seem as strange as it does to us now. From\ntheir point of view, as big company executives, they were high-ranking\nofficers. They got paid a lot more than privates. They got to\nhave expense account lunches at the best restaurants and fly around\non the company's Gulfstreams. It probably didn't occur to most of\nthem to ask if they were being paid market price.The ultimate way to get market price is to work for yourself, by\nstarting your own company. That seems obvious to any ambitious\nperson now. But in the mid 20th century it was an alien concept.\nNot because starting one's own company seemed too ambitious, but\nbecause it didn't seem ambitious enough. Even as late as the 1970s,\nwhen I grew up, the ambitious plan was to get lots of education at\nprestigious institutions, and then join some other prestigious\ninstitution and work one's way up the hierarchy. Your prestige was\nthe prestige of the institution you belonged to. People did start\ntheir own businesses of course, but educated people rarely did,\nbecause in those days there was practically zero concept of starting\nwhat we now call a startup: \na business that starts small and grows\nbig. That was much harder to do in the mid 20th century. Starting\none's own business meant starting a business that would start small\nand stay small. Which in those days of big companies often meant\nscurrying around trying to avoid being trampled by elephants. It\nwas more prestigious to be one of the executive class riding the\nelephant.By the 1970s, no one stopped to wonder where the big prestigious\ncompanies had come from in the first place. It seemed like they'd\nalways been there, like the chemical elements. And indeed, there\nwas a double wall between ambitious kids in the 20th century and\nthe origins of the big companies. Many of the big companies were\nroll-ups that didn't have clear founders. And when they did, the\nfounders didn't seem like us. Nearly all of them had been uneducated,\nin the sense of not having been to college. They were what Shakespeare\ncalled rude mechanicals. College trained one to be a member of the\nprofessional classes. Its graduates didn't expect to do the sort\nof grubby menial work that Andrew Carnegie or Henry Ford started\nout doing. \n[15]And in the 20th century there were more and more college graduates.\nThey increased from about 2% of the population in 1900 to about 25%\nin 2000. In the middle of the century our two big forces intersect,\nin the form of the GI Bill, which sent 2.2 million World War II\nveterans to college. Few thought of it in these terms, but the\nresult of making college the canonical path for the ambitious was\na world in which it was socially acceptable to work for Henry Ford,\nbut not to be Henry Ford.\n[16]I remember this world well. I came of age just as it was starting\nto break up. In my childhood it was still dominant. Not quite so\ndominant as it had been. We could see from old TV shows and yearbooks\nand the way adults acted that people in the 1950s and 60s had been\neven more conformist than us. The mid-century model was already\nstarting to get old. But that was not how we saw it at the time.\nWe would at most have said that one could be a bit more daring in\n1975 than 1965. And indeed, things hadn't changed much yet.But change was coming soon. And when the Duplo economy started to\ndisintegrate, it disintegrated in several different ways at once.\nVertically integrated companies literally dis-integrated because\nit was more efficient to. Incumbents faced new competitors as (a)\nmarkets went global and (b) technical innovation started to trump\neconomies of scale, turning size from an asset into a liability.\nSmaller companies were increasingly able to survive as formerly\nnarrow channels to consumers broadened. Markets themselves started\nto change faster, as whole new categories of products appeared. And\nlast but not least, the federal government, which had previously\nsmiled upon J. P. Morgan's world as the natural state of things,\nbegan to realize it wasn't the last word after all.What J. P. Morgan was to the horizontal axis, Henry Ford was to the\nvertical. He wanted to do everything himself. The giant plant he\nbuilt at River Rouge between 1917 and 1928 literally took in iron\nore at one end and sent cars out the other. 100,000 people worked\nthere. At the time it seemed the future. But that is not how car\ncompanies operate today. Now much of the design and manufacturing\nhappens in a long supply chain, whose products the car companies\nultimately assemble and sell. The reason car companies operate\nthis way is that it works better. Each company in the supply chain\nfocuses on what they know best. And they each have to do it well\nor they can be swapped out for another supplier.Why didn't Henry Ford realize that networks of cooperating companies\nwork better than a single big company? One reason is that supplier\nnetworks take a while to evolve. In 1917, doing everything himself\nseemed to Ford the only way to get the scale he needed. And the\nsecond reason is that if you want to solve a problem using a network\nof cooperating companies, you have to be able to coordinate their\nefforts, and you can do that much better with computers. Computers\nreduce the transaction costs that Coase argued are the raison d'etre\nof corporations. That is a fundamental change.In the early 20th century, big companies were synonymous with\nefficiency. In the late 20th century they were synonymous with\ninefficiency. To some extent this was because the companies\nthemselves had become sclerotic. But it was also because our\nstandards were higher.It wasn't just within existing industries that change occurred.\nThe industries themselves changed. It became possible to make lots\nof new things, and sometimes the existing companies weren't the\nones who did it best.Microcomputers are a classic example. The market was pioneered by\nupstarts like Apple. When it got big enough, IBM decided it was\nworth paying attention to. At the time IBM completely dominated\nthe computer industry. They assumed that all they had to do, now\nthat this market was ripe, was to reach out and pick it. Most\npeople at the time would have agreed with them. But what happened\nnext illustrated how much more complicated the world had become.\nIBM did launch a microcomputer. Though quite successful, it did\nnot crush Apple. But even more importantly, IBM itself ended up\nbeing supplanted by a supplier coming in from the side — from\nsoftware, which didn't even seem to be the same business. IBM's\nbig mistake was to accept a non-exclusive license for DOS. It must\nhave seemed a safe move at the time. No other computer manufacturer\nhad ever been able to outsell them. What difference did it make if\nother manufacturers could offer DOS too? The result of that\nmiscalculation was an explosion of inexpensive PC clones. Microsoft\nnow owned the PC standard, and the customer. And the microcomputer\nbusiness ended up being Apple vs Microsoft.Basically, Apple bumped IBM and then Microsoft stole its wallet.\nThat sort of thing did not happen to big companies in mid-century.\nBut it was going to happen increasingly often in the future.Change happened mostly by itself in the computer business. In other\nindustries, legal obstacles had to be removed first. Many of the\nmid-century oligopolies had been anointed by the federal government\nwith policies (and in wartime, large orders) that kept out competitors.\nThis didn't seem as dubious to government officials at the time as\nit sounds to us. They felt a two-party system ensured sufficient\ncompetition in politics. It ought to work for business too.Gradually the government realized that anti-competitive policies\nwere doing more harm than good, and during the Carter administration\nit started to remove them. The word used for this process was\nmisleadingly narrow: deregulation. What was really happening was\nde-oligopolization. It happened to one industry after another.\nTwo of the most visible to consumers were air travel and long-distance\nphone service, which both became dramatically cheaper after\nderegulation.Deregulation also contributed to the wave of hostile takeovers in\nthe 1980s. In the old days the only limit on the inefficiency of\ncompanies, short of actual bankruptcy, was the inefficiency of their\ncompetitors. Now companies had to face absolute rather than relative\nstandards. Any public company that didn't generate sufficient\nreturns on its assets risked having its management replaced with\none that would. Often the new managers did this by breaking companies\nup into components that were more valuable separately.\n[17]Version 1 of the national economy consisted of a few big blocks\nwhose relationships were negotiated in back rooms by a handful of\nexecutives, politicians, regulators, and labor leaders. Version 2\nwas higher resolution: there were more companies, of more different\nsizes, making more different things, and their relationships changed\nfaster. In this world there were still plenty of back room negotiations,\nbut more was left to market forces. Which further accelerated the\nfragmentation.It's a little misleading to talk of versions when describing a\ngradual process, but not as misleading as it might seem. There was\na lot of change in a few decades, and what we ended up with was\nqualitatively different. The companies in the S&P 500 in 1958 had\nbeen there an average of 61 years. By 2012 that number was 18 years.\n[18]The breakup of the Duplo economy happened simultaneously with the\nspread of computing power. To what extent were computers a precondition?\nIt would take a book to answer that. Obviously the spread of computing\npower was a precondition for the rise of startups. I suspect it\nwas for most of what happened in finance too. But was it a\nprecondition for globalization or the LBO wave? I don't know, but\nI wouldn't discount the possibility. It may be that the refragmentation\nwas driven by computers in the way the industrial revolution was\ndriven by steam engines. Whether or not computers were a precondition,\nthey have certainly accelerated it.The new fluidity of companies changed people's relationships with\ntheir employers. Why climb a corporate ladder that might be yanked\nout from under you? Ambitious people started to think of a career\nless as climbing a single ladder than as a series of jobs that might\nbe at different companies. More movement (or even potential movement)\nbetween companies introduced more competition in salaries. Plus\nas companies became smaller it became easier to estimate how much\nan employee contributed to the company's revenue. Both changes\ndrove salaries toward market price. And since people vary dramatically\nin productivity, paying market price meant salaries started to\ndiverge.By no coincidence it was in the early 1980s that the term \"yuppie\"\nwas coined. That word is not much used now, because the phenomenon\nit describes is so taken for granted, but at the time it was a label\nfor something novel. Yuppies were young professionals who made lots\nof money. To someone in their twenties today, this wouldn't seem\nworth naming. Why wouldn't young professionals make lots of money?\nBut until the 1980s, being underpaid early in your career was part\nof what it meant to be a professional. Young professionals were\npaying their dues, working their way up the ladder. The rewards\nwould come later. What was novel about yuppies was that they wanted\nmarket price for the work they were doing now.The first yuppies did not work for startups. That was still in the\nfuture. Nor did they work for big companies. They were professionals\nworking in fields like law, finance, and consulting. But their example \nrapidly inspired their peers. Once they saw that new BMW 325i, they \nwanted one too.Underpaying people at the beginning of their career only works if\neveryone does it. Once some employer breaks ranks, everyone else\nhas to, or they can't get good people. And once started this process\nspreads through the whole economy, because at the beginnings of\npeople's careers they can easily switch not merely employers but\nindustries.But not all young professionals benefitted. You had to produce to\nget paid a lot. It was no coincidence that the first yuppies worked\nin fields where it was easy to measure that.More generally, an idea was returning whose name sounds old-fashioned\nprecisely because it was so rare for so long: that you could make\nyour fortune. As in the past there were multiple ways to do it.\nSome made their fortunes by creating wealth, and others by playing\nzero-sum games. But once it became possible to make one's fortune,\nthe ambitious had to decide whether or not to. A physicist who\nchose physics over Wall Street in 1990 was making a sacrifice that\na physicist in 1960 didn't have to think about.The idea even flowed back into big companies. CEOs of big companies\nmake more now than they used to, and I think much of the reason is\nprestige. In 1960, corporate CEOs had immense prestige. They were\nthe winners of the only economic game in town. But if they made as\nlittle now as they did then, in real dollar terms, they'd seem like\nsmall fry compared to professional athletes and whiz kids making\nmillions from startups and hedge funds. They don't like that idea,\nso now they try to get as much as they can, which is more than they\nhad been getting. \n[19]Meanwhile a similar fragmentation was happening at the other end\nof the economic scale. As big companies' oligopolies became less\nsecure, they were less able to pass costs on to customers and thus\nless willing to overpay for labor. And as the Duplo world of a few\nbig blocks fragmented into many companies of different sizes — some\nof them overseas — it became harder for unions to enforce their\nmonopolies. As a result workers' wages also tended toward market\nprice. Which (inevitably, if unions had been doing their job) tended\nto be lower. Perhaps dramatically so, if automation had decreased\nthe need for some kind of work.And just as the mid-century model induced social as well as economic\ncohesion, its breakup brought social as well as economic fragmentation.\nPeople started to dress and act differently. Those who would later\nbe called the \"creative class\" became more mobile. People who didn't\ncare much for religion felt less pressure to go to church for\nappearances' sake, while those who liked it a lot opted for\nincreasingly colorful forms. Some switched from meat loaf to tofu,\nand others to Hot Pockets. Some switched from driving Ford sedans\nto driving small imported cars, and others to driving SUVs. Kids\nwho went to private schools or wished they did started to dress\n\"preppy,\" and kids who wanted to seem rebellious made a conscious\neffort to look disreputable. In a hundred ways people spread apart.\n[20]Almost four decades later, fragmentation is still increasing. Has\nit been net good or bad? I don't know; the question may be\nunanswerable. Not entirely bad though. We take for granted the\nforms of fragmentation we like, and worry only about the ones we\ndon't. But as someone who caught the tail end of mid-century\nconformism, \nI can tell you it was no utopia.\n[21]My goal here is not to say whether fragmentation has been good or\nbad, just to explain why it's happening. With the centripetal\nforces of total war and 20th century oligopoly mostly gone, what\nwill happen next? And more specifically, is it possible to reverse\nsome of the fragmentation we've seen?If it is, it will have to happen piecemeal. You can't reproduce\nmid-century cohesion the way it was originally produced. It would\nbe insane to go to war just to induce more national unity. And\nonce you understand the degree to which the economic history of the\n20th century was a low-res version 1, it's clear you can't reproduce\nthat either.20th century cohesion was something that happened at least in a\nsense naturally. The war was due mostly to external forces, and\nthe Duplo economy was an evolutionary phase. If you want cohesion\nnow, you'd have to induce it deliberately. And it's not obvious\nhow. I suspect the best we'll be able to do is address the symptoms\nof fragmentation. But that may be enough.The form of fragmentation people worry most about lately is economic inequality, and if you want to eliminate\nthat you're up against a truly formidable headwind that has\nbeen in operation since the stone age. Technology.Technology is\na lever. It magnifies work. And the lever not only grows increasingly\nlong, but the rate at which it grows is itself increasing.Which in turn means the variation in the amount of wealth people\ncan create has not only been increasing, but accelerating. The\nunusual conditions that prevailed in the mid 20th century masked\nthis underlying trend. The ambitious had little choice but to join\nlarge organizations that made them march in step with lots of other\npeople — literally in the case of the armed forces, figuratively\nin the case of big corporations. Even if the big corporations had\nwanted to pay people proportionate to their value, they couldn't\nhave figured out how. But that constraint has gone now. Ever since\nit started to erode in the 1970s, we've seen the underlying forces\nat work again.\n[22]Not everyone who gets rich now does it by creating wealth, certainly.\nBut a significant number do, and the Baumol Effect means all their\npeers get dragged along too.\n[23]\nAnd as long as it's possible to\nget rich by creating wealth, the default tendency will be for\neconomic inequality to increase. Even if you eliminate all the\nother ways to get rich. You can mitigate this with subsidies at\nthe bottom and taxes at the top, but unless taxes are high enough\nto discourage people from creating wealth, you're always going to\nbe fighting a losing battle against increasing variation in\nproductivity.\n[24]That form of fragmentation, like the others, is here to stay. Or\nrather, back to stay. Nothing is forever, but the tendency toward\nfragmentation should be more forever than most things, precisely\nbecause it's not due to any particular cause. It's simply a reversion\nto the mean. When Rockefeller said individualism was gone, he was\nright for a hundred years. It's back now, and that's likely to be\ntrue for longer.I worry that if we don't acknowledge this, we're headed for trouble.\nIf we think 20th century cohesion disappeared because of few policy\ntweaks, we'll be deluded into thinking we can get it back (minus\nthe bad parts, somehow) with a few countertweaks. And then we'll\nwaste our time trying to eliminate fragmentation, when we'd be\nbetter off thinking about how to mitigate its consequences.\nNotes[1]\nLester Thurow, writing in 1975, said the wage differentials\nprevailing at the end of World War II had become so embedded that\nthey \"were regarded as 'just' even after the egalitarian pressures\nof World War II had disappeared. Basically, the same differentials\nexist to this day, thirty years later.\" But Goldin and Margo think\nmarket forces in the postwar period also helped preserve the wartime\ncompression of wages — specifically increased demand for unskilled\nworkers, and oversupply of educated ones.(Oddly enough, the American custom of having employers pay for\nhealth insurance derives from efforts by businesses to circumvent\nNWLB wage controls in order to attract workers.)[2]\nAs always, tax rates don't tell the whole story. There were\nlots of exemptions, especially for individuals. And in World War\nII the tax codes were so new that the government had little acquired\nimmunity to tax avoidance. If the rich paid high taxes during the\nwar it was more because they wanted to than because they had to.After the war, federal tax receipts as a percentage of GDP were\nabout the same as they are now. In fact, for the entire period since\nthe war, tax receipts have stayed close to 18% of GDP, despite\ndramatic changes in tax rates. The lowest point occurred when\nmarginal income tax rates were highest: 14.1% in 1950. Looking at\nthe data, it's hard to avoid the conclusion that tax rates have had\nlittle effect on what people actually paid.[3]\nThough in fact the decade preceding the war had been a time\nof unprecedented federal power, in response to the Depression.\nWhich is not entirely a coincidence, because the Depression was one\nof the causes of the war. In many ways the New Deal was a sort of\ndress rehearsal for the measures the federal government took during\nwartime. The wartime versions were much more drastic and more\npervasive though. As Anthony Badger wrote, \"for many Americans the\ndecisive change in their experiences came not with the New Deal but\nwith World War II.\"[4]\nI don't know enough about the origins of the world wars to\nsay, but it's not inconceivable they were connected to the rise of\nbig corporations. If that were the case, 20th century cohesion would\nhave a single cause.[5]\nMore precisely, there was a bimodal economy consisting, in\nGalbraith's words, of \"the world of the technically dynamic, massively\ncapitalized and highly organized corporations on the one hand and\nthe hundreds of thousands of small and traditional proprietors on\nthe other.\" Money, prestige, and power were concentrated in the\nformer, and there was near zero crossover.[6]\nI wonder how much of the decline in families eating together\nwas due to the decline in families watching TV together afterward.[7]\nI know when this happened because it was the season Dallas\npremiered. Everyone else was talking about what was happening on\nDallas, and I had no idea what they meant.[8]\nI didn't realize it till I started doing research for this\nessay, but the meretriciousness of the products I grew up with is\na well-known byproduct of oligopoly. When companies can't compete\non price, they compete on tailfins.[9]\nMonroeville Mall was at the time of its completion in 1969\nthe largest in the country. In the late 1970s the movie Dawn of\nthe Dead was shot there. Apparently the mall was not just the\nlocation of the movie, but its inspiration; the crowds of shoppers\ndrifting through this huge mall reminded George Romero of zombies.\nMy first job was scooping ice cream in the Baskin-Robbins.[10]\nLabor unions were exempted from antitrust laws by the Clayton\nAntitrust Act in 1914 on the grounds that a person's work is not\n\"a commodity or article of commerce.\" I wonder if that means service\ncompanies are also exempt.[11]\nThe relationships between unions and unionized companies can\neven be symbiotic, because unions will exert political pressure to\nprotect their hosts. According to Michael Lind, when politicians\ntried to attack the A&P supermarket chain because it was putting\nlocal grocery stores out of business, \"A&P successfully defended\nitself by allowing the unionization of its workforce in 1938, thereby\ngaining organized labor as a constituency.\" I've seen this phenomenon\nmyself: hotel unions are responsible for more of the political\npressure against Airbnb than hotel companies.[12]\nGalbraith was clearly puzzled that corporate executives would\nwork so hard to make money for other people (the shareholders)\ninstead of themselves. He devoted much of The New Industrial\nState to trying to figure this out.His theory was that professionalism had replaced money as a motive,\nand that modern corporate executives were, like (good) scientists,\nmotivated less by financial rewards than by the desire to do good\nwork and thereby earn the respect of their peers. There is something\nin this, though I think lack of movement between companies combined\nwith self-interest explains much of observed behavior.[13]\nGalbraith (p. 94) says a 1952 study of the 800 highest paid\nexecutives at 300 big corporations found that three quarters of\nthem had been with their company for more than 20 years.[14]\nIt seems likely that in the first third of the 20th century\nexecutive salaries were low partly because companies then were more\ndependent on banks, who would have disapproved if executives got\ntoo much. This was certainly true in the beginning. The first big\ncompany CEOs were J. P. Morgan's hired hands.Companies didn't start to finance themselves with retained earnings\ntill the 1920s. Till then they had to pay out their earnings in\ndividends, and so depended on banks for capital for expansion.\nBankers continued to sit on corporate boards till the Glass-Steagall\nact in 1933.By mid-century big companies funded 3/4 of their growth from earnings.\nBut the early years of bank dependence, reinforced by the financial\ncontrols of World War II, must have had a big effect on social\nconventions about executive salaries. So it may be that the lack\nof movement between companies was as much the effect of low salaries\nas the cause.Incidentally, the switch in the 1920s to financing growth with\nretained earnings was one cause of the 1929 crash. The banks now\nhad to find someone else to lend to, so they made more margin loans.[15]\nEven now it's hard to get them to. One of the things I find\nhardest to get into the heads of would-be startup founders is how\nimportant it is to do certain kinds of menial work early in the\nlife of a company. Doing things that don't\nscale is to how Henry Ford got started as a high-fiber diet is\nto the traditional peasant's diet: they had no choice but to do the\nright thing, while we have to make a conscious effort.[16]\nFounders weren't celebrated in the press when I was a kid.\n\"Our founder\" meant a photograph of a severe-looking man with a\nwalrus mustache and a wing collar who had died decades ago. The\nthing to be when I was a kid was an executive. If you weren't\naround then it's hard to grasp the cachet that term had. The fancy\nversion of everything was called the \"executive\" model.[17]\nThe wave of hostile takeovers in the 1980s was enabled by a\ncombination of circumstances: court decisions striking down state\nanti-takeover laws, starting with the Supreme Court's 1982 decision\nin Edgar v. MITE Corp.; the Reagan administration's comparatively\nsympathetic attitude toward takeovers; the Depository Institutions\nAct of 1982, which allowed banks and savings and loans to buy\ncorporate bonds; a new SEC rule issued in 1982 (rule 415) that made\nit possible to bring corporate bonds to market faster; the creation\nof the junk bond business by Michael Milken; a vogue for conglomerates\nin the preceding period that caused many companies to be combined\nthat never should have been; a decade of inflation that left many\npublic companies trading below the value of their assets; and not\nleast, the increasing complacency of managements.[18]\nFoster, Richard. \"Creative Destruction Whips through Corporate\nAmerica.\" Innosight, February 2012.[19]\nCEOs of big companies may be overpaid. I don't know enough\nabout big companies to say. But it is certainly not impossible for\na CEO to make 200x as much difference to a company's revenues as\nthe average employee. Look at what Steve Jobs did for Apple when\nhe came back as CEO. It would have been a good deal for the board\nto give him 95% of the company. Apple's market cap the day Steve\ncame back in July 1997 was 1.73 billion. 5% of Apple now (January\n2016) would be worth about 30 billion. And it would not be if Steve\nhadn't come back; Apple probably wouldn't even exist anymore.Merely including Steve in the sample might be enough to answer the\nquestion of whether public company CEOs in the aggregate are overpaid.\nAnd that is not as facile a trick as it might seem, because the\nbroader your holdings, the more the aggregate is what you care\nabout.[20]\nThe late 1960s were famous for social upheaval. But that was\nmore rebellion (which can happen in any era if people are provoked\nsufficiently) than fragmentation. You're not seeing fragmentation\nunless you see people breaking off to both left and right.[21]\nGlobally the trend has been in the other direction. While\nthe US is becoming more fragmented, the world as a whole is becoming\nless fragmented, and mostly in good ways.[22]\nThere were a handful of ways to make a fortune in the mid\n20th century. The main one was drilling for oil, which was open\nto newcomers because it was not something big companies could\ndominate through economies of scale. How did individuals accumulate\nlarge fortunes in an era of such high taxes? Giant tax loopholes\ndefended by two of the most powerful men in Congress, Sam Rayburn\nand Lyndon Johnson.But becoming a Texas oilman was not in 1950 something one could\naspire to the way starting a startup or going to work on Wall Street\nwere in 2000, because (a) there was a strong local component and\n(b) success depended so much on luck.[23]\nThe Baumol Effect induced by startups is very visible in\nSilicon Valley. Google will pay people millions of dollars a year\nto keep them from leaving to start or join startups.[24]\nI'm not claiming variation in productivity is the only cause\nof economic inequality in the US. But it's a significant cause, and\nit will become as big a cause as it needs to, in the sense that if\nyou ban other ways to get rich, people who want to get rich will\nuse this route instead.Thanks to Sam Altman, Trevor Blackwell, Paul Buchheit, Patrick\nCollison, Ron Conway, Chris Dixon, Benedict Evans, Richard Florida,\nBen Horowitz, Jessica Livingston, Robert Morris, Tim O'Reilly, Geoff\nRalston, Max Roser, Alexia Tsotsis, and Qasar Younis for reading\ndrafts of this. Max also told me about several valuable sources.BibliographyAllen, Frederick Lewis. The Big Change. Harper, 1952.Averitt, Robert. The Dual Economy. Norton, 1968.Badger, Anthony. The New Deal. Hill and Wang, 1989.Bainbridge, John. The Super-Americans. Doubleday, 1961.Beatty, Jack. Collossus. Broadway, 2001.Brinkley, Douglas. Wheels for the World. Viking, 2003.Brownleee, W. Elliot. Federal Taxation in America. Cambridge, 1996.Chandler, Alfred. The Visible Hand. Harvard, 1977.Chernow, Ron. The House of Morgan. Simon & Schuster, 1990.Chernow, Ron. Titan: The Life of John D. Rockefeller. Random House,\n1998.Galbraith, John. The New Industrial State. Houghton Mifflin, 1967.Goldin, Claudia and Robert A. Margo. \"The Great Compression: The\nWage Structure in the United States at Mid-Century.\" NBER Working\nPaper 3817, 1991.Gordon, John. An Empire of Wealth. HarperCollins, 2004.Klein, Maury. The Genesis of Industrial America, 1870-1920. Cambridge,\n2007.Lind, Michael. Land of Promise. HarperCollins, 2012.Mickelthwaite, John, and Adrian Wooldridge. The Company. Modern\nLibrary, 2003.Nasaw, David. Andrew Carnegie. Penguin, 2006.Sobel, Robert. The Age of Giant Corporations. Praeger, 1993.Thurow, Lester. Generating Inequality: Mechanisms of Distribution.\nBasic Books, 1975.Witte, John. The Politics and Development of the Federal Income\nTax. Wisconsin, 1985.Related:" }, { "path": "data/PaulGrahamEssays/read.txt", "content": "November 2022In the science fiction books I read as a kid, reading had often\nbeen replaced by some more efficient way of acquiring knowledge.\nMysterious \"tapes\" would load it into one's brain like a program\nbeing loaded into a computer.That sort of thing is unlikely to happen anytime soon. Not just\nbecause it would be hard to build a replacement for reading, but\nbecause even if one existed, it would be insufficient. Reading about\nx doesn't just teach you about x; it also teaches you how to write.\n[1]Would that matter? If we replaced reading, would anyone need to be\ngood at writing?The reason it would matter is that writing is not just a way to\nconvey ideas, but also a way to have them.A good writer doesn't just think, and then write down what he\nthought, as a sort of transcript. A good writer will almost always\ndiscover new things in the process of writing. And there is, as far\nas I know, no substitute for this kind of discovery. Talking about\nyour ideas with other people is a good way to develop them. But\neven after doing this, you'll find you still discover new things\nwhen you sit down to write. There is a kind of thinking that can\nonly be done by writing.There are of course kinds of thinking that can be done without\nwriting. If you don't need to go too deeply into a problem, you can\nsolve it without writing. If you're thinking about how two pieces\nof machinery should fit together, writing about it probably won't\nhelp much. And when a problem can be described formally, you can\nsometimes solve it in your head. But if you need to solve a\ncomplicated, ill-defined problem, it will almost always help to\nwrite about it. Which in turn means that someone who's not good at\nwriting will almost always be at a disadvantage in solving such\nproblems.You can't think well without writing well, and you can't write well\nwithout reading well. And I mean that last \"well\" in both senses.\nYou have to be good at reading, and read good things.\n[2]People who just want information may find other ways to get it.\nBut people who want to have ideas can't afford to.Notes[1]\nAudiobooks can give you examples of good writing, but having\nthem read to you doesn't teach you as much about writing as reading\nthem yourself.[2]\nBy \"good at reading\" I don't mean good at the mechanics of\nreading. You don't have to be good at extracting words from the\npage so much as extracting meaning from the words." }, { "path": "data/PaulGrahamEssays/real.txt", "content": "April 2021When intellectuals talk about the death penalty, they talk about\nthings like whether it's permissible for the state to take someone's\nlife, whether the death penalty acts as a deterrent, and whether\nmore death sentences are given to some groups than others. But in\npractice the debate about the death penalty is not about whether\nit's ok to kill murderers. It's about whether it's ok to kill\ninnocent people, because at least 4% of people on death row are\ninnocent.When I was a kid I imagined that it was unusual for people to be\nconvicted of crimes they hadn't committed, and that in murder cases\nespecially this must be very rare. Far from it. Now, thanks to\norganizations like the\nInnocence Project,\nwe see a constant stream\nof stories about murder convictions being overturned after new\nevidence emerges. Sometimes the police and prosecutors were just\nvery sloppy. Sometimes they were crooked, and knew full well they\nwere convicting an innocent person.Kenneth Adams and three other men spent 18 years in prison on a\nmurder conviction. They were exonerated after DNA testing implicated\nthree different men, two of whom later confessed. The police had\nbeen told about the other men early in the investigation, but never\nfollowed up the lead.Keith Harward spent 33 years in prison on a murder conviction. He\nwas convicted because \"experts\" said his teeth matched photos of\nbite marks on one victim. He was exonerated after DNA testing showed\nthe murder had been committed by another man, Jerry Crotty.Ricky Jackson and two other men spent 39 years in prison after being\nconvicted of murder on the testimony of a 12 year old boy, who later\nrecanted and said he'd been coerced by police. Multiple people have\nconfirmed the boy was elsewhere at the time. The three men were\nexonerated after the county prosecutor dropped the charges, saying\n\"The state is conceding the obvious.\"Alfred Brown spent 12 years in prison on a murder conviction,\nincluding 10 years on death row. He was exonerated after it was\ndiscovered that the assistant district attorney had concealed phone\nrecords proving he could not have committed the crimes.Glenn Ford spent 29 years on death row after having been convicted\nof murder. He was exonerated after new evidence proved he was not\neven at the scene when the murder occurred. The attorneys assigned\nto represent him had never tried a jury case before.Cameron Willingham was actually executed in 2004 by lethal injection.\nThe \"expert\" who testified that he deliberately set fire to his\nhouse has since been discredited. A re-examination of the case\nordered by the state of Texas in 2009 concluded that \"a finding of\narson could not be sustained.\"Rich Glossip \nhas spent 20 years on death row after being convicted\nof murder on the testimony of the actual killer, who escaped with\na life sentence in return for implicating him. In 2015 he came\nwithin minutes of execution before it emerged that Oklahoma had\nbeen planning to kill him with an illegal combination of drugs.\nThey still plan to go ahead with the execution, perhaps as soon as\nthis summer, despite \nnew \nevidence exonerating him.I could go on. There are hundreds of similar cases. In Florida\nalone, 29 death row prisoners have been exonerated so far.Far from being rare, wrongful murder convictions are \nvery common.\nPolice are under pressure to solve a crime that has gotten a lot\nof attention. When they find a suspect, they want to believe he's\nguilty, and ignore or even destroy evidence suggesting otherwise.\nDistrict attorneys want to be seen as effective and tough on crime,\nand in order to win convictions are willing to manipulate witnesses\nand withhold evidence. Court-appointed defense attorneys are\noverworked and often incompetent. There's a ready supply of criminals\nwilling to give false testimony in return for a lighter sentence,\nsuggestible witnesses who can be made to say whatever police want,\nand bogus \"experts\" eager to claim that science proves the defendant\nis guilty. And juries want to believe them, since otherwise some\nterrible crime remains unsolved.This circus of incompetence and dishonesty is the real issue with\nthe death penalty. We don't even reach the point where theoretical\nquestions about the moral justification or effectiveness of capital\npunishment start to matter, because so many of the people sentenced\nto death are actually innocent. Whatever it means in theory, in\npractice capital punishment means killing innocent people.\nThanks to Trevor Blackwell, Jessica Livingston, and Don Knight for\nreading drafts of this.Related:" }, { "path": "data/PaulGrahamEssays/really.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nOctober 2009(This essay is derived from a talk at the 2009 Startup School.)I wasn't sure what to talk about at Startup School, so I decided\nto ask the founders of the startups we'd funded. What hadn't I\nwritten about yet?I'm in the unusual position of being able to test the essays I write\nabout startups. I hope the ones on other topics are right, but I\nhave no way to test them. The ones on startups get tested by about\n70 people every 6 months.So I sent all the founders an email asking what surprised them about\nstarting a startup. This amounts to asking what I got wrong, because\nif I'd explained things well enough, nothing should have surprised\nthem.I'm proud to report I got one response saying:\n\n What surprised me the most is that everything was actually\n fairly predictable!\n\nThe bad news is that I got over 100 other responses listing the\nsurprises they encountered.There were very clear patterns in the responses; it was remarkable\nhow often several people had been surprised by exactly the same\nthing. These were the biggest:\n1. Be Careful with CofoundersThis was the surprise mentioned by the most founders. There were\ntwo types of responses: that you have to be careful who you pick\nas a cofounder, and that you have to work hard to maintain your\nrelationship.What people wished they'd paid more attention to when choosing\ncofounders was character and commitment, not ability. This was\nparticularly true with startups that failed. The lesson: don't\npick cofounders who will flake.Here's a typical reponse:\n\n You haven't seen someone's true colors unless you've worked\n with them on a startup.\n\nThe reason character is so important is that it's tested more\nseverely than in most other situations. One founder said explicitly\nthat the relationship between founders was more important than\nability:\n\n I would rather cofound a startup with a friend than a stranger\n with higher output. Startups are so hard and emotional that\n the bonds and emotional and social support that come with\n friendship outweigh the extra output lost.\n\nWe learned this lesson a long time ago. If you look at the YC\napplication, there are more questions about the commitment and\nrelationship of the founders than their ability.Founders of successful startups talked less about choosing cofounders\nand more about how hard they worked to maintain their relationship.\n\n One thing that surprised me is how the relationship of startup\n founders goes from a friendship to a marriage. My relationship\n with my cofounder went from just being friends to seeing each\n other all the time, fretting over the finances and cleaning up\n shit. And the startup was our baby. I summed it up once like\n this: \"It's like we're married, but we're not fucking.\"\n\nSeveral people used that word \"married.\" It's a far more intense\nrelationship than you usually see between coworkers—partly because\nthe stresses are so much greater, and partly because at first the\nfounders are the whole company. So this relationship has to be\nbuilt of top quality materials and carefully maintained. It's the\nbasis of everything.\n2. Startups Take Over Your LifeJust as the relationship between cofounders is more intense than\nit usually is between coworkers, so is the relationship between the\nfounders and the company. Running a startup is not like having a\njob or being a student, because it never stops. This is so foreign\nto most people's experience that they don't get it till it happens.\n[1]\n\n I didn't realize I would spend almost every waking moment either\n working or thinking about our startup. You enter a whole\n different way of life when it's your company vs. working for\n someone else's company.\n\nIt's exacerbated by the fast pace of startups, which makes it seem\nlike time slows down:\n\n I think the thing that's been most surprising to me is how one's\n perspective on time shifts. Working on our startup, I remember\n time seeming to stretch out, so that a month was a huge interval.\n\nIn the best case, total immersion can be exciting:\n\n It's surprising how much you become consumed by your startup,\n in that you think about it day and night, but never once does\n it feel like \"work.\"\n\nThough I have to say, that quote is from someone we funded this\nsummer. In a couple years he may not sound so chipper.\n3. It's an Emotional Roller-coasterThis was another one lots of people were surprised about. The ups\nand downs were more extreme than they were prepared for.In a startup, things seem great one moment and hopeless the next.\nAnd by next, I mean a couple hours later.\n\n The emotional ups and downs were the biggest surprise for me.\n One day, we'd think of ourselves as the next Google and dream\n of buying islands; the next, we'd be pondering how to let our\n loved ones know of our utter failure; and on and on.\n\nThe hard part, obviously, is the lows. For a lot of founders that\nwas the big surprise:\n\n How hard it is to keep everyone motivated during rough days or\n weeks, i.e. how low the lows can be.\n\nAfter a while, if you don't have significant success to cheer you\nup, it wears you out:\n\n Your most basic advice to founders is \"just don't die,\" but the\n energy to keep a company going in lieu of unburdening success\n isn't free; it is siphoned from the founders themselves.\n\nThere's a limit to how much you can take. If you get to the point\nwhere you can't keep working anymore, it's not the end of the world.\nPlenty of famous founders have had some failures along the way.\n4. It Can Be FunThe good news is, the highs are also very high. Several founders\nsaid what surprised them most about doing a startup was how fun it\nwas:\n\n I think you've left out just how fun it is to do a startup. I\n am more fulfilled in my work than pretty much any of my friends\n who did not start companies.\n\nWhat they like most is the freedom:\n\n I'm surprised by how much better it feels to be working on\n something that is challenging and creative, something I believe\n in, as opposed to the hired-gun stuff I was doing before. I\n knew it would feel better; what's surprising is how much better.\n\nFrankly, though, if I've misled people here, I'm not eager to fix\nthat. I'd rather have everyone think starting a startup is grim\nand hard than have founders go into it expecting it to be fun, and\na few months later saying \"This is supposed to be fun? Are you\nkidding?\"The truth is, it wouldn't be fun for most people. A lot of what\nwe try to do in the application process is to weed out the people\nwho wouldn't like it, both for our sake and theirs.The best way to put it might be that starting a startup is fun the\nway a survivalist training course would be fun, if you're into that\nsort of thing. Which is to say, not at all, if you're not.\n5. Persistence Is the KeyA lot of founders were surprised how important persistence was in\nstartups. It was both a negative and a positive surprise: they were\nsurprised both by the degree of persistence required\n\n Everyone said how determined and resilient you must be, but\n going through it made me realize that the determination required\n was still understated.\n\nand also by the degree to which persistence alone was able to\ndissolve obstacles:\n\n If you are persistent, even problems that seem out of your\n control (i.e. immigration) seem to work themselves out.\n\nSeveral founders mentioned specifically how much more important\npersistence was than intelligence.\n\n I've been surprised again and again by just how much more\n important persistence is than raw intelligence.\n\nThis applies not just to intelligence but to ability in general,\nand that's why so many people said character was more important in\nchoosing cofounders.\n6. Think Long-TermYou need persistence because everything takes longer than you expect.\nA lot of people were surprised by that.\n\n I'm continually surprised by how long everything can take.\n Assuming your product doesn't experience the explosive growth\n that very few products do, everything from development to\n dealmaking (especially dealmaking) seems to take 2-3x longer\n than I always imagine.\n\nOne reason founders are surprised is that because they work fast,\nthey expect everyone else to. There's a shocking amount of shear\nstress at every point where a startup touches a more bureaucratic\norganization, like a big company or a VC fund. That's why fundraising\nand the enterprise market kill and maim so many startups. \n[2]But I think the reason most founders are surprised by how long it\ntakes is that they're overconfident. They think they're going to\nbe an instant success, like YouTube or Facebook. You tell them\nonly 1 out of 100 successful startups has a trajectory like that,\nand they all think \"we're going to be that 1.\"Maybe they'll listen to one of the more successful founders:\n\n The top thing I didn't understand before going into it is that\n persistence is the name of the game. For the vast majority of\n startups that become successful, it's going to be a really\n long journey, at least 3 years and probably 5+.\n\nThere is a positive side to thinking longer-term. It's not just\nthat you have to resign yourself to everything taking longer than\nit should. If you work patiently it's less stressful, and you can\ndo better work:\n\n Because we're relaxed, it's so much easier to have fun doing\n what we do. Gone is the awkward nervous energy fueled by the\n desperate need to not fail guiding our actions. We can concentrate\n on doing what's best for our company, product, employees and\n customers.\n\nThat's why things get so much better when you hit ramen profitability.\nYou can shift into a different mode of working.7. Lots of Little ThingsWe often emphasize how rarely startups win simply because they hit\non some magic idea. I think founders have now gotten that into\ntheir heads. But a lot were surprised to find this also applies\nwithin startups. You have to do lots of different things:\n\n It's much more of a grind than glamorous. A timeslice selected\n at random would more likely find me tracking down a weird DLL\n loading bug on Swedish Windows, or tracking down a bug in the\n financial model Excel spreadsheet the night before a board\n meeting, rather than having brilliant flashes of strategic\n insight.\n\nMost hacker-founders would like to spend all their time programming.\nYou won't get to, unless you fail. Which can be transformed into:\nIf you spend all your time programming, you will fail.The principle extends even into programming. There is rarely a\nsingle brilliant hack that ensures success:\n\n I learnt never to bet on any one feature or deal or anything\n to bring you success. It is never a single thing. Everything\n is just incremental and you just have to keep doing lots of\n those things until you strike something.\n\nEven in the rare cases where a clever hack makes your fortune, you\nprobably won't know till later:\n\n There is no such thing as a killer feature. Or at least you\n won't know what it is.\n\nSo the best strategy is to try lots of different things. The reason\nnot to put all your eggs in one basket is not the usual one,\nwhich applies even when you know which basket is best. In a startup\nyou don't even know that.\n8. Start with Something MinimalLots of founders mentioned how important it was to launch with the\nsimplest possible thing. By this point everyone knows you should\nrelease fast and iterate. It's practically a mantra at YC. But\neven so a lot of people seem to have been burned by not doing it:\n\n Build the absolute smallest thing that can be considered a\n complete application and ship it.\n\nWhy do people take too long on the first version? Pride, mostly.\nThey hate to release something that could be better. They worry\nwhat people will say about them. But you have to overcome this:\n\n Doing something \"simple\" at first glance does not mean you\n aren't doing something meaningful, defensible, or valuable.\n\nDon't worry what people will say. If your first version is so\nimpressive that trolls don't make fun of it, you waited too long\nto launch. \n[3]One founder said this should be your approach to all programming,\nnot just startups, and I tend to agree.\n\n Now, when coding, I try to think \"How can I write this such\n that if people saw my code, they'd be amazed at how little there\n is and how little it does?\"\n\nOver-engineering is poison. It's not like doing extra work for\nextra credit. It's more like telling a lie that you then have to\nremember so you don't contradict it.\n9. Engage UsersProduct development is a conversation with the user that doesn't\nreally start till you launch. Before you launch, you're like a\npolice artist before he's shown the first version of his sketch to\nthe witness.It's so important to launch fast that it may be better to think of\nyour initial version not as a product, but as a trick for getting\nusers to start talking to you.\n\n I learned to think about the initial stages of a startup as a\n giant experiment. All products should be considered experiments,\n and those that have a market show promising results extremely\n quickly.\n\nOnce you start talking to users, I guarantee you'll be surprised\nby what they tell you.\n\n When you let customers tell you what they're after, they will\n often reveal amazing details about what they find valuable as\n well what they're willing to pay for.\n\nThe surprise is generally positive as well as negative. They won't\nlike what you've built, but there will be other things they would\nlike that would be trivially easy to implement. It's not till you\nstart the conversation by launching the wrong thing that they can\nexpress (or perhaps even realize) what they're looking for.\n10. Change Your IdeaTo benefit from engaging with users you have to be willing to change\nyour idea. We've always encouraged founders to see a startup idea\nas a hypothesis rather than a blueprint. And yet they're still\nsurprised how well it works to change the idea.\n\n Normally if you complain about something being hard, the general\n advice is to work harder. With a startup, I think you should\n find a problem that's easy for you to solve. Optimizing in\n solution-space is familiar and straightforward, but you can\n make enormous gains playing around in problem-space.\n\nWhereas mere determination, without flexibility, is a greedy algorithm\nthat may get you nothing more than a mediocre local maximum:\n\n When someone is determined, there's still a danger that they'll\n follow a long, hard path that ultimately leads nowhere.\n\nYou want to push forward, but at the same time twist and turn to\nfind the most promising path. One founder put it very succinctly:\n\n Fast iteration is the key to success.\n\nOne reason this advice is so hard to follow is that people don't\nrealize how hard it is to judge startup ideas, particularly their\nown. Experienced founders learn to keep an open mind:\n\n Now I don't laugh at ideas anymore, because I realized how\n terrible I was at knowing if they were good or not.\n\nYou can never tell what will work. You just have to do whatever\nseems best at each point. We do this with YC itself. We still\ndon't know if it will work, but it seems like a decent hypothesis.\n11. Don't Worry about CompetitorsWhen you think you've got a great idea, it's sort of like having a\nguilty conscience about something. All someone has to do is look\nat you funny, and you think \"Oh my God, they know.\"These alarms are almost always false:\n\n Companies that seemed like competitors and threats at first\n glance usually never were when you really looked at it. Even\n if they were operating in the same area, they had a different\n goal.\n\nOne reason people overreact to competitors is that they overvalue\nideas. If ideas really were the key, a competitor with the same\nidea would be a real threat. But it's usually execution that\nmatters:\n\n All the scares induced by seeing a new competitor pop up are\n forgotten weeks later. It always comes down to your own product\n and approach to the market.\n\nThis is generally true even if competitors get lots of attention.\n\n Competitors riding on lots of good blogger perception aren't\n really the winners and can disappear from the map quickly. You\n need consumers after all.\n\nHype doesn't make satisfied users, at least not for something as\ncomplicated as technology.12. It's Hard to Get UsersA lot of founders complained about how hard it was to get users,\nthough.\n\n I had no idea how much time and effort needed to go into attaining\n users.\n\nThis is a complicated topic. When you can't get users, it's hard\nto say whether the problem is lack of exposure, or whether the\nproduct's simply bad. Even good products can be blocked by switching\nor integration costs:\n\n Getting people to use a new service is incredibly difficult.\n This is especially true for a service that other companies can\n use, because it requires their developers to do work. If you're\n small, they don't think it is urgent. \n[4]\n\nThe sharpest criticism of YC came from a founder who said we didn't\nfocus enough on customer acquisition:\n\n YC preaches \"make something people want\" as an engineering task,\n a never ending stream of feature after feature until enough\n people are happy and the application takes off. There's very\n little focus on the cost of customer acquisition.\n\nThis may be true; this may be something we need to fix, especially\nfor applications like games. If you make something where the\nchallenges are mostly technical, you can rely on word of mouth,\nlike Google did. One founder was surprised by how well that worked\nfor him:\n\n There is an irrational fear that no one will buy your product.\n But if you work hard and incrementally make it better, there\n is no need to worry.\n\nBut with other types of startups you may win less by features and\nmore by deals and marketing.\n13. Expect the Worst with DealsDeals fall through. That's a constant of the startup world. Startups\nare powerless, and good startup ideas generally seem wrong. So\neveryone is nervous about closing deals with you, and you have no\nway to make them.This is particularly true with investors:\n\n In retrospect, it would have been much better if we had operated\n under the assumption that we would never get any additional\n outside investment. That would have focused us on finding\n revenue streams early.\n\nMy advice is generally pessimistic. Assume you won't get money,\nand if someone does offer you any, assume you'll never get any more.\n\n If someone offers you money, take it. You say it a lot, but I\n think it needs even more emphasizing. We had the opportunity\n to raise a lot more money than we did last year and I wish we\n had.\n\nWhy do founders ignore me? Mostly because they're optimistic by\nnature. The mistake is to be optimistic about things you can't\ncontrol. By all means be optimistic about your ability to make\nsomething great. But you're asking for trouble if you're optimistic\nabout big companies or investors.\n14. Investors Are CluelessA lot of founders mentioned how surprised they were by the cluelessness\nof investors:\n\n They don't even know about the stuff they've invested in. I\n met some investors that had invested in a hardware device and\n when I asked them to demo the device they had difficulty switching\n it on.\n\nAngels are a bit better than VCs, because they usually have startup\nexperience themselves:\n\n VC investors don't know half the time what they are talking\n about and are years behind in their thinking. A few were great,\n but 95% of the investors we dealt with were unprofessional,\n didn't seem to be very good at business or have any kind of\n creative vision. Angels were generally much better to talk to.\n\nWhy are founders surprised that VCs are clueless? I think it's\nbecause they seem so formidable.The reason VCs seem formidable is that it's their profession to.\nYou get to be a VC by convincing asset managers to trust you with\nhundreds of millions of dollars. How do you do that? You have to\nseem confident, and you have to seem like you understand technology.\n[5]\n15. You May Have to Play GamesBecause investors are so bad at judging you, you have to work harder\nthan you should at selling yourself. One founder said the thing\nthat surprised him most was\n\n The degree to which feigning certitude impressed investors.\n\nThis is the thing that has surprised me most about YC founders'\nexperiences. This summer we invited some of the alumni to talk to\nthe new startups about fundraising, and pretty much 100% of their\nadvice was about investor psychology. I thought I was cynical about\nVCs, but the founders were much more cynical.\n\n A lot of what startup founders do is just posturing. It works.\n\nVCs themselves have no idea of the extent to which the startups\nthey like are the ones that are best at selling themselves to VCs.\n[6]\nIt's exactly the same phenomenon we saw a step earlier. VCs get\nmoney by seeming confident to LPs, and founders get money by seeming\nconfident to VCs.\n16. Luck Is a Big FactorWith two such random linkages in the path between startups and\nmoney, it shouldn't be surprising that luck is a big factor in\ndeals. And yet a lot of founders are surprised by it.\n\n I didn't realize how much of a role luck plays and how much is\n outside of our control.\n\nIf you think about famous startups, it's pretty clear how big a\nrole luck plays. Where would Microsoft be if IBM insisted on an\nexclusive license for DOS?Why are founders fooled by this? Business guys probably aren't,\nbut hackers are used to a world where skill is paramount, and you\nget what you deserve.\n\n When we started our startup, I had bought the hype of the startup\n founder dream: that this is a game of skill. It is, in some\n ways. Having skill is valuable. So is being determined as all\n hell. But being lucky is the critical ingredient.\n\nActually the best model would be to say that the outcome is the\nproduct of skill, determination, and luck. No matter how much\nskill and determination you have, if you roll a zero for luck, the\noutcome is zero.These quotes about luck are not from founders whose startups failed.\nFounders who fail quickly tend to blame themselves. Founders who\nsucceed quickly don't usually realize how lucky they were. It's\nthe ones in the middle who see how important luck is.\n17. The Value of CommunityA surprising number of founders said what surprised them most about\nstarting a startup was the value of community. Some meant the\nmicro-community of YC founders:\n\n The immense value of the peer group of YC companies, and facing\n similar obstacles at similar times.\n\nwhich shouldn't be that surprising, because that's why it's structured\nthat way. Others were surprised at the value of the startup community\nin the larger sense:\n\n How advantageous it is to live in Silicon Valley, where you\n can't help but hear all the cutting-edge tech and startup news,\n and run into useful people constantly.\n\nThe specific thing that surprised them most was the general spirit\nof benevolence:\n\n One of the most surprising things I saw was the willingness of\n people to help us. Even people who had nothing to gain went out\n of their way to help our startup succeed.\n\nand particularly how it extended all the way to the top:\n\n The surprise for me was how accessible important and interesting\n people are. It's amazing how easily you can reach out to people\n and get immediate feedback.\n\nThis is one of the reasons I like being part of this world. Creating\nwealth is not a zero-sum game, so you don't have to stab people in\nthe back to win.\n18. You Get No RespectThere was one surprise founders mentioned that I'd forgotten about:\nthat outside the startup world, startup founders get no respect.\n\n In social settings, I found that I got a lot more respect when\n I said, \"I worked on Microsoft Office\" instead of \"I work at a\n small startup you've never heard of called x.\"\n\nPartly this is because the rest of the world just doesn't get\nstartups, and partly it's yet another consequence of the fact that\nmost good startup ideas seem bad:\n\n If you pitch your idea to a random person, 95% of the time\n you'll find the person instinctively thinks the idea will be a\n flop and you're wasting your time (although they probably won't\n say this directly).\n\nUnfortunately this extends even to dating:\n\n It surprised me that being a startup founder does not get you\n more admiration from women.\n\nI did know about that, but I'd forgotten.\n19. Things Change as You GrowThe last big surprise founders mentioned is how much things changed\nas they grew. The biggest change was that you got to program even\nless:\n\n Your job description as technical founder/CEO is completely\n rewritten every 6-12 months. Less coding, more\n managing/planning/company building, hiring, cleaning up messes,\n and generally getting things in place for what needs to happen\n a few months from now.\n\nIn particular, you now have to deal with employees, who often have\ndifferent motivations:\n\n I knew the founder equation and had been focused on it since I\n knew I wanted to start a startup as a 19 year old. The employee\n equation is quite different so it took me a while to get it\n down.\n\nFortunately, it can become a lot less stressful once you reach\ncruising altitude:\n\n I'd say 75% of the stress is gone now from when we first started.\n Running a business is so much more enjoyable now. We're more\n confident. We're more patient. We fight less. We sleep more.\n\nI wish I could say it was this way for every startup that succeeded,\nbut 75% is probably on the high side.\nThe Super-PatternThere were a few other patterns, but these were the biggest. One's\nfirst thought when looking at them all is to ask if there's a\nsuper-pattern, a pattern to the patterns.I saw it immediately, and so did a YC founder I read the list to.\nThese are supposed to be the surprises, the things I didn't tell\npeople. What do they all have in common? They're all things I\ntell people. If I wrote a new essay with the same outline as this\nthat wasn't summarizing the founders' responses, everyone would say\nI'd run out of ideas and was just repeating myself.What is going on here?When I look at the responses, the common theme is that\nstarting a startup was like I said, but way more so. People just\ndon't seem to get how different it is till they do it. Why? The\nkey to that mystery is to ask, how different from what? Once you\nphrase it that way, the answer is obvious: from a job. Everyone's\nmodel of work is a job. It's completely pervasive. Even if you've\nnever had a job, your parents probably did, along with practically\nevery other adult you've met.Unconsciously, everyone expects a startup to be like a job, and\nthat explains most of the surprises. It explains why people are\nsurprised how carefully you have to choose cofounders and how hard\nyou have to work to maintain your relationship. You don't have to\ndo that with coworkers. It explains why the ups and downs are\nsurprisingly extreme. In a job there is much more damping. But\nit also explains why the good times are surprisingly good: most\npeople can't imagine such freedom. As you go down the list, almost\nall the surprises are surprising in how much a startup differs from\na job.You probably can't overcome anything so pervasive as the model of\nwork you grew up with. So the best solution is to be consciously\naware of that. As you go into a startup, you'll be thinking \"everyone\nsays it's really extreme.\" Your next thought will probably be \"but\nI can't believe it will be that bad.\" If you want to avoid being\nsurprised, the next thought after that should be: \"and the reason\nI can't believe it will be that bad is that my model of work is a\njob.\"\nNotes[1]\nGraduate students might understand it. In grad school you\nalways feel you should be working on your thesis. It doesn't end\nevery semester like classes do.[2]\nThe best way for a startup to engage with slow-moving\norganizations is to fork off separate processes to deal with them.\nIt's when they're on the critical path that they kill you—when\nyou depend on closing a deal to move forward. It's worth taking\nextreme measures to avoid that.[3]\nThis is a variant of Reid Hoffman's principle that if you\naren't embarrassed by what you launch with, you waited too long to\nlaunch.[4]\nThe question to ask about what you've built is not whether it's\ngood, but whether it's good enough to supply the activation energy\nrequired.[5]\nSome VCs seem to understand technology because they actually\ndo, but that's overkill; the defining test is whether you can talk\nabout it well enough to convince limited partners.[6]\nThis is the same phenomenon you see with defense contractors\nor fashion brands. The dumber the customers, the more effort you\nexpend on the process of selling things to them rather than making\nthe things you sell.Thanks: to Jessica Livingston for reading drafts of this,\nand to all the founders who responded to my email.Related:" }, { "path": "data/PaulGrahamEssays/relres.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nMarch 2009A couple days ago I finally got being a good startup founder down\nto two words: relentlessly resourceful.Till then the best I'd managed was to get the opposite quality down\nto one: hapless. Most dictionaries say hapless means unlucky. But\nthe dictionaries are not doing a very good job. A team that outplays\nits opponents but loses because of a bad decision by the referee\ncould be called unlucky, but not hapless. Hapless implies passivity.\nTo be hapless is to be battered by circumstances—to let the world\nhave its way with you, instead of having your way with the world.\n\n[1]Unfortunately there's no antonym of hapless, which makes it difficult\nto tell founders what to aim for. \"Don't be hapless\" is not much\nof rallying cry.It's not hard to express the quality we're looking for in metaphors.\nThe best is probably a running back. A good running back is not\nmerely determined, but flexible as well. They want to get downfield,\nbut they adapt their plans on the fly.Unfortunately this is just a metaphor, and not a useful one to most\npeople outside the US. \"Be like a running back\" is no better than\n\"Don't be hapless.\"But finally I've figured out how to express this quality directly.\nI was writing a talk for \ninvestors, and I had to explain what to\nlook for in founders. What would someone who was the opposite of\nhapless be like? They'd be relentlessly resourceful. Not merely\nrelentless. That's not enough to make things go your way except\nin a few mostly uninteresting domains. In any interesting domain,\nthe difficulties will be novel. Which means you can't simply plow\nthrough them, because you don't know initially how hard they are;\nyou don't know whether you're about to plow through a block of foam\nor granite. So you have to be resourceful. You have to keep\ntrying new things.Be relentlessly resourceful.That sounds right, but is it simply a description\nof how to be successful in general? I don't think so. This isn't\nthe recipe for success in writing or painting, for example. In\nthat kind of work the recipe is more to be actively curious.\nResourceful implies the obstacles are external, which they generally\nare in startups. But in writing and painting they're mostly internal;\nthe obstacle is your own obtuseness.\n[2]There probably are other fields where \"relentlessly resourceful\"\nis the recipe for success. But though other fields may share it,\nI think this is the best short description we'll find of what makes\na good startup founder. I doubt it could be made more precise.Now that we know what we're looking for, that leads to other\nquestions. For example, can this quality be taught? After four\nyears of trying to teach it to people, I'd say that yes, surprisingly\noften it can. Not to everyone, but to many people. \n[3]\nSome\npeople are just constitutionally passive, but others have a latent\nability to be relentlessly resourceful that only needs to be brought\nout.This is particularly true of young people who have till now always\nbeen under the thumb of some kind of authority. Being relentlessly\nresourceful is definitely not the recipe for success in big companies,\nor in most schools. I don't even want to think what the recipe is\nin big companies, but it is certainly longer and messier, involving\nsome combination of resourcefulness, obedience, and building\nalliances.Identifying this quality also brings us closer to answering a\nquestion people often wonder about: how many startups there could\nbe. There is not, as some people seem to think, any economic upper\nbound on this number. There's no reason to believe there is any\nlimit on the amount of newly created wealth consumers can absorb,\nany more than there is a limit on the number of theorems that can\nbe proven. So probably the limiting factor on the number of startups\nis the pool of potential founders. Some people would make good\nfounders, and others wouldn't. And now that we can say what makes\na good founder, we know how to put an upper bound on the size of\nthe pool.This test is also useful to individuals. If you want to know whether\nyou're the right sort of person to start a startup, ask yourself\nwhether you're relentlessly resourceful. And if you want to know\nwhether to recruit someone as a cofounder, ask if they are.You can even use it tactically. If I were running a startup, this\nwould be the phrase I'd tape to the mirror. \"Make something people\nwant\" is the destination, but \"Be relentlessly resourceful\" is how\nyou get there.\nNotes[1]\nI think the reason the dictionaries are wrong is that the\nmeaning of the word has shifted. No one writing a dictionary from\nscratch today would say that hapless meant unlucky. But a couple\nhundred years ago they might have. People were more at the mercy\nof circumstances in the past, and as a result a lot of the words\nwe use for good and bad outcomes have origins in words about luck.When I was living in Italy, I was once trying to tell someone\nthat I hadn't had much success in doing something, but I couldn't\nthink of the Italian word for success. I spent some time trying\nto describe the word I meant. Finally she said \"Ah! Fortuna!\"[2]\nThere are aspects of startups where the recipe is to be\nactively curious. There can be times when what you're doing is\nalmost pure discovery. Unfortunately these times are a small\nproportion of the whole. On the other hand, they are in research\ntoo.[3]\nI'd almost say to most people, but I realize (a) I have no\nidea what most people are like, and (b) I'm pathologically optimistic\nabout people's ability to change.Thanks to Trevor Blackwell and Jessica Livingston for reading drafts\nof this." }, { "path": "data/PaulGrahamEssays/revolution.txt", "content": "April 2009Recently I realized I'd been holding two ideas in my head that would explode if combined.The first is that startups may represent a new economic phase, on the scale of the Industrial Revolution. I'm not sure of this, but there seems a decent chance it's true. People are dramatically more \nproductive as founders or early employees of startups—imagine how much less Larry and Sergey would have achieved if they'd gone to work for a big company—and that scale of improvement can change social customs.The second idea is that startups are a type of business that flourishes in certain places that specialize in it—that Silicon Valley specializes in startups in the same way Los Angeles specializes in movies, or New York in finance. [1]What if both are true? What if startups are both a new economic phase and also a type of business that only flourishes in certain centers?If so, this revolution is going to be particularly revolutionary. All previous revolutions have spread. Agriculture, cities, and industrialization all spread widely. If startups end up being like the movie business, with just a handful of centers and one dominant one, that's going to have novel consequences.There are already signs that startups may not spread particularly well. The spread of startups seems to be proceeding slower than the spread of the Industrial Revolution, despite the fact that communication is so much faster now.Within a few decades of the founding of Boulton & Watt there were steam engines scattered over northern Europe and North America. Industrialization didn't spread much beyond those regions for a while. It only spread to places where there was a strong middle class—countries where a private citizen could make a fortune without having it confiscated. Otherwise it wasn't worth investing in factories. But in a country with a strong middle class it was easy for industrial techniques to take root. An individual mine or factory owner could decide to install a steam engine, and within a few years he could probably find someone local to make him one. So steam engines spread fast. And they spread widely, because the locations of mines and factories were determined by features like rivers, harbors, and sources of raw materials. \n [2]Startups don't seem to spread so well, partly because they're more a social than a technical phenomenon, and partly because they're not tied to geography. An individual European manufacturer could import industrial techniques and they'd work fine. This doesn't seem to work so well with startups: you need a community of expertise, as you do in the movie business. [3]\n Plus there aren't the same forces driving startups to spread. Once railroads or electric power grids were invented, every region had to have them. An area without railroads or power was a rich potential market. But this isn't true with startups. There's no need for a Microsoft of France or Google of Germany.Governments may decide they want to encourage startups locally, but government policy can't call them into being the way a genuine need could.How will this all play out? If I had to predict now, I'd say that startups will spread, but very slowly, because their spread will be driven not by government policies (which won't work) or by market need (which doesn't exist) but, to the extent that it happens at all, by the same random factors that have caused startup culture to spread thus far. And such random factors will increasingly be outweighed by the pull of existing startup hubs.Silicon Valley is where it is because William Shockley wanted to move back to Palo Alto, where he grew up, and the experts he lured west to work with him liked it so much they stayed. Seattle owes much of its position as a tech center to the same cause: Gates and Allen wanted to move home. Otherwise Albuquerque might have Seattle's place in the rankings. Boston is a tech center because it's the intellectual capital of the US and probably the world. And if Battery Ventures hadn't turned down Facebook, Boston would be significantly bigger now on the startup radar screen.But of course it's not a coincidence that Facebook got funded in the Valley and not Boston. There are more and bolder investors in Silicon Valley than in Boston, and even undergrads know it.Boston's case illustrates the difficulty you'd have establishing a new startup hub this late in the game. If you wanted to create a startup hub by reproducing the way existing ones happened, the \nway to do it would be to establish a first-rate research university in a place so nice that rich people wanted to live there. Then the town would be hospitable to both groups you need: both founders and investors. That's the combination that yielded Silicon Valley. But Silicon Valley didn't have Silicon Valley to compete with. If you tried now to create a startup hub by planting a great university in a nice place, it would have a harder time getting started, because many of the best startups it produced would be sucked away to existing startup hubs.Recently I suggested a potential shortcut: \npay startups to move. Once you had enough good startups in one place, it would create a self-sustaining chain reaction. Founders would start to move there without being paid, because that was where their peers were, and investors would appear too, because that was where the deals were.In practice I doubt any government would have the balls to try this, or the brains to do it right. I didn't mean it as a practical suggestion, but more as an exploration of the lower bound of what it would take to create a startup hub deliberately.The most likely scenario is (1) that no government will successfully establish a startup hub, and (2) that the spread of startup culture will thus be driven by the random factors that have driven it so far, but (3) that these factors will be increasingly outweighed by the pull of existing startup hubs. Result: this revolution, if it is one, will be unusually localized.\nNotes[1]\nThere are two very different types of startup: one kind that evolves naturally, and one kind that's called into being to \"commercialize\" a scientific discovery. Most computer/software startups are now the first type, and most pharmaceutical startups the second. When I talk about startups in this essay, I mean type I startups. There is no difficulty making type II startups spread: all you have to do is fund medical research labs; commercializing whatever new discoveries the boffins throw off is as straightforward as building a new airport. Type II startups neither require nor produce startup culture. But that means having type II startups won't get you type I startups. Philadelphia is a case in point: lots of type II startups, but hardly any type I.Incidentally, Google may appear to be an instance of a type II startup, but it wasn't. Google is not pagerank commercialized. They could have used another algorithm and everything would have turned out the same. What made Google Google is that they cared about doing search well at a critical point in the evolution of the web.[2]\n Watt didn't invent the steam engine. His critical invention was a refinement that made steam engines dramatically more efficient: the separate condenser. But that oversimplifies his role. He had such a different attitude to the problem and approached it with such energy that he transformed the field. Perhaps the most accurate way to put it would be to say that Watt reinvented the steam engine.[3]\nThe biggest counterexample here is Skype. If you're doing\nsomething that would get shut down in the US, it becomes an \nadvantage to be located elsewhere. That's why Kazaa took\nthe place of Napster. And the expertise and connections the \nfounders gained from running Kazaa helped ensure the success\nof Skype.Thanks to Patrick Collison, Jessica Livingston, and Fred Wilson for reading drafts of this." }, { "path": "data/PaulGrahamEssays/richnow.txt", "content": "April 2021Every year since 1982, Forbes magazine has published a list of the\nrichest Americans. If we compare the 100 richest people in 1982 to\nthe 100 richest in 2020, we notice some big differences.In 1982 the most common source of wealth was inheritance. Of the\n100 richest people, 60 inherited from an ancestor. There were 10\ndu Pont heirs alone. By 2020 the number of heirs had been cut in\nhalf, accounting for only 27 of the biggest 100 fortunes.Why would the percentage of heirs decrease? Not because inheritance\ntaxes increased. In fact, they decreased significantly during this\nperiod. The reason the percentage of heirs has decreased is not\nthat fewer people are inheriting great fortunes, but that more\npeople are making them.How are people making these new fortunes? Roughly 3/4 by starting\ncompanies and 1/4 by investing. Of the 73 new fortunes in 2020, 56\nderive from founders' or early employees' equity (52 founders, 2\nearly employees, and 2 wives of founders), and 17 from managing\ninvestment funds.There were no fund managers among the 100 richest Americans in 1982.\nHedge funds and private equity firms existed in 1982, but none of\ntheir founders were rich enough yet to make it into the top 100.\nTwo things changed: fund managers discovered new ways to generate\nhigh returns, and more investors were willing to trust them with\ntheir money.\n[1]But the main source of new fortunes now is starting companies, and\nwhen you look at the data, you see big changes there too. People\nget richer from starting companies now than they did in 1982, because\nthe companies do different things.In 1982, there were two dominant sources of new wealth: oil and\nreal estate. Of the 40 new fortunes in 1982, at least 24 were due\nprimarily to oil or real estate. Now only a small number are: of\nthe 73 new fortunes in 2020, 4 were due to real estate and only 2\nto oil.By 2020 the biggest source of new wealth was what are sometimes\ncalled \"tech\" companies. Of the 73 new fortunes, about 30 derive\nfrom such companies. These are particularly common among the richest\nof the rich: 8 of the top 10 fortunes in 2020 were new fortunes of\nthis type.Arguably it's slightly misleading to treat tech as a category.\nIsn't Amazon really a retailer, and Tesla a car maker? Yes and no.\nMaybe in 50 years, when what we call tech is taken for granted, it\nwon't seem right to put these two businesses in the same category.\nBut at the moment at least, there is definitely something they share\nin common that distinguishes them. What retailer starts AWS? What\ncar maker is run by someone who also has a rocket company?The tech companies behind the top 100 fortunes also form a\nwell-differentiated group in the sense that they're all companies\nthat venture capitalists would readily invest in, and the others\nmostly not. And there's a reason why: these are mostly companies\nthat win by having better technology, rather than just a CEO who's\nreally driven and good at making deals.To that extent, the rise of the tech companies represents a qualitative\nchange. The oil and real estate magnates of the 1982 Forbes 400\ndidn't win by making better technology. They won by being really\ndriven and good at making deals. \n[2]\nAnd indeed, that way of\ngetting rich is so old that it predates the Industrial Revolution.\nThe courtiers who got rich in the (nominal) service of European\nroyal houses in the 16th and 17th centuries were also, as a rule,\nreally driven and good at making deals.People who don't look any deeper than the Gini coefficient look\nback on the world of 1982 as the good old days, because those who\ngot rich then didn't get as rich. But if you dig into how they\ngot rich, the old days don't look so good. In 1982, 84% of the\nrichest 100 people got rich by inheritance, extracting natural\nresources, or doing real estate deals. Is that really better than\na world in which the richest people get rich by starting tech\ncompanies?Why are people starting so many more new companies than they used\nto, and why are they getting so rich from it? The answer to the\nfirst question, curiously enough, is that it's misphrased. We\nshouldn't be asking why people are starting companies, but why\nthey're starting companies again.\n[3]In 1892, the New York Herald Tribune compiled a list of all the\nmillionaires in America. They found 4047 of them. How many had\ninherited their wealth then? Only about 20%, which is less than the\nproportion of heirs today. And when you investigate the sources of\nthe new fortunes, 1892 looks even more like today. Hugh Rockoff\nfound that \"many of the richest ... gained their initial edge from\nthe new technology of mass production.\"\n[4]So it's not 2020 that's the anomaly here, but 1982. The real question\nis why so few people had gotten rich from starting companies in\n1982. And the answer is that even as the Herald Tribune's list was\nbeing compiled, a wave of consolidation \nwas sweeping through the\nAmerican economy. In the late 19th and early 20th centuries,\nfinanciers like J. P. Morgan combined thousands of smaller companies\ninto a few hundred giant ones with commanding economies of scale.\nBy the end of World War II, as Michael Lind writes, \"the major\nsectors of the economy were either organized as government-backed\ncartels or dominated by a few oligopolistic corporations.\"\n[5]In 1960, most of the people who start startups today would have\ngone to work for one of them. You could get rich from starting your\nown company in 1890 and in 2020, but in 1960 it was not really a\nviable option. You couldn't break through the oligopolies to get\nat the markets. So the prestigious route in 1960 was not to start\nyour own company, but to work your way up the corporate ladder at\nan existing one.\n[6]Making everyone a corporate employee decreased economic inequality\n(and every other kind of variation), but if your model of normal\nis the mid 20th century, you have a very misleading model in that\nrespect. J. P. Morgan's economy turned out to be just a phase, and\nstarting in the 1970s, it began to break up.Why did it break up? Partly senescence. The big companies that\nseemed models of scale and efficiency in 1930 had by 1970 become\nslack and bloated. By 1970 the rigid structure of the economy was\nfull of cosy nests that various groups had built to insulate\nthemselves from market forces. During the Carter administration the\nfederal government realized something was amiss and began, in a\nprocess they called \"deregulation,\" to roll back the policies that\npropped up the oligopolies.But it wasn't just decay from within that broke up J. P. Morgan's\neconomy. There was also pressure from without, in the form of new\ntechnology, and particularly microelectronics. The best way to\nenvision what happened is to imagine a pond with a crust of ice on\ntop. Initially the only way from the bottom to the surface is around\nthe edges. But as the ice crust weakens, you start to be able to\npunch right through the middle.The edges of the pond were pure tech: companies that actually\ndescribed themselves as being in the electronics or software business.\nWhen you used the word \"startup\" in 1990, that was what you meant.\nBut now startups are punching right through the middle of the ice\ncrust and displacing incumbents like retailers and TV networks and\ncar companies.\n[7]But though the breakup of J. P. Morgan's economy created a new world\nin the technological sense, it was a reversion to the norm in the\nsocial sense. If you only look back as far as the mid 20th century,\nit seems like people getting rich by starting their own companies\nis a recent phenomenon. But if you look back further, you realize\nit's actually the default. So what we should expect in the future\nis more of the same. Indeed, we should expect both the number and\nwealth of founders to grow, because every decade it gets easier to\nstart a startup.Part of the reason it's getting easier to start a startup is social.\nSociety is (re)assimilating the concept. If you start one now, your\nparents won't freak out the way they would have a generation ago,\nand knowledge about how to do it is much more widespread. But the\nmain reason it's easier to start a startup now is that it's cheaper.\nTechnology has driven down the cost of both building products and\nacquiring customers.The decreasing cost of starting a startup has in turn changed the\nbalance of power between founders and investors. Back when starting\na startup meant building a factory, you needed investors' permission\nto do it at all. But now investors need founders more than founders\nneed investors, and that, combined with the increasing amount of\nventure capital available, has driven up valuations.\n[8]So the decreasing cost of starting a startup increases the number\nof rich people in two ways: it means that more people start them,\nand that those who do can raise money on better terms.But there's also a third factor at work: the companies themselves\nare more valuable, because newly founded companies grow faster than\nthey used to. Technology hasn't just made it cheaper to build and\ndistribute things, but faster too.This trend has been running for a long time. IBM, founded in 1896,\ntook 45 years to reach a billion 2020 dollars in revenue.\nHewlett-Packard, founded in 1939, took 25 years. Microsoft, founded\nin 1975, took 13 years. Now the norm for fast-growing companies is\n7 or 8 years.\n[9]Fast growth has a double effect on the value of founders' stock.\nThe value of a company is a function of its revenue and its growth\nrate. So if a company grows faster, you not only get to a billion\ndollars in revenue sooner, but the company is more valuable when\nit reaches that point than it would be if it were growing slower.That's why founders sometimes get so rich so young now. The low\ninitial cost of starting a startup means founders can start young,\nand the fast growth of companies today means that if they succeed\nthey could be surprisingly rich just a few years later.It's easier now to start and grow a company than it has ever been.\nThat means more people start them, that those who do get better\nterms from investors, and that the resulting companies become more\nvaluable. Once you understand how these mechanisms work, and that\nstartups were suppressed for most of the 20th century, you don't\nhave to resort to some vague right turn the country took under\nReagan to explain why America's Gini coefficient is increasing. Of\ncourse the Gini coefficient is increasing. With more people starting\nmore valuable companies, how could it not be?Notes[1]\nInvestment firms grew rapidly after a regulatory change by\nthe Labor Department in 1978 allowed pension funds to invest in\nthem, but the effects of this growth were not yet visible in the\ntop 100 fortunes in 1982.[2]\nGeorge Mitchell deserves mention as an exception. Though\nreally driven and good at making deals, he was also the first to\nfigure out how to use fracking to get natural gas out of shale.[3]\nWhen I say people are starting more companies, I mean the\ntype of company meant to grow \nvery big. There has actually been a\ndecrease in the last couple decades in the overall number of new\ncompanies. But the vast majority of companies are small retail and\nservice businesses. So what the statistics about the decreasing\nnumber of new businesses mean is that people are starting fewer\nshoe stores and barber shops.People sometimes get confused when they see a graph labelled\n\"startups\" that's going down, because there are two senses of the\nword \"startup\": (1) the founding of a company, and (2) a particular\ntype of company designed to grow big fast. The statistics mean\nstartup in sense (1), not sense (2).[4]\nRockoff, Hugh. \"Great Fortunes of the Gilded Age.\" NBER Working\nPaper 14555, 2008.[5]\nLind, Michael. Land of Promise. HarperCollins, 2012.It's also likely that the high tax rates in the mid 20th century\ndeterred people from starting their own companies. Starting one's\nown company is risky, and when risk isn't rewarded, people opt for\nsafety instead.But it wasn't simply cause and effect. The oligopolies and high tax\nrates of the mid 20th century were all of a piece. Lower taxes are\nnot just a cause of entrepreneurship, but an effect as well: the\npeople getting rich in the mid 20th century from real estate and\noil exploration lobbied for and got huge tax loopholes that made\ntheir effective tax rate much lower, and presumably if it had been\nmore common to grow big companies by building new technology, the\npeople doing that would have lobbied for their own loopholes as\nwell.[6]\nThat's why the people who did get rich in the mid 20th century\nso often got rich from oil exploration or real estate. Those were\nthe two big areas of the economy that weren't susceptible to\nconsolidation.[7]\nThe pure tech companies used to be called \"high technology\" startups.\nBut now that startups can punch through the middle of the ice crust,\nwe don't need a separate name for the edges, and the term \"high-tech\"\nhas a decidedly retro \nsound.[8]\nHigher valuations mean you either sell less stock to get a\ngiven amount of money, or get more money for a given amount of\nstock. The typical startup does some of each. Obviously you end up\nricher if you keep more stock, but you should also end up richer\nif you raise more money, because (a) it should make the company\nmore successful, and (b) you should be able to last longer before\nthe next round, or not even need one. Notice all those shoulds\nthough. In practice a lot of money slips through them.It might seem that the huge rounds raised by startups nowadays\ncontradict the claim that it has become cheaper to start one. But\nthere's no contradiction here; the startups that raise the most are\nthe ones doing it by choice, in order to grow faster, not the ones\ndoing it because they need the money to survive. There's nothing\nlike not needing money to make people offer it to you.You would think, after having been on the side of labor in its fight\nwith capital for almost two centuries, that the far left would be\nhappy that labor has finally prevailed. But none of them seem to\nbe. You can almost hear them saying \"No, no, not that way.\"[9]\nIBM was created in 1911 by merging three companies, the most\nimportant of which was Herman Hollerith's Tabulating Machine Company,\nfounded in 1896. In 1941 its revenues were $60 million.Hewlett-Packard's revenues in 1964 were $125 million.Microsoft's revenues in 1988 were $590 million.Thanks to Trevor Blackwell, Jessica Livingston, Bob Lesko, Robert Morris, \nRuss Roberts, and Alex Tabarrok for reading drafts of this, and to Jon Erlichman for growth data." }, { "path": "data/PaulGrahamEssays/road.txt", "content": "September 2001\n(This article explains why much of the next generation of software\nmay be server-based, what that will mean for programmers,\nand why this new kind of software is a great opportunity for startups.\nIt's derived from a talk at BBN Labs.)\nIn the summer of 1995, my friend Robert Morris and I decided to\nstart a startup. The PR campaign leading up to Netscape's IPO was\nrunning full blast then, and there was a lot of talk in the press\nabout online commerce. At the time there might have been thirty\nactual stores on the Web, all made by hand. If there were going\nto be a lot of online stores, there would need to be software for making\nthem, so we decided to write some.For the first week or so we intended to make this an ordinary \ndesktop application. Then one day we had the idea of making the\nsoftware run on our Web server, using the browser as an\ninterface. We tried rewriting the software to work over\nthe Web, and it was clear that this was the way to go.\nIf we wrote our software to run on the server, it would be a lot easier\nfor the users and for us as well.This turned out to be a good plan. Now, as \nYahoo Store, this\nsoftware is the most popular online store builder, with\nabout 14,000 users.When we started Viaweb, hardly anyone understood what we meant when\nwe said that the software ran on the server. It was not until\nHotmail was launched a year later that people started to get it.\nNow everyone knows that this is a valid approach. There is\na name now for what we were: an Application Service Provider,\nor ASP.I think that a lot of the next generation of software will be\nwritten on this model. Even Microsoft, who have the most to\nlose, seem to see the inevitablity of moving some things off\nthe desktop. If software moves\noff the desktop and onto servers, it will mean a very different\nworld for developers. This article describes the surprising\nthings we saw, as some of the first visitors to this new world.\nTo the extent software does move onto\nservers, what I'm describing here is the future.The Next Thing?When we look back on the desktop software era, I think we'll marvel\nat the inconveniences people put up with, just as we marvel now at\nwhat early car owners put up with. For the first twenty or thirty\nyears, you had to be a car expert to own a car. But cars were such\na big win that lots of people who weren't car experts wanted to\nhave them as well.Computers are in this phase now. When you own a desktop computer,\nyou end up learning a lot more than you wanted to know about what's\nhappening inside it. But more than half the households in the US\nown one. My mother has a computer that she uses for email and for\nkeeping accounts. About a year ago she was alarmed to receive a\nletter from Apple, offering her a discount on a new version of the\noperating system. There's something wrong when a sixty-five year\nold woman who wants to use a computer for email and accounts has\nto think about installing new operating systems. Ordinary users\nshouldn't even know the words \"operating system,\" much less \"device\ndriver\" or \"patch.\"There is now another way to deliver software that will save users\nfrom becoming system administrators. Web-based applications are\nprograms that run on Web servers and use Web pages as the user\ninterface. For the average user this new kind of software will be\neasier, cheaper, more mobile, more reliable, and often more powerful\nthan desktop software.With Web-based software, most users won't have to think about\nanything except the applications they use. All the messy, changing\nstuff will be sitting on a server somewhere, maintained by the kind\nof people who are good at that kind of thing. And so you won't\nordinarily need a computer, per se, to use software. All you'll\nneed will be something with a keyboard, a screen, and a Web browser.\nMaybe it will have wireless Internet access. Maybe it will also\nbe your cell phone. Whatever it is, it will be consumer electronics:\nsomething that costs about $200, and that people choose mostly\nbased on how the case looks. You'll pay more for Internet services\nthan you do for the hardware, just as you do now with telephones. [1]It will take about a tenth of a second for a click to get to the\nserver and back, so users of heavily interactive software, like\nPhotoshop, will still want to have the computations happening on\nthe desktop. But if you look at the kind of things most people\nuse computers for, a tenth of a second latency would not be a\nproblem. My mother doesn't really need a desktop computer, and\nthere are a lot of people like her.The Win for UsersNear my house there is a car with a bumper sticker that reads \"death\nbefore inconvenience.\" Most people, most of the time, will take\nwhatever choice requires least work. If Web-based software wins,\nit will be because it's more convenient. And it looks as if it\nwill be, for users and developers both.To use a purely Web-based application, all you need is a browser\nconnected to the Internet. So you can use a Web-based application\nanywhere. When you install software on your desktop computer, you\ncan only use it on that computer. Worse still, your files are\ntrapped on that computer. The inconvenience of this model becomes\nmore and more evident as people get used to networks.The thin end of the wedge here was Web-based email. Millions of\npeople now realize that you should have access to email messages\nno matter where you are. And if you can see your email, why not\nyour calendar? \nIf you can discuss a document with your colleagues,\nwhy can't you edit it? Why should any of your data be trapped on\nsome computer sitting on a faraway desk?The whole idea of \"your computer\" is going away, and being replaced\nwith \"your data.\" You should be able to get at your data from any\ncomputer. Or rather, any client, and a client doesn't have to be\na computer.Clients shouldn't store data; they should be like telephones. In\nfact they may become telephones, or vice versa. And as clients\nget smaller, you have another reason not to keep your data on them:\nsomething you carry around with you can be lost or stolen. Leaving\nyour PDA in a taxi is like a disk crash, except that your data is\nhanded to someone else \ninstead of being vaporized.With purely Web-based software, neither your data nor the applications\nare kept on the client. So you don't have to install anything to\nuse it. And when there's no installation, you don't have to worry\nabout installation going wrong. There can't be incompatibilities\nbetween the application and your operating system, because the\nsoftware doesn't run on your operating system.Because it needs no installation, it will be easy, and common, to\ntry Web-based software before you \"buy\" it. You should expect to\nbe able to test-drive any Web-based application for free, just by\ngoing to the site where it's offered. At Viaweb our whole site\nwas like a big arrow pointing users to the test drive.After trying the demo, signing up for the service should require\nnothing more than filling out a brief form (the briefer the better).\nAnd that should be the last work the user has to do. With Web-based\nsoftware, you should get new releases without paying extra, or\ndoing any work, or possibly even knowing about it.Upgrades won't be the big shocks they are now. Over time applications\nwill quietly grow more powerful. This will take some effort on\nthe part of the developers. They will have to design software so\nthat it can be updated without confusing the users. That's a new\nproblem, but there are ways to solve it.With Web-based applications, everyone uses the same version, and\nbugs can be fixed as soon as they're discovered. So Web-based\nsoftware should have far fewer bugs than desktop software. At\nViaweb, I doubt we ever had ten known bugs at any one time. That's\norders of magnitude better than desktop software.Web-based applications can be used by several people at the same\ntime. This is an obvious win for collaborative applications, but\nI bet users will start to want this in most applications once they\nrealize it's possible. It will often be useful to let two people\nedit the same document, for example. Viaweb let multiple users\nedit a site simultaneously, more because that was the right way to\nwrite the software than because we expected users to want to, but\nit turned out that many did.When you use a Web-based application, your data will be safer.\nDisk crashes won't be a thing of the past, but users won't hear\nabout them anymore. They'll happen within server farms. And\ncompanies offering Web-based applications will actually do backups--\nnot only because they'll have real system administrators worrying\nabout such things, but because an ASP that does lose people's data\nwill be in big, big trouble. When people lose their own data in\na disk crash, they can't get that mad, because they only have\nthemselves to be mad at. When a company loses their data for them,\nthey'll get a lot madder.Finally, Web-based software should be less vulnerable to viruses.\nIf the client doesn't run anything except a browser, there's less\nchance of running viruses, and no data locally to damage. And a\nprogram that attacked the servers themselves should find them very\nwell defended. [2]For users, Web-based software will be less stressful. I think if\nyou looked inside the average Windows user you'd find a huge and\npretty much untapped desire for software meeting that description.\nUnleashed, it could be a powerful force.City of CodeTo developers, the most conspicuous difference between Web-based\nand desktop software is that a Web-based application is not a single\npiece of code. It will be a collection of programs of different\ntypes rather than a single big binary. And so designing Web-based\nsoftware is like desiging a city rather than a building: as well\nas buildings you need roads, street signs, utilities, police and\nfire departments, and plans for both growth and various kinds of\ndisasters.At Viaweb, software included fairly big applications that users\ntalked to directly, programs that those programs used, programs\nthat ran constantly in the background looking for problems, programs\nthat tried to restart things if they broke, programs that ran\noccasionally to compile statistics or build indexes for searches,\nprograms we ran explicitly to garbage-collect resources or to move\nor restore data, programs that pretended to be users (to measure\nperformance or expose bugs), programs for diagnosing network\ntroubles, programs for doing backups, interfaces to outside services,\nsoftware that drove an impressive collection of dials displaying\nreal-time server statistics (a hit with visitors, but indispensable\nfor us too), modifications (including bug fixes) to open-source\nsoftware, and a great many configuration files and settings. Trevor\nBlackwell wrote a spectacular program for moving stores to new\nservers across the country, without shutting them down, after we\nwere bought by Yahoo. Programs paged us, sent faxes and email to\nusers, conducted transactions with credit card processors, and\ntalked to one another through sockets, pipes, http requests, ssh,\nudp packets, shared memory, and files. Some of Viaweb even consisted\nof the absence of programs, since one of the keys to Unix security\nis not to run unnecessary utilities that people might use to break\ninto your servers.It did not end with software. We spent a lot of time thinking\nabout server configurations. We built the servers ourselves, from\ncomponents-- partly to save money, and partly to get exactly what\nwe wanted. We had to think about whether our upstream ISP had fast\nenough connections to all the backbones. We serially \ndated\nRAID suppliers.But hardware is not just something to worry about. When you control\nit you can do more for users. With a desktop application, you can\nspecify certain minimum hardware, but you can't add more. If you\nadminister the servers, you can in one step enable all your users\nto page people, or send faxes, or send commands by phone, or process\ncredit cards, etc, just by installing the relevant hardware. We\nalways looked for new ways to add features with hardware, not just\nbecause it pleased users, but also as a way to distinguish ourselves\nfrom competitors who (either because they sold desktop software,\nor resold Web-based applications through ISPs) didn't have direct\ncontrol over the hardware.Because the software in a Web-based application will be a collection\nof programs rather than a single binary, it can be written in any\nnumber of different languages. When you're writing desktop software,\nyou're practically forced to write the application in the same\nlanguage as the underlying operating system-- meaning C and C++.\nAnd so these languages (especially among nontechnical people like\nmanagers and VCs) got to be considered as the languages for \"serious\"\nsoftware development. But that was just an artifact of the way\ndesktop software had to be delivered. For server-based software\nyou can use any language you want. [3] Today a lot of the top\nhackers are using languages far removed from C and C++: Perl,\nPython, and even Lisp.With server-based software, no one can tell you what language to\nuse, because you control the whole system, right down to the\nhardware. Different languages are good for different tasks. You\ncan use whichever is best for each. And when you have competitors,\n\"you can\" means \"you must\" (we'll return to this later), because\nif you don't take advantage of this possibility, your competitors\nwill.Most of our competitors used C and C++, and this made their software\nvisibly inferior because (among other things), they had no way\naround the statelessness of CGI scripts. If you were going to\nchange something, all the changes had to happen on one page, with\nan Update button at the bottom. As I've written elsewhere, by\nusing Lisp, which many people still consider \na research language,\nwe could make the Viaweb editor behave more like desktop software.ReleasesOne of the most important changes in this new world is the way you\ndo releases. In the desktop software business, doing a release is\na huge trauma, in which the whole company sweats and strains to\npush out a single, giant piece of code. Obvious comparisons suggest\nthemselves, both to the process and the resulting product.With server-based software, you can make changes almost as you\nwould in a program you were writing for yourself. You release\nsoftware as a series of incremental changes instead of an occasional\nbig explosion. A typical desktop software company might do one or\ntwo releases a year. At Viaweb we often did three to five releases\na day.When you switch to this new model, you realize how much software\ndevelopment is affected by the way it is released. Many of the\nnastiest problems you see in the desktop software business are due\nto catastrophic nature of releases.When you release only one new version a year, you tend to deal with\nbugs wholesale. Some time before the release date you assemble a\nnew version in which half the code has been torn out and replaced,\nintroducing countless bugs. Then a squad of QA people step in and\nstart counting them, and the programmers work down the list, fixing\nthem. They do not generally get to the end of the list, and indeed,\nno one is sure where the end is. It's like fishing rubble out of\na pond. You never really know what's happening inside the software.\nAt best you end up with a statistical sort of correctness.With server-based software, most of the change is small and\nincremental. That in itself is less likely to introduce bugs. It\nalso means you know what to test most carefully when you're about\nto release software: the last thing you changed. You end up with\na much firmer grip on the code. As a general rule, you do know\nwhat's happening inside it. You don't have the source code memorized,\nof course, but when you read the source you do it like a pilot\nscanning the instrument panel, not like a detective trying to\nunravel some mystery.Desktop software breeds a certain fatalism about bugs. You know\nthat you're shipping something loaded with bugs, and you've even\nset up mechanisms to compensate for it (e.g. patch releases). So\nwhy worry about a few more? Soon you're releasing whole features\nyou know are broken. \nApple \ndid this earlier this year. They felt\nunder pressure to release their new OS, whose release date had\nalready slipped four times, but some of the software (support for\nCDs and DVDs) wasn't ready. The solution? They released the OS\nwithout the unfinished parts, and users will have to install them\nlater.With Web-based software, you never have to release software before\nit works, and you can release it as soon as it does work.The industry veteran may be thinking, it's a fine-sounding idea to\nsay that you never have to release software before it works, but\nwhat happens when you've promised to deliver a new version of your\nsoftware by a certain date? With Web-based software, you wouldn't\nmake such a promise, because there are no versions. Your software\nchanges gradually and continuously. Some changes might be bigger\nthan others, but the idea of versions just doesn't naturally fit\nonto Web-based software.If anyone remembers Viaweb this might sound odd, because we were\nalways announcing new versions. This was done entirely for PR\npurposes. The trade press, we learned, thinks in version numbers.\nThey will give you major coverage for a major release, meaning a\nnew first digit on the version number, and generally a paragraph\nat most for a point release, meaning a new digit after the decimal\npoint.Some of our competitors were offering desktop software and actually\nhad version numbers. And for these releases, the mere fact of\nwhich seemed to us evidence of their backwardness, they would get\nall kinds of publicity. We didn't want to miss out, so we started\ngiving version numbers to our software too. When we wanted some\npublicity, we'd make a list of all the features we'd added since\nthe last \"release,\" stick a new version number on the software,\nand issue a press release saying that the new version was available\nimmediately. Amazingly, no one ever called us on it.By the time we were bought, we had done this three times, so we\nwere on Version 4. Version 4.1 if I remember correctly. After\nViaweb became Yahoo Store, there was no longer such a desperate\nneed for publicity, so although the software continued to evolve,\nthe whole idea of version numbers was quietly dropped.BugsThe other major technical advantage of Web-based software is that\nyou can reproduce most bugs. You have the users' data right there\non your disk. If someone breaks your software, you don't have to\ntry to guess what's going on, as you would with desktop software:\nyou should be able to reproduce the error while they're on the\nphone with you. You might even know about it already, if you have\ncode for noticing errors built into your application.Web-based software gets used round the clock, so everything you do\nis immediately put through the wringer. Bugs turn up quickly.Software companies are sometimes accused of letting the users debug\ntheir software. And that is just what I'm advocating. For Web-based\nsoftware it's actually a good plan, because the bugs are fewer and\ntransient. When you release software gradually you get far fewer\nbugs to start with. And when you can reproduce errors and release\nchanges instantly, you can find and fix most bugs as soon as they\nappear. We never had enough bugs at any one time to bother with\na formal bug-tracking system.You should test changes before you release them, of course, so no\nmajor bugs should get released. Those few that inevitably slip\nthrough will involve borderline cases and will only affect the few\nusers that encounter them before someone calls in to complain. As\nlong as you fix bugs right away, the net effect, for the average\nuser, is far fewer bugs. I doubt the average Viaweb user ever saw\na bug.Fixing fresh bugs is easier than fixing old ones. It's usually\nfairly quick to find a bug in code you just wrote. When it turns\nup you often know what's wrong before you even look at the source,\nbecause you were already worrying about it subconsciously. Fixing\na bug in something you wrote six months ago (the average case if\nyou release once a year) is a lot more work. And since you don't\nunderstand the code as well, you're more likely to fix it in an\nugly way, or even introduce more bugs. [4]When you catch bugs early, you also get fewer compound bugs.\nCompound bugs are two separate bugs that interact: you trip going\ndownstairs, and when you reach for the handrail it comes off in\nyour hand. In software this kind of bug is the hardest to find,\nand also tends to have the worst consequences. [5] The traditional\n\"break everything and then filter out the bugs\" approach inherently\nyields a lot of compound bugs. And software that's released in a\nseries of small changes inherently tends not to. The floors are\nconstantly being swept clean of any loose objects that might later\nget stuck in something.It helps if you use a technique called functional programming.\nFunctional programming means avoiding side-effects. It's something\nyou're more likely to see in research papers than commercial\nsoftware, but for Web-based applications it turns out to be really\nuseful. It's hard to write entire programs as purely functional\ncode, but you can write substantial chunks this way. It makes\nthose parts of your software easier to test, because they have no\nstate, and that is very convenient in a situation where you are\nconstantly making and testing small modifications. I wrote much\nof Viaweb's editor in this style, and we made our scripting language,\nRTML, \na purely functional language.People from the desktop software business will find this hard to\ncredit, but at Viaweb bugs became almost a game. Since most released\nbugs involved borderline cases, the users who encountered them were\nlikely to be advanced users, pushing the envelope. Advanced users\nare more forgiving about bugs, especially since you probably\nintroduced them in the course of adding some feature they were\nasking for. In fact, because bugs were rare and you had to be\ndoing sophisticated things to see them, advanced users were often\nproud to catch one. They would call support in a spirit more of\ntriumph than anger, as if they had scored points off us.SupportWhen you can reproduce errors, it changes your approach to customer\nsupport. At most software companies, support is offered as a way\nto make customers feel better. They're either calling you about\na known bug, or they're just doing something wrong and you have to\nfigure out what. In either case there's not much you can learn\nfrom them. And so you tend to view support calls as a pain in the\nass that you want to isolate from your developers as much as\npossible.This was not how things worked at Viaweb. At Viaweb, support was\nfree, because we wanted to hear from customers. If someone had a\nproblem, we wanted to know about it right away so that we could\nreproduce the error and release a fix.So at Viaweb the developers were always in close contact with\nsupport. The customer support people were about thirty feet away\nfrom the programmers, and knew that they could always interrupt\nanything with a report of a genuine bug. We would leave a board\nmeeting to fix a serious bug.Our approach to support made everyone happier. The customers were\ndelighted. Just imagine how it would feel to call a support line\nand be treated as someone bringing important news. The customer\nsupport people liked it because it meant they could help the users,\ninstead of reading scripts to them. And the programmers liked it\nbecause they could reproduce bugs instead of just hearing vague\nsecond-hand reports about them.Our policy of fixing bugs on the fly changed the relationship\nbetween customer support people and hackers. At most software\ncompanies, support people are underpaid human shields, and hackers\nare little copies of God the Father, creators of the world. Whatever\nthe procedure for reporting bugs, it is likely to be one-directional:\nsupport people who hear about bugs fill out some form that eventually\ngets passed on (possibly via QA) to programmers, who put it on\ntheir list of things to do. It was very different at Viaweb.\nWithin a minute of hearing about a bug from a customer, the support\npeople could be standing next to a programmer hearing him say \"Shit,\nyou're right, it's a bug.\" It delighted the support people to hear\nthat \"you're right\" from the hackers. They used to bring us bugs\nwith the same expectant air as a cat bringing you a mouse it has\njust killed. It also made them more careful in judging the\nseriousness of a bug, because now their honor was on the line.After we were bought by Yahoo, the customer support people were\nmoved far away from the programmers. It was only then that we\nrealized that they were effectively QA and to some extent marketing\nas well. In addition to catching bugs, they were the keepers of\nthe knowledge of vaguer, buglike things, like features that confused\nusers. [6] They were also a kind of proxy focus group; we could\nask them which of two new features users wanted more, and they were\nalways right.MoraleBeing able to release software immediately is a big motivator.\nOften as I was walking to work I would think of some change I wanted\nto make to the software, and do it that day. This worked for bigger\nfeatures as well. Even if something was going to take two weeks\nto write (few projects took longer), I knew I could see the effect\nin the software as soon as it was done.If I'd had to wait a year for the next release, I would have shelved\nmost of these ideas, for a while at least. The thing about ideas,\nthough, is that they lead to more ideas. Have you ever noticed\nthat when you sit down to write something, half the ideas that end\nup in it are ones you thought of while writing it? The same thing\nhappens with software. Working to implement one idea gives you\nmore ideas. So shelving an idea costs you not only that delay in\nimplementing it, but also all the ideas that implementing it would\nhave led to. In fact, shelving an idea probably even inhibits new\nideas: as you start to think of some new feature, you catch sight\nof the shelf and think \"but I already have a lot of new things I\nwant to do for the next release.\"What big companies do instead of implementing features is plan\nthem. At Viaweb we sometimes ran into trouble on this account.\nInvestors and analysts would ask us what we had planned for the\nfuture. The truthful answer would have been, we didn't have any\nplans. We had general ideas about things we wanted to improve,\nbut if we knew how we would have done it already. What were we\ngoing to do in the next six months? Whatever looked like the biggest\nwin. I don't know if I ever dared give this answer, but that was\nthe truth. Plans are just another word for ideas on the shelf.\nWhen we thought of good ideas, we implemented them.At Viaweb, as at many software companies, most code had one definite\nowner. But when you owned something you really owned it: no one\nexcept the owner of a piece of software had to approve (or even\nknow about) a release. There was no protection against breakage\nexcept the fear of looking like an idiot to one's peers, and that\nwas more than enough. I may have given the impression that we just\nblithely plowed forward writing code. We did go fast, but we\nthought very carefully before we released software onto those\nservers. And paying attention is more important to reliability\nthan moving slowly. Because he pays close attention, a Navy pilot\ncan land a 40,000 lb. aircraft at 140 miles per hour on a pitching\ncarrier deck, at night, more safely than the average teenager can\ncut a bagel.This way of writing software is a double-edged sword of course.\nIt works a lot better for a small team of good, trusted programmers\nthan it would for a big company of mediocre ones, where bad ideas\nare caught by committees instead of the people that had them.Brooks in ReverseFortunately, Web-based software does require fewer programmers.\nI once worked for a medium-sized desktop software company that had\nover 100 people working in engineering as a whole. Only 13 of\nthese were in product development. All the rest were working on\nreleases, ports, and so on. With Web-based software, all you need\n(at most) are the 13 people, because there are no releases, ports,\nand so on.Viaweb was written by just three people. [7] I was always under\npressure to hire more, because we wanted to get bought, and we knew\nthat buyers would have a hard time paying a high price for a company\nwith only three programmers. (Solution: we hired more, but created\nnew projects for them.)When you can write software with fewer programmers, it saves you\nmore than money. As Fred Brooks pointed out in The Mythical\nMan-Month, adding people to a project tends to slow it down. The\nnumber of possible connections between developers grows exponentially\nwith the size of the group. The larger the group, the more time\nthey'll spend in meetings negotiating how their software will work\ntogether, and the more bugs they'll get from unforeseen interactions.\nFortunately, this process also works in reverse: as groups get\nsmaller, software development gets exponentially more efficient.\nI can't remember the programmers at Viaweb ever having an actual\nmeeting. We never had more to say at any one time than we could\nsay as we were walking to lunch.If there is a downside here, it is that all the programmers have\nto be to some degree system administrators as well. When you're\nhosting software, someone has to be watching the servers, and in\npractice the only people who can do this properly are the ones who\nwrote the software. At Viaweb our system had so many components\nand changed so frequently that there was no definite border between\nsoftware and infrastructure. Arbitrarily declaring such a border\nwould have constrained our design choices. And so although we were\nconstantly hoping that one day (\"in a couple months\") everything\nwould be stable enough that we could hire someone whose job was\njust to worry about the servers, it never happened.I don't think it could be any other way, as long as you're still\nactively developing the product. Web-based software is never going\nto be something you write, check in, and go home. It's a live\nthing, running on your servers right now. A bad bug might not just\ncrash one user's process; it could crash them all. If a bug in\nyour code corrupts some data on disk, you have to fix it. And so\non. We found that you don't have to watch the servers every minute\n(after the first year or so), but you definitely want to keep an\neye on things you've changed recently. You don't release code late\nat night and then go home.Watching UsersWith server-based software, you're in closer touch with your code.\nYou can also be in closer touch with your users. Intuit is famous\nfor introducing themselves to customers at retail stores and asking\nto follow them home. If you've ever watched someone use your\nsoftware for the first time, you know what surprises must have\nawaited them.Software should do what users think it will. But you can't have\nany idea what users will be thinking, believe me, until you watch\nthem. And server-based software gives you unprecedented information\nabout their behavior. You're not limited to small, artificial\nfocus groups. You can see every click made by every user. You\nhave to consider carefully what you're going to look at, because\nyou don't want to violate users' privacy, but even the most general\nstatistical sampling can be very useful.When you have the users on your server, you don't have to rely on\nbenchmarks, for example. Benchmarks are simulated users. With\nserver-based software, you can watch actual users. To decide what\nto optimize, just log into a server and see what's consuming all\nthe CPU. And you know when to stop optimizing too: we eventually\ngot the Viaweb editor to the point where it was memory-bound rather\nthan CPU-bound, and since there was nothing we could do to decrease\nthe size of users' data (well, nothing easy), we knew we might as\nwell stop there.Efficiency matters for server-based software, because you're paying\nfor the hardware. The number of users you can support per server\nis the divisor of your capital cost, so if you can make your software\nvery efficient you can undersell competitors and still make a\nprofit. At Viaweb we got the capital cost per user down to about\n$5. It would be less now, probably less than the cost of sending\nthem the first month's bill. Hardware is free now, if your software\nis reasonably efficient.Watching users can guide you in design as well as optimization.\nViaweb had a scripting language called RTML that let advanced users\ndefine their own page styles. We found that RTML became a kind of\nsuggestion box, because users only used it when the predefined page\nstyles couldn't do what they wanted. Originally the editor put\nbutton bars across the page, for example, but after a number of\nusers used RTML to put buttons down the left \nside, \nwe made that an\noption (in fact the default) in the predefined page styles.Finally, by watching users you can often tell when they're in\ntrouble. And since the customer is always right, that's a sign of\nsomething you need to fix. At Viaweb the key to getting users was\nthe online test drive. It was not just a series of slides built\nby marketing people. In our test drive, users actually used the\nsoftware. It took about five minutes, and at the end of it they\nhad built a real, working store.\nThe test drive was the way we got nearly all our new users. I\nthink it will be the same for most Web-based applications. If\nusers can get through a test drive successfully, they'll like the\nproduct. If they get confused or bored, they won't. So anything\nwe could do to get more people through the test drive would increase\nour growth rate.I studied click trails of people taking the test drive and found\nthat at a certain step they would get confused and click on the\nbrowser's Back button. (If you try writing Web-based applications,\nyou'll find that the Back button becomes one of your most interesting\nphilosophical problems.) So I added a message at that point, telling\nusers that they were nearly finished, and reminding them not to\nclick on the Back button. Another great thing about Web-based\nsoftware is that you get instant feedback from changes: the number\nof people completing the test drive rose immediately from 60% to\n90%. And since the number of new users was a function of the number\nof completed test drives, our revenue growth increased by 50%, just\nfrom that change.MoneyIn the early 1990s I read an article in which someone said that\nsoftware was a subscription business. At first this seemed a very\ncynical statement. But later I realized that it reflects reality:\nsoftware development is an ongoing process. I think it's cleaner\nif you openly charge subscription fees, instead of forcing people\nto keep buying and installing new versions so that they'll keep\npaying you. And fortunately, subscriptions are the natural way to\nbill for Web-based applications.Hosting applications is an area where companies will play a role\nthat is not likely to be filled by freeware. Hosting applications\nis a lot of stress, and has real expenses. No one is going to want\nto do it for free.For companies, Web-based applications are an ideal source of revenue.\nInstead of starting each quarter with a blank slate, you have a\nrecurring revenue stream. Because your software evolves gradually,\nyou don't have to worry that a new model will flop; there never\nneed be a new model, per se, and if you do something to the software\nthat users hate, you'll know right away. You have no trouble with\nuncollectable bills; if someone won't pay you can just turn off\nthe service. And there is no possibility of piracy.That last \"advantage\" may turn out to be a problem. Some amount\nof piracy is to the advantage of software companies. If some user\nreally would not have bought your software at any price, you haven't\nlost anything if he uses a pirated copy. In fact you gain, because\nhe is one more user helping to make your software the standard--\nor who might buy a copy later, when he graduates from high school.When they can, companies like to do something called price\ndiscrimination, which means charging each customer as much as they\ncan afford. [8] Software is particularly suitable for price\ndiscrimination, because the marginal cost is close to zero. This\nis why some software costs more to run on Suns than on Intel boxes:\na company that uses Suns is not interested in saving money and can\nsafely be charged more. Piracy is effectively the lowest tier of\nprice discrimination. I think that software companies understand\nthis and deliberately turn a blind eye to some kinds of piracy. [9] \nWith server-based software they are going to have to come up with \nsome other solution.Web-based software sells well, especially in comparison to desktop\nsoftware, because it's easy to buy. You might think that people\ndecide to buy something, and then buy it, as two separate steps.\nThat's what I thought before Viaweb, to the extent I thought about\nthe question at all. In fact the second step can propagate back\ninto the first: if something is hard to buy, people will change\ntheir mind about whether they wanted it. And vice versa: you'll\nsell more of something when it's easy to buy. I buy more books\nbecause Amazon exists. Web-based software is just about the easiest\nthing in the world to buy, especially if you have just done an\nonline demo. Users should not have to do much more than enter a\ncredit card number. (Make them do more at your peril.)\nSometimes Web-based software is offered through ISPs acting as\nresellers. This is a bad idea. You have to be administering the\nservers, because you need to be constantly improving both hardware\nand software. If you give up direct control of the servers, you\ngive up most of the advantages of developing Web-based applications.Several of our competitors shot themselves in the foot this way--\nusually, I think, because they were overrun by suits who were\nexcited about this huge potential channel, and didn't realize that\nit would ruin the product they hoped to sell through it. Selling\nWeb-based software through ISPs is like selling sushi through\nvending machines.CustomersWho will the customers be? At Viaweb they were initially individuals\nand smaller companies, and I think this will be the rule with\nWeb-based applications. These are the users who are ready to try\nnew things, partly because they're more flexible, and partly because\nthey want the lower costs of new technology.Web-based applications will often be the best thing for big companies\ntoo (though they'll be slow to realize it). The best intranet is\nthe Internet. If a company uses true Web-based applications, the\nsoftware will work better, the servers will be better administered,\nand employees will have access to the system from anywhere.The argument against this approach usually hinges on security: if\naccess is easier for employees, it will be for bad guys too. Some\nlarger merchants were reluctant to use Viaweb because they thought\ncustomers' credit card information would be safer on their own\nservers. It was not easy to make this point diplomatically, but\nin fact the data was almost certainly safer in our hands than\ntheirs. Who can hire better people to manage security, a technology\nstartup whose whole business is running servers, or a clothing\nretailer? Not only did we have better people worrying about\nsecurity, we worried more about it. If someone broke into the\nclothing retailer's servers, it would affect at most one merchant,\ncould probably be hushed up, and in the worst case might get one\nperson fired. If someone broke into ours, it could affect thousands\nof merchants, would probably end up as news on CNet, and could put\nus out of business.If you want to keep your money safe, do you keep it under your\nmattress at home, or put it in a bank? This argument applies to\nevery aspect of server administration: not just security, but\nuptime, bandwidth, load management, backups, etc. Our existence\ndepended on doing these things right. Server problems were the\nbig no-no for us, like a dangerous toy would be for a toy maker,\nor a salmonella outbreak for a food processor.A big company that uses Web-based applications is to that extent\noutsourcing IT. Drastic as it sounds, I think this is generally\na good idea. Companies are likely to get better service this way\nthan they would from in-house system administrators. System\nadministrators can become cranky and unresponsive because they're\nnot directly exposed to competitive pressure: a salesman has to\ndeal with customers, and a developer has to deal with competitors'\nsoftware, but a system administrator, like an old bachelor, has\nfew external forces to keep him in line. [10] At Viaweb we had\nexternal forces in plenty to keep us in line. The people calling\nus were customers, not just co-workers. If a server got wedged,\nwe jumped; just thinking about it gives me a jolt of adrenaline,\nyears later.So Web-based applications will ordinarily be the right answer for\nbig companies too. They will be the last to realize it, however,\njust as they were with desktop computers. And partly for the same\nreason: it will be worth a lot of money to convince big companies\nthat they need something more expensive.There is always a tendency for rich customers to buy expensive\nsolutions, even when cheap solutions are better, because the people\noffering expensive solutions can spend more to sell them. At Viaweb\nwe were always up against this. We lost several high-end merchants\nto Web consulting firms who convinced them they'd be better off if\nthey paid half a million dollars for a custom-made online store on\ntheir own server. They were, as a rule, not better off, as more\nthan one discovered when Christmas shopping season came around and\nloads rose on their server. Viaweb was a lot more sophisticated\nthan what most of these merchants got, but we couldn't afford to\ntell them. At $300 a month, we couldn't afford to send a team of\nwell-dressed and authoritative-sounding people to make presentations\nto customers.A large part of what big companies pay extra for is the cost of\nselling expensive things to them. (If the Defense Department pays\na thousand dollars for toilet seats, it's partly because it costs\na lot to sell toilet seats for a thousand dollars.) And this is\none reason intranet software will continue to thrive, even though\nit is probably a bad idea. It's simply more expensive. There is\nnothing you can do about this conundrum, so the best plan is to go\nfor the smaller customers first. The rest will come in time.Son of ServerRunning software on the server is nothing new. In fact it's the\nold model: mainframe applications are all server-based. If\nserver-based software is such a good idea, why did it lose last\ntime? Why did desktop computers eclipse mainframes?At first desktop computers didn't look like much of a threat. The\nfirst users were all hackers-- or hobbyists, as they were called\nthen. They liked microcomputers because they were cheap. For the\nfirst time, you could have your own computer. The phrase \"personal\ncomputer\" is part of the language now, but when it was first used\nit had a deliberately audacious sound, like the phrase \"personal\nsatellite\" would today.Why did desktop computers take over? I think it was because they\nhad better software. And I think the reason microcomputer software\nwas better was that it could be written by small companies.I don't think many people realize how fragile and tentative startups\nare in the earliest stage. Many startups begin almost by accident--\nas a couple guys, either with day jobs or in school, writing a\nprototype of something that might, if it looks promising, turn into\na company. At this larval stage, any significant obstacle will stop\nthe startup dead in its tracks. Writing mainframe software required\ntoo much commitment up front. Development machines were expensive,\nand because the customers would be big companies, you'd need an\nimpressive-looking sales force to sell it to them. Starting a\nstartup to write mainframe software would be a much more serious\nundertaking than just hacking something together on your Apple II\nin the evenings. And so you didn't get a lot of startups writing\nmainframe applications.The arrival of desktop computers inspired a lot of new software,\nbecause writing applications for them seemed an attainable goal to\nlarval startups. Development was cheap, and the customers would\nbe individual people that you could reach through computer stores\nor even by mail-order.The application that pushed desktop computers out into the mainstream\nwas VisiCalc, the \nfirst spreadsheet. It was written by two guys\nworking in an attic, and yet did things no mainframe software could\ndo. [11] VisiCalc was such an advance, in its time, that people\nbought Apple IIs just to run it. And this was the beginning of a\ntrend: desktop computers won because startups wrote software for\nthem.It looks as if server-based software will be good this time around,\nbecause startups will write it. Computers are so cheap now that\nyou can get started, as we did, using a desktop computer as a\nserver. Inexpensive processors have eaten the workstation market\n(you rarely even hear the word now) and are most of the way through\nthe server market; Yahoo's servers, which deal with loads as high\nas any on the Internet, all have the same inexpensive Intel processors\nthat you have in your desktop machine. And once you've written\nthe software, all you need to sell it is a Web site. Nearly all\nour users came direct to our site through word of mouth and references\nin the press. [12]Viaweb was a typical larval startup. We were terrified of starting\na company, and for the first few months comforted ourselves by\ntreating the whole thing as an experiment that we might call off\nat any moment. Fortunately, there were few obstacles except\ntechnical ones. While we were writing the software, our Web server\nwas the same desktop machine we used for development, connected to\nthe outside world by a dialup line. Our only expenses in that\nphase were food and rent.There is all the more reason for startups to write Web-based software\nnow, because writing desktop software has become a lot less fun.\nIf you want to write desktop software now you do it on Microsoft's\nterms, calling their APIs and working around their buggy OS. And\nif you manage to write something that takes off, you may find that\nyou were merely doing market research for Microsoft.If a company wants to make a platform that startups will build on,\nthey have to make it something that hackers themselves will want\nto use. That means it has to be inexpensive and well-designed.\nThe Mac was popular with hackers when it first came out, and a lot\nof them wrote software for it. [13] You see this less with Windows,\nbecause hackers don't use it. The kind of people who are good at\nwriting software tend to be running Linux or FreeBSD now.I don't think we would have started a startup to write desktop\nsoftware, because desktop software has to run on Windows, and before\nwe could write software for Windows we'd have to use it. The Web \nlet us do an end-run around Windows, and deliver software running \non Unix direct to users through the browser. That is a liberating \nprospect, a lot like the arrival of PCs twenty-five years ago.MicrosoftBack when desktop computers arrived, IBM was the giant that everyone\nwas afraid of. It's hard to imagine now, but I remember the feeling\nvery well. Now the frightening giant is Microsoft, and I don't\nthink they are as blind to the threat facing them as IBM was.\nAfter all, Microsoft deliberately built their business in IBM's\nblind spot.I mentioned earlier that my mother doesn't really need a desktop\ncomputer. Most users probably don't. That's a problem for Microsoft,\nand they know it. If applications run on remote servers, no one\nneeds Windows. What will Microsoft do? Will they be able to use\ntheir control of the desktop to prevent, or constrain, this new\ngeneration of software?My guess is that Microsoft will develop some kind of server/desktop\nhybrid, where the operating system works together with servers they\ncontrol. At a minimum, files will be centrally available for users\nwho want that. I don't expect Microsoft to go all the way to the\nextreme of doing the computations on the server, with only a browser\nfor a client, if they can avoid it. If you only need a browser for\na client, you don't need Microsoft on the client, and if Microsoft\ndoesn't control the client, they can't push users towards their\nserver-based applications.I think Microsoft will have a hard time keeping the genie in the\nbottle. There will be too many different types of clients for them\nto control them all. And if Microsoft's applications only work\nwith some clients, competitors will be able to trump them by offering\napplications that work from any client. [14]In a world of Web-based applications, there is no automatic place\nfor Microsoft. They may succeed in making themselves a place, but\nI don't think they'll dominate this new world as they did the world\nof desktop applications.It's not so much that a competitor will trip them up as that they\nwill trip over themselves. With the rise of Web-based software,\nthey will be facing not just technical problems but their own\nwishful thinking. What they need to do is cannibalize their existing\nbusiness, and I can't see them facing that. The same single-mindedness\nthat has brought them this far will now be working against them.\nIBM was in exactly the same situation, and they could not master\nit. IBM made a late and half-hearted entry into the microcomputer\nbusiness because they were ambivalent about threatening their cash\ncow, mainframe computing. Microsoft will likewise be hampered by\nwanting to save the desktop. A cash cow can be a damned heavy\nmonkey on your back.I'm not saying that no one will dominate server-based applications.\nSomeone probably will eventually. But I think that there will be\na good long period of cheerful chaos, just as there was in the\nearly days of microcomputers. That was a good time for startups.\nLots of small companies flourished, and did it by making cool\nthings.Startups but More SoThe classic startup is fast and informal, with few people and little\nmoney. Those few people work very hard, and technology magnifies\nthe effect of the decisions they make. If they win, they win big.In a startup writing Web-based applications, everything you associate\nwith startups is taken to an extreme. You can write and launch a\nproduct with even fewer people and even less money. You have to\nbe even faster, and you can get away with being more informal.\nYou can literally launch your product as three guys sitting in the\nliving room of an apartment, and a server collocated at an ISP.\nWe did.Over time the teams have gotten smaller, faster, and more informal.\nIn 1960, software development meant a roomful of men with horn\nrimmed glasses and narrow black neckties, industriously writing\nten lines of code a day on IBM coding forms. In 1980, it was a\nteam of eight to ten people wearing jeans to the office and typing\ninto vt100s. Now it's a couple of guys sitting in a living room\nwith laptops. (And jeans turn out not to be the last word in\ninformality.)Startups are stressful, and this, unfortunately, is also taken to\nan extreme with Web-based applications. \nMany software companies, especially at the beginning, have periods\nwhere the developers slept under their desks and so on. The alarming\nthing about Web-based software is that there is nothing to prevent\nthis becoming the default. The stories about sleeping under desks\nusually end: then at last we shipped it and we all went home and\nslept for a week. Web-based software never ships. You can work\n16-hour days for as long as you want to. And because you can, and\nyour competitors can, you tend to be forced to. You can, so you\nmust. It's Parkinson's Law running in reverse.The worst thing is not the hours but the responsibility. Programmers\nand system administrators traditionally each have their own separate\nworries. Programmers have to worry about bugs, and system\nadministrators have to worry about infrastructure. Programmers\nmay spend a long day up to their elbows in source code, but at some\npoint they get to go home and forget about it. System administrators\nnever quite leave the job behind, but when they do get paged at\n4:00 AM, they don't usually have to do anything very complicated.\nWith Web-based applications, these two kinds of stress get combined.\nThe programmers become system administrators, but without the\nsharply defined limits that ordinarily make the job bearable.At Viaweb we spent the first six months just writing software. We\nworked the usual long hours of an early startup. In a desktop\nsoftware company, this would have been the part where we were\nworking hard, but it felt like a vacation compared to the next\nphase, when we took users onto our server. The second biggest\nbenefit of selling Viaweb to Yahoo (after the money) was to be able\nto dump ultimate responsibility for the whole thing onto the\nshoulders of a big company.Desktop software forces users to become system administrators.\nWeb-based software forces programmers to. There is less stress in\ntotal, but more for the programmers. That's not necessarily bad\nnews. If you're a startup competing with a big company, it's good\nnews. [15] Web-based applications offer a straightforward way to\noutwork your competitors. No startup asks for more.Just Good EnoughOne thing that might deter you from writing Web-based applications\nis the lameness of Web pages as a UI. That is a problem, I admit.\nThere were a few things we would have really liked to add to\nHTML and HTTP. What matters, though, is that Web pages are just\ngood enough.There is a parallel here with the first microcomputers. The\nprocessors in those machines weren't actually intended to be the\nCPUs of computers. They were designed to be used in things like\ntraffic lights. But guys like Ed Roberts, who designed the \nAltair,\nrealized that they were just good enough. You could combine one\nof these chips with some memory (256 bytes in the first Altair),\nand front panel switches, and you'd have a working computer. Being\nable to have your own computer was so exciting that there were\nplenty of people who wanted to buy them, however limited.Web pages weren't designed to be a UI for applications, but they're\njust good enough. And for a significant number of users, software\nthat you can use from any browser will be enough of a win in itself\nto outweigh any awkwardness in the UI. Maybe you can't write the\nbest-looking spreadsheet using HTML, but you can write a spreadsheet\nthat several people can use simultaneously from different locations\nwithout special client software, or that can incorporate live data\nfeeds, or that can page you when certain conditions are triggered.\nMore importantly, you can write new kinds of applications that\ndon't even have names yet. VisiCalc was not merely a microcomputer\nversion of a mainframe application, after all-- it was a new type\nof application.Of course, server-based applications don't have to be Web-based.\nYou could have some other kind of client. But I'm pretty sure\nthat's a bad idea. It would be very convenient if you could assume\nthat everyone would install your client-- so convenient that you\ncould easily convince yourself that they all would-- but if they\ndon't, you're hosed. Because Web-based software assumes nothing\nabout the client, it will work anywhere the Web works. That's a\nbig advantage already, and the advantage will grow as new Web\ndevices proliferate. Users will like you because your software\njust works, and your life will be easier because you won't have to\ntweak it for every new client. [16]I feel like I've watched the evolution of the Web as closely as\nanyone, and I can't predict what's going to happen with clients.\nConvergence is probably coming, but where? I can't pick a winner.\nOne thing I can predict is conflict between AOL and Microsoft.\nWhatever Microsoft's .NET turns out to be, it will probably involve\nconnecting the desktop to servers. Unless AOL fights back, they\nwill either be pushed aside or turned into a pipe between Microsoft\nclient and server software. If Microsoft and AOL get into a client\nwar, the only thing sure to work on both will be browsing the Web,\nmeaning Web-based applications will be the only kind that work\neverywhere.How will it all play out? I don't know. And you don't have to\nknow if you bet on Web-based applications. No one can break that\nwithout breaking browsing. The Web may not be the only way to\ndeliver software, but it's one that works now and will continue to\nwork for a long time. Web-based applications are cheap to develop,\nand easy for even the smallest startup to deliver. They're a lot\nof work, and of a particularly stressful kind, but that only makes\nthe odds better for startups.Why Not?E. B. White was amused to learn from a farmer friend that many\nelectrified fences don't have any current running through them.\nThe cows apparently learn to stay away from them, and after that\nyou don't need the current. \"Rise up, cows!\" he wrote, \"Take your\nliberty while despots snore!\"If you're a hacker who has thought of one day starting a startup,\nthere are probably two things keeping you from doing it. One is\nthat you don't know anything about business. The other is that\nyou're afraid of competition. Neither of these fences have any\ncurrent in them.There are only two things you have to know about business: build\nsomething users love, and make more than you spend. If you get\nthese two right, you'll be ahead of most startups. You can figure\nout the rest as you go.You may not at first make more than you spend, but as long as the\ngap is closing fast enough you'll be ok. If you start out underfunded,\nit will at least encourage a habit of frugality. The less you\nspend, the easier it is to make more than you spend. Fortunately,\nit can be very cheap to launch a Web-based application. We launched\non under $10,000, and it would be even cheaper today. We had to\nspend thousands on a server, and thousands more to get SSL. (The\nonly company selling SSL software at the time was Netscape.) Now\nyou can rent a much more powerful server, with SSL included, for\nless than we paid for bandwidth alone. You could launch a Web-based\napplication now for less than the cost of a fancy office chair.As for building something users love, here are some general tips.\nStart by making something clean and simple that you would want to\nuse yourself. Get a version 1.0 out fast, then continue to improve\nthe software, listening closely to the users as you do. The customer\nis always right, but different customers are right about different\nthings; the least sophisticated users show you what you need to\nsimplify and clarify, and the most sophisticated tell you what\nfeatures you need to add. The best thing software can be is easy,\nbut the way to do this is to get the defaults right, not to limit\nusers' choices. Don't get complacent if your competitors' software\nis lame; the standard to compare your software to is what it could\nbe, not what your current competitors happen to have. Use your\nsoftware yourself, all the time. Viaweb was supposed to be an\nonline store builder, but we used it to make our own site too.\nDon't listen to marketing people or designers or product managers\njust because of their job titles. If they have good ideas, use\nthem, but it's up to you to decide; software has to be designed by\nhackers who understand design, not designers who know a little\nabout software. If you can't design software as well as implement\nit, don't start a startup.Now let's talk about competition. What you're afraid of is not\npresumably groups of hackers like you, but actual companies, with\noffices and business plans and salesmen and so on, right? Well,\nthey are more afraid of you than you are of them, and they're right.\nIt's a lot easier for a couple of hackers to figure out how to rent\noffice space or hire sales people than it is for a company of any\nsize to get software written. I've been on both sides, and I know.\nWhen Viaweb was bought by Yahoo, I suddenly found myself working\nfor a big company, and it was like trying to run through waist-deep\nwater.I don't mean to disparage Yahoo. They had some good hackers, and\nthe top management were real butt-kickers. For a big company, they\nwere exceptional. But they were still only about a tenth as\nproductive as a small startup. No big company can do much better\nthan that. What's scary about Microsoft is that a company so\nbig can develop software at all. They're like a mountain that\ncan walk.Don't be intimidated. You can do as much that Microsoft can't as\nthey can do that you can't. And no one can stop you. You don't\nhave to ask anyone's permission to develop Web-based applications.\nYou don't have to do licensing deals, or get shelf space in retail\nstores, or grovel to have your application bundled with the OS.\nYou can deliver software right to the browser, and no one can get\nbetween you and potential users without preventing them from browsing\nthe Web.You may not believe it, but I promise you, Microsoft is scared of\nyou. The complacent middle managers may not be, but Bill is,\nbecause he was you once, back in 1975, the last time a new way of\ndelivering software appeared.Notes[1] Realizing that much of the money is in the services, companies\nbuilding lightweight clients have usually tried to combine the\nhardware with an \nonline service. \n This approach has not worked\nwell, partly because you need two different kinds of companies to\nbuild consumer electronics and to run an online service, and partly\nbecause users hate the idea. Giving away the razor and making\nmoney on the blades may work for Gillette, but a razor is much\nsmaller commitment than a Web terminal. Cell phone handset makers\nare satisfied to sell hardware without trying to capture the service\nrevenue as well. That should probably be the model for Internet\nclients too. If someone just sold a nice-looking little box with\na Web browser that you could use to connect through any ISP, every\ntechnophobe in the country would buy one.[2] Security always depends more on not screwing up than any design\ndecision, but the nature of server-based software will make developers\npay more attention to not screwing up. Compromising a server could\ncause such damage that ASPs (that want to stay in business) are\nlikely to be careful about security.[3] In 1995, when we started Viaweb, Java applets were supposed to\nbe the technology everyone was going to use to develop server-based\napplications. Applets seemed to us an old-fashioned idea. Download\nprograms to run on the client? Simpler just to go all the way and\nrun the programs on the server. We wasted little time\non applets, but countless other startups must have been lured into\nthis tar pit. Few can have escaped alive, or Microsoft could not\nhave gotten away with dropping Java in the most recent version of\nExplorer.[4] This point is due to Trevor Blackwell, who adds \"the cost of\nwriting software goes up more than linearly with its size. Perhaps\nthis is mainly due to fixing old bugs, and the cost can be more\nlinear if all bugs are found quickly.\"[5] The hardest kind of bug to find may be a variant of compound\nbug where one bug happens to compensate for another. When you fix\none bug, the other becomes visible. But it will seem as if the\nfix is at fault, since that was the last thing you changed.[6] Within Viaweb we once had a contest to describe the worst thing\nabout our software. Two customer support people tied for first\nprize with entries I still shiver to recall. We fixed both problems\nimmediately.[7] Robert Morris wrote the ordering system, which shoppers used\nto place orders. Trevor Blackwell wrote the image generator and\nthe manager, which merchants used to retrieve orders, view statistics,\nand configure domain names etc. I wrote the editor, which merchants\nused to build their sites. The ordering system and image generator\nwere written in C and C++, the manager mostly in Perl, and the editor\nin Lisp.[8] Price discrimination is so pervasive (how often have you heard\na retailer claim that their buying power meant lower prices for\nyou?) that I was surprised to find it was outlawed in the U.S. by\nthe Robinson-Patman Act of 1936. This law does not appear to be\nvigorously enforced.[9] In No Logo, Naomi Klein says that clothing brands favored by\n\"urban youth\" do not try too hard to prevent shoplifting because\nin their target market the shoplifters are also the fashion leaders.[10] Companies often wonder what to outsource and what not to.\nOne possible answer: outsource any job that's not directly exposed\nto competitive pressure, because outsourcing it will thereby expose\nit to competitive pressure.[11] The two guys were Dan Bricklin and Bob Frankston. Dan wrote\na prototype in Basic in a couple days, then over the course of the\nnext year they worked together (mostly at night) to make a more\npowerful version written in 6502 machine language. Dan was at\nHarvard Business School at the time and Bob nominally had a day\njob writing software. \"There was no great risk in doing a business,\"\nBob wrote, \"If it failed it failed. No big deal.\"[12] It's not quite as easy as I make it sound. It took a painfully\nlong time for word of mouth to get going, and we did not start to\nget a lot of press coverage until we hired a \nPR firm \n(admittedly\nthe best in the business) for $16,000 per month. However, it was\ntrue that the only significant channel was our own Web site.[13] If the Mac was so great, why did it lose? Cost, again.\nMicrosoft concentrated on the software business, and unleashed a\nswarm of cheap component suppliers on Apple hardware. It did not\nhelp, either, that suits took over during a critical period.[14] One thing that would help Web-based applications, and help\nkeep the next generation of software from being overshadowed by\nMicrosoft, would be a good open-source browser. Mozilla is\nopen-source but seems to have suffered from having been corporate\nsoftware for so long. A small, fast browser that was actively\nmaintained would be a great thing in itself, and would probably\nalso encourage companies to build little Web appliances.Among other things, a proper open-source browser would cause HTTP\nand HTML to continue to evolve (as e.g. Perl has). It would help\nWeb-based applications greatly to be able to distinguish between\nselecting a link and following it; all you'd need to do this would\nbe a trivial enhancement of HTTP, to allow multiple urls in a\nrequest. Cascading menus would also be good.If you want to change the world, write a new Mosaic. Think it's\ntoo late? In 1998 a lot of people thought it was too late to launch\na new search engine, but Google proved them wrong. There is always\nroom for something new if the current options suck enough. Make\nsure it works on all the free OSes first-- new things start with\ntheir users.[15] Trevor Blackwell, who probably knows more about this from\npersonal experience than anyone, writes:\"I would go farther in saying that because server-based software\nis so hard on the programmers, it causes a fundamental economic\nshift away from large companies. It requires the kind of intensity\nand dedication from programmers that they will only be willing to\nprovide when it's their own company. Software companies can hire\nskilled people to work in a not-too-demanding environment, and can\nhire unskilled people to endure hardships, but they can't hire\nhighly skilled people to bust their asses. Since capital is no\nlonger needed, big companies have little to bring to the table.\"[16] In the original version of this essay, I advised avoiding\nJavascript. That was a good plan in 2001, but Javascript now works.\nThanks to Sarah Harlin, Trevor Blackwell, Robert Morris, Eric Raymond, Ken Anderson,\nand Dan Giffin for reading drafts of this paper; to Dan Bricklin and\nBob Frankston for information about VisiCalc; and again to Ken Anderson\nfor inviting me to speak at BBN.\n\nYou'll find this essay and 14 others in\nHackers & Painters.\n" }, { "path": "data/PaulGrahamEssays/ronco.txt", "content": "January 2015No one, VC or angel, has invested in more of the top startups than\nRon Conway. He knows what happened in every deal in the Valley,\nhalf the time because he arranged it.And yet he's a super nice guy. In fact, nice is not the word.\nRonco is good. I know of zero instances in which he has behaved\nbadly. It's hard even to imagine.When I first came to Silicon Valley I thought \"How lucky that someone\nso powerful is so benevolent.\" But gradually I realized it wasn't\nluck. It was by being benevolent that Ronco became so powerful.\nAll the deals he gets to invest in come to him through referrals.\nGoogle did. Facebook did. Twitter was a referral from Evan Williams\nhimself. And the reason so many people refer deals to him is that\nhe's proven himself to be a good guy.Good does not mean being a pushover. I would not want to face an\nangry Ronco. But if Ron's angry at you, it's because you did\nsomething wrong. Ron is so old school he's Old Testament. He will\nsmite you in his just wrath, but there's no malice in it.In almost every domain there are advantages to seeming good. It\nmakes people trust you. But actually being good is an expensive\nway to seem good. To an amoral person it might seem to be overkill.In some fields it might be, but apparently not in the startup world.\nThough plenty of investors are jerks, there is a clear trend among\nthem: the most successful investors are also the most upstanding. \n[1]It was not always this way. I would not feel confident saying that\nabout investors twenty years ago.What changed? The startup world became more transparent and more\nunpredictable. Both make it harder to seem good without actually\nbeing good.It's obvious why transparency has that effect. When an investor\nmaltreats a founder now, it gets out. Maybe not all the way to the\npress, but other founders hear about it, and that investor\nstarts to lose deals. \n[2]The effect of unpredictability is more subtle. It increases the\nwork of being inconsistent. If you're going to be two-faced, you\nhave to know who you should be nice to and who you can get away\nwith being nasty to. In the startup world, things change so rapidly\nthat you can't tell. The random college kid you talk to today might\nin a couple years be the CEO of the hottest startup in the Valley.\nIf you can't tell who to be nice to, you have to be nice to everyone.\nAnd probably the only people who can manage that are the people who\nare genuinely good.In a sufficiently connected and unpredictable world, you can't seem\ngood without being good.As often happens, Ron discovered how to be the investor of the\nfuture by accident. He didn't foresee the future of startup\ninvesting, realize it would pay to be upstanding, and force himself\nto behave that way. It would feel unnatural to him to behave any\nother way. He was already \nliving in the future.Fortunately that future is not limited to the startup world. The\nstartup world is more transparent and unpredictable than most, but\nalmost everywhere the trend is in that direction.Notes[1]\nI'm not saying that if you sort investors by benevolence\nyou've also sorted them by returns, but rather that if you do a\nscatterplot with benevolence on the x axis and returns on the y,\nyou'd see a clear upward trend.[2]\nY Combinator in particular, because it aggregates data\nfrom so many startups, has a pretty comprehensive view of\ninvestor behavior.\nThanks to Sam Altman and Jessica Livingston for reading drafts of\nthis." }, { "path": "data/PaulGrahamEssays/rootsoflisp.txt", "content": "May 2001\n\n(I wrote this article to help myself understand exactly\nwhat McCarthy discovered. You don't need to know this stuff\nto program in Lisp, but it should be helpful to \nanyone who wants to\nunderstand the essence of Lisp — both in the sense of its\norigins and its semantic core. The fact that it has such a core\nis one of Lisp's distinguishing features, and the reason why,\nunlike other languages, Lisp has dialects.)In 1960, John \nMcCarthy published a remarkable paper in\nwhich he did for programming something like what Euclid did for\ngeometry. He showed how, given a handful of simple\noperators and a notation for functions, you can\nbuild a whole programming language.\nHe called this language Lisp, for \"List Processing,\"\nbecause one of his key ideas was to use a simple\ndata structure called a list for both\ncode and data.It's worth understanding what McCarthy discovered, not\njust as a landmark in the history of computers, but as\na model for what programming is tending to become in\nour own time. It seems to me that there have been\ntwo really clean, consistent models of programming so\nfar: the C model and the Lisp model.\nThese two seem points of high ground, with swampy lowlands\nbetween them. As computers have grown more powerful,\nthe new languages being developed have been moving\nsteadily toward the Lisp model. A popular recipe\nfor new programming languages in the past 20 years \nhas been to take the C model of computing and add to\nit, piecemeal, parts taken from the Lisp model,\nlike runtime typing and garbage collection.In this article I'm going to try to explain in the\nsimplest possible terms what McCarthy discovered.\nThe point is not just to learn about an interesting\ntheoretical result someone figured out forty years ago,\nbut to show where languages are heading.\nThe unusual thing about Lisp — in fact, the defining\nquality of Lisp — is that it can be written in\nitself. To understand what McCarthy meant by this,\nwe're going to retrace his steps, with his mathematical\nnotation translated into running Common Lisp code." }, { "path": "data/PaulGrahamEssays/rss.txt", "content": "Aaron Swartz created a scraped\nfeed\nof the essays page." }, { "path": "data/PaulGrahamEssays/safe.txt", "content": "August 2015I recently got an email from a founder that helped me understand\nsomething important: why it's safe for startup founders to be nice\npeople.I grew up with a cartoon idea of a very successful businessman (in\nthe cartoon it was always a man): a rapacious, cigar-smoking,\ntable-thumping guy in his fifties who wins by exercising power, and\nisn't too fussy about how. As I've written before, one of\nthe things that has surprised me most about startups is \nhow few of\nthe most successful founders are like that. Maybe successful people\nin other industries are; I don't know; but not startup founders.\n[1]I knew this empirically, but I never saw the math of why till I got\nthis founder's email. In it he said he worried that he was\nfundamentally soft-hearted and tended to give away too much for\nfree. He thought perhaps he needed \"a little dose of sociopath-ness.\"I told him not to worry about it, because so long as he built\nsomething good enough to spread by word of mouth, he'd have a\nsuperlinear growth curve. If he was bad at extracting money from\npeople, at worst this curve would be some constant multiple less\nthan 1 of what it might have been. But a constant multiple of any\ncurve is exactly the same shape. The numbers on the Y axis are\nsmaller, but the curve is just as steep, and when anything grows\nat the rate of a successful startup, the Y axis will take care of\nitself.Some examples will make this clear. Suppose your company is making\n$1000 a month now, and you've made something so great that it's\ngrowing at 5% a week. Two years from now, you'll be making about\n$160k a month.Now suppose you're so un-rapacious that you only extract half as\nmuch from your users as you could. That means two years later\nyou'll be making $80k a month instead of $160k. How far behind are\nyou? How long will it take to catch up with where you'd have been\nif you were extracting every penny? A mere 15 weeks. After two\nyears, the un-rapacious founder is only 3.5 months behind the\nrapacious one. \n[2]If you're going to optimize a number, the one to choose is your\ngrowth rate. Suppose as before that you only extract half as much\nfrom users as you could, but that you're able to grow 6% a week\ninstead of 5%. Now how are you doing compared to the rapacious\nfounder after two years? You're already ahead—$214k a month\nversus $160k—and pulling away fast. In another year you'll be\nmaking $4.4 million a month to the rapacious founder's $2 million.Obviously one case where it would help to be rapacious is when\ngrowth depends on that. What makes startups different is that\nusually it doesn't. Startups usually win by making something so\ngreat that people recommend it to their friends. And being rapacious\nnot only doesn't help you do that, but probably hurts. \n[3]The reason startup founders can safely be nice is that making great\nthings is compounded, and rapacity isn't.So if you're a founder, here's a deal you can make with yourself\nthat will both make you happy and make your company successful.\nTell yourself you can be as nice as you want, so long as you work\nhard on your growth rate to compensate. Most successful startups\nmake that tradeoff unconsciously. Maybe if you do it consciously\nyou'll do it even better.Notes[1]\nMany think successful startup founders are driven by money.\nIn fact the secret weapon of the most successful founders is that\nthey aren't. If they were, they'd have taken one of the acquisition\noffers that every fast-growing startup gets on the way up. What\ndrives the most successful founders is the same thing that drives\nmost people who make things: the company is their project.[2]\nIn fact since 2 ≈ 1.05 ^ 15, the un-rapacious founder is\nalways 15 weeks behind the rapacious one.[3]\nThe other reason it might help to be good at squeezing money\nout of customers is that startups usually lose money at first, and\nmaking more per customer makes it easier to get to profitability\nbefore your initial funding runs out. But while it is very common\nfor startups to die\nfrom running through their initial funding and then being unable\nto raise more, the underlying cause is usually slow growth or\nexcessive spending rather than insufficient effort to extract money\nfrom existing customers.Thanks to Sam Altman, Harj Taggar, Jessica Livingston, and\nGeoff Ralston for reading drafts of this, and to Randall Bennett\nfor being such a nice guy." }, { "path": "data/PaulGrahamEssays/say.txt", "content": "January 2004\nHave you ever seen an old photo of yourself and\nbeen embarrassed at the way you looked? Did we actually\ndress like that? We did. And we had no idea how\nsilly we looked.\nIt's the nature of fashion to be invisible, in the\nsame way the movement of the earth is invisible to all\nof us riding on it.What scares me is that there are moral fashions too.\nThey're just as arbitrary, and just as invisible to most people.\nBut they're much more dangerous.\nFashion is mistaken for good design; \nmoral fashion is mistaken for good.\nDressing oddly gets you laughed at. Violating\nmoral fashions can get you fired, ostracized, imprisoned, or\neven killed.If you could travel back in a time machine, one thing\nwould be true no matter where you went: you'd have to watch\nwhat you said. \nOpinions we consider harmless could have \ngotten you in big trouble.\nI've already said at least one thing that would have gotten me in big\ntrouble in most of Europe in the seventeenth century,\nand did get Galileo in big trouble when he said\nit — that the earth moves. [1]\nIt seems to be a constant throughout history: In every\nperiod, people believed things that were just ridiculous,\nand believed them so strongly that you would have gotten in\nterrible trouble for saying otherwise.Is our time any different?\nTo anyone who has read any amount of history, the answer is\nalmost certainly no. It would be a remarkable coincidence if ours\nwere the first era to get everything just right.It's tantalizing to think we believe\nthings that people in the future will find ridiculous.\nWhat would someone coming back to visit us in a time machine\nhave to be careful not to say?\nThat's what I want to study here.\nBut\nI want to do more than just shock everyone with\nthe heresy du jour. I want to find general\nrecipes for discovering what you can't say, in any era.The Conformist TestLet's start with a test: \nDo you have any opinions that you would be reluctant to express\nin front of a group of your peers?If the answer is no,\nyou might want to stop and think about that. If everything\nyou believe is something you're supposed to believe, could\nthat possibly be a coincidence? Odds are it isn't. Odds are\nyou just think what you're told.The other alternative would be that you independently considered\nevery question and came up with the exact same answers that\nare now considered acceptable. That seems unlikely, because\nyou'd also have to make the same mistakes. Mapmakers\ndeliberately put slight mistakes in their maps so they can\ntell when someone copies them. If another map has the same\nmistake, that's very convincing evidence.Like every other era in history, our moral map almost certainly\ncontains a few mistakes. And anyone who makes the same mistakes\nprobably didn't do it by accident. It would be\nlike someone claiming they had independently decided in\n1972 that bell-bottom jeans were a good idea.If you believe everything you're supposed to now, how can\nyou be sure you wouldn't also have believed everything you\nwere supposed to if you had grown up among the plantation\nowners of the pre-Civil War South, or in Germany in the 1930s — or\namong the Mongols in 1200, for that matter? Odds are you\nwould have.Back in the era of terms like \"well-adjusted,\" the idea\nseemed to be that there was something wrong with\nyou if you thought things you didn't dare say out loud.\nThis seems backward. Almost certainly, there\nis something wrong with you if you don't think things\nyou don't dare say out loud.TroubleWhat can't we say? One way to find these ideas is simply to look\nat things people do say, and get in trouble for. [2]Of course, we're not just looking for things we can't say. \nWe're looking for things we can't say that are true, or at least\nhave enough chance of being true that the question\nshould remain open. But many of the\nthings people get in trouble for saying probably\ndo make it over this second, lower threshold. No one\ngets in trouble for saying\nthat 2 + 2 is 5, or that people in Pittsburgh are ten feet tall.\nSuch obviously false statements might be treated as jokes, or\nat worst as evidence of insanity, but they are not likely to\nmake anyone mad. The statements that make people mad are\nthe ones they worry might be believed.\nI suspect the statements that make people maddest\nare those they worry might be true.If Galileo had said that people in Padua were ten feet tall,\nhe would have been regarded as a harmless eccentric. Saying \nthe earth orbited the sun was another matter. The church knew\nthis would set people thinking.Certainly, as we look back on the past, this rule of thumb works\nwell. A lot of the statements people got in trouble for seem\nharmless now. So it's likely that visitors from the\nfuture would agree with at least some of the statements that\nget people in trouble today. Do we have no Galileos? Not\nlikely.To find them,\nkeep track of opinions that get\npeople in trouble, and start asking, could this be true?\nOk, it may be heretical (or whatever modern equivalent), but\nmight it also be true?HeresyThis won't get us all the answers, though. What if no one\nhappens to have gotten in trouble for a particular idea yet?\nWhat if some idea would be so radioactively controversial that\nno one would dare express it in public? How can we find these too?Another approach is to follow that word, heresy. In every period\nof history, there seem to have been labels that got applied to \nstatements to shoot them down before anyone had a chance to ask\nif they were true or not. \"Blasphemy\", \"sacrilege\", and \"heresy\"\nwere such\nlabels for a good part of western history, as in more recent times\n\"indecent\", \"improper\", and \"unamerican\" have been. By now these\nlabels have lost their sting. They always do.\nBy now they're mostly used ironically.\nBut in their time,\nthey had real force.The word \"defeatist\", for example, has no particular political\nconnotations now.\nBut in Germany in 1917 it was a weapon, used by Ludendorff in\na purge of those who favored a negotiated peace.\nAt the start of World War II it was used\nextensively by Churchill and his supporters to silence their\nopponents.\nIn 1940, any argument against Churchill's aggressive policy was \"defeatist\".\nWas it right or wrong? Ideally, no one got far enough to ask\nthat.\nWe have such labels today, of course, quite a lot of them,\nfrom the all-purpose \"inappropriate\" to the dreaded \"divisive.\"\nIn any period, it should be easy to figure out what such labels are,\nsimply by looking at what people call ideas they disagree\nwith besides untrue. When a politician says his opponent is\nmistaken, that's a straightforward criticism, but when he\nattacks a statement as \"divisive\" or \"racially insensitive\"\ninstead of arguing that it's false, we should start paying\nattention.So another way to figure out which of our taboos future generations\nwill laugh at is to start with the\nlabels. Take a label — \"sexist\", for example — and try to think\nof some ideas that would be called that. Then for each ask, might\nthis be true?Just start listing ideas at random? Yes, because they\nwon't really be random. The ideas that come to mind first\nwill be the most plausible ones. They'll be things you've already \nnoticed but didn't let yourself think.In 1989 some clever researchers tracked\nthe eye movements of radiologists as they scanned chest images for\nsigns of lung cancer. [3] They found that even when the radiologists\nmissed a cancerous lesion, their eyes had usually paused at the site of it.\nPart of their brain knew there was something there; it just\ndidn't percolate all the way up into conscious knowledge. \nI think many interesting heretical thoughts are already mostly \nformed in our minds. If we turn off our self-censorship\ntemporarily, those will be the first to emerge.Time and SpaceIf we could look into the future it would be obvious which\nof our taboos they'd laugh at.\nWe can't do that, but we can do something almost as good: we can\nlook into the past. Another way to figure out what we're\ngetting wrong is to look at what used to be acceptable\nand is now unthinkable.Changes between the past and the present sometimes do represent\nprogress. In a field like physics,\nif we disagree with past generations it's because we're\nright and they're wrong. But this becomes rapidly less true as \nyou move away from the certainty of the hard sciences. By the time\nyou get to social questions, many changes are just fashion.\nThe age of consent fluctuates like hemlines.We may imagine that we are a great deal smarter and more virtuous than\npast generations, but the more history you read, the less likely\nthis seems. People in past times were much like us. Not heroes,\nnot barbarians. Whatever their ideas were, they were ideas\nreasonable people could believe.So here is another source of interesting heresies. Diff present\nideas against those of various past cultures, and see what you \nget. [4]\nSome will be\nshocking by present standards. Ok, fine; but which might also be true?You don't have to look into the past to find big differences. \nIn our own time, different societies have wildly varying ideas\nof what's ok and what isn't.\nSo you can try diffing other cultures' ideas against ours as well.\n(The best way to do that is to visit them.)\n\nAny idea that's considered harmless in a significant\npercentage of times and places, and yet is taboo in ours,\nis a candidate for something we're mistaken\nabout.For example, at the high water mark of political correctness\nin the early 1990s, Harvard distributed to its\nfaculty and staff a brochure saying, among other things, that it\nwas inappropriate to compliment a colleague or student's\nclothes. No more \"nice shirt.\"\nI think this principle is rare among the world's cultures, past or present.\nThere are probably more where it's considered especially\npolite to compliment someone's clothing than where it's considered\nimproper.\n\nOdds are this is, in a mild form, an example of one of\nthe taboos a visitor from the future would\nhave to be careful to avoid if he happened to set his time machine for\nCambridge, Massachusetts, 1992. [5]PrigsOf course, if they have time machines in the future they'll\nprobably have a separate reference manual just for Cambridge.\nThis has always been a fussy place, a town of i dotters and\nt crossers, where you're liable to get both your grammar and \nyour ideas corrected in the same conversation. And that\nsuggests another way to find taboos. Look for prigs,\nand see what's inside their heads.Kids' heads are repositories of all our taboos.\nIt seems fitting to us that kids' ideas should be bright and clean.\nThe picture we give them of the world is \nnot merely simplified, to suit their developing minds, \nbut sanitized as well, to suit our\nideas of what kids ought to think. [6]You can see this on a small scale in the matter of\ndirty words. A lot of my friends are starting to have children\nnow, and they're all trying \nnot to use words like\n\"fuck\" and \"shit\" within baby's hearing, lest baby start using \nthese words too.\nBut these\nwords are part of the language, and adults use them all the\ntime. So parents are giving their kids an inaccurate idea of \nthe language by not using\nthem. Why do they do this? Because they don't think it's\nfitting that kids should use the whole language. We like\nchildren to seem innocent. [7]Most adults, likewise, deliberately give kids a misleading\nview of the world.\nOne of the most obvious\nexamples is Santa Claus. We think it's cute for little kids to\nbelieve in Santa Claus. I myself think it's cute for little\nkids to believe in Santa Claus. But one wonders, do we tell\nthem this stuff for their sake, or for ours?I'm not arguing for or against this idea here. It is probably\ninevitable that parents should want to dress up their kids'\nminds in cute little baby outfits. I'll probably do it myself.\nThe important thing for our purposes is that, as a result,\na well brought-up teenage kid's brain is a more\nor less complete collection of all our taboos — and in mint\ncondition, because they're untainted by experience. \nWhatever we think that will later turn out to be ridiculous, \nit's almost certainly inside that head.How do we get at these ideas? By the following thought experiment.\nImagine a kind of latter-day Conrad character\nwho has worked for a time as a mercenary in Africa, for a time\nas a doctor in Nepal, for a time as the manager of a\nnightclub in Miami. The specifics don't matter — just\nsomeone who has\nseen a lot. Now imagine comparing what's inside this guy's head\nwith what's inside the head\nof a well-behaved sixteen year old girl from\nthe suburbs. What does he think that\nwould shock her?\nHe knows the world; she knows, or at least embodies, present\ntaboos. Subtract one from the other, and the result is what\nwe can't say.\nMechanismI can think of one more way to figure out what we can't\nsay: to look at how taboos are created. How do moral\nfashions arise, and why are they adopted?\nIf we can understand this mechanism, we\nmay be able to see it at work in our own time.Moral fashions don't seem to be created the way ordinary\nfashions are. Ordinary fashions seem to arise by accident when\neveryone imitates the whim of some influential person.\nThe fashion for broad-toed shoes in\nlate fifteenth century Europe began because Charles VIII of\nFrance had six toes on one foot. The fashion for the\nname Gary began when the actor Frank Cooper adopted the name\nof a tough mill town in Indiana. Moral fashions more often\nseem to be created deliberately. When there's something we\ncan't say, it's often because some group doesn't want us to.The prohibition will be strongest when the group is nervous. \nThe irony of Galileo's situation was that he got in trouble\nfor repeating Copernicus's ideas. Copernicus himself didn't.\nIn fact, Copernicus was a canon of a cathedral, and dedicated his\nbook to the pope. But by Galileo's time the church was in\nthe throes of the Counter-Reformation and was much more\nworried about unorthodox ideas.To launch a taboo, a group has to be poised halfway between\nweakness and power. A confident group doesn't need taboos\nto protect it. It's not considered improper to\nmake disparaging remarks about Americans, or the English.\nAnd yet a group has to be powerful enough to enforce a\ntaboo. Coprophiles, as of this writing, don't seem to be\nnumerous or energetic enough to have had their\ninterests promoted to a lifestyle.I suspect the biggest source of moral taboos will turn out to\nbe power struggles in which one side only barely has\nthe upper hand. That's where you'll find a group\npowerful enough to enforce taboos, but weak enough to need them.Most struggles, whatever they're really about, will be cast\nas struggles between competing ideas.\nThe English Reformation was at bottom a struggle for wealth and power,\nbut it ended up being\ncast as a struggle to preserve the souls\nof Englishmen from the corrupting influence of Rome.\nIt's easier to get people to fight for an idea.\nAnd whichever side wins, their\nideas will also be considered to have triumphed, as if God\nwanted to signal his agreement by selecting that side as the victor.We often like to think of World War II as a triumph\nof freedom over totalitarianism. We conveniently forget that\nthe Soviet Union was also one of the winners.I'm not saying that struggles are never about ideas,\njust that they will always be made to seem to be about\nideas, whether they are or not. And just as there is nothing\nso unfashionable as the last, discarded fashion, there is\nnothing so wrong as the principles of the most recently\ndefeated opponent.\n\nRepresentational art is only now\nrecovering from the approval of both Hitler and Stalin. [8]Although moral fashions tend to arise from different sources\nthan fashions in clothing, the mechanism of their adoption seems\nmuch the same. The early adopters will be driven by ambition:\nself-consciously cool people who want to distinguish themselves\nfrom the common herd. As the fashion becomes established they'll\nbe joined by a second, much larger group, driven by fear. [9] This\nsecond group adopt the fashion not because they want to stand\nout but because they are afraid of standing out.So if you want to figure out what we can't say, look at the\nmachinery of fashion and try to predict what it would make\nunsayable. What groups are powerful but nervous, and what\nideas would they like to suppress? What ideas were tarnished by\nassociation when they ended up on the losing side of a recent\nstruggle? If a self-consciously cool person wanted to differentiate\nhimself from preceding fashions (e.g. from his parents), \nwhich of their ideas would he tend to reject?\nWhat are conventional-minded people afraid of saying?This technique won't find us all the things we can't say.\nI can think of some that aren't the result of\nany recent struggle. Many of our taboos are rooted\ndeep in the past. But this approach, combined with the\npreceding four, will turn up a good number of unthinkable\nideas.WhySome would ask, why would one want to do this? Why deliberately\ngo poking around among nasty, disreputable ideas? Why look \nunder rocks?I do it, first of all, for the same reason I did look under\nrocks as a kid: plain curiosity. And I'm especially curious about\nanything that's forbidden. Let me see and decide for myself.Second, I do it because I don't like the idea of being mistaken.\nIf, like other eras, we believe things that will later seem ridiculous,\nI want to know what they are so that I, at least, can avoid\nbelieving them.Third, I do it because it's good for the brain. To do good work\nyou need a brain that can go anywhere. And you especially need a\nbrain that's in the habit of going where it's not supposed to.Great work tends to grow out of ideas\nthat others have overlooked, and no idea is so overlooked as one that's\nunthinkable.\nNatural selection, for example.\nIt's so simple. Why didn't anyone think of it before? Well,\nthat is all too obvious. Darwin himself was careful to tiptoe\naround the implications of his theory. He wanted to spend his\ntime thinking about biology, not arguing with people who accused\nhim of being an atheist.In the sciences, especially, it's a great advantage to be able to\nquestion assumptions.\nThe m.o. of scientists, or at least of the\ngood ones, is precisely that: look for places where\nconventional wisdom is broken, and then try to pry apart the\ncracks and see what's underneath. That's where new theories come\nfrom.A good scientist, in other words, does not merely ignore\nconventional wisdom, but makes a special effort to break it.\nScientists go looking for trouble.\nThis should be the m.o. of any scholar, but \nscientists seem much more willing to look under rocks. [10]Why? It could\nbe that the scientists are simply smarter; most physicists could,\nif necessary, make it through a PhD program in French literature,\nbut few professors of French literature could make it through\na PhD program in physics. Or it could be because it's clearer\nin the sciences whether theories are true or false, and this\nmakes scientists bolder. (Or it could be that, because it's\nclearer in the sciences whether theories are true or false, you\nhave to be smart to get jobs as a scientist, rather than just a\ngood politician.)Whatever the reason, there seems a clear correlation between\nintelligence and willingness to consider shocking ideas.\nThis isn't just because smart people actively work to find holes in\nconventional thinking. I think conventions also have\nless hold over them to start with.\nYou can see that in the\nway they dress.It's not only in the sciences that heresy pays off.\nIn any competitive field, you can\nwin big by seeing things that others daren't. \nAnd in every\nfield there are probably heresies few dare utter. Within\nthe US car industry there is a lot of hand-wringing now\nabout declining market share.\nYet the cause is so obvious that any observant outsider could\nexplain it in a second: they make bad cars. And they have for\nso long that by now the US car brands are antibrands — something\nyou'd buy a car despite, not because of. Cadillac stopped\nbeing the Cadillac of cars in about 1970. And yet I suspect\nno one dares say this. [11] Otherwise these companies would have\ntried to fix the problem.Training yourself to think unthinkable thoughts has advantages\nbeyond the thoughts themselves. It's like stretching.\nWhen you stretch before running, you put your body into positions\nmuch more extreme\nthan any it will assume during the run.\nIf you can think things\nso outside the box that they'd make people's hair stand on end,\nyou'll have no trouble with the small trips outside the box that\npeople call innovative.Pensieri StrettiWhen you find something you can't say, what do you do with it?\nMy advice is, don't say it. Or at least, pick your battles.Suppose in the future there is a movement to ban\nthe color yellow. Proposals to paint anything yellow are\ndenounced as \"yellowist\", as is anyone suspected of liking the \ncolor. People who like orange are tolerated but viewed with\nsuspicion. Suppose you realize there is nothing\nwrong with yellow. If you go around saying this, you'll be\ndenounced as a yellowist too, and you'll find yourself having a \nlot of arguments with anti-yellowists.\nIf your aim in life is to rehabilitate the color yellow, that may\nbe what you want.\nBut if you're mostly interested in\nother questions, being labelled as a yellowist will just be\na distraction. Argue with idiots, and you become an idiot.The most important thing is to be able to think what you\nwant, not to say what you want. And if you feel you have to\nsay everything you think, it may inhibit you from thinking \nimproper thoughts. I think it's better to follow the opposite\npolicy. Draw a sharp line between your thoughts and your\nspeech. Inside your head, anything is allowed.\nWithin my head I make a point of encouraging the most outrageous\nthoughts I can imagine. \nBut, as in\na secret society, nothing that happens within the building\nshould be told to outsiders. The first rule of Fight\nClub is, you do not talk about Fight Club.When Milton was going to visit Italy in the 1630s,\nSir Henry Wootton, who had been ambassador to Venice, told him\nhis motto should be\n\"i pensieri stretti & il viso sciolto.\" Closed thoughts\nand an open face. Smile at everyone, and don't tell them\nwhat you're thinking. This was wise advice.\nMilton was an argumentative fellow, and the Inquisition\nwas a bit restive at that time. But I think the difference \nbetween Milton's situation and ours is only a matter of\ndegree.\nEvery era has its heresies, and if you don't get imprisoned for them you\nwill at least get in enough trouble that it becomes a complete\ndistraction.I admit it seems cowardly to keep quiet.\nWhen I read about the harassment to which\nthe Scientologists subject their critics [12], or that pro-Israel groups\nare \"compiling dossiers\" on those who speak out against Israeli\nhuman rights abuses [13], or about people being sued for\nviolating the DMCA [14], part of me wants\nto say, \"All right, you bastards, bring it on.\"\nThe problem is, there are so many things you can't say.\nIf you said them all you'd \nhave no time left for your real work.\nYou'd have to turn into Noam Chomsky. [15]The trouble with keeping your thoughts secret, though,\nis that you lose the advantages of discussion. Talking\nabout an idea leads to more ideas.\nSo the optimal plan, if you can manage it,\nis to have a few trusted\nfriends you can speak openly to. This is not just a\nway to develop ideas; it's also a good\nrule of thumb for choosing friends. The people\nyou can say heretical things to without getting jumped on\nare also the most interesting to know.Viso Sciolto?I don't think we need\nthe viso sciolto so much as the pensieri stretti.\nPerhaps the best policy is to make it plain that you don't\nagree with whatever zealotry is current in your time, but\nnot to be too specific about what you disagree with. Zealots\nwill try to draw you out, but you don't have to answer them.\nIf they try to force you to treat a question on their\nterms by asking \"are you with us or against us?\" you can\nalways just answer \"neither\".Better still, answer \"I haven't decided.\"\nThat's what Larry Summers\ndid when a group tried to put\nhim in this position. Explaining himself later, he said\n\"I don't do litmus tests.\" [16]\nA lot of the\nquestions people get hot about are actually quite complicated.\nThere is no prize for getting the answer quickly.If the anti-yellowists seem to be getting out of hand and\nyou want to fight back, there are ways\nto do it without getting yourself accused of being a\nyellowist. Like skirmishers in\nan ancient army, you want to avoid directly engaging the\nmain body of the enemy's troops. Better to harass them\nwith arrows from a distance.One way to do this is to ratchet the debate up one level of\nabstraction.\nIf you argue against censorship in general, you can avoid being\naccused of whatever heresy is contained\nin the book or film that someone is trying to censor.\nYou can attack labels with meta-labels: labels that refer\nto the use of labels to prevent discussion.\nThe spread of the term \"political correctness\" meant the beginning of\nthe end of political correctness, because it enabled one to\nattack the phenomenon as a whole without being accused of any\nof the specific heresies it sought to suppress.Another way to counterattack is with metaphor. Arthur Miller\nundermined the House Un-American Activities Committee\nby writing a play, \"The Crucible,\" about the Salem witch trials.\nHe never referred directly to the committee and so gave them\nno way to reply.\nWhat could HUAC do, defend the Salem witch trials? And yet\nMiller's metaphor stuck so well that to this day the activities\nof the committee are often described as a \"witch-hunt.\"Best of all, probably, is humor. Zealots, whatever their \ncause, invariably lack a sense of humor.\nThey can't reply in kind to jokes.\nThey're as unhappy on the territory of\nhumor as a mounted knight on a skating rink.\nVictorian prudishness, for example, seems to have been defeated\nmainly by treating it as a joke. Likewise its reincarnation as\npolitical correctness.\n\"I am glad that I\nmanaged to write 'The Crucible,'\" Arthur Miller wrote,\n\"but looking back I have often wished I'd\nhad the temperament to do an absurd comedy, which is what the\nsituation deserved.\" [17]ABQA Dutch friend says\nI should use Holland as an example of a tolerant society.\nIt's true they have a long tradition of\ncomparative open-mindedness. For centuries the low countries were the place\nto go to say things you couldn't say anywhere else,\nand this helped to make the region a center of scholarship and industry\n(which have been closely tied for longer than most people realize).\nDescartes, though claimed by the French, did much of his thinking in\nHolland.And yet, I wonder. The Dutch seem to live their lives up to their\nnecks in rules and regulations. There's so much you can't do there;\nis there really nothing\nyou can't say?Certainly the fact that they value open-mindedness is no guarantee.\nWho thinks they're not open-minded? Our hypothetical prim miss from\nthe suburbs thinks she's open-minded. Hasn't she been\ntaught to be? Ask anyone, and they'll say the same thing: they're\npretty open-minded, though they draw the line at things that are really\nwrong. (Some tribes\nmay avoid \"wrong\" as\njudgemental, and may instead use a more neutral sounding euphemism\nlike \"negative\" or \"destructive\".)When people are bad at math, they know it, because they get the\nwrong answers on tests. But when people are bad at open-mindedness\nthey don't know it. In fact they tend to think the opposite.\nRemember, it's the nature of fashion to be invisible. It wouldn't\nwork otherwise. Fashion doesn't\nseem like fashion to someone in the grip of it. It just seems like\nthe right thing to do. It's only by looking from a distance that\nwe see oscillations in people's idea of the right thing to do, and\ncan identify them as fashions.Time gives us such distance for free. Indeed, the arrival of new\nfashions makes old fashions easy to see, because they\nseem so ridiculous by contrast. From one end of a pendulum's\nswing, the other end seems especially far away.To see fashion in your own time, though, requires a conscious effort.\nWithout time to give you distance, you have to create distance yourself.\nInstead of being part of the mob, stand\nas far away from it as you can and watch what it's\ndoing. And pay especially close attention whenever an idea is being\nsuppressed. Web filters for children and employees often ban\nsites containing pornography, violence, and hate speech. What\ncounts as pornography and violence? And what, exactly, is\n\"hate speech?\" This sounds like a phrase out of 1984.Labels like that are probably the biggest external clue.\nIf a statement is false,\nthat's the worst thing you can say about it. You don't\nneed to say that it's heretical. And if it isn't false, it\nshouldn't be suppressed. So when you see statements being\nattacked as x-ist or y-ic (substitute your current values of\nx and y), whether in 1630 or 2030, that's a sure sign that\nsomething is wrong. When you hear such labels being used,\nask why.Especially if you hear yourself using them. It's not just\nthe mob you need to learn to watch from a distance. You need to be\nable to watch your own thoughts from a distance. That's not\na radical idea, by the way; it's the main difference between\nchildren and adults. When a child gets angry because he's\ntired, he doesn't know what's happening. An adult can\ndistance himself enough from the\nsituation to say \"never mind, I'm just tired.\" I don't\nsee why one couldn't, by a similar process, learn to\nrecognize and discount the effects of moral fashions.You have to take that extra step if you want to think clearly.\nBut it's harder, because now you're working against social customs \ninstead of with them. Everyone encourages you to grow up to the \npoint where you can discount your own bad moods. Few encourage \nyou to continue to the point where you can discount society's bad\nmoods.How can you see the wave, when you're the water? Always be\nquestioning. That's the only defence. What can't you say? And why?NotesThanks to Sarah Harlin, Trevor Blackwell, Jessica Livingston,\nRobert Morris, Eric Raymond and Bob van der Zwaan for reading drafts of this\nessay, and to Lisa Randall, Jackie McDonough, Ryan Stanley and Joel Rainey \nfor conversations about heresy.\nNeedless to say they bear no blame for opinions\nexpressed in it, and especially for opinions not\nexpressed in it." }, { "path": "data/PaulGrahamEssays/schlep.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nJanuary 2012There are great startup ideas lying around unexploited right under\nour noses. One reason we don't see them is a phenomenon I call\nschlep blindness. Schlep was originally a Yiddish word but has\npassed into general use in the US. It means a tedious, unpleasant\ntask.No one likes schleps, but hackers especially dislike them. \nMost hackers who start startups wish they could do it by just writing\nsome clever software, putting it on a server somewhere, and watching\nthe money roll in—without ever having to talk to users, or negotiate\nwith other companies, or deal with other people's broken code.\nMaybe that's possible, but I haven't seen it.One of the many things we do at Y Combinator is teach hackers about\nthe inevitability of schleps. No, you can't start a startup by\njust writing code. I remember going through this realization myself.\nThere was a point in 1995 when I was still trying to convince myself\nI could start a company by just writing code. But I soon learned\nfrom experience that schleps are not merely inevitable, but pretty\nmuch what business consists of. A company is defined by the schleps\nit will undertake. And schleps should be dealt with the same way\nyou'd deal with a cold swimming pool: just jump in. Which is not\nto say you should seek out unpleasant work per se, but that you\nshould never shrink from it if it's on the path to something great.The most dangerous thing about our dislike of schleps is that much\nof it is unconscious. Your unconscious won't even let you see ideas\nthat involve painful schleps. That's schlep blindness.The phenomenon isn't limited to startups. Most people don't\nconsciously decide not to be in as good physical shape as Olympic\nathletes, for example. Their unconscious mind decides for them,\nshrinking from the work involved.The most striking example I know of schlep blindness is \nStripe, or\nrather Stripe's idea. For over a decade, every hacker who'd ever\nhad to process payments online knew how painful the experience was.\nThousands of people must have known about this problem. And yet\nwhen they started startups, they decided to build recipe sites, or\naggregators for local events. Why? Why work on problems few care\nmuch about and no one will pay for, when you could fix one of the\nmost important components of the world's infrastructure? Because\nschlep blindness prevented people from even considering the idea\nof fixing payments.Probably no one who applied to Y Combinator to work on a recipe\nsite began by asking \"should we fix payments, or build a recipe\nsite?\" and chose the recipe site. Though the idea of fixing payments\nwas right there in plain sight, they never saw it, because their\nunconscious mind shrank from the complications involved. You'd\nhave to make deals with banks. How do you do that? Plus you're\nmoving money, so you're going to have to deal with fraud, and people\ntrying to break into your servers. Plus there are probably all\nsorts of regulations to comply with. It's a lot more intimidating\nto start a startup like this than a recipe site.That scariness makes ambitious ideas doubly valuable. In addition\nto their intrinsic value, they're like undervalued stocks in the\nsense that there's less demand for them among founders. If you\npick an ambitious idea, you'll have less competition, because\neveryone else will have been frightened off by the challenges\ninvolved. (This is also true of starting a startup generally.)How do you overcome schlep blindness? Frankly, the most valuable\nantidote to schlep blindness is probably ignorance. Most successful\nfounders would probably say that if they'd known when they were\nstarting their company about the obstacles they'd have to overcome,\nthey might never have started it. Maybe that's one reason the most\nsuccessful startups of all so often have young founders.In practice the founders grow with the problems. But no one seems\nable to foresee that, not even older, more experienced founders.\nSo the reason younger founders have an advantage is that they make\ntwo mistakes that cancel each other out. They don't know how much\nthey can grow, but they also don't know how much they'll need to.\nOlder founders only make the first mistake.Ignorance can't solve everything though. Some ideas so obviously\nentail alarming schleps that anyone can see them. How do you see\nideas like that? The trick I recommend is to take yourself out of\nthe picture. Instead of asking \"what problem should I solve?\" ask\n\"what problem do I wish someone else would solve for me?\" If someone\nwho had to process payments before Stripe had tried asking that,\nStripe would have been one of the first things they wished for.It's too late now to be Stripe, but there's plenty still broken in\nthe world, if you know how to see it.Thanks to Sam Altman, Paul Buchheit, Patrick Collison,\nAaron Iba, Jessica Livingston, Emmett Shear, and Harj Taggar\nfor reading drafts of this." }, { "path": "data/PaulGrahamEssays/seesv.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nOctober 2010Silicon Valley proper is mostly suburban sprawl. At first glance\nit doesn't seem there's anything to see. It's not the sort of place\nthat has conspicuous monuments. But if you look, there are subtle\nsigns you're in a place that's different from other places.1. Stanford\nUniversityStanford is a strange place. Structurally it is to an ordinary\nuniversity what suburbia is to a city. It's enormously spread out,\nand feels surprisingly empty much of the time. But notice the\nweather. It's probably perfect. And notice the beautiful mountains\nto the west. And though you can't see it, cosmopolitan San Francisco\nis 40 minutes to the north. That combination is much of the reason\nSilicon Valley grew up around this university and not some other\none.2. University\nAveA surprising amount of the work of the Valley is done in the cafes\non or just off University Ave in Palo Alto. If you visit on a\nweekday between 10 and 5, you'll often see founders pitching\ninvestors. In case you can't tell, the founders are the ones leaning\nforward eagerly, and the investors are the ones sitting back with\nslightly pained expressions.3. The Lucky\nOfficeThe office at 165 University Ave was Google's first. Then it was\nPaypal's. (Now it's Wepay's.) The interesting thing about it is\nthe location. It's a smart move to put a startup in a place with\nrestaurants and people walking around instead of in an office park,\nbecause then the people who work there want to stay there, instead\nof fleeing as soon as conventional working hours end. They go out\nfor dinner together, talk about ideas, and then come back and\nimplement them.It's important to realize that Google's current location in an\noffice park is not where they started; it's just where they were\nforced to move when they needed more space. Facebook was till\nrecently across the street, till they too had to move because they\nneeded more space.4. Old\nPalo AltoPalo Alto was not originally a suburb. For the first 100 years or\nso of its existence, it was a college town out in the countryside.\nThen in the mid 1950s it was engulfed in a wave of suburbia that\nraced down the peninsula. But Palo Alto north of Oregon expressway\nstill feels noticeably different from the area around it. It's one\nof the nicest places in the Valley. The buildings are old (though\nincreasingly they are being torn down and replaced with generic\nMcMansions) and the trees are tall. But houses are very\nexpensive—around $1000 per square foot. This is post-exit\nSilicon Valley.\n5. Sand\nHill RoadIt's interesting to see the VCs' offices on the north side of Sand\nHill Road precisely because they're so boringly uniform. The\nbuildings are all more or less the same, their exteriors express\nvery little, and they are arranged in a confusing maze. (I've been\nvisiting them for years and I still occasionally get lost.) It's\nnot a coincidence. These buildings are a pretty accurate reflection\nof the VC business.If you go on a weekday you may see groups of founders there to meet\nVCs. But mostly you won't see anyone; bustling is the last word\nyou'd use to describe the atmos. Visiting Sand Hill Road reminds\nyou that the opposite of \"down and dirty\" would be \"up and clean.\"6. Castro\nStreetIt's a tossup whether Castro Street or University Ave should be\nconsidered the heart of the Valley now. University Ave would have\nbeen 10 years ago. But Palo Alto is getting expensive. Increasingly\nstartups are located in Mountain View, and Palo Alto is a place\nthey come to meet investors. Palo Alto has a lot of different\ncafes, but there is one that clearly dominates in Mountain View:\nRed\nRock.7. GoogleGoogle spread out from its first building in Mountain View \nto a lot of the surrounding ones. But because the\nbuildings were built at different times by different people,\nthe place doesn't have the sterile, walled-off feel that a typical\nlarge company's headquarters have. It definitely has a flavor of\nits own though. You sense there is something afoot. The general\natmos is vaguely utopian; there are lots of Priuses, and people who\nlook like they drive them.You can't get into Google unless you know someone there. It's very\nmuch worth seeing inside if you can, though. Ditto for Facebook,\nat the end of California Ave in Palo Alto, though there is nothing\nto see outside.8. Skyline\nDriveSkyline Drive runs along the crest of the Santa Cruz mountains. On\none side is the Valley, and on the other is the sea—which\nbecause it's cold and foggy and has few harbors, plays surprisingly\nlittle role in the lives of people in the Valley, considering how\nclose it is. Along some parts of Skyline the dominant trees are\nhuge redwoods, and in others they're live oaks. Redwoods mean those\nare the parts where the fog off the coast comes in at night; redwoods\ncondense rain out of fog. The MROSD manages a collection of great walking trails off\nSkyline.9. 280Silicon Valley has two highways running the length of it: 101, which\nis pretty ugly, and 280, which is one of the more beautiful highways\nin the world. I always take 280 when I have a choice. Notice the\nlong narrow lake to the west? That's the San Andreas Fault. It\nruns along the base of the hills, then heads uphill through Portola\nValley. One of the MROSD trails runs right along\nthe fault. A string of rich neighborhoods runs along the\nfoothills to the west of 280: Woodside, Portola Valley, Los Altos\nHills, Saratoga, Los Gatos.SLAC goes right under 280 a little bit south of Sand Hill Road. And a couple miles south of that is the Valley's equivalent of the \"Welcome to Las Vegas\" sign: The Dish.\nNotesI skipped the Computer\nHistory Museum because this is a list of where to see the Valley\nitself, not where to see artifacts from it. I also skipped San\nJose. San Jose calls itself the capital of Silicon Valley, but\nwhen people in the Valley use the phrase \"the city,\" they mean San\nFrancisco. San Jose is a dotted line on a map.Thanks to Sam Altman, Paul Buchheit, Patrick Collison, and Jessica Livingston\nfor reading drafts of this." }, { "path": "data/PaulGrahamEssays/segway.txt", "content": "July 2009The Segway hasn't delivered on its initial promise, to put it mildly.\r\nThere are several reasons why, but one is that people don't want\r\nto be seen riding them. Someone riding a Segway looks like a dork.My friend Trevor Blackwell built \r\nhis own Segway, \r\nwhich we called\r\nthe Segwell. He also built a one-wheeled version, \r\nthe Eunicycle,\r\nwhich looks exactly like a regular unicycle till you realize the\r\nrider isn't pedaling. He has ridden them both to downtown Mountain\r\nView to get coffee. When he rides the Eunicycle, people smile at\r\nhim. But when he rides the Segwell, they shout abuse from their\r\ncars: \"Too lazy to walk, ya fuckin homo?\"Why do Segways provoke this reaction? The reason you look like a\r\ndork riding a Segway is that you look smug. You don't seem to\r\nbe working hard enough.Someone riding a motorcycle isn't working any harder. But because\r\nhe's sitting astride it, he seems to be making an effort. When\r\nyou're riding a Segway you're just standing there. And someone who's\r\nbeing whisked along while seeming to do no work — someone in a sedan\r\nchair, for example — can't help but look smug.Try this thought experiment and it becomes clear: imagine something\r\nthat worked like the Segway, but that you rode with one foot in\r\nfront of the other, like a skateboard. That wouldn't seem nearly\r\nas uncool.So there may be a way to capture more of the market Segway hoped\r\nto reach: make a version that doesn't look so easy for the rider.\r\nIt would also be helpful if the styling was in the tradition of\r\nskateboards or bicycles rather than medical devices.Curiously enough, what got Segway into this problem was that the\r\ncompany was itself a kind of Segway. It was too easy for them;\r\nthey were too successful raising money. If they'd had to grow the\r\ncompany gradually, by iterating through several versions they sold\r\nto real users, they'd have learned pretty quickly that people looked\r\nstupid riding them. Instead they had enough to work in secret. They\r\nhad focus groups aplenty, I'm sure, but they didn't have the people\r\nyelling insults out of cars. So they never realized they were\r\nzooming confidently down a blind alley." }, { "path": "data/PaulGrahamEssays/selfindulgence.txt", "content": "July 2010When we sold our startup in 1998 I suddenly got a lot of money. I\r\nnow had to think about something I hadn't had to think about before:\r\nhow not to lose it. I knew it was possible to go from rich to\r\npoor, just as it was possible to go from poor to rich. But while\r\nI'd spent a lot of the past several years studying the paths from\r\npoor to rich, \r\nI knew practically nothing about the paths from rich\r\nto poor. Now, in order to avoid them, I had to learn where they\r\nwere.So I started to pay attention to how fortunes are lost. If you'd\r\nasked me as a kid how rich people became poor, I'd have said by\r\nspending all their money. That's how it happens in books and movies,\r\nbecause that's the colorful way to do it. But in fact the way most\r\nfortunes are lost is not through excessive expenditure, but through\r\nbad investments.It's hard to spend a fortune without noticing. Someone with ordinary\r\ntastes would find it hard to blow through more than a few tens of\r\nthousands of dollars without thinking \"wow, I'm spending a lot of\r\nmoney.\" Whereas if you start trading derivatives, you can lose a\r\nmillion dollars (as much as you want, really) in the blink of an\r\neye.In most people's minds, spending money on luxuries sets off alarms\r\nthat making investments doesn't. Luxuries seem self-indulgent.\r\nAnd unless you got the money by inheriting it or winning a lottery,\r\nyou've already been thoroughly trained that self-indulgence leads\r\nto trouble. Investing bypasses those alarms. You're not spending\r\nthe money; you're just moving it from one asset to another. Which\r\nis why people trying to sell you expensive things say \"it's an\r\ninvestment.\"The solution is to develop new alarms. This can be a tricky business,\r\nbecause while the alarms that prevent you from overspending are so\r\nbasic that they may even be in our DNA, the ones that prevent you\r\nfrom making bad investments have to be learned, and are sometimes\r\nfairly counterintuitive.A few days ago I realized something surprising: the situation with\r\ntime is much the same as with money. The most dangerous way to\r\nlose time is not to spend it having fun, but to spend it doing fake\r\nwork. When you spend time having fun, you know you're being\r\nself-indulgent. Alarms start to go off fairly quickly. If I woke\r\nup one morning and sat down on the sofa and watched TV all day, I'd\r\nfeel like something was terribly wrong. Just thinking about it\r\nmakes me wince. I'd start to feel uncomfortable after sitting on\r\na sofa watching TV for 2 hours, let alone a whole day.And yet I've definitely had days when I might as well have sat in\r\nfront of a TV all day — days at the end of which, if I asked myself\r\nwhat I got done that day, the answer would have been: basically,\r\nnothing. I feel bad after these days too, but nothing like as bad\r\nas I'd feel if I spent the whole day on the sofa watching TV. If\r\nI spent a whole day watching TV I'd feel like I was descending into\r\nperdition. But the same alarms don't go off on the days when I get\r\nnothing done, because I'm doing stuff that seems, superficially,\r\nlike real work. Dealing with email, for example. You do it sitting\r\nat a desk. It's not fun. So it must be work.With time, as with money, avoiding pleasure is no longer enough to\r\nprotect you. It probably was enough to protect hunter-gatherers,\r\nand perhaps all pre-industrial societies. So nature and nurture\r\ncombine to make us avoid self-indulgence. But the world has gotten\r\nmore complicated: the most dangerous traps now are new behaviors\r\nthat bypass our alarms about self-indulgence by mimicking more\r\nvirtuous types. And the worst thing is, they're not even fun.\nThanks to Sam Altman, Trevor Blackwell, Patrick Collison, Jessica\r\nLivingston, and Robert Morris for reading drafts of this." }, { "path": "data/PaulGrahamEssays/sfp.txt", "content": "October 2005The first Summer Founders Program has just finished. We were\nsurprised how well it went. Overall only about 10% of startups \nsucceed, but if I had to guess now, I'd predict three or four of \nthe eight startups we funded will make it.Of the startups that needed further funding, I believe all have\neither closed a round or are likely to soon. Two have already\nturned down (lowball) acquisition offers.We would have been happy if just one of the eight seemed promising\nby the end of the summer. What's going on? Did some kind of anomaly\nmake this summer's applicants especially good? We worry about that,\nbut we can't think of one. We'll find out this winter.The whole summer was full of surprises. The best was that the hypothesis we were testing seems to be\ncorrect. Young hackers can start viable companies. This is good\nnews for two reasons: (a) it's an encouraging thought, and (b) it \nmeans that Y Combinator, which is predicated on the idea, is not\nhosed.AgeMore precisely, the hypothesis was that success in a startup depends\nmainly on how smart and energetic you are, and much less on how old\nyou are or how much business experience you have. The results so\nfar bear this out. The 2005 summer founders ranged in age from 18 \nto 28 (average 23), and there is no correlation between their ages\nand how well they're doing.This should not really be surprising. Bill Gates and Michael Dell \nwere both 19 when they started the companies that made them famous.\nYoung founders are not a new phenomenon: the trend began as soon\nas computers got cheap enough for college kids to afford them.Another of our hypotheses was that you can start a startup on less\nmoney than most people think. Other investors were surprised to\nhear the most we gave any group was $20,000. But we knew it was\npossible to start on that little because we started Viaweb on\n$10,000.And so it proved this summer. Three months' funding is enough to\nget into second gear. We had a demo day for potential investors\nten weeks in, and seven of the eight groups had a prototype ready\nby that time. One, Reddit, had\nalready launched, and were able to give a demo of their live site.A researcher who studied the SFP startups said the one thing they \nhad in common was that they all worked ridiculously hard. People\nthis age are commonly seen as lazy. I think in some cases it's not\nso much that they lack the appetite for work, but that the work\nthey're offered is unappetizing.The experience of the SFP suggests that if you let motivated people\ndo real work, they work hard, whatever their age. As one of the\nfounders said \"I'd read that starting a startup consumed your life, \nbut I had no idea what that meant until I did it.\"I'd feel guilty if I were a boss making people work this hard. But\nwe're not these people's bosses. They're working on their own\nprojects. And what makes them work is not us but their competitors.\nLike good athletes, they don't work hard because the coach yells\nat them, but because they want to win.We have less power than bosses, and yet the founders work harder \nthan employees. It seems like a win for everyone. The only catch\nis that we get on average only about 5-7% of the upside, while an\nemployer gets nearly all of it. (We're counting on it being 5-7%\nof a much larger number.)As well as working hard, the groups all turned out to be extraordinarily\nresponsible. I can't think of a time when one failed to do something\nthey'd promised to, even by being late for an appointment. This\nis another lesson the world has yet to learn. One of the founders\ndiscovered that the hardest part of arranging a meeting with\nexecutives at a big cell phone carrier was getting a rental company\nto rent him a car, because he was too young.I think the problem here is much the same as with the apparent\nlaziness of people this age. They seem lazy because the work they're\ngiven is pointless, and they act irresponsible because they're not\ngiven any power. Some of them, anyway. We only have a sample size\nof about twenty, but it seems so far that if you let people in their\nearly twenties be their own bosses, they rise to the occasion.MoraleThe summer founders were as a rule very idealistic. They also \nwanted very much to get rich. These qualities might seem incompatible,\nbut they're not. These guys want to get rich, but they want to do\nit by changing the world. They wouldn't (well, seven of the eight\ngroups wouldn't) be interested in making money by speculating in\nstocks. They want to make something people use.I think this makes them more effective as founders. As hard as \npeople will work for money, they'll work harder for a cause. And \nsince success in a startup depends so much on motivation, the\nparadoxical result is that the people likely to make the most money\nare those who aren't in it just for the money.The founders of Kiko, for example, \nare working on an Ajax calendar. They want to get rich, but they\npay more attention to design than they would if that were their\nonly motivation. You can tell just by looking at it.I never considered it till this summer, but this might be another\nreason startups run by hackers tend to do better than those run by\nMBAs. Perhaps it's not just that hackers understand technology\nbetter, but that they're driven by more powerful motivations.\nMicrosoft, as I've said before, is a dangerously misleading example. \nTheir mean corporate culture only works for monopolies. \nGoogle is a better model.Considering that the summer founders are the sharks in this ocean,\nwe were surprised how frightened most of them were of competitors.\nBut now that I think of it, we were just as frightened when we\nstarted Viaweb. For the first year, our initial reaction to news \nof a competitor was always: we're doomed. Just as a hypochondriac\nmagnifies his symptoms till he's convinced he has some terrible\ndisease, when you're not used to competitors you magnify them into\nmonsters.Here's a handy rule for startups: competitors are rarely as dangerous\nas they seem. Most will self-destruct before you can destroy them.\nAnd it certainly doesn't matter how many of them there are, any\nmore than it matters to the winner of a marathon how many runners\nare behind him.\"It's a crowded market,\" I remember one founder saying worriedly.\"Are you the current leader?\" I asked.\"Yes.\"\"Is anyone able to develop software faster than you?\"\"Probably not.\"\"Well, if you're ahead now, and you're the fastest, then you'll\nstay ahead. What difference does it make how many others there\nare?\"Another group was worried when they realized they had to rewrite\ntheir software from scratch. I told them it would be a bad sign\nif they didn't. The main function of your initial version is to \nbe rewritten.That's why we advise groups to ignore issues like scalability,\ninternationalization, and heavy-duty security at first. [1] I can\nimagine an advocate of \"best practices\" saying these ought to be\nconsidered from the start. And he'd be right, except that they\ninterfere with the primary function of software in a startup: to \nbe a vehicle for experimenting with its own design. Having to\nretrofit internationalization or scalability is a pain, certainly. \nThe only bigger pain is not needing to, because your initial version\nwas too big and rigid to evolve into something users wanted.I suspect this is another reason startups beat big companies.\nStartups can be irresponsible and release version 1s that are light\nenough to evolve. In big companies, all the pressure is in the \ndirection of over-engineering.What Got LearnedOne thing we were curious about this summer was where these groups \nwould need help. That turned out to vary a lot. Some we helped\nwith technical advice-- for example, about how to set up an application\nto run on multiple servers. Most we helped with strategy questions,\nlike what to patent, and what to charge for and what to give away.\nNearly all wanted advice about dealing with future investors: how \nmuch money should they take and what kind of terms should they\nexpect?However, all the groups quickly learned how to deal with stuff like\npatents and investors. These problems aren't intrinsically difficult,\njust unfamiliar.It was surprising-- slightly frightening even-- how fast they\nlearned. The weekend before the demo day for investors, we had a \npractice session where all the groups gave their presentations. \nThey were all terrible. We tried to explain how to make them better,\nbut we didn't have much hope. So on demo day I told the assembled\nangels and VCs that these guys were hackers, not MBAs, and so while\ntheir software was good, we should not expect slick presentations \nfrom them.The groups then proceeded to give fabulously slick presentations. \nGone were the mumbling recitations of lists of features. It was\nas if they'd spent the past week at acting school. I still don't \nknow how they did it.Perhaps watching each others' presentations helped them see what\nthey'd been doing wrong. Just as happens in college, the summer \nfounders learned a lot from one another-- maybe more than they\nlearned from us. A lot of the problems they face are the same, \nfrom dealing with investors to hacking Javascript.I don't want to give the impression there were no problems this \nsummer. A lot went wrong, as usually happens with startups. One\ngroup got an \"exploding\nterm-sheet\" from some VCs. Pretty much all the groups who had\ndealings with big companies found that big companies do everything\ninfinitely slowly. (This is to be expected. If big companies\nweren't incapable, there would be no room for startups to exist.)\nAnd of course there were the usual nightmares associated with\nservers. In short, the disasters this summer were just the usual childhood\ndiseases. Some of this summer's eight startups will \nprobably die eventually; it would be extraordinary if all eight \nsucceeded. But what kills them will not be dramatic, external \nthreats, but a mundane, internal one: not getting enough done.So far, though, the news is all good. In fact, we were surprised\nhow much fun the summer was for us. The main reason was how much\nwe liked the founders. They're so earnest and hard-working. They\nseem to like us too. And this illustrates another advantage of\ninvesting over hiring: our relationship with them is way better \nthan it would be between a boss and an employee. Y Combinator ends\nup being more like an older brother than a parent.I was surprised how much time I spent making introductions.\nFortunately I discovered that when a startup needed to talk to\nsomeone, I could usually get to the right person by at most one\nhop. I remember wondering, how did my friends get to be so eminent?\nand a second later realizing: shit, I'm forty.Another surprise was that the three-month batch format,\nwhich we were forced into by the constraints of the summer, turned\nout to be an advantage. When we started Y Combinator, we planned\nto invest the way other venture firms do: as proposals came in, \nwe'd evaluate them and decide yes or no. The SFP\nwas just an experiment to get things started. But it worked so\nwell that we plan to do \nall \nour investing this way, one cycle in\nthe summer and one in winter. It's more efficient for us, and\nbetter for the startups too.Several groups said our weekly dinners saved them from a common\nproblem afflicting startups: working so hard that one has no social\nlife. (I remember that part all too well.) This way, they were\nguaranteed a social event at least once a week.IndependenceI've heard Y Combinator described as an \"incubator.\" Actually we're\nthe opposite: incubators exert more control than ordinary VCs, and\nwe make a point of exerting less. Among other things, incubators\nusually make you work in their office-- that's where the \nword \"incubator\" comes from. That seems the wrong model. If\ninvestors get too involved, they smother one of the most powerful \nforces in a startup: the feeling that it's your own company.Incubators were conspicuous failures during the Bubble. There's \nstill debate about whether this was because of the Bubble, or because\nthey're a bad idea. My vote is they're a bad idea. I think they \nfail because they select for the wrong people. When we were starting\na startup, we would never have taken funding from an \"incubator.\"\nWe can find office space, thanks; just give us the money. And \npeople with that attitude are the ones likely to succeed in startups.Indeed, one quality all the founders shared this summer was a spirit\nof independence. I've been wondering about that. Are some people\njust a lot more independent than others, or would everyone be this\nway if they were allowed to?As with most nature/nurture questions, the answer is probably: some\nof each. But my main conclusion from the summer is that there's\nmore environment in the mix than most people realize. I could see\nthat from how the founders' attitudes changed during the \nsummer. Most were emerging from twenty or so years of being told\nwhat to do. They seemed a little surprised at having total freedom.\nBut they grew into it really quickly; some of these guys now seem\nabout four inches taller (metaphorically) than they did at the\nbeginning of the summer.When we asked the summer founders what surprised them most about\nstarting a company, one said \"the most shocking thing is that it \nworked.\"It will take more experience to know for sure, but my guess is that\na lot of hackers could do this-- that if you put people in a position\nof independence, they develop the qualities they need. Throw them\noff a cliff, and most will find on the way down that they have \nwings.The reason this is news to anyone is that the same forces work in\nthe other direction too. Most hackers are \nemployees, and this molds\nyou into someone to whom starting a startup seems impossible as\nsurely as starting a startup molds you into someone who can handle\nit.If I'm right, \"hacker\" will mean something different in twenty years\nthan it does now. Increasingly it will mean the people who run the\ncompany. Y Combinator is just accelerating a process that would\nhave happened anyway. Power is shifting from the people who deal\nwith money to the people who create technology, and if our experience\nthis summer is any guide, this will be a good thing.Notes[1] By heavy-duty security I mean efforts to protect against truly\ndetermined attackers.The image\nshows us, the 2005 summer founders, and Smartleaf\nco-founders Mark Nitzberg and Olin Shivers at the 30-foot table \nKate Courteau designed for us. Photo by Alex Lewin.Thanks to Sarah Harlin, Steve Huffman, Jessica Livingston,\nZak Stone, and Aaron Swartz for reading drafts of this.\n" }, { "path": "data/PaulGrahamEssays/siliconvalley.txt", "content": "May 2006(This essay is derived from a keynote at Xtech.)Could you reproduce Silicon Valley elsewhere, or is there something\nunique about it?It wouldn't be surprising if it were hard to reproduce in other\ncountries, because you couldn't reproduce it in most of the US\neither. What does it take to make a silicon valley even here?What it takes is the right people. If you could get the right ten\nthousand people to move from Silicon Valley to Buffalo, Buffalo\nwould become Silicon Valley. \n[1]That's a striking departure from the past. Up till a couple decades\nago, geography was destiny for cities. All great cities were located\non waterways, because cities made money by trade, and water was the\nonly economical way to ship.Now you could make a great city anywhere, if you could get the right\npeople to move there. So the question of how to make a silicon\nvalley becomes: who are the right people, and how do you get them\nto move?Two TypesI think you only need two kinds of people to create a technology\nhub: rich people and nerds. They're the limiting reagents in the\nreaction that produces startups, because they're the only ones\npresent when startups get started. Everyone else will move.Observation bears this out: within the US, towns have become startup\nhubs if and only if they have both rich people and nerds. Few\nstartups happen in Miami, for example, because although it's full\nof rich people, it has few nerds. It's not the kind of place nerds\nlike.Whereas Pittsburgh has the opposite problem: plenty of nerds, but\nno rich people. The top US Computer Science departments are said\nto be MIT, Stanford, Berkeley, and Carnegie-Mellon. MIT yielded\nRoute 128. Stanford and Berkeley yielded Silicon Valley. But\nCarnegie-Mellon? The record skips at that point. Lower down the\nlist, the University of Washington yielded a high-tech community\nin Seattle, and the University of Texas at Austin yielded one in\nAustin. But what happened in Pittsburgh? And in Ithaca, home of\nCornell, which is also high on the list?I grew up in Pittsburgh and went to college at Cornell, so I can\nanswer for both. The weather is terrible, particularly in winter,\nand there's no interesting old city to make up for it, as there is\nin Boston. Rich people don't want to live in Pittsburgh or Ithaca.\nSo while there are plenty of hackers who could start startups,\nthere's no one to invest in them.Not BureaucratsDo you really need the rich people? Wouldn't it work to have the\ngovernment invest in the nerds? No, it would not. Startup investors\nare a distinct type of rich people. They tend to have a lot of\nexperience themselves in the technology business. This (a) helps\nthem pick the right startups, and (b) means they can supply advice\nand connections as well as money. And the fact that they have a\npersonal stake in the outcome makes them really pay attention.Bureaucrats by their nature are the exact opposite sort of people\nfrom startup investors. The idea of them making startup investments\nis comic. It would be like mathematicians running Vogue-- or\nperhaps more accurately, Vogue editors running a math journal.\n[2]Though indeed, most things bureaucrats do, they do badly. We just\ndon't notice usually, because they only have to compete against\nother bureaucrats. But as startup investors they'd have to compete\nagainst pros with a great deal more experience and motivation.Even corporations that have in-house VC groups generally forbid\nthem to make their own investment decisions. Most are only allowed\nto invest in deals where some reputable private VC firm is willing\nto act as lead investor.Not BuildingsIf you go to see Silicon Valley, what you'll see are buildings.\nBut it's the people that make it Silicon Valley, not the buildings.\nI read occasionally about attempts to set up \"technology\nparks\" in other places, as if the active ingredient of Silicon\nValley were the office space. An article about Sophia Antipolis\nbragged that companies there included Cisco, Compaq, IBM, NCR, and\nNortel. Don't the French realize these aren't startups?Building office buildings for technology companies won't get you a\nsilicon valley, because the key stage in the life of a startup\nhappens before they want that kind of space. The key stage is when\nthey're three guys operating out of an apartment. Wherever the\nstartup is when it gets funded, it will stay. The defining quality\nof Silicon Valley is not that Intel or Apple or Google have offices\nthere, but that they were started there.So if you want to reproduce Silicon Valley, what you need to reproduce\nis those two or three founders sitting around a kitchen table\ndeciding to start a company. And to reproduce that you need those\npeople.UniversitiesThe exciting thing is, all you need are the people. If you could\nattract a critical mass of nerds and investors to live somewhere,\nyou could reproduce Silicon Valley. And both groups are highly\nmobile. They'll go where life is good. So what makes a place good\nto them?What nerds like is other nerds. Smart people will go wherever other\nsmart people are. And in particular, to great universities. In\ntheory there could be other ways to attract them, but so far\nuniversities seem to be indispensable. Within the US, there are\nno technology hubs without first-rate universities-- or at least,\nfirst-rate computer science departments.So if you want to make a silicon valley, you not only need a\nuniversity, but one of the top handful in the world. It has to be\ngood enough to act as a magnet, drawing the best people from thousands\nof miles away. And that means it has to stand up to existing magnets\nlike MIT and Stanford.This sounds hard. Actually it might be easy. My professor friends,\nwhen they're deciding where they'd like to work, consider one thing\nabove all: the quality of the other faculty. What attracts professors\nis good colleagues. So if you managed to recruit, en masse, a\nsignificant number of the best young researchers, you could create\na first-rate university from nothing overnight. And you could do\nthat for surprisingly little. If you paid 200 people hiring bonuses\nof $3 million apiece, you could put together a faculty that would\nbear comparison with any in the world. And from that point the\nchain reaction would be self-sustaining. So whatever it costs to\nestablish a mediocre university, for an additional half billion or\nso you could have a great one. \n[3]PersonalityHowever, merely creating a new university would not be enough to\nstart a silicon valley. The university is just the seed. It has\nto be planted in the right soil, or it won't germinate. Plant it\nin the wrong place, and you just create Carnegie-Mellon.To spawn startups, your university has to be in a town that has\nattractions other than the university. It has to be a place where\ninvestors want to live, and students want to stay after they graduate.The two like much the same things, because most startup investors\nare nerds themselves. So what do nerds look for in a town? Their\ntastes aren't completely different from other people's, because a\nlot of the towns they like most in the US are also big tourist\ndestinations: San Francisco, Boston, Seattle. But their tastes\ncan't be quite mainstream either, because they dislike other big\ntourist destinations, like New York, Los Angeles, and Las Vegas.There has been a lot written lately about the \"creative class.\" The\nthesis seems to be that as wealth derives increasingly from ideas,\ncities will prosper only if they attract those who have them. That\nis certainly true; in fact it was the basis of Amsterdam's prosperity\n400 years ago.A lot of nerd tastes they share with the creative class in general.\nFor example, they like well-preserved old neighborhoods instead of\ncookie-cutter suburbs, and locally-owned shops and restaurants\ninstead of national chains. Like the rest of the creative class,\nthey want to live somewhere with personality.What exactly is personality? I think it's the feeling that each\nbuilding is the work of a distinct group of people. A town with\npersonality is one that doesn't feel mass-produced. So if you want\nto make a startup hub-- or any town to attract the \"creative class\"--\nyou probably have to ban large development projects.\nWhen a large tract has been developed by a single organization, you\ncan always tell. \n[4]Most towns with personality are old, but they don't have to be.\nOld towns have two advantages: they're denser, because they were\nlaid out before cars, and they're more varied, because they were\nbuilt one building at a time. You could have both now. Just have\nbuilding codes that ensure density, and ban large scale developments.A corollary is that you have to keep out the biggest developer of\nall: the government. A government that asks \"How can we build a\nsilicon valley?\" has probably ensured failure by the way they framed\nthe question. You don't build a silicon valley; you let one grow.NerdsIf you want to attract nerds, you need more than a town with\npersonality. You need a town with the right personality. Nerds\nare a distinct subset of the creative class, with different tastes\nfrom the rest. You can see this most clearly in New York, which\nattracts a lot of creative people, but few nerds. \n[5]What nerds like is the kind of town where people walk around smiling.\nThis excludes LA, where no one walks at all, and also New York,\nwhere people walk, but not smiling. When I was in grad school in\nBoston, a friend came to visit from New York. On the subway back\nfrom the airport she asked \"Why is everyone smiling?\" I looked and\nthey weren't smiling. They just looked like they were compared to\nthe facial expressions she was used to.If you've lived in New York, you know where these facial expressions\ncome from. It's the kind of place where your mind may be excited,\nbut your body knows it's having a bad time. People don't so much\nenjoy living there as endure it for the sake of the excitement.\nAnd if you like certain kinds of excitement, New York is incomparable.\nIt's a hub of glamour, a magnet for all the shorter half-life\nisotopes of style and fame.Nerds don't care about glamour, so to them the appeal of New York\nis a mystery. People who like New York will pay a fortune for a\nsmall, dark, noisy apartment in order to live in a town where the\ncool people are really cool. A nerd looks at that deal and sees\nonly: pay a fortune for a small, dark, noisy apartment.Nerds will pay a premium to live in a town where the smart people\nare really smart, but you don't have to pay as much for that. It's\nsupply and demand: glamour is popular, so you have to pay a lot for\nit.Most nerds like quieter pleasures. They like cafes instead of\nclubs; used bookshops instead of fashionable clothing shops; hiking\ninstead of dancing; sunlight instead of tall buildings. A nerd's\nidea of paradise is Berkeley or Boulder.YouthIt's the young nerds who start startups, so it's those specifically\nthe city has to appeal to. The startup hubs in the US are all\nyoung-feeling towns. This doesn't mean they have to be new.\nCambridge has the oldest town plan in America, but it feels young\nbecause it's full of students.What you can't have, if you want to create a silicon valley, is a\nlarge, existing population of stodgy people. It would be a waste\nof time to try to reverse the fortunes of a declining industrial town\nlike Detroit or Philadelphia by trying to encourage startups. Those\nplaces have too much momentum in the wrong direction. You're better\noff starting with a blank slate in the form of a small town. Or\nbetter still, if there's a town young people already flock to, that\none.The Bay Area was a magnet for the young and optimistic for decades\nbefore it was associated with technology. It was a place people\nwent in search of something new. And so it became synonymous with\nCalifornia nuttiness. There's still a lot of that there. If you\nwanted to start a new fad-- a new way to focus one's \"energy,\" for\nexample, or a new category of things not to eat-- the Bay Area would\nbe the place to do it. But a place that tolerates oddness in the\nsearch for the new is exactly what you want in a startup hub, because\neconomically that's what startups are. Most good startup ideas\nseem a little crazy; if they were obviously good ideas, someone\nwould have done them already.(How many people are going to want computers in their houses?\nWhat, another search engine?)That's the connection between technology and liberalism. Without\nexception the high-tech cities in the US are also the most liberal.\nBut it's not because liberals are smarter that this is so. It's\nbecause liberal cities tolerate odd ideas, and smart people by\ndefinition have odd ideas.Conversely, a town that gets praised for being \"solid\" or representing\n\"traditional values\" may be a fine place to live, but it's never\ngoing to succeed as a startup hub. The 2004 presidential election,\nthough a disaster in other respects, conveniently supplied us with\na county-by-county \nmap of such places. \n[6]To attract the young, a town must have an intact center. In most\nAmerican cities the center has been abandoned, and the growth, if\nany, is in the suburbs. Most American cities have been turned\ninside out. But none of the startup hubs has: not San Francisco,\nor Boston, or Seattle. They all have intact centers.\n[7]\nMy guess is that no city with a dead center could be turned into a\nstartup hub. Young people don't want to live in the suburbs.Within the US, the two cities I think could most easily be turned\ninto new silicon valleys are Boulder and Portland. Both have the\nkind of effervescent feel that attracts the young. They're each\nonly a great university short of becoming a silicon valley, if they\nwanted to.TimeA great university near an attractive town. Is that all it takes?\nThat was all it took to make the original Silicon Valley. Silicon\nValley traces its origins to William Shockley, one of the inventors\nof the transistor. He did the research that won him the Nobel Prize\nat Bell Labs, but when he started his own company in 1956 he moved\nto Palo Alto to do it. At the time that was an odd thing to do.\nWhy did he? Because he had grown up there and remembered how nice\nit was. Now Palo Alto is suburbia, but then it was a charming\ncollege town-- a charming college town with perfect weather and San\nFrancisco only an hour away.The companies that rule Silicon Valley now are all descended in\nvarious ways from Shockley Semiconductor. Shockley was a difficult\nman, and in 1957 his top people-- \"the traitorous eight\"-- left to\nstart a new company, Fairchild Semiconductor. Among them were\nGordon Moore and Robert Noyce, who went on to found Intel, and\nEugene Kleiner, who founded the VC firm Kleiner Perkins. Forty-two\nyears later, Kleiner Perkins funded Google, and the partner responsible\nfor the deal was John Doerr, who came to Silicon Valley in 1974 to\nwork for Intel.So although a lot of the newest companies in Silicon Valley don't\nmake anything out of silicon, there always seem to be multiple links\nback to Shockley. There's a lesson here: startups beget startups.\nPeople who work for startups start their own. People who get rich\nfrom startups fund new ones. I suspect this kind of organic growth\nis the only way to produce a startup hub, because it's the only way\nto grow the expertise you need.That has two important implications. The first is that you need\ntime to grow a silicon valley. The university you could create in\na couple years, but the startup community around it has to grow\norganically. The cycle time is limited by the time it takes a\ncompany to succeed, which probably averages about five years.The other implication of the organic growth hypothesis is that you\ncan't be somewhat of a startup hub. You either have a self-sustaining\nchain reaction, or not. Observation confirms this too: cities\neither have a startup scene, or they don't. There is no middle\nground. Chicago has the third largest metropolitan area in America.\nAs source of startups it's negligible compared to Seattle, number 15.The good news is that the initial seed can be quite small. Shockley\nSemiconductor, though itself not very successful, was big enough.\nIt brought a critical mass of experts in an important new technology\ntogether in a place they liked enough to stay.CompetingOf course, a would-be silicon valley faces an obstacle the original\none didn't: it has to compete with Silicon Valley. Can that be\ndone? Probably.One of Silicon Valley's biggest advantages is its venture capital\nfirms. This was not a factor in Shockley's day, because VC funds\ndidn't exist. In fact, Shockley Semiconductor and Fairchild\nSemiconductor were not startups at all in our sense. They were\nsubsidiaries-- of Beckman Instruments and Fairchild Camera and\nInstrument respectively. Those companies were apparently willing\nto establish subsidiaries wherever the experts wanted to live.Venture investors, however, prefer to fund startups within an hour's\ndrive. For one, they're more likely to notice startups nearby.\nBut when they do notice startups in other towns they prefer them\nto move. They don't want to have to travel to attend board meetings,\nand in any case the odds of succeeding are higher in a startup hub.The centralizing effect of venture firms is a double one: they cause\nstartups to form around them, and those draw in more startups through\nacquisitions. And although the first may be weakening because it's\nnow so cheap to start some startups, the second seems as strong as ever.\nThree of the most admired\n\"Web 2.0\" companies were started outside the usual startup hubs,\nbut two of them have already been reeled in through acquisitions.Such centralizing forces make it harder for new silicon valleys to\nget started. But by no means impossible. Ultimately power rests\nwith the founders. A startup with the best people will beat one\nwith funding from famous VCs, and a startup that was sufficiently\nsuccessful would never have to move. So a town that\ncould exert enough pull over the right people could resist and\nperhaps even surpass Silicon Valley.For all its power, Silicon Valley has a great weakness: the paradise\nShockley found in 1956 is now one giant parking lot. San Francisco\nand Berkeley are great, but they're forty miles away. Silicon\nValley proper is soul-crushing suburban sprawl. It\nhas fabulous weather, which makes it significantly better than the\nsoul-crushing sprawl of most other American cities. But a competitor\nthat managed to avoid sprawl would have real leverage. All a city\nneeds is to be the kind of place the next traitorous eight look at\nand say \"I want to stay here,\" and that would be enough to get the\nchain reaction started.Notes[1]\nIt's interesting to consider how low this number could be\nmade. I suspect five hundred would be enough, even if they could\nbring no assets with them. Probably just thirty, if I could pick them, \nwould be enough to turn Buffalo into a significant startup hub.[2]\nBureaucrats manage to allocate research funding moderately\nwell, but only because (like an in-house VC fund) they outsource\nmost of the work of selection. A professor at a famous university\nwho is highly regarded by his peers will get funding, pretty much\nregardless of the proposal. That wouldn't work for startups, whose\nfounders aren't sponsored by organizations, and are often unknowns.[3]\nYou'd have to do it all at once, or at least a whole department\nat a time, because people would be more likely to come if they\nknew their friends were. And you should probably start from scratch,\nrather than trying to upgrade an existing university, or much energy\nwould be lost in friction.[4]\nHypothesis: Any plan in which multiple independent buildings\nare gutted or demolished to be \"redeveloped\" as a single project\nis a net loss of personality for the city, with the exception of\nthe conversion of buildings not previously public, like warehouses.[5]\nA few startups get started in New York, but less\nthan a tenth as many per capita as in Boston, and mostly\nin less nerdy fields like finance and media.[6]\nSome blue counties are false positives (reflecting the\nremaining power of Democractic party machines), but there are no\nfalse negatives. You can safely write off all the red counties.[7]\nSome \"urban renewal\" experts took a shot at destroying Boston's\nin the 1960s, leaving the area around city hall a bleak wasteland,\nbut most neighborhoods successfully resisted them.Thanks to Chris Anderson, Trevor Blackwell, Marc Hedlund,\nJessica Livingston, Robert Morris, Greg Mcadoo, Fred Wilson,\nand Stephen Wolfram for\nreading drafts of this, and to Ed Dumbill for inviting me to speak.(The second part of this talk became Why Startups\nCondense in America.)" }, { "path": "data/PaulGrahamEssays/simply.txt", "content": "March 2021I try to write using ordinary words and simple sentences.That kind of writing is easier to read, and the easier something\nis to read, the more deeply readers will engage with it. The less\nenergy they expend on your prose, the more they'll have left for\nyour ideas.And the further they'll read. Most readers' energy tends to flag\npart way through an article or essay. If the friction of reading\nis low enough, more keep going till the end.There's an Italian dish called saltimbocca, which means \"leap\ninto the mouth.\" My goal when writing might be called saltintesta:\nthe ideas leap into your head and you barely notice the words that\ngot them there.It's too much to hope that writing could ever be pure ideas. You\nmight not even want it to be. But for most writers, most of the\ntime, that's the goal to aim for. The gap between most writing and\npure ideas is not filled with poetry.Plus it's more considerate to write simply. When you write in a\nfancy way to impress people, you're making them do extra work just\nso you can seem cool. It's like trailing a long train behind you\nthat readers have to carry.And remember, if you're writing in English, that a lot of your\nreaders won't be native English speakers. Their understanding of\nideas may be way ahead of their understanding of English. So you\ncan't assume that writing about a difficult topic means you can\nuse difficult words.Of course, fancy writing doesn't just conceal ideas. It can also\nconceal the lack of them. That's why some people write that way,\nto conceal the fact that they have \n nothing to say. Whereas writing\nsimply keeps you honest. If you say nothing simply, it will be\nobvious to everyone, including you.Simple writing also lasts better. People reading your stuff in the\nfuture will be in much the same position as people from other\ncountries reading it today. The culture and the language will have\nchanged. It's not vain to care about that, any more than it's vain\nfor a woodworker to build a chair to last.Indeed, lasting is not merely an accidental quality of chairs, or\nwriting. It's a sign you did a good job.But although these are all real advantages of writing simply, none\nof them are why I do it. The main reason I write simply is that it\noffends me not to. When I write a sentence that seems too complicated,\nor that uses unnecessarily intellectual words, it doesn't seem fancy\nto me. It seems clumsy.There are of course times when you want to use a complicated sentence\nor fancy word for effect. But you should never do it by accident.The other reason my writing ends up being simple is the way I do\nit. I write the first draft fast, then spend days editing it, trying\nto get everything just right. Much of this editing is cutting, and\nthat makes simple writing even simpler." }, { "path": "data/PaulGrahamEssays/smart.txt", "content": "October 2021If you asked people what was special about Einstein, most would say\nthat he was really smart. Even the ones who tried to give you a\nmore sophisticated-sounding answer would probably think this first.\nTill a few years ago I would have given the same answer myself. But\nthat wasn't what was special about Einstein. What was special about\nhim was that he had important new ideas. Being very smart was a\nnecessary precondition for having those ideas, but the two are not\nidentical.It may seem a hair-splitting distinction to point out that intelligence\nand its consequences are not identical, but it isn't. There's a big\ngap between them. Anyone who's spent time around universities and\nresearch labs knows how big. There are a lot of genuinely smart\npeople who don't achieve very much.I grew up thinking that being smart was the thing most to be desired.\nPerhaps you did too. But I bet it's not what you really want. Imagine\nyou had a choice between being really smart but discovering nothing\nnew, and being less smart but discovering lots of new ideas. Surely\nyou'd take the latter. I would. The choice makes me uncomfortable,\nbut when you see the two options laid out explicitly like that,\nit's obvious which is better.The reason the choice makes me uncomfortable is that being smart\nstill feels like the thing that matters, even though I know\nintellectually that it isn't. I spent so many years thinking it\nwas. The circumstances of childhood are a perfect storm for fostering\nthis illusion. Intelligence is much easier to measure than the value\nof new ideas, and you're constantly being judged by it. Whereas\neven the kids who will ultimately discover new things aren't usually\ndiscovering them yet. For kids that way inclined, intelligence is\nthe only game in town.There are more subtle reasons too, which persist long into adulthood.\nIntelligence wins in conversation, and thus becomes the basis of\nthe dominance hierarchy.\n[1]\nPlus having new ideas is such a new\nthing historically, and even now done by so few people, that society\nhasn't yet assimilated the fact that this is the actual destination,\nand intelligence merely a means to an end.\n[2]Why do so many smart people fail to discover anything new? Viewed\nfrom that direction, the question seems a rather depressing one.\nBut there's another way to look at it that's not just more optimistic,\nbut more interesting as well. Clearly intelligence is not the only\ningredient in having new ideas. What are the other ingredients?\nAre they things we could cultivate?Because the trouble with intelligence, they say, is that it's mostly\ninborn. The evidence for this seems fairly convincing, especially\nconsidering that most of us don't want it to be true, and the\nevidence thus has to face a stiff headwind. But I'm not going\nto get into that question here, because it's the other ingredients\nin new ideas that I care about, and it's clear that many of them\ncan be cultivated.That means the truth is excitingly different from the story I got\nas a kid. If intelligence is what matters, and also mostly inborn,\nthe natural consequence is a sort of Brave New World fatalism. The\nbest you can do is figure out what sort of work you have an \"aptitude\"\nfor, so that whatever intelligence you were born with will at least\nbe put to the best use, and then work as hard as you can at it.\nWhereas if intelligence isn't what matters, but only one of several\ningredients in what does, and many of those aren't inborn, things\nget more interesting. You have a lot more control, but the problem\nof how to arrange your life becomes that much more complicated.So what are the other ingredients in having new ideas? The fact\nthat I can even ask this question proves the point I raised earlier\n— that society hasn't assimilated the fact that it's this and not\nintelligence that matters. Otherwise we'd all know the answers\nto such a fundamental question.\n[3]I'm not going to try to provide a complete catalogue of the other\ningredients here. This is the first time I've posed\nthe question to myself this way, and I think it may take a while\nto answer. But I wrote recently about one of the most important:\nan obsessive interest in a particular topic. \nAnd this can definitely be cultivated.Another quality you need in order to discover new ideas is\nindependent-mindedness. I wouldn't want to \nclaim that this is\ndistinct from intelligence — I'd be reluctant to call someone smart\nwho wasn't independent-minded — but though largely inborn, this\nquality seems to be something that can be cultivated to some extent.There are general techniques for having new ideas — for example,\nfor working on your own projects\nand\nfor overcoming the obstacles you face with early work\n— and these\ncan all be learned. Some of them can be learned by societies. And\nthere are also collections of techniques for generating specific types\nof new ideas, like startup ideas and \nessay topics.And of course there are a lot of fairly mundane ingredients in\ndiscovering new ideas, like working hard, \ngetting enough sleep, avoiding certain\nkinds of stress, having the right colleagues, and finding tricks\nfor working on what you want even when it's not what you're supposed\nto be working on. Anything that prevents people from doing great\nwork has an inverse that helps them to. And this class of ingredients\nis not as boring as it might seem at first. For example, having new\nideas is generally associated with youth. But perhaps it's not youth\nper se that yields new ideas, but specific things that come with\nyouth, like good health and lack of responsibilities. Investigating\nthis might lead to strategies that will help people of any age to\nhave better ideas.One of the most surprising ingredients in having new ideas is writing\nability. There's a class of new ideas that are best discovered by\nwriting essays and books. And that \"by\" is deliberate: you don't\nthink of the ideas first, and then merely write them down. There\nis a kind of thinking that one does by writing, and if you're clumsy\nat writing, or don't enjoy doing it, that will get in your way if\nyou try to do this kind of thinking.\n[4]I predict the gap between intelligence and new ideas will turn out\nto be an interesting place. If we think of this gap merely as a measure\nof unrealized potential, it becomes a sort of wasteland that we try to\nhurry through with our eyes averted. But if we flip the question,\nand start inquiring into the other ingredients in new ideas that\nit implies must exist, we can mine this gap for discoveries about\ndiscovery.\nNotes[1]\nWhat wins in conversation depends on who with. It ranges from\nmere aggressiveness at the bottom, through quick-wittedness in the\nmiddle, to something closer to actual intelligence at the top,\nthough probably always with some component of quick-wittedness.[2]\nJust as intelligence isn't the only ingredient in having new\nideas, having new ideas isn't the only thing intelligence is useful\nfor. It's also useful, for example, in diagnosing problems and figuring\nout how to fix them. Both overlap with having new ideas, but both\nhave an end that doesn't.Those ways of using intelligence are much more common than having\nnew ideas. And in such cases intelligence is even harder to distinguish\nfrom its consequences.[3]\nSome would attribute the difference between intelligence and\nhaving new ideas to \"creativity,\" but this doesn't seem a very\nuseful term. As well as being pretty vague, it's shifted half a frame\nsideways from what we care about: it's neither separable from\nintelligence, nor responsible for all the difference between\nintelligence and having new ideas.[4]\nCuriously enough, this essay is an example. It started out\nas an essay about writing ability. But when I came to the distinction\nbetween intelligence and having new ideas, that seemed so much more\nimportant that I turned the original essay inside out, making that\nthe topic and my original topic one of the points in it. As in many\nother fields, that level of reworking is easier to contemplate once\nyou've had a lot of practice.\nThanks to Trevor Blackwell, Patrick Collison, Jessica Livingston,\nRobert Morris, Michael Nielsen, and Lisa Randall for reading drafts\nof this.\n" }, { "path": "data/PaulGrahamEssays/softwarepatents.txt", "content": "\nMarch 2006(This essay is derived from a talk at Google.)A few weeks ago I found to my surprise that I'd been granted four patents. \nThis was all the more surprising\nbecause I'd only applied for three. The patents aren't mine, of\ncourse. They were assigned to Viaweb, and became Yahoo's when they\nbought us. But the news set me thinking about the question of\nsoftware patents generally.Patents are a hard problem. I've had to advise most of the startups\nwe've funded about them, and despite years of experience I'm still\nnot always sure I'm giving the right advice.One thing I do feel pretty certain of is that if you're against\nsoftware patents, you're against patents in general. Gradually our\nmachines consist more and more of software. Things that used to\nbe done with levers and cams and gears are now done with loops and\ntrees and closures. There's nothing special about physical embodiments\nof control systems that should make them patentable, and the software\nequivalent not.Unfortunately, patent law is inconsistent on this point. Patent\nlaw in most countries says that algorithms aren't patentable. This\nrule is left over from a time when \"algorithm\" meant something like\nthe Sieve of Eratosthenes. In 1800, people could not see as readily\nas we can that a great many patents on mechanical objects were\nreally patents on the algorithms they embodied.Patent lawyers still have to pretend that's what they're doing when\nthey patent algorithms. You must not use the word \"algorithm\" in\nthe title of a patent application, just as you must not use the\nword \"essays\" in the title of a book. If you want to patent an\nalgorithm, you have to frame it as a computer system executing that algorithm.\nThen it's mechanical; phew. The default euphemism for algorithm\nis \"system and method.\" Try a patent search for that phrase and\nsee how many results you get.Since software patents are no different from hardware patents,\npeople who say \"software patents are evil\" are saying simply \"patents\nare evil.\" So why do so many people complain about software patents\nspecifically?I think the problem is more with the patent office than the concept\nof software patents. Whenever software meets government, bad things\nhappen, because software changes fast and government changes slow.\nThe patent office has been overwhelmed by both the volume and the\nnovelty of applications for software patents, and as a result they've\nmade a lot of mistakes.The most common is to grant patents that shouldn't be granted. To\nbe patentable, an invention has to be more than new. It also has\nto be non-obvious. And this, especially, is where the USPTO has\nbeen dropping the ball. Slashdot has an icon that expresses the\nproblem vividly: a knife and fork with the words \"patent pending\"\nsuperimposed.The scary thing is, this is the only icon they have for\npatent stories. Slashdot readers now take it for granted that a\nstory about a patent will be about a bogus patent.\nThat's how bad the problem has become.The problem with Amazon's notorious one-click patent, for example,\nis not that it's a software patent, but that it's obvious. Any\nonline store that kept people's shipping addresses would have\nimplemented this. The reason Amazon did it first was not that they\nwere especially smart, but because they were one of the earliest\nsites with enough clout to force customers to log in before they\ncould buy something. \n[1]We, as hackers, know the USPTO is letting people patent the knives\nand forks of our world. The problem is, the USPTO are not hackers.\nThey're probably good at judging new inventions for casting steel\nor grinding lenses, but they don't understand software yet.At this point an optimist would be tempted to add \"but they will\neventually.\" Unfortunately that might not be true. The problem\nwith software patents is an instance of a more general one: the\npatent office takes a while to understand new technology. If so,\nthis problem will only get worse, because the rate of technological\nchange seems to be increasing. In thirty years, the patent office\nmay understand the sort of things we now patent as software, but\nthere will be other new types of inventions they understand even\nless.Applying for a patent is a negotiation. You generally apply for a\nbroader patent than you think you'll be granted, and the examiners\nreply by throwing out some of your claims and granting others. So\nI don't really blame Amazon for applying for the one-click patent.\nThe big mistake was the patent office's, for not insisting on\nsomething narrower, with real technical content. By granting such\nan over-broad patent, the USPTO in effect slept with Amazon on the\nfirst date. Was Amazon supposed to say no?Where Amazon went over to the dark side was not in applying for the\npatent, but in enforcing it. A lot of companies (Microsoft, for\nexample) have been granted large numbers of preposterously over-broad\npatents, but they keep them mainly for defensive purposes. Like\nnuclear weapons, the main role of big companies' patent portfolios\nis to threaten anyone who attacks them with a counter-suit. Amazon's\nsuit against Barnes & Noble was thus the equivalent of a nuclear\nfirst strike.That suit probably hurt Amazon more than it helped them. Barnes &\nNoble was a lame site; Amazon would have crushed them anyway. To\nattack a rival they could have ignored, Amazon put a lasting black\nmark on their own reputation. Even now I think if you asked hackers\nto free-associate about Amazon, the one-click patent would turn up\nin the first ten topics.Google clearly doesn't feel that merely holding patents is evil.\nThey've applied for a lot of them. Are they hypocrites? Are patents\nevil?There are really two variants of that question, and people answering\nit often aren't clear in their own minds which they're answering.\nThere's a narrow variant: is it bad, given the current legal system,\nto apply for patents? and also a broader one: is it bad that the\ncurrent legal system allows patents?These are separate questions. For example, in preindustrial societies\nlike medieval Europe, when someone attacked you, you didn't call\nthe police. There were no police. When attacked, you were supposed\nto fight back, and there were conventions about how to do it. Was\nthis wrong? That's two questions: was it wrong to take justice\ninto your own hands, and was it wrong that you had to? We tend to\nsay yes to the second, but no to the first. If no one else will\ndefend you, you have to defend yourself. \n[2]The situation with patents is similar. Business is a kind of\nritualized warfare. Indeed, it evolved from actual warfare: most\nearly traders switched on the fly from merchants to pirates depending\non how strong you seemed. In business there are certain rules\ndescribing how companies may and may not compete with one another,\nand someone deciding that they're going to play by their own rules\nis missing the point. Saying \"I'm not going to apply for patents\njust because everyone else does\" is not like saying \"I'm not going\nto lie just because everyone else does.\" It's more like saying\n\"I'm not going to use TCP/IP just because everyone else does.\" Oh\nyes you are.A closer comparison might be someone seeing a hockey game for the\nfirst time, realizing with shock that the players were deliberately\nbumping into one another, and deciding that one would on no account\nbe so rude when playing hockey oneself.Hockey allows checking. It's part of the game. If your team refuses\nto do it, you simply lose. So it is in business. Under the present\nrules, patents are part of the game.What does that mean in practice? We tell the startups we fund not\nto worry about infringing patents, because startups rarely get sued\nfor patent infringement. There are only two reasons someone might\nsue you: for money, or to prevent you from competing with them.\nStartups are too poor to be worth suing for money. And in practice\nthey don't seem to get sued much by competitors, either. They don't\nget sued by other startups because (a) patent suits are an expensive\ndistraction, and (b) since the other startups are as young as they\nare, their patents probably haven't issued yet. \n[3]\nNor do startups,\nat least in the software business, seem to get sued much by established\ncompetitors. Despite all the patents Microsoft holds, I don't know\nof an instance where they sued a startup for patent infringement.\nCompanies like Microsoft and Oracle don't win by winning lawsuits.\nThat's too uncertain. They win by locking competitors out of their\nsales channels. If you do manage to threaten them, they're more\nlikely to buy you than sue you.When you read of big companies filing patent suits against smaller\nones, it's usually a big company on the way down, grasping at\nstraws. For example, Unisys's attempts to enforce their patent on\nLZW compression. When you see a big company threatening patent\nsuits, sell. When a company starts fighting over IP, it's a sign\nthey've lost the real battle, for users.A company that sues competitors for patent infringement is like\na defender who has been beaten so thoroughly that he turns to plead\nwith the referee. You don't do that if you can still reach the\nball, even if you genuinely believe you've been fouled. So a company\nthreatening patent suits is a company in trouble.When we were working on Viaweb, a bigger company in the e-commerce\nbusiness was granted a patent on online ordering, or something like\nthat. I got a call from a VP there asking if we'd like to license\nit. I replied that I thought the patent was completely bogus, and\nwould never hold up in court. \"Ok,\" he replied. \"So, are you guys\nhiring?\"If your startup grows big enough, however, you'll start to get sued,\nno matter what you do. If you go public, for example, you'll be\nsued by multiple patent trolls who hope you'll pay them off to go\naway. More on them later.In other words, no one will sue you for patent infringement till\nyou have money, and once you have money, people will sue you whether\nthey have grounds to or not. So I advise fatalism. Don't waste\nyour time worrying about patent infringement. You're probably\nviolating a patent every time you tie your shoelaces. At the start,\nat least, just worry about making something great and getting lots\nof users. If you grow to the point where anyone considers you worth\nattacking, you're doing well.We do advise the companies we fund to apply for patents, but not\nso they can sue competitors. Successful startups either get bought\nor grow into big companies. If a startup wants to grow into a big\ncompany, they should apply for patents to build up the patent\nportfolio they'll need to maintain an armed truce with other big\ncompanies. If they want to get bought, they should apply for patents\nbecause patents are part of the mating dance with acquirers.Most startups that succeed do it by getting bought, and most acquirers\ncare about patents. Startup acquisitions are usually a build-vs-buy\ndecision for the acquirer. Should we buy this little startup or\nbuild our own? And two things, especially, make them decide not\nto build their own: if you already have a large and rapidly growing\nuser base, and if you have a fairly solid patent application on\ncritical parts of your software.There's a third reason big companies should prefer buying to building:\nthat if they built their own, they'd screw it up. But few big\ncompanies are smart enough yet to admit this to themselves. It's\nusually the acquirer's engineers who are asked how hard it would\nbe for the company to build their own, and they overestimate their\nabilities. \n[4]\nA patent seems to change the balance. It gives the\nacquirer an excuse to admit they couldn't copy what you're doing.\nIt may also help them to grasp what's special about your technology.Frankly, it surprises me how small a role patents play in the\nsoftware business. It's kind of ironic, considering all the dire\nthings experts say about software patents stifling innovation, but\nwhen one looks closely at the software business, the most striking\nthing is how little patents seem to matter.In other fields, companies regularly sue competitors for patent\ninfringement. For example, the airport baggage scanning business\nwas for many years a cozy duopoly shared between two companies,\nInVision and L-3. In 2002 a startup called Reveal appeared, with\nnew technology that let them build scanners a third the size. They\nwere sued for patent infringement before they'd even released a\nproduct.You rarely hear that kind of story in our world. The one example\nI've found is, embarrassingly enough, Yahoo, which filed a patent\nsuit against a gaming startup called Xfire in 2005. Xfire doesn't\nseem to be a very big deal, and it's hard to say why Yahoo felt\nthreatened. Xfire's VP of engineering had worked at Yahoo on similar\nstuff-- in fact, he was listed as an inventor on the patent Yahoo\nsued over-- so perhaps there was something personal about it. My\nguess is that someone at Yahoo goofed. At any rate they didn't\npursue the suit very vigorously.Why do patents play so small a role in software? I can think of\nthree possible reasons.One is that software is so complicated that patents by themselves\nare not worth very much. I may be maligning other fields here, but\nit seems that in most types of engineering you can hand the details\nof some new technique to a group of medium-high quality people and\nget the desired result. For example, if someone develops a new\nprocess for smelting ore that gets a better yield, and you assemble\na team of qualified experts and tell them about it, they'll be able\nto get the same yield. This doesn't seem to work in software.\nSoftware is so subtle and unpredictable that \"qualified experts\"\ndon't get you very far.That's why we rarely hear phrases like \"qualified expert\" in the\nsoftware business. What that level of ability can get you is, say,\nto make your software compatible with some other piece of software--\nin eight months, at enormous cost. To do anything harder you need\nindividual brilliance. If you assemble a team of qualified experts\nand tell them to make a new web-based email program, they'll get\ntheir asses kicked by a team of inspired nineteen year olds.Experts can implement, but they can't design.\nOr rather, expertise in implementation is the only kind most people,\nincluding the experts themselves, can measure. \n[5]But design is a definite skill. It's not just an airy intangible.\nThings always seem intangible when you don't understand them.\nElectricity seemed an airy intangible to most people in 1800. Who\nknew there was so much to know about it? So it is with design.\nSome people are good at it and some people are bad at it, and there's\nsomething very tangible they're good or bad at.The reason design counts so much in software is probably that there\nare fewer constraints than on physical things. Building physical\nthings is expensive and dangerous. The space of possible choices\nis smaller; you tend to have to work as part of a larger group; and\nyou're subject to a lot of regulations. You don't have any of that\nif you and a couple friends decide to create a new web-based\napplication.Because there's so much scope for design in software, a successful\napplication tends to be way more than the sum of its patents. What\nprotects little companies from being copied by bigger competitors\nis not just their patents, but the thousand little things the big\ncompany will get wrong if they try.The second reason patents don't count for much in our world is that\nstartups rarely attack big companies head-on, the way Reveal did.\nIn the software business, startups beat established companies by\ntranscending them. Startups don't build desktop word processing\nprograms to compete with Microsoft Word. \n[6]\nThey build Writely.\nIf this paradigm is crowded, just wait for the next one; they run\npretty frequently on this route.Fortunately for startups, big companies are extremely good at denial.\nIf you take the trouble to attack them from an oblique angle, they'll\nmeet you half-way and maneuver to keep you in their blind spot. To\nsue a startup would mean admitting it was dangerous, and that often\nmeans seeing something the big company doesn't want to see. IBM\nused to sue its mainframe competitors regularly, but they didn't\nbother much about the microcomputer industry because they didn't\nwant to see the threat it posed. Companies building web based apps\nare similarly protected from Microsoft, which even now doesn't want\nto imagine a world in which Windows is irrelevant.The third reason patents don't seem to matter very much in software\nis public opinion-- or rather, hacker opinion. In a recent interview,\nSteve Ballmer coyly left open the possibility of attacking Linux\non patent grounds. But I doubt Microsoft would ever be so stupid.\nThey'd face the mother of all boycotts. And not just from the\ntechnical community in general; a lot of their own people would\nrebel.Good hackers care a lot about matters of principle, and they are\nhighly mobile. If a company starts misbehaving, smart people won't\nwork there. For some reason this seems to be more true in software\nthan other businesses. I don't think it's because hackers have\nintrinsically higher principles so much as that their skills are\neasily transferrable. Perhaps we can split the difference and say\nthat mobility gives hackers the luxury of being principled.Google's \"don't be evil\" policy may for this reason be the most\nvaluable thing they've discovered. It's very constraining in some\nways. If Google does do something evil, they get doubly whacked\nfor it: once for whatever they did, and again for hypocrisy. But\nI think it's worth it. It helps them to hire the best people, and\nit's better, even from a purely selfish point of view, to be\nconstrained by principles than by stupidity.(I wish someone would get this point across to the present\nadministration.)I'm not sure what the proportions are of the preceding three\ningredients, but the custom among the big companies seems to be not\nto sue the small ones, and the startups are mostly too busy and too\npoor to sue one another. So despite the huge number of software\npatents there's not a lot of suing going on. With one exception:\npatent trolls.Patent trolls are companies consisting mainly of lawyers whose whole\nbusiness is to accumulate patents and threaten to sue companies who\nactually make things. Patent trolls, it seems safe to say, are\nevil. I feel a bit stupid saying that, because when you're saying\nsomething that Richard Stallman and Bill Gates would both agree\nwith, you must be perilously close to tautologies.The CEO of Forgent, one of the most notorious patent trolls, says\nthat what his company does is \"the American way.\" Actually that's\nnot true. The American way is to make money by creating wealth, not by suing people. \n[7]\nWhat companies like Forgent do is actually the proto-industrial\nway. In the period just before the industrial revolution, some of\nthe greatest fortunes in countries like England and France were\nmade by courtiers who extracted some lucrative right from the crown--\nlike the right to collect taxes on the import of silk-- and then\nused this to squeeze money from the merchants in that business. So\nwhen people compare patent trolls to the mafia, they're more right\nthan they know, because the mafia too are not merely bad, but bad\nspecifically in the sense of being an obsolete business model.Patent trolls seem to have caught big companies by surprise. In\nthe last couple years they've extracted hundreds of millions of\ndollars from them. Patent trolls are hard to fight precisely because\nthey create nothing. Big companies are safe from being sued by\nother big companies because they can threaten a counter-suit. But\nbecause patent trolls don't make anything, there's nothing they can\nbe sued for. I predict this loophole will get closed fairly quickly,\nat least by legal standards. It's clearly an abuse of the system,\nand the victims are powerful.\n[8]But evil as patent trolls are, I don't think they hamper innovation\nmuch. They don't sue till a startup has made money, and by that\npoint the innovation that generated it has already happened. I\ncan't think of a startup that avoided working on some problem because\nof patent trolls.So much for hockey as the game is played now. What about the more\ntheoretical question of whether hockey would be a better game without\nchecking? Do patents encourage or discourage innovation?This is a very hard question to answer in the general case. People\nwrite whole books on the topic. One of my main hobbies is the\nhistory of technology, and even though I've studied the subject for\nyears, it would take me several weeks of research to be able to say\nwhether patents have in general been a net win.One thing I can say is that 99.9% of the people who express opinions\non the subject do it not based on such research, but out of a kind\nof religious conviction. At least, that's the polite way of putting\nit; the colloquial version involves speech coming out of organs not\ndesigned for that purpose.Whether they encourage innovation or not, patents were at least\nintended to. You don't get a patent for nothing. In return for\nthe exclusive right to use an idea, you have to publish it,\nand it was largely to encourage such openness that patents were\nestablished.Before patents, people protected ideas by keeping them secret. With\npatents, central governments said, in effect, if you tell everyone\nyour idea, we'll protect it for you. There is a parallel here to\nthe rise of civil order, which happened at roughly the same time.\nBefore central governments were powerful enough to enforce order,\nrich people had private armies. As governments got more powerful,\nthey gradually compelled magnates to cede most responsibility for\nprotecting them. (Magnates still have bodyguards, but no longer\nto protect them from other magnates.)Patents, like police, are involved in many abuses. But in both\ncases the default is something worse. The choice is not \"patents\nor freedom?\" any more than it is \"police or freedom?\" The actual\nquestions are respectively \"patents or secrecy?\" and \"police or\ngangs?\"As with gangs, we have some idea what secrecy would be like, because\nthat's how things used to be. The economy of medieval Europe was\ndivided up into little tribes, each jealously guarding their\nprivileges and secrets. In Shakespeare's time, \"mystery\" was\nsynonymous with \"craft.\" Even today we can see an echo of the\nsecrecy of medieval guilds, in the now pointless secrecy of the\nMasons.The most memorable example of medieval industrial secrecy is probably\nVenice, which forbade glassblowers to leave the city, and sent\nassassins after those who tried. We might like to think we wouldn't\ngo so far, but the movie industry has already tried to pass laws\nprescribing three year prison terms just for putting movies on\npublic networks. Want to try a frightening thought experiment? If\nthe movie industry could have any law they wanted, where would they\nstop? Short of the death penalty, one assumes, but how close would\nthey get?Even worse than the spectacular abuses might be the overall decrease\nin efficiency that would accompany increased secrecy. As anyone\nwho has dealt with organizations that operate on a \"need to know\"\nbasis can attest, dividing information up into little cells is\nterribly inefficient. The flaw in the \"need to know\" principle is\nthat you don't know who needs to know something. An idea\nfrom one area might spark a great discovery in another. But the\ndiscoverer doesn't know he needs to know it.If secrecy were the only protection for ideas, companies wouldn't\njust have to be secretive with other companies; they'd have to be\nsecretive internally. This would encourage what is already the\nworst trait of big companies.I'm not saying secrecy would be worse than patents, just that we\ncouldn't discard patents for free. Businesses would become more\nsecretive to compensate, and in some fields this might get ugly.\nNor am I defending the current patent system. There is clearly a\nlot that's broken about it. But the breakage seems to affect\nsoftware less than most other fields.In the software business I know from experience whether patents\nencourage or discourage innovation, and the answer is the type that\npeople who like to argue about public policy least like to hear:\nthey don't affect innovation much, one way or the other. Most\ninnovation in the software business happens in startups, and startups\nshould simply ignore other companies' patents. At least, that's\nwhat we advise, and we bet money on that advice.The only real role of patents, for most startups, is as an element\nof the mating dance with acquirers. There patents do help a little.\nAnd so they do encourage innovation indirectly, in that they give\nmore power to startups, which is where, pound for pound, the most\ninnovation happens. But even in the mating dance, patents are of\nsecondary importance. It matters more to make something great and\nget a lot of users.Notes[1]\nYou have to be careful here, because a great discovery often\nseems obvious in retrospect. One-click ordering, however, is not\nsuch a discovery.[2]\n\"Turn the other cheek\" skirts the issue; the critical question\nis not how to deal with slaps, but sword thrusts.[3]\nApplying for a patent is now very slow, but it might actually\nbe bad if that got fixed. At the moment the time it takes to get\na patent is conveniently just longer than the time it takes a startup\nto succeed or fail.[4]\nInstead of the canonical \"could you build this?\" maybe the corp\ndev guys should be asking \"will you build this?\" or even \"why haven't\nyou already built this?\"[5]\nDesign ability is so hard to measure that you can't even trust\nthe design world's internal standards. You can't assume that someone\nwith a degree in design is any good at design, or that an eminent\ndesigner is any better than his peers. If that worked, any company\ncould build products as good as Apple's just by hiring \nsufficiently qualified designers.[6]\nIf anyone wanted to try, we'd be interested to hear from them.\nI suspect it's one of those things that's not as hard as everyone\nassumes.[7]\nPatent trolls can't even claim, like speculators, that they\n\"create\" liquidity.[8]\nIf big companies don't want to wait for the government to take\naction, there is a way to fight back themselves. For a long time\nI thought there wasn't, because there was nothing to grab onto.\nBut there is one resource patent trolls need: lawyers. Big technology\ncompanies between them generate a lot of legal business. If they\nagreed among themselves never to do business with any firm employing\nanyone who had worked for a patent troll, either as an employee or\nas outside counsel, they could probably starve the trolls of the\nlawyers they need.Thanks to Dan Bloomberg, Paul Buchheit, Sarah Harlin, \nJessica Livingston, and Peter Norvig\nfor reading drafts of this, to Joel Lehrer and Peter Eng for answering\nmy questions about patents, and to Ankur Pansari for inviting me\nto speak." }, { "path": "data/PaulGrahamEssays/spam.txt", "content": "\n\nLike to build things? Try Hacker\nNews.\n\n\n\n\nAugust 2002(This article describes the spam-filtering techniques\nused in the spamproof web-based mail reader we\nbuilt to exercise Arc. An\nimproved algorithm is described in Better\nBayesian Filtering.)I think it's possible to stop spam, and that \ncontent-based filters are the way to do it.\nThe Achilles heel of the spammers is their message.\nThey can circumvent any other barrier you set up. They have so far, at\nleast. But they have to deliver their message, whatever it\nis. If we can write software that recognizes their messages,\nthere is no way they can get around that._ _ _To the recipient, spam is easily recognizable. If you hired \nsomeone to read your mail and discard the spam, they would\nhave little trouble doing it. How much do we have\nto do, short of AI, to automate this process?I think we will be able to solve the problem with fairly\nsimple algorithms. In fact, I've found that you can filter\npresent-day spam acceptably well using nothing more than a\nBayesian combination of the spam probabilities of individual\nwords. Using a slightly tweaked (as described below) Bayesian\nfilter, we now miss less than 5 per 1000 spams, with 0 false positives.The statistical approach is not usually the first one people\ntry when they write spam filters. Most hackers' first instinct is\nto try to write software that recognizes individual properties of\nspam. You look at spams\nand you think, the gall of these guys to try sending me mail \nthat begins \"Dear Friend\" or has a subject line that's all\nuppercase and ends in eight exclamation points. I can filter\nout that stuff with about one line of code.And so you do,\nand in the beginning it works. A few simple rules will take\na big bite out of your incoming spam. Merely looking\nfor the word \"click\" will catch 79.7% of the\nemails in my spam corpus, with only 1.2% false positives.I spent about six months writing software that looked for\nindividual spam features before I tried the statistical\napproach. What I found was that recognizing that last few\npercent of spams got very hard, and that as I\nmade the filters stricter I got more false positives.False positives are innocent emails that get mistakenly\nidentified as spams.\nFor most users,\nmissing legitimate email is\nan order of magnitude worse than receiving spam, so a\nfilter that yields false positives is like an acne cure\nthat carries a risk of death to the patient.The more spam a user gets, the less\nlikely he'll be to notice one innocent mail sitting in his\nspam folder. And strangely enough, the better your spam filters get,\nthe more dangerous false positives become, because when the\nfilters are really good, users will be more likely to\nignore everything they catch.I don't know why I avoided trying the statistical approach\nfor so long. I think it was because I got addicted to\ntrying to identify spam features myself, as if I were playing\nsome kind of competitive game with the spammers. (Nonhackers\ndon't often realize this, but most hackers are very competitive.)\nWhen I did try statistical analysis, I\nfound immediately that it was much cleverer than I had been.\nIt discovered, of course, that terms like \"virtumundo\" and\n\"teens\" were good indicators of spam. But it also\ndiscovered that \"per\" and \"FL\" and \"ff0000\" are good \nindicators of spam. In fact, \"ff0000\" (html for bright red)\nturns out to be as good an indicator of spam as any \npornographic term._ _ _Here's a sketch of how I do statistical filtering. I start\nwith one corpus of spam and one of nonspam mail. At the\nmoment each one has about 4000 messages in it. I scan\nthe entire text, including headers and embedded html\nand javascript, of each message in each corpus.\nI currently consider alphanumeric characters,\ndashes, apostrophes, and dollar signs to be part of tokens,\nand everything else to be a token separator. (There is\nprobably room for improvement here.) I ignore tokens that\nare all digits, and I also ignore html comments, not even\nconsidering them as token separators.I count the number\nof times each token (ignoring case, currently) occurs in\neach corpus. At this stage I end up with two large hash \ntables, one for each corpus, mapping tokens to number\nof occurrences.Next I create a third hash table, this time mapping\neach token to the probability that an email containing it is a spam,\nwhich I calculate as follows [1]:\n\n(let ((g (* 2 (or (gethash word good) 0)))\n (b (or (gethash word bad) 0)))\n (unless (< (+ g b) 5)\n (max .01\n (min .99 (float (/ (min 1 (/ b nbad))\n (+ (min 1 (/ g ngood)) \n (min 1 (/ b nbad)))))))))\n\nwhere word is the token whose probability we're\ncalculating, good and bad are the hash tables\nI created in the first step, and ngood and nbad\nare the number of nonspam and spam messages respectively.I explained this as code to show a couple of important details.\nI want to bias the probabilities slightly to avoid false\npositives, and by trial and error I've found that a good\nway to do it is to double all the numbers in good.\nThis helps to distinguish between words that occasionally\ndo occur in legitimate email and words that almost never do. \nI only consider words that occur more than five times in\ntotal (actually, because of the doubling, occurring three \ntimes in nonspam mail would be enough). And then there is\nthe question of what probability to assign to words that\noccur in one corpus but not the other. Again by trial and \nerror I chose .01 and .99. There may be room for tuning\nhere, but as the corpus grows such tuning will happen\nautomatically anyway.The especially observant will notice that while I consider\neach corpus to be a single long stream of text for purposes\nof counting occurrences, I use the number of emails in\neach, rather than their combined length, as the divisor \nin calculating spam probabilities. This adds another\nslight bias to protect against false positives.When new mail arrives, it is scanned into tokens, and\nthe most interesting fifteen tokens, where interesting is \nmeasured by how far their spam probability is from a\nneutral .5, are used to calculate the probability that\nthe mail is spam. If probs\nis a list of the fifteen individual probabilities, you\ncalculate the \ncombined probability thus:\n\n(let ((prod (apply #'* probs)))\n (/ prod (+ prod (apply #'* (mapcar #'(lambda (x) \n (- 1 x))\n probs)))))\n\nOne question that arises in\npractice is what probability to assign to a word you've\nnever seen, i.e. one that doesn't occur in the hash table\nof word probabilities. I've found, again by trial and\nerror, that .4 is a good number to use. If you've never\nseen a word before, it is probably fairly innocent; spam\nwords tend to be all too familiar.There are examples of this algorithm being applied to\nactual emails in an appendix at the end.I treat mail as spam if the algorithm above gives it a\nprobability of more than .9 of being spam. But in practice\nit would not matter much where I put this threshold, because\nfew probabilities end up in the middle of the range._ _ _One great advantage of the statistical approach is that you\ndon't have to read so many spams. Over the past six months,\nI've read literally thousands of spams, and it is really\nkind of demoralizing. Norbert Wiener said if you compete\nwith slaves you become a slave, and there is something\nsimilarly degrading about competing with spammers. To\nrecognize individual spam features you have to try to get\ninto the mind of the spammer, and frankly I want to spend\nas little time inside the minds of spammers as possible.But the real advantage of the Bayesian approach, of course,\nis that you know what\nyou're measuring. Feature-recognizing filters like\nSpamAssassin assign a spam \"score\" to email. The Bayesian\napproach assigns an actual probability. The problem with\na \"score\" is that no one knows what it means. The user\ndoesn't know what it means, but worse still, neither does\nthe developer of the filter. How many points should an\nemail get for having the word \"sex\" in it? A probability\ncan of course be mistaken, but there is little ambiguity\nabout what it means, or how evidence should be combined\nto calculate it. Based on my corpus, \"sex\" indicates\na .97 probability of the containing email being a spam,\nwhereas \"sexy\" indicates .99 probability.\nAnd Bayes' Rule, equally unambiguous, says that an email\ncontaining both words would, in the (unlikely)\nabsence of any other evidence, have a 99.97% chance of\nbeing a spam.Because it is measuring probabilities, the Bayesian approach\nconsiders all the evidence in the email, both good and bad.\nWords that occur disproportionately rarely\nin spam (like \"though\" or \"tonight\" or \"apparently\")\ncontribute as much to decreasing the probability as\nbad words like \"unsubscribe\" and \"opt-in\" do to\nincreasing it. So an otherwise innocent email that happens\nto include the word \"sex\" is not going to get tagged as spam.Ideally, of course, the probabilities should be calculated\nindividually for each user. I get a lot of email containing\nthe word \"Lisp\", and (so far) no spam that does. So a word\nlike that is effectively a kind of password for sending\nmail to me. In my earlier spam-filtering software, the user\ncould set up a list of such words and mail containing\nthem would automatically get past the filters. On my\nlist I put words like \"Lisp\" and also my zipcode, so\nthat (otherwise rather spammy-sounding) receipts from\nonline orders would get through. I thought I was being\nvery clever, but I found that the Bayesian filter did the\nsame thing for me, and moreover discovered of a lot of words I\nhadn't thought of.When I said at the start that our filters let through less than\n5 spams per 1000 with 0 false positives, I'm talking about\nfiltering my mail based on a corpus of my mail. But these\nnumbers are not misleading, because that is the approach I'm\nadvocating: filter each user's mail based on the spam and\nnonspam mail he receives. Essentially, each user should\nhave two delete buttons, ordinary delete and delete-as-spam.\nAnything deleted as spam goes into the spam corpus, \nand everything else goes into the nonspam corpus.You could start\nusers with a seed filter, but ultimately each user should have\nhis own per-word probabilities based on the actual mail he\nreceives. This (a) makes the filters more effective, (b) lets\neach user decide their own precise definition of spam,\nand (c) perhaps best of all makes it hard for spammers\nto tune mails to get through the filters. If a lot of the \nbrain of the filter is in the individual databases, then \nmerely tuning spams to get through the seed filters\nwon't guarantee anything about how well they'll get through\nindividual users' varying and much more trained filters.Content-based spam filtering is often combined with a whitelist,\na list of senders whose mail can be accepted with no filtering.\nOne easy way to build such a\nwhitelist is to keep a list of every address the user has\never sent mail to. If a mail reader has a delete-as-spam\nbutton then you could also add the from address\nof every email the user has deleted as ordinary trash.I'm an advocate of whitelists, but more as a way to save \ncomputation than as a way to improve filtering. I used to think that\nwhitelists would make filtering easier, because you'd\nonly have to filter email from people you'd never heard\nfrom, and someone sending you mail for the first time is\nconstrained by convention in what they can say to you.\nSomeone you already know might send you an email talking about sex,\nbut someone sending you mail for the first time would not \nbe likely to. The problem is, people can have more than one \nemail address, so a new from-address doesn't guarantee that\nthe sender is writing to you for the first time.\nIt is not unusual\nfor an old friend (especially if he is a hacker) to suddenly\nsend you an email with a new from-address, so you can't\nrisk false positives by filtering mail from unknown \naddresses especially stringently.In a sense, though, my filters do themselves embody a kind\nof whitelist (and blacklist) because they are based on\nentire messages, including the headers. So to that\nextent they \"know\" the email addresses of trusted senders\nand even the routes by which mail gets from them to me. \nAnd they know the same about spam, including the server \nnames, mailer versions, and protocols._ _ _If I thought that I could keep up current rates of spam\nfiltering, I would consider this problem solved. But it\ndoesn't mean much to be able to filter out most present-day\nspam, because spam evolves.\nIndeed, most \nantispam techniques so far have been like pesticides that\ndo nothing more than create a new, resistant strain of bugs.I'm more hopeful about Bayesian filters, because they evolve\nwith the spam. So as spammers start using \"c0ck\" \ninstead of \"cock\" to evade simple-minded spam filters \nbased on individual words, Bayesian filters automatically\nnotice. Indeed, \"c0ck\" is far more damning evidence than\n\"cock\", and Bayesian filters know precisely how much more.Still, anyone who proposes a plan for spam filtering has to\nbe able to answer the question: if the spammers knew\nexactly what you were doing,\nhow well could they get past you? For example, I think that if\nchecksum-based spam filtering becomes a serious obstacle,\nthe spammers will just\nswitch to mad-lib techniques for generating message bodies.To beat Bayesian filters, it would not be enough for spammers\nto make their emails unique or to stop using individual\nnaughty words. They'd have to make their mails indistinguishable\nfrom your ordinary mail. And this I think would severely\nconstrain them. Spam is mostly sales\npitches, so unless your regular mail is all sales pitches,\nspams will inevitably have a different character. And \nthe spammers would also, of course, have to change (and keep \nchanging) their whole infrastructure, because otherwise\nthe headers would look as bad to the Bayesian filters as ever,\nno matter what they did to the message body. I don't know\nenough about the infrastructure that spammers use to know\nhow hard it would be to make the headers look innocent, but\nmy guess is that it would be even harder than making the \nmessage look innocent.Assuming they could solve the problem of the headers,\nthe spam of the future will probably look something like\nthis:\n\nHey there. Thought you should check out the following:\nhttp://www.27meg.com/foo\n\nbecause that is about as much sales pitch as content-based\nfiltering will leave the spammer room to make. (Indeed, it\nwill be hard even to get this past filters, because if everything\nelse in the email is neutral, the spam probability will hinge on\nthe url, and it will take some effort to make that look neutral.)Spammers range from businesses running so-called\nopt-in lists who don't even try to conceal their identities,\nto guys who hijack mail servers to send out spams promoting\nporn sites. If we use filtering to whittle their\noptions down to mails like the one above, that should\npretty much put the spammers on the \"legitimate\" end of\nthe spectrum out of business; they feel obliged\nby various state laws to include boilerplate about why\ntheir spam is not spam, and how to cancel your\n\"subscription,\" and that kind of text is easy to \nrecognize.(I used to think it was naive to believe that stricter laws\nwould decrease spam. Now I think that while stricter laws \nmay not decrease the amount of spam that spammers send,\nthey can certainly help filters to decrease the amount of \nspam that recipients actually see.)All along the spectrum, if you restrict the sales pitches spammers\ncan make, you will inevitably tend to put them out of\nbusiness. That word business is an important one to\nremember. The spammers are businessmen. They send spam because\nit works. It works because although the response rate\nis abominably low (at best 15 per million, vs 3000 per\nmillion for a catalog mailing), the cost, to them, is \npractically nothing. The cost is enormous for the recipients, \nabout 5 man-weeks for each million recipients who spend \na second to delete the spam, but the spammer\ndoesn't have to pay that.Sending spam does cost the spammer something, though. [2]\nSo the lower we can get the\nresponse rate-- whether by filtering, or by using filters to force\nspammers to dilute their pitches-- the fewer businesses will find it\nworth their while to send spam.The reason the spammers use the kinds of \nsales\npitches that they do is to increase response rates.\nThis is possibly even more disgusting\nthan getting inside the mind of a spammer,\nbut let's take a quick look inside the mind of someone\nwho responds to a spam. This person is either\nastonishingly credulous or deeply in denial about their \nsexual interests. In either case, repulsive or\nidiotic as the spam seems to us, it is exciting\nto them. The spammers wouldn't say these things if they\ndidn't sound exciting. And \"thought you\nshould check out the following\" is just not going to\nhave nearly the pull with the spam recipient as\nthe kinds of things that spammers say now.\nResult: if it can't contain exciting sales pitches,\nspam becomes less effective as a marketing vehicle,\nand fewer businesses want to use it.That is the big win in the end. I started writing spam\nfiltering software because I didn't want have to look at\nthe stuff anymore.\nBut if we get good enough at filtering\nout spam, it will stop working, and the spammers\nwill actually stop sending it._ _ _Of all the approaches to fighting spam, from software to laws,\nI believe Bayesian filtering will be the single most\neffective. But I also\nthink that the more different kinds of antispam efforts\nwe undertake, the better, because any measure that\nconstrains spammers will tend to make filtering easier.\nAnd even within the world of content-based filtering, I think\nit will be a good thing if there are many different kinds\nof software being used simultaneously. The more different \nfilters there are, the harder it will be for\nspammers to tune spams to get through them.\nAppendix: Examples of FilteringHere is an example of a spam that arrived while I was writing\nthis article. The fifteen most interesting words in this spam are:\n\nqvp0045\nindira\nmx-05\nintimail\n$7500\nfreeyankeedom\ncdo\nbluefoxmedia\njpg\nunsecured\nplatinum\n3d0\nqves\n7c5\n7c266675\n\nThe words are a mix of stuff from the headers and from the\nmessage body, which is typical of spam. Also typical of spam\nis that every one of these words has a spam probability,\nin my database, of .99. In fact there are more than fifteen words\nwith probabilities of .99, and these are just the first\nfifteen seen.Unfortunately that makes this email a boring example of\nthe use of Bayes' Rule. To see an interesting variety of\nprobabilities we have to look at this actually quite\natypical spam.The fifteen most interesting words in this spam, with their probabilities,\nare:\n\nmadam 0.99\npromotion 0.99\nrepublic 0.99\nshortest 0.047225013\nmandatory 0.047225013\nstandardization 0.07347802\nsorry 0.08221981\nsupported 0.09019077\npeople's 0.09019077\nenter 0.9075001\nquality 0.8921298\norganization 0.12454646\ninvestment 0.8568143\nvery 0.14758544\nvaluable 0.82347786 \n\nThis time the evidence is a mix of good and bad. A word like \n\"shortest\" is almost as much evidence for innocence as a\nword like \"madam\" or \"promotion\" is for guilt. But still the\ncase for guilt is stronger. If you combine these numbers\naccording to Bayes' Rule, the resulting probability is .9027.\"Madam\" is obviously from spams beginning\n\"Dear Sir or Madam.\" They're not very common, but the\nword \"madam\" never occurs in my legitimate email, and\nit's all about the ratio.\"Republic\" scores high because\nit often shows up in Nigerian scam emails, and also occurs once\nor twice in spams referring to Korea and South Africa.\nYou might say that it's\nan accident that it thus helps identify this spam. But I've\nfound when examining spam probabilities that there are\na lot of these accidents, and they have an uncanny tendency to\npush things in the right direction rather than the wrong one.\nIn this case, it is not entirely a coincidence that the word\n\"Republic\" occurs in Nigerian scam emails and this spam.\nThere is a whole class of dubious business propositions involving\nless developed countries, and these in turn are more likely\nto have names that specify explicitly (because they aren't) that they\nare republics.[3]On the other hand, \"enter\" is a genuine miss. It occurs\nmostly in unsubscribe instructions, but here is used in a\ncompletely innocent way. Fortunately the statistical approach is\nfairly robust, and can tolerate quite a lot of misses\nbefore the results start to be thrown off.For comparison, \nhere is an example of that rare bird, a spam that\ngets through the filters. Why? Because by sheer chance it happens\nto be loaded with words that occur in my actual email:\n\nperl 0.01\npython 0.01\ntcl 0.01\nscripting 0.01\nmorris 0.01\ngraham 0.01491078\nguarantee 0.9762507\ncgi 0.9734398\npaul 0.027040077\nquite 0.030676773\npop3 0.042199217\nvarious 0.06080265\nprices 0.9359873\nmanaged 0.06451222\ndifficult 0.071706355\n\nThere are a couple pieces of good news here. First, this mail\nprobably wouldn't get through the filters of someone who didn't\nhappen to specialize in programming languages and have a good\nfriend called Morris. For the average user, all the top five words here \nwould be neutral and would not contribute to the spam probability.Second, I think filtering based on word pairs \n(see below) might well\ncatch this one: \"cost effective\", \"setup fee\", \"money back\" -- pretty\nincriminating stuff. And of course if they continued to spam me\n(or a network I was part of), \"Hostex\" itself would be\nrecognized as a spam term.Finally, here is an innocent email.\nIts fifteen most interesting words are as follows:\n\ncontinuation 0.01\ndescribe 0.01\ncontinuations 0.01\nexample 0.033600237\nprogramming 0.05214485 \ni'm 0.055427782\nexamples 0.07972858 \ncolor 0.9189189 \nlocalhost 0.09883721\nhi 0.116539136\ncalifornia 0.84421706\nsame 0.15981844\nspot 0.1654587\nus-ascii 0.16804294\nwhat 0.19212411\n\nMost of the words here indicate the mail is an innocent one.\nThere are two bad smelling words, \"color\"\n(spammers love colored fonts) and \"California\"\n(which occurs in testimonials and also in menus in\nforms), but they are not enough to outweigh obviously\ninnocent words like \"continuation\" and \"example\".It's interesting that \"describe\" rates as so thoroughly\ninnocent. It hasn't occurred in a\nsingle one of my 4000 spams. The data turns out to be\nfull of such surprises. One of the things you learn\nwhen you analyze spam texts is how\nnarrow a subset of the language spammers operate in. It's\nthat fact, together with the equally characteristic vocabulary\nof any individual user's mail, that makes Bayesian filtering\na good bet.Appendix: More IdeasOne idea that I haven't tried yet is to filter based on\nword pairs, or even triples, rather than individual words.\nThis should yield a much sharper estimate of the probability.\nFor example, in my current database, the word \"offers\"\nhas a probability of .96. If you based the probabilities \non word pairs, you'd end up with \"special offers\"\nand \"valuable offers\" having probabilities of .99\nand, say, \"approach offers\" (as in \"this approach offers\")\nhaving a probability of .1 or less.The reason I haven't done this is that filtering based on\nindividual words already works so well. But it does\nmean that there is room to tighten the filters if spam\ngets harder to detect.\n(Curiously, a filter based on word pairs would be\nin effect a Markov-chaining text generator running\nin reverse.)Specific spam features (e.g. not seeing the recipient's\naddress in the to: field) do of course have value in \nrecognizing spam. They can be considered in this\nalgorithm by treating them as virtual words. I'll probably\ndo this in future versions, at least for a handful of the\nmost egregious spam indicators. Feature-recognizing\nspam filters are right in many details; what they lack\nis an overall discipline for combining evidence.Recognizing nonspam features may be more important than\nrecognizing spam features. False positives are such a\nworry that they demand extraordinary measures. I will\nprobably in future versions add a second level of testing\ndesigned specifically to avoid false positives. If a\nmail triggers this second level of filters it will be accepted\neven if its spam probability is above the threshold.I don't expect this second level of filtering to be Bayesian.\nIt will inevitably \nbe not only ad hoc, but based on guesses, because the number of\nfalse positives will not tend to be large enough to notice patterns.\n(It is just as well, anyway, if a backup system doesn't rely on the same\ntechnology as the primary system.)Another thing I may try in the future is to focus extra attention\non specific parts of the email. For example, about 95% of current\nspam includes the url of a site they want\nyou to visit. (The remaining 5% want you to call a phone number,\nreply by email or to a US mail address, or in a few\ncases to buy a certain stock.) The url is in such cases\npractically enough by itself to determine whether the email\nis spam.Domain names differ from the rest of the text in\na (non-German) email in that they often consist of several\nwords stuck together. Though computationally expensive \nin the general case, it might be worth trying to \ndecompose them. If a filter has never seen the\ntoken \"xxxporn\" before it will have an individual spam\nprobability of .4, whereas \"xxx\" and \"porn\" individually\nhave probabilities (in my corpus) of .9889 and .99\nrespectively, and a combined probability of .9998.I expect decomposing domain names to become more\nimportant as spammers are gradually forced to stop using\nincriminating words in the text of their messages. (A url\nwith an ip address is of course an extremely incriminating sign,\nexcept in the mail of a few sysadmins.)It might be a good idea to have a cooperatively maintained\nlist of urls promoted by spammers. We'd need a trust metric\nof the type studied by Raph Levien to prevent malicious\nor incompetent submissions, but if we had such a thing it\nwould provide a boost to any filtering software. It would\nalso be a convenient basis for boycotts.Another way to test dubious urls would be to send out a\ncrawler to look at the site before the user looked at the\nemail mentioning it. You could use a Bayesian filter to\nrate the site just as you would an email, and whatever\nwas found on the site could be included in calculating\nthe probability of the email being a spam. A url that led\nto a redirect would of course be especially suspicious.One cooperative project that I think really would be a good\nidea would be to accumulate a giant corpus of spam. A large,\nclean corpus is the key to making Bayesian filtering work\nwell. Bayesian filters could actually use the corpus as\ninput. But such a corpus would be useful for other kinds\nof filters too, because it could be used to test them.Creating such a corpus poses some technical problems. We'd\nneed trust metrics to prevent malicious or incompetent\nsubmissions, of course. We'd also need ways of erasing \npersonal information (not just to-addresses and ccs, but\nalso e.g. the arguments to unsubscribe urls, which often\nencode the to-address) from mails in the corpus. If anyone\nwants to take on this project, it would be a good thing for\nthe world.Appendix: Defining SpamI think there is a rough\nconsensus on what spam is, but it would be useful to have\nan explicit definition. We'll need to do this if we want to establish\na central corpus of spam, or even to compare spam filtering\nrates meaningfully.To start with, spam is not unsolicited commercial email.\nIf someone in my neighborhood heard that I was looking for an old\nRaleigh three-speed in good condition, and sent me an email\noffering to sell me one, I'd be delighted, and yet this\nemail would be both commercial and unsolicited. The\ndefining feature of spam (in fact, its raison d'etre)\nis not that it is unsolicited, but that it is automated.It is merely incidental, too, that spam is usually commercial.\nIf someone started sending mass email to support some political\ncause, for example, it would be just as much spam as email\npromoting a porn site.I propose we define spam as unsolicited automated email.\nThis definition thus includes some email\nthat many legal definitions of spam don't. Legal definitions\nof spam, influenced presumably by lobbyists, tend to exclude\nmail sent by companies that have an \"existing relationship\" with\nthe recipient. But buying something from a company, for\nexample, does not imply that you have solicited\nongoing email from them.\nIf I order something from an online\nstore, and they then send me a stream of spam, it's still\nspam.Companies sending spam often give you a way to \"unsubscribe,\"\nor ask you to go to their site and change your \"account\npreferences\" if you want to stop getting spam. This is\nnot enough to stop the mail from being spam. Not opting out\nis not the same as opting in. Unless the \nrecipient explicitly checked a clearly labelled box (whose\ndefault was no) asking to receive the email, then it is spam.In some business relationships, you do implicitly solicit\ncertain kinds of mail. When you order online, I think you\nimplicitly solicit a receipt, and notification when the\norder ships.\nI don't mind when Verisign sends me mail warning that\na domain name is about to expire (at least, if they are the\nactual \nregistrar for it). But when Verisign sends me\nemail offering a FREE Guide to Building My\nE-Commerce Web Site, that's spam.\nNotes:[1] The examples in this article are translated\ninto Common Lisp for, believe it or not, greater accessibility.\nThe application described here is one that we wrote in order to\ntest a new Lisp dialect called Arc that is \nnot yet released.[2] Currently the lowest rate seems to be about $200 to send a million spams.\nThat's very cheap, 1/50th of a cent per spam.\nBut filtering out 95%\nof spam, for example, would increase the spammers' cost to reach\na given audience by a factor of 20. Few can have\nmargins big enough to absorb that.[3] As a rule of thumb, the more qualifiers there are before the\nname of a country, the more corrupt the rulers. A\ncountry called The Socialist People's Democratic Republic\nof X is probably the last place in the world you'd want to live.\nThanks to Sarah Harlin for reading drafts of this; Daniel Giffin (who is \nalso writing the production Arc interpreter) for several good ideas about\nfiltering and for creating our mail infrastructure; Robert Morris,\nTrevor Blackwell and Erann Gat for many discussions about spam; Raph \nLevien for advice about trust metrics; and Chip Coldwell \nand Sam Steingold for advice about statistics.\n\nYou'll find this essay and 14 others in\nHackers & Painters.\n\n\nMore Info:" }, { "path": "data/PaulGrahamEssays/speak.txt", "content": "March 2012I'm not a very good speaker. I say \"um\" a lot. Sometimes I have\nto pause when I lose my train of thought. I wish I were a better\nspeaker. But I don't wish I were a better speaker like I wish I\nwere a better writer. What I really want is to have good ideas,\nand that's a much bigger part of being a good writer than being a\ngood speaker.Having good ideas is most of writing well. If you know what you're\ntalking about, you can say it in the plainest words and you'll be\nperceived as having a good style. With speaking it's the opposite:\nhaving good ideas is an alarmingly small component of being a good\nspeaker.I first noticed this at a conference several years ago.\nThere was another speaker who was much better than me.\nHe had all of us roaring with laughter. I seemed awkward and\nhalting by comparison. Afterward I put my talk online like I usually\ndo. As I was doing it I tried to imagine what a transcript of the\nother guy's talk would be like, and it was only then I realized he\nhadn't said very much.Maybe this would have been obvious to someone who knew more about\nspeaking, but it was a revelation to me how much less ideas mattered\nin speaking than writing.\n[1]A few years later I heard a talk by someone who was not merely a\nbetter speaker than me, but a famous speaker. Boy was he good. So\nI decided I'd pay close attention to what he said, to learn how he\ndid it. After about ten sentences I found myself thinking \"I don't\nwant to be a good speaker.\"Being a really good speaker is not merely orthogonal to having good ideas,\nbut in many ways pushes you in the opposite direction. For example,\nwhen I give a talk, I usually write it out beforehand. I know that's\na mistake; I know delivering a \nprewritten \ntalk makes it harder to\nengage with an audience. The way to get the attention of an audience\nis to give them your full attention, and when you're delivering\na prewritten talk, your attention is always divided between the\naudience and the talk — even if you've memorized it. If you want\nto engage an audience, it's better to start with no more than an outline\nof what you want to say and \nad lib the individual sentences. But\nif you do that, you might spend no more time thinking about each\nsentence than it takes to say it.\n[2]\nOccasionally the stimulation\nof talking to a live audience makes you think of new things, but\nin general this is not going to generate ideas as well as writing\ndoes, where you can spend as long on each sentence as you want.If you rehearse a prewritten speech enough, you can get\nasymptotically close to the sort of engagement you get when speaking\nad lib. Actors do. But here again there's a tradeoff between\nsmoothness and ideas. All the time you spend practicing a talk,\nyou could instead spend making it better. Actors don't face\nthat temptation, except in the rare cases where they've written the\nscript, but any speaker does. Before I give a talk I can usually\nbe found sitting in a corner somewhere with a copy printed out on\npaper, trying to rehearse it in my head. But I always end up\nspending most of the time rewriting it instead. Every talk I give\nends up being given from a manuscript full of things crossed out\nand rewritten. Which of course makes me um even more, because I\nhaven't had any time to practice the new bits.\n[3]Depending on your audience, there are even worse tradeoffs than\nthese. Audiences like to be flattered; they like jokes; they like\nto be swept off their feet by a vigorous stream of words. As you\ndecrease the intelligence of the audience, being a good speaker is\nincreasingly a matter of being a good bullshitter. That's true in\nwriting too of course, but the descent is steeper with talks. Any\ngiven person is dumber as a member of an audience than as a reader.\nJust as a speaker ad libbing can only spend as long thinking about\neach sentence as it takes to say it, a person hearing a talk can\nonly spend as long thinking about each sentence as it takes to hear\nit. Plus people in an audience are always affected by the reactions\nof those around them, and the reactions that spread from person to\nperson in an audience are disproportionately the more brutish sort,\njust as low notes travel through walls better than high ones. Every\naudience is an incipient mob, and a good speaker uses that. Part\nof the reason I laughed so much at the talk by the good speaker at\nthat conference was that everyone else did.\n[4]So are talks useless? They're certainly inferior to the written\nword as a source of ideas. But that's not all talks are good for.\nWhen I go to a talk, it's usually because I'm interested in the\nspeaker. Listening to a talk is the closest most of us can get to\nhaving a conversation with someone like the president, who doesn't\nhave time to meet individually with all the people who want to meet\nhim.Talks are also good at motivating me to do things. It's probably\nno coincidence that so many famous speakers are described as\nmotivational speakers. That may be what public speaking is really\nfor. It's probably what it was originally for. The emotional\nreactions you can elicit with a talk can be a powerful force.\nI wish I could say that this force was more often used for good than\nill, but I'm not sure.Notes[1]\nI'm not talking here about academic talks, which are a \ndifferent type of thing. While the\naudience at an academic talk might appreciate a joke, they will (or\nat least should) make a conscious effort to see what new ideas\nyou're presenting.[2]\nThat's the lower bound. In practice you can often do better,\nbecause talks are usually about things you've written or talked\nabout before, and when you ad lib, you end up reproducing some of\nthose sentences. Like early medieval architecture, impromptu talks\nare made of spolia. Which feels a bit dishonest, incidentally,\nbecause you have to deliver these sentences as if you'd just thought\nof them.[3]\nRobert Morris points out that there is a way in which practicing\ntalks makes them better: reading a talk out loud can expose awkward\nparts. I agree and in fact I read most things I write out loud at\nleast once for that reason.[4]\nFor sufficiently small audiences, it may not be true that being\npart of an audience makes people dumber. The real decline seems\nto set in when the audience gets too big for the talk to feel like\na conversation — maybe around 10 people.\nThanks to Sam Altman and Robert Morris for reading drafts\nof this." }, { "path": "data/PaulGrahamEssays/start.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nMarch 2005(This essay is derived from a talk at the Harvard Computer\nSociety.)You need three things to create a successful startup: to start with\ngood people, to make something customers actually want, and to spend\nas little money as possible. Most startups that fail do it because\nthey fail at one of these. A startup that does all three will\nprobably succeed.And that's kind of exciting, when you think about it, because all\nthree are doable. Hard, but doable. And since a startup that\nsucceeds ordinarily makes its founders rich, that implies getting\nrich is doable too. Hard, but doable.If there is one message I'd like to get across about startups,\nthat's it. There is no magically difficult step that requires\nbrilliance to solve.The IdeaIn particular, you don't need a brilliant \nidea to start a startup\naround. The way a startup makes money is to offer people better\ntechnology than they have now. But what people have now is often\nso bad that it doesn't take brilliance to do better.Google's plan, for example, was simply to create a search site that\ndidn't suck. They had three new ideas: index more of the Web, use\nlinks to rank search results, and have clean, simple web pages with\nunintrusive keyword-based ads. Above all, they were determined to\nmake a site that was good to use. No doubt there are great technical\ntricks within Google, but the overall plan was straightforward.\nAnd while they probably have bigger ambitions now, this alone brings\nthem a billion dollars a year. [1]There are plenty of other areas that are just as backward as search\nwas before Google. I can think of several heuristics for generating\nideas for startups, but most reduce to this: look at something\npeople are trying to do, and figure out how to do it in a way that\ndoesn't suck.For example, dating sites currently suck far worse than search did\nbefore Google. They all use the same simple-minded model.\nThey seem to have approached the problem by thinking about how to\ndo database matches instead of how dating works in the real world.\nAn undergrad could build something better as a class project. And\nyet there's a lot of money at stake. Online dating is a valuable\nbusiness now, and it might be worth a hundred times as much if it\nworked.An idea for a startup, however, is only a beginning. A lot of\nwould-be startup founders think the key to the whole process is the\ninitial idea, and from that point all you have to do is execute.\nVenture capitalists know better. If you go to VC firms with a\nbrilliant idea that you'll tell them about if they sign a nondisclosure\nagreement, most will tell you to get lost. That shows how much a \nmere idea is worth. The market price is less than the inconvenience \nof signing an NDA.Another sign of how little the initial idea is worth is the number\nof startups that change their plan en route. Microsoft's original\nplan was to make money selling programming languages, of all things.\nTheir current business model didn't occur to them until IBM dropped\nit in their lap five years later.Ideas for startups are worth something, certainly, but the trouble\nis, they're not transferrable. They're not something you could\nhand to someone else to execute. Their value is mainly as starting\npoints: as questions for the people who had them to continue thinking\nabout.What matters is not ideas, but the people who have them. Good\npeople can fix bad ideas, but good ideas can't save bad people. \nPeopleWhat do I mean by good people? One of the best tricks I learned \nduring our startup was a rule for deciding \nwho to hire. Could you\ndescribe the person as an animal? It might be hard to translate \nthat into another language, but I think everyone in the US knows \nwhat it means. It means someone who takes their work a little too \nseriously; someone who does what they do so well that they pass\nright through professional and cross over into obsessive.What it means specifically depends on the job: a salesperson who\njust won't take no for an answer; a hacker who will stay up till \n4:00 AM rather than go to bed leaving code with a bug in it; a PR \nperson who will cold-call New York Times reporters on their cell\nphones; a graphic designer who feels physical pain when something \nis two millimeters out of place.Almost everyone who worked for us was an animal at what they did. \nThe woman in charge of sales was so tenacious that I used to feel\nsorry for potential customers on the phone with her. You could \nsense them squirming on the hook, but you knew there would be no \nrest for them till they'd signed up.If you think about people you know, you'll find the animal test is\neasy to apply. Call the person's image to mind and imagine the\nsentence \"so-and-so is an animal.\" If you laugh, they're not. You\ndon't need or perhaps even want this quality in big companies, but\nyou need it in a startup.For programmers we had three additional tests. Was the person\ngenuinely smart? If so, could they actually get things done? And\nfinally, since a few good hackers have unbearable personalities, \ncould we stand to have them around?That last test filters out surprisingly few people. We could bear\nany amount of nerdiness if someone was truly smart. What we couldn't\nstand were people with a lot of attitude. But most of those weren't\ntruly smart, so our third test was largely a restatement of the\nfirst.When nerds are unbearable it's usually because they're trying too\nhard to seem smart. But the smarter they are, the less pressure\nthey feel to act smart. So as a rule you can recognize genuinely\nsmart people by their ability to say things like \"I don't know,\" \n\"Maybe you're right,\" and \"I don't understand x well enough.\"This technique doesn't always work, because people can be influenced\nby their environment. In the MIT CS department, there seems to be\na tradition of acting like a brusque know-it-all. I'm told it derives\nultimately from Marvin Minsky, in the same way the classic airline\npilot manner is said to derive from Chuck Yeager. Even genuinely\nsmart people start to act this way there, so you have to make\nallowances.It helped us to have Robert Morris, who is one of the readiest to\nsay \"I don't know\" of anyone I've met. (At least, he was before he \nbecame a professor at MIT.) No one dared put on attitude around \nRobert, because he was obviously smarter than they were and yet had\nzero attitude himself.Like most startups, ours began with a group of friends, and it was\nthrough personal contacts that we got most of the people we hired.\nThis is a crucial difference between startups and big companies.\nBeing friends with someone for even a couple days will tell you \nmore than companies could ever learn in interviews. [2]It's no coincidence that startups start around universities, because\nthat's where smart people meet. It's not what people learn in \nclasses at MIT and Stanford that has made technology companies\nspring up around them. They could sing campfire songs in the classes\nso long as admissions worked the same.If you start a startup, there's a good chance it will be with people\nyou know from college or grad school. So in theory you ought to \ntry to make friends with as many smart people as you can in school,\nright? Well, no. Don't make a conscious effort to schmooze; that\ndoesn't work well with hackers.What you should do in college is work on your own projects. Hackers\nshould do this even if they don't plan to start startups, because \nit's the only real way to learn how to program. In some cases you\nmay collaborate with other students, and this is the best way to\nget to know good hackers. The project may even grow into a startup.\nBut once again, I wouldn't aim too directly at either target. Don't\nforce things; just work on stuff you like with people you like.Ideally you want between two and four founders. It would be hard\nto start with just one. One person would find the moral weight of\nstarting a company hard to bear. Even Bill Gates, who seems to be \nable to bear a good deal of moral weight, had to have a co-founder. \nBut you don't want so many founders that the company starts to look\nlike a group photo. Partly because you don't need a lot of people\nat first, but mainly because the more founders you have, the worse\ndisagreements you'll have. When there are just two or three founders,\nyou know you have to resolve disputes immediately or perish. If\nthere are seven or eight, disagreements can linger and harden into\nfactions. You don't want mere voting; you need unanimity.In a technology startup, which most startups are, the founders\nshould include technical people. During the Internet Bubble there \nwere a number of startups founded by business people who then went\nlooking for hackers to create their product for them. This doesn't \nwork well. Business people are bad at deciding what to do with \ntechnology, because they don't know what the options are, or which\nkinds of problems are hard and which are easy. And when business\npeople try to hire hackers, they can't tell which ones are \ngood.\nEven other hackers have a hard time doing that. \nFor business people it's roulette.Do the founders of a startup have to include business people? That\ndepends. We thought so when we started ours, and we asked several \npeople who were said to know about this mysterious thing called\n\"business\" if they would be the president. But they all said no,\nso I had to do it myself. And what I discovered was that business\nwas no great mystery. It's not something like physics or medicine\nthat requires extensive study. You just try to get people to pay\nyou for stuff.I think the reason I made such a mystery of business was that I was\ndisgusted by the idea of doing it. I wanted to work in the pure, \nintellectual world of software, not deal with customers' mundane \nproblems. People who don't want to get dragged into some kind of\nwork often develop a protective incompetence at it. Paul Erdos was\nparticularly good at this. By seeming unable even to cut a grapefruit\nin half (let alone go to the store and buy one), he forced other\npeople to do such things for him, leaving all his time free for\nmath. Erdos was an extreme case, but most husbands use the same \ntrick to some degree.Once I was forced to discard my protective incompetence, I found\nthat business was neither so hard nor so boring as I feared. There\nare esoteric areas of business that are quite hard, like tax law\nor the pricing of derivatives, but you don't need to know about \nthose in a startup. All you need to know about business to run a \nstartup are commonsense things people knew before there were business\nschools, or even universities.If you work your way down the Forbes 400 making an x next to the \nname of each person with an MBA, you'll learn something important\nabout business school. After Warren Buffett, you don't hit another \nMBA till number 22,\nPhil Knight, the CEO of Nike. There are only 5 MBAs in the top\n50. What you notice in the Forbes 400 are a lot of people with \ntechnical backgrounds. Bill Gates, Steve Jobs, Larry Ellison,\nMichael Dell, Jeff Bezos, Gordon Moore. The rulers of the technology\nbusiness tend to come from technology, not business. So if you \nwant to invest two years in something that will help you succeed \nin business, the evidence suggests you'd do better to learn how to \nhack than get an MBA. [3]There is one reason you might want to include business people in a\nstartup, though: because you have to have at least one person willing\nand able to focus on what customers want. Some believe only business\npeople can do this-- that hackers can implement software, but not \ndesign it. That's nonsense. There's nothing about knowing how to\nprogram that prevents hackers from understanding users, or about\nnot knowing how to program that magically enables business people \nto understand them.If you can't understand users, however, you should either learn how\nor find a co-founder who can. That is the single most important\nissue for technology startups, and the rock that sinks more of them\nthan anything else.What Customers WantIt's not just startups that have to worry about this. I think most\nbusinesses that fail do it because they don't give customers what\nthey want. Look at restaurants. A large percentage fail, about a\nquarter in the first year. But can you think of one restaurant\nthat had really good food and went out of business?Restaurants with great food seem to prosper no matter what. A \nrestaurant with great food can be expensive, crowded, noisy, dingy,\nout of the way, and even have bad service, and people will keep\ncoming. It's true that a restaurant with mediocre food can sometimes \nattract customers through gimmicks. But that approach is very \nrisky. It's more straightforward just to make the food good.It's the same with technology. You hear all kinds of reasons why\nstartups fail. But can you think of one that had a massively popular\nproduct and still failed?In nearly every failed startup, the real problem was that customers\ndidn't want the product. For most, the cause of death is listed \nas \"ran out of funding,\" but that's only the immediate cause. Why \ncouldn't they get more funding? Probably because the product was\na dog, or never seemed likely to be done, or both.When I was trying to think of the things every startup needed to \ndo, I almost included a fourth: get a version 1 out as soon as you\ncan. But I decided not to, because that's implicit in making\nsomething customers want. The only way to make something customers\nwant is to get a prototype in front of them and refine it based on \ntheir reactions.The other approach is what I call the \"Hail Mary\" strategy. You \nmake elaborate plans for a product, hire a team of engineers to \ndevelop it (people who do this tend to use the term \"engineer\" for \nhackers), and then find after a year that you've spent two million\ndollars to develop something no one wants. This was not uncommon\nduring the Bubble, especially in companies run by business types, \nwho thought of software development as something terrifying that\ntherefore had to be carefully planned.We never even considered that approach. As a Lisp hacker, I come \nfrom the tradition of rapid prototyping. I would not claim (at\nleast, not here) that this is the right way to write every program,\nbut it's certainly the right way to write software for a startup.\nIn a startup, your initial plans are almost certain to be wrong in\nsome way, and your first priority should be to figure out where. \nThe only way to do that is to try implementing them.Like most startups, we changed our plan on the fly. At first we\nexpected our customers to be Web consultants. But it turned out\nthey didn't like us, because our software was easy to use and we hosted\nthe site. It would be too easy for clients to fire them. We also\nthought we'd be able to sign up a lot of catalog companies, because\nselling online was a natural extension of their existing business.\nBut in 1996 that was a hard sell. The middle managers we talked \nto at catalog companies saw the Web not as an opportunity, but as\nsomething that meant more work for them.We did get a few of the more adventurous catalog companies. Among\nthem was Frederick's of Hollywood, which gave us valuable experience\ndealing with heavy loads on our servers. But most of our users \nwere small, individual merchants who saw the Web as an opportunity \nto build a business. Some had retail stores, but many only existed\nonline. And so we changed direction to focus on these users.\nInstead of concentrating on the features Web consultants and catalog\ncompanies would want, we worked to make the software easy to use.I learned something valuable from that. It's worth trying very, \nvery hard to make technology easy to use. Hackers are so used to\ncomputers that they have no idea how horrifying software seems to\nnormal people. Stephen Hawking's editor told him that every equation\nhe included in his book would cut sales in half. When you work on\nmaking technology easier to use, you're riding that curve up instead \nof down. A 10% improvement in ease of use doesn't just increase \nyour sales 10%. It's more likely to double your sales.How do you figure out what customers want? Watch them. One of the\nbest places to do this was at trade shows. Trade shows didn't pay \nas a way of getting new customers, but they were worth it as market\nresearch. We didn't just give canned presentations at trade shows.\nWe used to show people how to build real, working stores. Which \nmeant we got to watch as they used our software, and talk to them \nabout what they needed.No matter what kind of startup you start, it will probably be a \nstretch for you, the founders, to understand what users want. The\nonly kind of software you can build without studying users is the \nsort for which you are the typical user. But this is just the kind\nthat tends to be open source: operating systems, programming\nlanguages, editors, and so on. So if you're developing technology\nfor money, you're probably not going to be developing it for people\nlike you. Indeed, you can use this as a way to generate ideas for\nstartups: what do people who are not like you want from technology?When most people think of startups, they think of companies like\nApple or Google. Everyone knows these, because they're big consumer\nbrands. But for every startup like that, there are twenty more \nthat operate in niche markets or live quietly down in the infrastructure.\nSo if you start a successful startup, odds are you'll start one of \nthose.Another way to say that is, if you try to start the kind of startup\nthat has to be a big consumer brand, the odds against succeeding\nare steeper. The best odds are in niche markets. Since startups \nmake money by offering people something better than they had before,\nthe best opportunities are where things suck most. And it would \nbe hard to find a place where things suck more than in corporate \nIT departments. You would not believe the amount of money companies\nspend on software, and the crap they get in return. This imbalance\nequals opportunity.If you want ideas for startups, one of the most valuable things you\ncould do is find a middle-sized non-technology company and spend a \ncouple weeks just watching what they do with computers. Most good\nhackers have no more idea of the horrors perpetrated in these places\nthan rich Americans do of what goes on in Brazilian slums.Start by writing software for smaller companies, because it's easier\nto sell to them. It's worth so much to sell stuff to big companies\nthat the people selling them the crap they currently use spend a\nlot of time and money to do it. And while you can outhack Oracle\nwith one frontal lobe tied behind your back, you can't outsell an\nOracle salesman. So if you want to win through better technology,\naim at smaller customers. [4]They're the more strategically valuable part of the market anyway. \nIn technology, the low end always eats the high end. It's easier \nto make an inexpensive product more powerful than to make a powerful\nproduct cheaper. So the products that start as cheap, simple options\ntend to gradually grow more powerful till, like water rising in a \nroom, they squash the \"high-end\" products against the ceiling. Sun\ndid this to mainframes, and Intel is doing it to Sun. Microsoft\nWord did it to desktop publishing software like Interleaf and\nFramemaker. Mass-market digital cameras are doing it to the expensive\nmodels made for professionals. Avid did it to the manufacturers \nof specialized video editing systems, and now Apple is doing it to\nAvid. Henry Ford did it to the car makers that preceded\nhim. If you build the simple, inexpensive option, you'll not only\nfind it easier to sell at first, but you'll also be in the best \nposition to conquer the rest of the market.It's very dangerous to let anyone fly under you. If you have the\ncheapest, easiest product, you'll own the low end. And if you\ndon't, you're in the crosshairs of whoever does.Raising MoneyTo make all this happen, you're going to need money. Some startups\nhave been self-funding-- Microsoft for example-- but most aren't.\nI think it's wise to take money from investors. To be self-funding,\nyou have to start as a consulting company, and it's hard to switch\nfrom that to a product company.Financially, a startup is like a pass/fail course. The way to get\nrich from a startup is to maximize the company's chances of succeeding,\nnot to maximize the amount of stock you retain. So if you can trade\nstock for something that improves your odds, it's probably a smart \nmove.To most hackers, getting investors seems like a terrifying and\nmysterious process. Actually it's merely tedious. I'll try to\ngive an outline of how it works.The first thing you'll need is a few tens of thousands of dollars \nto pay your expenses while you develop a prototype. This is called\nseed capital. Because so little money is involved, raising seed\ncapital is comparatively easy-- at least in the sense of getting a\nquick yes or no.Usually you get seed money from individual rich people called\n\"angels.\" Often they're people who themselves got rich from technology.\nAt the seed stage, investors don't expect you to have an elaborate\nbusiness plan. Most know that they're supposed to decide quickly.\nIt's not unusual to get a check within a week based on a half-page\nagreement.We started Viaweb with $10,000 of seed money from our friend Julian.\nBut he gave us a lot more than money. He's a former CEO and also\na corporate lawyer, so he gave us a lot of valuable advice about\nbusiness, and also did all the legal work of getting us set up as\na company. Plus he introduced us to one of the two \nangel investors who supplied our next round of funding.Some angels, especially those with technology backgrounds, may be \nsatisfied with a demo and a verbal description of what you plan to \ndo. But many will want a copy of your business plan, if only to\nremind themselves what they invested in.Our angels asked for one, and looking back, I'm amazed how much\nworry it caused me. \"Business plan\" has that word \"business\" in\nit, so I figured it had to be something I'd have to read a book\nabout business plans to write. Well, it doesn't. At this stage,\nall most investors expect is a brief description of what you plan \nto do and how you're going to make money from it, and the resumes \nof the founders. If you just sit down and write out what you've\nbeen saying to one another, that should be fine. It shouldn't take\nmore than a couple hours, and you'll probably find that writing it\nall down gives you more ideas about what to do.For the angel to have someone to make the check out to, you're going\nto have to have some kind of company. Merely incorporating yourselves\nisn't hard. The problem is, for the company to exist, you have to\ndecide who the founders are, and how much stock they each have. If\nthere are two founders with the same qualifications who are both\nequally committed to the business, that's easy. But if you have a\nnumber of people who are expected to contribute in varying degrees,\narranging the proportions of stock can be hard. And once you've\ndone it, it tends to be set in stone.I have no tricks for dealing with this problem. All I can say is,\ntry hard to do it right. I do have a rule of thumb for recognizing\nwhen you have, though. When everyone feels they're getting a\nslightly bad deal, that they're doing more than they should for the\namount of stock they have, the stock is optimally apportioned.There is more to setting up a company than incorporating it, of\ncourse: insurance, business license, unemployment compensation, \nvarious things with the IRS. I'm not even sure what the list is,\nbecause we, ah, skipped all that. When we got real funding near\nthe end of 1996, we hired a great CFO, who fixed everything \nretroactively. It turns out that no one comes and arrests you if\nyou don't do everything you're supposed to when starting a company.\nAnd a good thing too, or a lot of startups would never get started.\n[5]It can be dangerous to delay turning yourself into a company, because\none or more of the founders might decide to split off and start \nanother company doing the same thing. This does happen. So when\nyou set up the company, as well as as apportioning the stock, you\nshould get all the founders to sign something agreeing that everyone's\nideas belong to this company, and that this company is going to be\neveryone's only job.[If this were a movie, ominous music would begin here.]While you're at it, you should ask what else they've signed. One\nof the worst things that can happen to a startup is to run into \nintellectual property problems. We did, and it came closer to \nkilling us than any competitor ever did.As we were in the middle of getting bought, we discovered that one\nof our people had, early on, been bound by an agreement that said\nall his ideas belonged to the giant company that was paying for him\nto go to grad school. In theory, that could have meant someone\nelse owned big chunks of our software. So the acquisition came to\na screeching halt while we tried to sort this out. The problem \nwas, since we'd been about to be acquired, we'd allowed ourselves \nto run low on cash. Now we needed to raise more to keep going. \nBut it's hard to raise money with an IP cloud over your head, because\ninvestors can't judge how serious it is.Our existing investors, knowing that we needed money and had nowhere\nelse to get it, at this point attempted certain gambits which I\nwill not describe in detail, except to remind readers that the word \n\"angel\" is a metaphor. The founders thereupon proposed to walk \naway from the company, after giving the investors a brief tutorial \non how to administer the servers themselves. And while this was\nhappening, the acquirers used the delay as an excuse to welch on \nthe deal.Miraculously it all turned out ok. The investors backed down; we\ndid another round of funding at a reasonable valuation; the giant\ncompany finally gave us a piece of paper saying they didn't own our\nsoftware; and six months later we were bought by Yahoo for much\nmore than the earlier acquirer had agreed to pay. So we were happy\nin the end, though the experience probably took several years off \nmy life.Don't do what we did. Before you consummate a startup, ask \neveryone about their previous IP history.Once you've got a company set up, it may seem presumptuous to go\nknocking on the doors of rich people and asking them to invest tens\nof thousands of dollars in something that is really just a bunch \nof guys with some ideas. But when you look at it from the rich\npeople's point of view, the picture is more encouraging. Most rich \npeople are looking for good investments. If you really think you\nhave a chance of succeeding, you're doing them a favor by letting\nthem invest. Mixed with any annoyance they might feel about being \napproached will be the thought: are these guys the next Google?Usually angels are financially equivalent to founders. They get \nthe same kind of stock and get diluted the same amount in future\nrounds. How much stock should they get? That depends on how\nambitious you feel. When you offer x percent of your company for\ny dollars, you're implicitly claiming a certain value for the whole\ncompany. Venture investments are usually described in terms of\nthat number. If you give an investor new shares equal to 5% of\nthose already outstanding in return for $100,000, then you've done\nthe deal at a pre-money valuation of $2 million.How do you decide what the value of the company should be? There\nis no rational way. At this stage the company is just a bet. I\ndidn't realize that when we were raising money. Julian\nthought we ought to value the company at several million \ndollars. I thought it was preposterous to claim that a couple\nthousand lines of code, which was all we had at the time, were worth\nseveral million dollars. Eventually we settled on one million,\nbecause Julian said no one would invest in a company with a valuation\nany lower. [6]What I didn't grasp at the time was that the valuation wasn't just \nthe value of the code we'd written so far. It was also the value\nof our ideas, which turned out to be right, and of all the future\nwork we'd do, which turned out to be a lot.The next round of funding is the one in which you might deal with \nactual \nventure capital firms. \nBut don't wait till you've burned \nthrough your last round of funding to start approaching them. VCs are slow to\nmake up their minds. They can take months. You don't want to be \nrunning out of money while you're trying to negotiate with them.Getting money from an actual VC firm is a bigger deal than getting\nmoney from angels. The amounts of money involved are larger, millions\nusually. So the deals take longer, dilute you more, and impose\nmore onerous conditions.Sometimes the VCs want to install a new CEO of their own choosing. \nUsually the claim is that you need someone mature and experienced,\nwith a business background. Maybe in some cases this is true. And\nyet Bill Gates was young and inexperienced and had no business \nbackground, and he seems to have done ok. Steve Jobs got booted\nout of his own company by someone mature and experienced, with a\nbusiness background, who then proceeded to ruin the company. So I\nthink people who are mature and experienced, with a business\nbackground, may be overrated. We used to call these guys \"newscasters,\"\nbecause they had neat hair and spoke in deep, confident voices, and\ngenerally didn't know much more than they read on the teleprompter.We talked to a number of VCs, but eventually we ended up financing\nour startup entirely with angel money. The main reason was that \nwe feared a brand-name VC firm would stick us with a newscaster as\npart of the deal. That might have been ok if he was content to\nlimit himself to talking to the press, but what if he wanted to \nhave a say in running the company? That would have led to disaster,\nbecause our software was so complex. We were a company whose whole\nm.o. was to win through better technology. The strategic decisions\nwere mostly decisions about technology, and we didn't need any help\nwith those.This was also one reason we didn't go public. Back in 1998 our CFO\ntried to talk me into it. In those days you could go public as a\ndogfood portal, so as a company with a real product and real revenues,\nwe might have done well. But I feared it would have meant taking\non a newscaster-- someone who, as they say, \"can talk Wall Street's\nlanguage.\"I'm happy to see Google is bucking that trend. They didn't talk\nWall Street's language when they did their IPO, and Wall Street\ndidn't buy. And now Wall Street is collectively kicking itself.\nThey'll pay attention next time. Wall Street learns new languages \nfast when money is involved.You have more leverage negotiating with VCs than you realize. The \nreason is other VCs. I know a number of VCs now, and when you talk\nto them you realize that it's a seller's market. Even now there\nis too much money chasing too few good deals.VCs form a pyramid. At the top are famous ones like Sequoia and\nKleiner Perkins, but beneath those are a huge number you've never \nheard of. What they all have in common is that a dollar from them \nis worth one dollar. Most VCs will tell you that they don't just \nprovide money, but connections and advice. If you're talking to \nVinod Khosla or John Doerr or Mike Moritz, this is true. But such\nadvice and connections can come very expensive. And as you go down\nthe food chain the VCs get rapidly \n\ndumber. A few steps down from \nthe top you're basically talking to bankers who've picked up a few\nnew vocabulary words from reading Wired. (Does your product\nuse XML?) So I'd advise you to be skeptical about claims\nof experience and connections. Basically, a VC is a source of\nmoney. I'd be inclined to go with whoever offered the most money \nthe soonest with the least strings attached.You may wonder how much to tell VCs. And you should, because some\nof them may one day be funding your competitors. I think the best\nplan is not to be overtly secretive, but not to tell them everything\neither. After all, as most VCs say, they're more interested in the\npeople than the ideas. The main reason they want to talk about\nyour idea is to judge you, not the idea. So as long as you seem\nlike you know what you're doing, you can probably keep a few things\nback from them. [7]Talk to as many VCs as you can, even if you don't want their money,\nbecause a) they may be on the board of someone who will buy you, \nand b) if you seem impressive, they'll be discouraged from investing\nin your competitors. The most efficient way to reach VCs, especially\nif you only want them to know about you and don't want their money,\nis at the conferences that are occasionally organized for startups \nto present to them.Not Spending ItWhen and if you get an infusion of real money from investors, what\nshould you do with it? Not spend it, that's what. In nearly every \nstartup that fails, the proximate cause is running out of money. \nUsually there is something deeper wrong. But even a proximate cause\nof death is worth trying hard to avoid.During the Bubble many startups tried to \"get big fast.\" Ideally\nthis meant getting a lot of customers fast. But it was easy for\nthe meaning to slide over into hiring a lot of people fast.Of the two versions, the one where you get a lot of customers fast\nis of course preferable. But even that may be overrated. The idea\nis to get there first and get all the users, leaving none for\ncompetitors. But I think in most businesses the advantages of being\nfirst to market are not so overwhelmingly great. Google is again\na case in point. When they appeared it seemed as if search was a\nmature market, dominated by big players who'd spent millions to\nbuild their brands: Yahoo, Lycos, Excite, Infoseek, Altavista, \nInktomi. Surely 1998 was a little late to arrive at the party.But as the founders of Google knew, brand is worth next to nothing\nin the search business. You can come along at any point and make \nsomething better, and users will gradually seep over to you. As \nif to emphasize the point, Google never did any advertising. They're\nlike dealers; they sell the stuff, but they know better than to use\nit themselves.The competitors Google buried would have done better to spend those\nmillions improving their software. Future startups should learn\nfrom that mistake. Unless you're in a market where products are \nas undifferentiated as cigarettes or vodka or laundry detergent,\nspending a lot on brand advertising is a sign of breakage. And few\nif any Web businesses are so undifferentiated. The dating sites \nare running big ad campaigns right now, which is all the \nmore evidence they're ripe for the picking. (Fee, fie, fo, fum, I \nsmell a company run by marketing guys.)We were compelled by circumstances to grow slowly, and in retrospect\nit was a good thing. The founders all learned to do every job in \nthe company. As well as writing software, I had to do sales and\ncustomer support. At sales I was not very good. I was persistent,\nbut I didn't have the smoothness of a good salesman. My message \nto potential customers was: you'd be stupid not to sell online, and \nif you sell online you'd be stupid to use anyone else's software. \nBoth statements were true, but that's not the way to convince people.I was great at customer support though. Imagine talking to a\ncustomer support person who not only knew everything about the\nproduct, but would apologize abjectly if there was a bug, and then\nfix it immediately, while you were on the phone with them. Customers\nloved us. And we loved them, because when you're growing slow by\nword of mouth, your first batch of users are the ones who were smart\nenough to find you by themselves. There is nothing more valuable,\nin the early stages of a startup, than smart users. If you listen\nto them, they'll tell you exactly how to make a winning product. \nAnd not only will they give you this advice for free, they'll pay\nyou.We officially launched in early 1996. By the end of that year we\nhad about 70 users. Since this was the era of \"get big fast,\" I\nworried about how small and obscure we were. But in fact we were\ndoing exactly the right thing. Once you get big (in users or\nemployees) it gets hard to change your product. That year was\neffectively a laboratory for improving our software. By the end \nof it, we were so far ahead of our competitors that they never had \na hope of catching up. And since all the hackers had spent many\nhours talking to users, we understood online commerce way better\nthan anyone else.That's the key to success as a startup. There is nothing more \nimportant than understanding your business. You might think that\nanyone in a business must, ex officio, understand it. Far from it. \nGoogle's secret\nweapon was simply that they understood search. I was working for \nYahoo when Google appeared, and Yahoo didn't understand search. I\nknow because I once tried to convince the powers that be that we\nhad to make search better, and I got in reply what was then the\nparty line about it: that Yahoo was no longer a mere \"search engine.\"\nSearch was now only a small percentage of our page views, less than\none month's growth, and now that we were established as a \"media \ncompany,\" or \"portal,\" or whatever we were, search could safely be\nallowed to wither and drop off, like an umbilical cord.Well, a small fraction of page views they may be, but they are an \nimportant fraction, because they are the page views that Web sessions \nstart with. I think Yahoo gets that now.Google understands a few other things most Web companies still\ndon't. The most important is that you should put users before\nadvertisers, even though the advertisers are paying and users aren't.\nOne of my favorite bumper stickers reads \"if the people lead, the \nleaders will follow.\" Paraphrased for the Web, this becomes \"get\nall the users, and the advertisers will follow.\" More generally,\ndesign your product to please users first, and then think about how\nto make money from it. If you don't put users first, you leave a \ngap for competitors who do.To make something users love, you have to understand them. And the\nbigger you are, the harder that is. So I say \"get big slow.\" The\nslower you burn through your funding, the more time you have to\nlearn.The other reason to spend money slowly is to encourage a culture \nof cheapness. That's something Yahoo did understand. David Filo's \ntitle was \"Chief Yahoo,\" but he was proud that his unofficial title\nwas \"Cheap Yahoo.\" Soon after we arrived at Yahoo, we got an email\nfrom Filo, who had been crawling around our directory hierarchy, \nasking if it was really necessary to store so much of our data on\nexpensive RAID drives. I was impressed by that. Yahoo's market\ncap then was already in the billions, and they were still worrying\nabout wasting a few gigs of disk space.When you get a couple million dollars from a VC firm, you tend to\nfeel rich. It's important to realize you're not. A rich company\nis one with large revenues. This money isn't revenue. It's money\ninvestors have given you in the hope you'll be able to generate \nrevenues. So despite those millions in the bank, you're still poor.For most startups the model should be grad student, not law firm.\nAim for cool and cheap, not expensive and impressive. For us the\ntest of whether a startup understood this was whether they had Aeron\nchairs. The Aeron came out during the Bubble and was very popular\nwith startups. Especially the type, all too common then, that was\nlike a bunch of kids playing house with money supplied by VCs. We \nhad office chairs so cheap that the arms all fell off. This was \nslightly embarrassing at the time, but in retrospect the grad-studenty\natmosphere of our office was another of those things we did right \nwithout knowing it.Our offices were in a wooden triple-decker in Harvard Square. It\nhad been an apartment until about the 1970s, and there was still a \nclaw-footed bathtub in the bathroom. It must once have been inhabited\nby someone fairly eccentric, because a lot of the chinks in the \nwalls were stuffed with aluminum foil, as if to protect against \ncosmic rays. When eminent visitors came to see us, we were a bit\nsheepish about the low production values. But in fact that place\nwas the perfect space for a startup. We felt like our role was to \nbe impudent underdogs instead of corporate stuffed shirts, and that \nis exactly the spirit you want.An apartment is also the right kind of place for developing software.\nCube farms suck for that, as you've probably discovered if you've\ntried it. Ever notice how much easier it is to hack at home than\nat work? So why not make work more like home?When you're looking for space for a startup, don't feel that it has\nto look professional. Professional means doing good work, not\nelevators and glass walls. I'd advise most startups to avoid\ncorporate space at first and just rent an apartment. You want to\nlive at the office in a startup, so why not have a place designed\nto be lived in as your office?Besides being cheaper and better to work in, apartments tend to be\nin better locations than office buildings. And for a startup\nlocation is very important. The key to productivity is for people\nto come back to work after dinner. Those hours after the phone\nstops ringing are by far the best for getting work done. Great\nthings happen when a group of employees go out to dinner together, \ntalk over ideas, and then come back to their offices to implement \nthem. So you want to be in a place where there are a lot of\nrestaurants around, not some dreary office park that's a wasteland\nafter 6:00 PM. Once a company shifts over into the model where \neveryone drives home to the suburbs for dinner, however late, you've\nlost something extraordinarily valuable. God help you if you\nactually start in that mode.If I were going to start a startup today, there are only three \nplaces I'd consider doing it: on the Red Line near Central, Harvard,\nor Davis Squares (Kendall is too sterile); in Palo Alto on University\nor California Aves; and in Berkeley immediately north or south of \ncampus. These are the only places I know that have the right kind\nof vibe.The most important way to not spend money is by not hiring people. \nI may be an extremist, but I think hiring people is the worst thing\na company can do. To start with, people are a recurring expense, \nwhich is the worst kind. They also tend to cause you to grow out \nof your space, and perhaps even move to the sort of uncool office\nbuilding that will make your software worse. But worst of all,\nthey slow you down: instead of sticking your head in someone's \noffice and checking out an idea with them, eight people have to\nhave a meeting about it. So the fewer people you can hire, the\nbetter.During the Bubble a lot of startups had the opposite policy. They\nwanted to get \"staffed up\" as soon as possible, as if you couldn't \nget anything done unless there was someone with the corresponding \njob title. That's big company thinking. Don't hire people to fill\nthe gaps in some a priori org chart. The only reason to hire someone\nis to do something you'd like to do but can't.If hiring unnecessary people is expensive and slows you down, why\ndo nearly all companies do it? I think the main reason is that\npeople like the idea of having a lot of people working for them.\nThis weakness often extends right up to the CEO. If you ever end\nup running a company, you'll find the most common question people\nask is how many employees you have. This is their way of weighing\nyou. It's not just random people who ask this; even reporters do.\nAnd they're going to be a lot more impressed if the answer is a\nthousand than if it's ten.This is ridiculous, really. If two companies have the same revenues,\nit's the one with fewer employees that's more impressive. When \npeople used to ask me how many people our startup had, and I answered\n\"twenty,\" I could see them thinking that we didn't count for much.\nI used to want to add \"but our main competitor, whose ass we regularly\nkick, has a hundred and forty, so can we have credit for the larger\nof the two numbers?\"As with office space, the number of your employees is a choice \nbetween seeming impressive, and being impressive. Any of you who \nwere nerds in high school know about this \nchoice. Keep doing it when you start a company.Should You?But should you start a company? Are you the right sort of person\nto do it? If you are, is it worth it?More people are the right sort of person to start a startup than\nrealize it. That's the main reason I wrote this. There could be \nten times more startups than there are, and that would probably be\na good thing.I was, I now realize, exactly the right sort of person to start a \nstartup. But the idea terrified me at first. I was forced into \nit because I was a Lisp hacker. The company\nI'd been consulting for seemed to be running into trouble, and there \nwere not a lot of other companies using Lisp. Since I couldn't \nbear the thought of programming in another language (this was 1995,\nremember, when \"another language\" meant C++) the only option seemed\nto be to start a new company using Lisp.I realize this sounds far-fetched, but if you're a Lisp hacker\nyou'll know what I mean. And if the idea of starting a startup\nfrightened me so much that I only did it out of necessity, there \nmust be a lot of people who would be good at it but who are too \nintimidated to try.So who should start a startup? Someone who is a good hacker, between\nabout 23 and 38, and who wants to solve the money problem in one\nshot instead of getting paid gradually over a conventional working\nlife.I can't say precisely what a good hacker is. At a first rate \nuniversity this might include the top half of computer science \nmajors. Though of course you don't have to be a CS major to be a\nhacker; I was a philosophy major in college.It's hard to tell whether you're a good hacker, especially when\nyou're young. Fortunately the process of starting startups tends\nto select them automatically. What drives people to start startups\nis (or should be) looking at existing technology and thinking, don't \nthese guys realize they should be doing x, y, and z? And that's \nalso a sign that one is a good hacker.I put the lower bound at 23 not because there's something that\ndoesn't happen to your brain till then, but because you need to see\nwhat it's like in an existing business before you try running your\nown. The business doesn't have to be a startup. I spent a year\nworking for a software company to pay off my college loans. It was\nthe worst year of my adult life, but I learned, without realizing \nit at the time, a lot of valuable lessons about the software business.\nIn this case they were mostly negative lessons: don't have a lot\nof meetings; don't have chunks of code that multiple people own;\ndon't have a sales guy running the company; don't make a high-end\nproduct; don't let your code get too big; don't leave finding bugs\nto QA people; don't go too long between releases; don't isolate\ndevelopers from users; don't move from Cambridge to Route 128; and\nso on. [8] But negative lessons are just as valuable as positive \nones. Perhaps even more valuable: it's hard to repeat a brilliant\nperformance, but it's straightforward to avoid errors. [9]The other reason it's hard to start a company before 23 is that \npeople won't take you seriously. VCs won't trust you, and will try\nto reduce you to a mascot as a condition of funding. Customers\nwill worry you're going to flake out and leave them stranded. Even\nyou yourself, unless you're very unusual, will feel your age to \nsome degree; you'll find it awkward to be the boss of someone much \nolder than you, and if you're 21, hiring only people younger rather \nlimits your options.Some people could probably start a company at 18 if they wanted to.\nBill Gates was 19 when he and Paul Allen started Microsoft. (Paul \nAllen was 22, though, and that probably made a difference.) So if\nyou're thinking, I don't care what he says, I'm going to start a\ncompany now, you may be the sort of person who could get away with\nit.The other cutoff, 38, has a lot more play in it. One reason I put \nit there is that I don't think many people have the physical stamina\nmuch past that age. I used to work till 2:00 or 3:00 AM every\nnight, seven days a week. I don't know if I could do that now.Also,\nstartups are a big risk financially. If you try something that\nblows up and leaves you broke at 26, big deal; a lot of 26 year\nolds are broke. By 38 you can't take so many risks-- especially\nif you have kids.My final test may be the most restrictive. Do you actually want\nto start a startup? What it amounts to, economically, is compressing\nyour working life into the smallest possible space. Instead of\nworking at an ordinary rate for 40 years, you work like hell for \nfour. And maybe end up with nothing-- though in that case it\nprobably won't take four years.During this time you'll do little but work, because when you're not\nworking, your competitors will be. My only leisure activities were\nrunning, which I needed to do to keep working anyway, and about\nfifteen minutes of reading a night. I had a girlfriend for a total\nof two months during that three year period. Every couple weeks I\nwould take a few hours off to visit a used bookshop or go to a \nfriend's house for dinner. I went to visit my family twice.\nOtherwise I just worked.Working was often fun, because the people I worked with were some\nof my best friends. Sometimes it was even technically interesting.\nBut only about 10% of the time. The best I can say for the other\n90% is that some of it is funnier in hindsight than it seemed then.\nLike the time the power went off in Cambridge for about six hours,\nand we made the mistake of trying to start a gasoline powered\ngenerator inside our offices. I won't try that again.I don't think the amount of bullshit you have to deal with in a\nstartup is more than you'd endure in an ordinary working life. It's\nprobably less, in fact; it just seems like a lot because it's \ncompressed into a short period. So mainly what a startup buys you \nis time. That's the way to think about it if you're trying to \ndecide whether to start one. If you're the sort of person who would\nlike to solve the money problem once and for all instead of working \nfor a salary for 40 years, then a startup makes sense.For a lot of people the conflict is between startups and graduate\nschool. Grad students are just the age, and just the sort of people,\nto start software startups. You may worry that if you do you'll \nblow your chances of an academic career. But it's possible to be \npart of a startup and stay in grad school, especially at first. \nTwo of our three original hackers were in grad school the whole \ntime, and both got their degrees. \nThere are few sources of energy\nso powerful as a procrastinating grad student.If you do have to\nleave grad school, in the worst case it won't be for too long. If\na startup fails, it will probably fail quickly enough that you can \nreturn to academic life. And if it succeeds, you may find you no \nlonger have such a burning desire to be an assistant professor.If you want to do it, do it. Starting a startup is not the great\nmystery it seems from outside. It's not something you have to know\nabout \"business\" to do. Build something users love, and spend less\nthan you make. How hard is that?Notes[1] Google's revenues are about two billion a year, but half comes\nfrom ads on other sites.[2] One advantage startups have over established companies is that\nthere are no discrimination laws about starting businesses. For \nexample, I would be reluctant to start a startup with a woman\nwho had small children, or was likely to have them soon. But you're\nnot allowed to ask prospective employees if they plan to have kids \nsoon. Believe it or not, under current US law, you're not even \nallowed to discriminate on the basis of intelligence. Whereas when\nyou're starting a company, you can discriminate on any basis you\nwant about who you start it with.[3] Learning to hack is a lot cheaper than business school, because\nyou can do it mostly on your own. For the price of a Linux box, a\ncopy of K&R, and a few hours of advice from your neighbor's fifteen\nyear old son, you'll be well on your way.[4] Corollary: Avoid starting a startup to sell things to the biggest\ncompany of all, the government. Yes, there are lots of opportunities\nto sell them technology. But let someone else start those startups.[5] A friend who started a company in Germany told me they do care \nabout the paperwork there, and that there's more of it. Which helps\nexplain why there are not more startups in Germany.[6] At the seed stage our valuation was in principle $100,000, because\nJulian got 10% of the company. But this is a very misleading number,\nbecause the money was the least important of the things Julian gave us.[7] The same goes for companies that seem to want to acquire you.\nThere will be a few that are only pretending to in order to pick\nyour brains. But you can never tell for sure which these are, so\nthe best approach is to seem entirely open, but to fail to mention\na few critical technical secrets.[8] I was as bad an employee as this place was a company. I\napologize to anyone who had to work with me there.[9] You could probably write a book about how to succeed in business\nby doing everything in exactly the opposite way from the DMV.Thanks to Trevor Blackwell, Sarah Harlin, Jessica Livingston,\nand Robert Morris for reading drafts of this essay, and to Steve\nMelendez and Gregory Price for inviting me to speak." }, { "path": "data/PaulGrahamEssays/startupfunding.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nNovember 2005\nVenture funding works like gears. A typical startup goes through\nseveral rounds of funding, and at each round you want to take just\nenough money to reach the speed where you can shift into the next\ngear.Few startups get it quite right. Many are underfunded. A few are\noverfunded, which is like trying to start driving in third gear.I think it would help founders to understand funding better—not\njust the mechanics of it, but what investors are thinking. I was\nsurprised recently when I realized that all the worst problems we\nfaced in our startup were due not to competitors, but investors.\nDealing with competitors was easy by comparison.I don't mean to suggest that our investors were nothing but a drag\non us. They were helpful in negotiating deals, for example. I\nmean more that conflicts with investors are particularly nasty.\nCompetitors punch you in the jaw, but investors have you by the\nballs.Apparently our situation was not unusual. And if trouble with\ninvestors is one of the biggest threats to a startup, managing them\nis one of the most important skills founders need to learn.Let's start by talking about the five sources of startup funding.\nThen we'll trace the life of a hypothetical (very fortunate) startup\nas it shifts gears through successive rounds.Friends and FamilyA lot of startups get their first funding from friends and family.\nExcite did, for example: after the founders graduated from college,\nthey borrowed $15,000 from their parents to start a company. With\nthe help of some part-time jobs they made it last 18 months.If your friends or family happen to be rich, the line blurs between\nthem and angel investors. At Viaweb we got our first $10,000 of\nseed money from our friend Julian, but he was sufficiently rich\nthat it's hard to say whether he should be classified as a friend\nor angel. He was also a lawyer, which was great, because it meant\nwe didn't have to pay legal bills out of that initial small sum.The advantage of raising money from friends and family is that\nthey're easy to find. You already know them. There are three main\ndisadvantages: you mix together your business and personal life;\nthey will probably not be as well connected as angels or venture\nfirms; and they may not be accredited investors, which could\ncomplicate your life later.The SEC defines an \"accredited investor\" as someone with over a\nmillion dollars in liquid assets or an income of over $200,000 a\nyear. The regulatory burden is much lower if a company's shareholders\nare all accredited investors. Once you take money from the general\npublic you're more restricted in what you can do. \n[1]A startup's life will be more complicated, legally, if any of the\ninvestors aren't accredited. In an IPO, it might not merely add\nexpense, but change the outcome. A lawyer I asked about it said:\n\n When the company goes public, the SEC will carefully study all\n prior issuances of stock by the company and demand that it take\n immediate action to cure any past violations of securities laws.\n Those remedial actions can delay, stall or even kill the IPO.\n\nOf course the odds of any given startup doing an IPO are small.\nBut not as small as they might seem. A lot of startups that end up\ngoing public didn't seem likely to at first. (Who could have guessed\nthat the company Wozniak and Jobs started in their spare time selling\nplans for microcomputers would yield one of the biggest IPOs of the\ndecade?) Much of the value of a startup consists of that tiny\nprobability multiplied by the huge outcome.It wasn't because they weren't accredited investors that I didn't\nask my parents for seed money, though. When we were starting Viaweb,\nI didn't know about the concept of an accredited investor, and\ndidn't stop to think about the value of investors' connections.\nThe reason I didn't take money from my parents was that I didn't\nwant them to lose it.ConsultingAnother way to fund a startup is to get a job. The best sort of\njob is a consulting project in which you can build whatever software\nyou wanted to sell as a startup. Then you can gradually transform\nyourself from a consulting company into a product company, and have\nyour clients pay your development expenses.This is a good plan for someone with kids, because it takes most\nof the risk out of starting a startup. There never has to be a\ntime when you have no revenues. Risk and reward are usually\nproportionate, however: you should expect a plan that cuts the risk\nof starting a startup also to cut the average return. In this case,\nyou trade decreased financial risk for increased risk that your\ncompany won't succeed as a startup.But isn't the consulting company itself a startup? No, not generally.\nA company has to be more than small and newly founded to be a\nstartup. There are millions of small businesses in America, but\nonly a few thousand are startups. To be a startup, a company has\nto be a product business, not a service business. By which I mean\nnot that it has to make something physical, but that it has to have\none thing it sells to many people, rather than doing custom work\nfor individual clients. Custom work doesn't scale. To be a startup\nyou need to be the band that sells a million copies of a song, not\nthe band that makes money by playing at individual weddings and bar\nmitzvahs.The trouble with consulting is that clients have an awkward habit\nof calling you on the phone. Most startups operate close to the\nmargin of failure, and the distraction of having to deal with clients\ncould be enough to put you over the edge. Especially if you have\ncompetitors who get to work full time on just being a startup.So you have to be very disciplined if you take the consulting route.\nYou have to work actively to prevent your company growing into a\n\"weed tree,\" dependent on this source of easy but low-margin money.\n[2]Indeed, the biggest danger of consulting may be that it gives you\nan excuse for failure. In a startup, as in grad school, a lot of\nwhat ends up driving you are the expectations of your family and\nfriends. Once you start a startup and tell everyone that's what\nyou're doing, you're now on a path labelled \"get rich or bust.\" You\nnow have to get rich, or you've failed.Fear of failure is an extraordinarily powerful force. Usually it\nprevents people from starting things, but once you publish some\ndefinite ambition, it switches directions and starts working in\nyour favor. I think it's a pretty clever piece of jiujitsu to set\nthis irresistible force against the slightly less immovable object\nof becoming rich. You won't have it driving you if your stated\nambition is merely to start a consulting company that you will one\nday morph into a startup.An advantage of consulting, as a way to develop a product, is that\nyou know you're making something at least one customer wants. But\nif you have what it takes to start a startup you should have\nsufficient vision not to need this crutch.Angel InvestorsAngels are individual rich people. The word was first used\nfor backers of Broadway plays, but now applies to individual investors\ngenerally. Angels who've made money in technology are preferable,\nfor two reasons: they understand your situation, and they're a\nsource of contacts and advice.The contacts and advice can be more important than the money. When\ndel.icio.us took money from investors, they took money from, among\nothers, Tim O'Reilly. The amount he put in was small compared to\nthe VCs who led the round, but Tim is a smart and influential guy\nand it's good to have him on your side.You can do whatever you want with money from consulting or friends\nand family. With angels we're now talking about venture funding\nproper, so it's time to introduce the concept of exit strategy.\nYounger would-be founders are often surprised that investors expect\nthem either to sell the company or go public. The reason is that\ninvestors need to get their capital back. They'll only consider\ncompanies that have an exit strategy—meaning companies that could\nget bought or go public.This is not as selfish as it sounds. There are few large, private\ntechnology companies. Those that don't fail all seem to get bought\nor go public. The reason is that employees are investors too—of\ntheir time—and they want just as much to be able to cash out. If\nyour competitors offer employees stock options that might make them\nrich, while you make it clear you plan to stay private, your\ncompetitors will get the best people. So the principle of an \"exit\"\nis not just something forced on startups by investors, but part of\nwhat it means to be a startup.Another concept we need to introduce now is valuation. When someone\nbuys shares in a company, that implicitly establishes a value for\nit. If someone pays $20,000 for 10% of a company, the company is\nin theory worth $200,000. I say \"in theory\" because in early stage\ninvesting, valuations are voodoo. As a company gets more established,\nits valuation gets closer to an actual market value. But in a newly\nfounded startup, the valuation number is just an artifact of the\nrespective contributions of everyone involved.Startups often \"pay\" investors who will help the company in some\nway by letting them invest at low valuations. If I had a startup\nand Steve Jobs wanted to invest in it, I'd give him the stock for\n$10, just to be able to brag that he was an investor. Unfortunately,\nit's impractical (if not illegal) to adjust the valuation of the\ncompany up and down for each investor. Startups' valuations are\nsupposed to rise over time. So if you're going to sell cheap stock\nto eminent angels, do it early, when it's natural for the company\nto have a low valuation.Some angel investors join together in syndicates. Any city where\npeople start startups will have one or more of them. In Boston the\nbiggest is the Common\nAngels. In the Bay Area it's the Band\nof Angels. You can find groups near you through the Angel Capital Association.\n[3]\nHowever, most angel investors don't belong to these groups. In\nfact, the more prominent the angel, the less likely they are to\nbelong to a group.Some angel groups charge you money to pitch your idea to them.\nNeedless to say, you should never do this.One of the dangers of taking investment from individual angels,\nrather than through an angel group or investment firm, is that they\nhave less reputation to protect. A big-name VC firm will not screw\nyou too outrageously, because other founders would avoid them if\nword got out. With individual angels you don't have this protection,\nas we found to our dismay in our own startup. In many startups'\nlives there comes a point when you're at the investors' \nmercy—when you're out of money and the only place to get more is your\nexisting investors. When we got into such a scrape, our investors\ntook advantage of it in a way that a name-brand VC probably wouldn't\nhave.Angels have a corresponding advantage, however: they're also not\nbound by all the rules that VC firms are. And so they can, for\nexample, allow founders to cash out partially in a funding round,\nby selling some of their stock directly to the investors. I think\nthis will become more common; the average founder is eager to do\nit, and selling, say, half a million dollars worth of stock will\nnot, as VCs fear, cause most founders to be any less committed to\nthe business.The same angels who tried to screw us also let us do this, and so\non balance I'm grateful rather than angry. (As in families, relations\nbetween founders and investors can be complicated.)The best way to find angel investors is through personal introductions.\nYou could try to cold-call angel groups near you, but angels, like\nVCs, will pay more attention to deals recommended by someone they\nrespect.Deal terms with angels vary a lot. There are no generally accepted\nstandards. Sometimes angels' deal terms are as fearsome as VCs'.\nOther angels, particularly in the earliest stages, will invest based\non a two-page agreement.Angels who only invest occasionally may not themselves know what\nterms they want. They just want to invest in this startup. What\nkind of anti-dilution protection do they want? Hell if they know.\nIn these situations, the deal terms tend to be random: the angel\nasks his lawyer to create a vanilla agreement, and the terms end\nup being whatever the lawyer considers vanilla. Which in practice\nusually means, whatever existing agreement he finds lying around\nhis firm. (Few legal documents are created from scratch.)These heaps o' boilerplate are a problem for small startups, because\nthey tend to grow into the union of all preceding documents. I\nknow of one startup that got from an angel investor what amounted\nto a five hundred pound handshake: after deciding to invest, the\nangel presented them with a 70-page agreement. The startup didn't\nhave enough money to pay a lawyer even to read it, let alone negotiate\nthe terms, so the deal fell through.One solution to this problem would be to have the startup's lawyer\nproduce the agreement, instead of the angel's. Some angels might\nbalk at this, but others would probably welcome it.Inexperienced angels often get cold feet when the time comes to\nwrite that big check. In our startup, one of the two angels in the\ninitial round took months to pay us, and only did after repeated\nnagging from our lawyer, who was also, fortunately, his lawyer.It's obvious why investors delay. Investing in startups is risky!\nWhen a company is only two months old, every day you wait\ngives you 1.7% more data about their trajectory. But the investor\nis already being compensated for that risk in the low price of the\nstock, so it is unfair to delay.Fair or not, investors do it if you let them. Even VCs do it. And\nfunding delays are a big distraction for founders, who ought to be\nworking on their company, not worrying about investors. What's a\nstartup to do? With both investors and acquirers, the only leverage\nyou have is competition. If an investor knows you have other\ninvestors lined up, he'll be a lot more eager to close-- and not\njust because he'll worry about losing the deal, but because if other\ninvestors are interested, you must be worth investing in. It's the\nsame with acquisitions. No one wants to buy you till someone else\nwants to buy you, and then everyone wants to buy you.The key to closing deals is never to stop pursuing alternatives.\nWhen an investor says he wants to invest in you, or an acquirer\nsays they want to buy you, don't believe it till you get the\ncheck. Your natural tendency when an investor says yes will\nbe to relax and go back to writing code. Alas, you can't; you have\nto keep looking for more investors, if only to get this one to act.\n[4]Seed Funding FirmsSeed firms are like angels in that they invest relatively small\namounts at early stages, but like VCs in that they're companies\nthat do it as a business, rather than individuals making occasional\ninvestments on the side.Till now, nearly all seed firms have been so-called \"incubators,\"\nso Y Combinator gets called\none too, though the only thing we have in common is that we invest\nin the earliest phase.According to the National Association of Business Incubators, there\nare about 800 incubators in the US. This is an astounding number,\nbecause I know the founders of a lot of startups, and I can't think\nof one that began in an incubator.What is an incubator? I'm not sure myself. The defining quality\nseems to be that you work in their space. That's where the name\n\"incubator\" comes from. They seem to vary a great deal in other\nrespects. At one extreme is the sort of pork-barrel project where\na town gets money from the state government to renovate a vacant\nbuilding as a \"high-tech incubator,\" as if it were merely lack of\nthe right sort of office space that had till now prevented the town\nfrom becoming a \nstartup hub. \nAt the other extreme are places like\nIdealab, which generates ideas for new startups internally and hires\npeople to work for them.The classic Bubble incubators, most of which now seem to be dead,\nwere like VC firms except that they took a much bigger role in the\nstartups they funded. In addition to working in their space, you\nwere supposed to use their office staff, lawyers, accountants, and\nso on.Whereas incubators tend (or tended) to exert more control than VCs,\nY Combinator exerts less. \nAnd we think it's better if startups operate out of their own\npremises, however crappy, than the offices of their investors. So\nit's annoying that we keep getting called an \"incubator,\" but perhaps\ninevitable, because there's only one of us so far and no word yet\nfor what we are. If we have to be called something, the obvious\nname would be \"excubator.\" (The name is more excusable if one\nconsiders it as meaning that we enable people to escape cubicles.)Because seed firms are companies rather than individual people,\nreaching them is easier than reaching angels. Just go to their web\nsite and send them an email. The importance of personal introductions\nvaries, but is less than with angels or VCs.The fact that seed firms are companies also means the investment\nprocess is more standardized. (This is generally true with angel\ngroups too.) Seed firms will probably have set deal terms they use\nfor every startup they fund. The fact that the deal terms are\nstandard doesn't mean they're favorable to you, but if other startups\nhave signed the same agreements and things went well for them, it's\na sign the terms are reasonable.Seed firms differ from angels and VCs in that they invest exclusively\nin the earliest phases—often when the company is still just an\nidea. Angels and even VC firms occasionally do this, but they also\ninvest at later stages.The problems are different in the early stages. For example, in\nthe first couple months a startup may completely redefine their idea. So seed investors usually care less\nabout the idea than the people. This is true of all venture funding,\nbut especially so in the seed stage.Like VCs, one of the advantages of seed firms is the advice they\noffer. But because seed firms operate in an earlier phase, they\nneed to offer different kinds of advice. For example, a seed firm\nshould be able to give advice about how to approach VCs, which VCs\nobviously don't need to do; whereas VCs should be able to give\nadvice about how to hire an \"executive team,\" which is not an issue\nin the seed stage.In the earliest phases, a lot of the problems are technical, so\nseed firms should be able to help with technical as well as business\nproblems.Seed firms and angel investors generally want to invest in the\ninitial phases of a startup, then hand them off to VC firms for the\nnext round. Occasionally startups go from seed funding direct to\nacquisition, however, and I expect this to become increasingly\ncommon.Google has been aggressively pursuing this route, and now Yahoo is too. Both\nnow compete directly with VCs. And this is a smart move. Why wait\nfor further funding rounds to jack up a startup's price? When a\nstartup reaches the point where VCs have enough information to\ninvest in it, the acquirer should have enough information to buy\nit. More information, in fact; with their technical depth, the\nacquirers should be better at picking winners than VCs.Venture Capital FundsVC firms are like seed firms in that they're actual companies, but\nthey invest other people's money, and much larger amounts of it.\nVC investments average several million dollars. So they tend to\ncome later in the life of a startup, are harder to get, and come\nwith tougher terms.The word \"venture capitalist\" is sometimes used loosely for any\nventure investor, but there is a sharp difference between VCs and\nother investors: VC firms are organized as funds, much like\nhedge funds or mutual funds. The fund managers, who are called\n\"general partners,\" get about 2% of the fund annually as a management\nfee, plus about 20% of the fund's gains.There is a very sharp dropoff in performance among VC firms, because\nin the VC business both success and failure are self-perpetuating.\nWhen an investment scores spectacularly, as Google did for Kleiner\nand Sequoia, it generates a lot of good publicity for the VCs. And\nmany founders prefer to take money from successful VC firms, because\nof the legitimacy it confers. Hence a vicious (for the losers)\ncycle: VC firms that have been doing badly will only get the deals\nthe bigger fish have rejected, causing them to continue to do badly.As a result, of the thousand or so VC funds in the US now, only\nabout 50 are likely to make money, and it is very hard for a new\nfund to break into this group.In a sense, the lower-tier VC firms are a bargain for founders.\nThey may not be quite as smart or as well connected as the big-name\nfirms, but they are much hungrier for deals. This means you should\nbe able to get better terms from them.Better how? The most obvious is valuation: they'll take less of\nyour company. But as well as money, there's power. I think founders\nwill increasingly be able to stay on as CEO, and on terms that will\nmake it fairly hard to fire them later.The most dramatic change, I predict,\nis that VCs will allow founders to \ncash out partially by selling\nsome of their stock direct to the VC firm. VCs have traditionally\nresisted letting founders get anything before the ultimate \"liquidity\nevent.\" But they're also desperate for deals. And since I know\nfrom my own experience that the rule against buying stock from\nfounders is a stupid one, this is a natural place for things to\ngive as venture funding becomes more and more a seller's market.The disadvantage of taking money from less known firms is that\npeople will assume, correctly or not, that you were turned down by\nthe more exalted ones. But, like where you went to college, the\nname of your VC stops mattering once you have some performance to\nmeasure. So the more confident you are, the less you need a\nbrand-name VC. We funded Viaweb entirely with angel money; it never\noccurred to us that the backing of a well known VC firm would make\nus seem more impressive.\n[5]Another danger of less known firms is that, like angels, they have\nless reputation to protect. I suspect it's the lower-tier firms\nthat are responsible for most of the tricks that have given VCs\nsuch a bad reputation among hackers. They are doubly hosed: the\ngeneral partners themselves are less able, and yet they have harder\nproblems to solve, because the top VCs skim off all the best deals,\nleaving the lower-tier firms exactly the startups that are likely\nto blow up.For example, lower-tier firms are much more likely to pretend to\nwant to do a deal with you just to lock you up while they decide\nif they really want to. One experienced CFO said:\n\n The better ones usually will not give a term sheet unless they\n really want to do a deal. The second or third tier firms have a\n much higher break rate—it could be as high as 50%.\n\nIt's obvious why: the lower-tier firms' biggest fear, when chance\nthrows them a bone, is that one of the big dogs will notice and\ntake it away. The big dogs don't have to worry about that.Falling victim to this trick could really hurt you. As one\nVC told me:\n\n If you were talking to four VCs, told three of them that you\n accepted a term sheet, and then have to call them back to tell\n them you were just kidding, you are absolutely damaged goods.\n\nHere's a partial solution: when a VC offers you a term sheet, ask\nhow many of their last 10 term sheets turned into deals. This will\nat least force them to lie outright if they want to mislead you.Not all the people who work at VC firms are partners. Most firms\nalso have a handful of junior employees called something like\nassociates or analysts. If you get a call from a VC\nfirm, go to their web site and check whether the person you talked\nto is a partner. Odds are it will be a junior person; they scour\nthe web looking for startups their bosses could invest in. The\njunior people will tend to seem very positive about your company.\nThey're not pretending; they want to believe you're a hot\nprospect, because it would be a huge coup for them if their firm\ninvested in a company they discovered. Don't be misled by this\noptimism. It's the partners who decide, and they view things with\na colder eye.Because VCs invest large amounts, the money comes with more\nrestrictions. Most only come into effect if the company gets into\ntrouble. For example, VCs generally write it into the deal that\nin any sale, they get their investment back first. So if the company\ngets sold at a low price, the founders could get nothing. Some VCs\nnow require that in any sale they get 4x their investment back\nbefore the common stock holders (that is, you) get anything, but\nthis is an abuse that should be resisted.Another difference with large investments is that the founders are\nusually required to accept \"vesting\"—to surrender their stock and\nearn it back over the next 4-5 years. VCs don't want to invest\nmillions in a company the founders could just walk away from.\nFinancially, vesting has little effect, but in some situations it\ncould mean founders will have less power. If VCs got de facto\ncontrol of the company and fired one of the founders, he'd lose any\nunvested stock unless there was specific protection against this.\nSo vesting would in that situation force founders to toe the line.The most noticeable change when a startup takes serious funding is\nthat the founders will no longer have complete control. Ten years\nago VCs used to insist that founders step down as CEO and hand the\njob over to a business guy they supplied. This is less the rule\nnow, partly because the disasters of the Bubble showed that generic\nbusiness guys don't make such great CEOs.But while founders will increasingly be able to stay on as CEO,\nthey'll have to cede some power, because the board of directors\nwill become more powerful. In the seed stage, the board is generally\na formality; if you want to talk to the other board members, you\njust yell into the next room. This stops with VC-scale money. In\na typical VC funding deal, the board of directors might be composed\nof two VCs, two founders, and one outside person acceptable to both.\nThe board will have ultimate power, which means the founders now\nhave to convince instead of commanding.This is not as bad as it sounds, however. Bill Gates is in the\nsame position; he doesn't have majority control of Microsoft; in\nprinciple he also has to convince instead of commanding. And yet\nhe seems pretty commanding, doesn't he? As long as things are going\nsmoothly, boards don't interfere much. The danger comes when there's\na bump in the road, as happened to Steve Jobs at Apple.Like angels, VCs prefer to invest in deals that come to them through\npeople they know. So while nearly all VC funds have some address\nyou can send your business plan to, VCs privately admit the chance\nof getting funding by this route is near zero. One recently told\nme that he did not know a single startup that got funded this way.I suspect VCs accept business plans \"over the transom\" more as a\nway to keep tabs on industry trends than as a source of deals. In\nfact, I would strongly advise against mailing your business plan\nrandomly to VCs, because they treat this as evidence of laziness.\nDo the extra work of getting personal introductions. As one VC put\nit:\n\n I'm not hard to find. I know a lot of people. If you can't find\n some way to reach me, how are you going to create a successful\n company?\n\nOne of the most difficult problems for startup founders is deciding\nwhen to approach VCs. You really only get one chance, because they\nrely heavily on first impressions. And you can't approach some and\nsave others for later, because (a) they ask who else you've talked\nto and when and (b) they talk among themselves. If you're talking\nto one VC and he finds out that you were rejected by another several\nmonths ago, you'll definitely seem shopworn.So when do you approach VCs? When you can convince them. If the\nfounders have impressive resumes and the idea isn't hard to understand,\nyou could approach VCs quite early. Whereas if the founders are\nunknown and the idea is very novel, you might have to launch the\nthing and show that users loved it before VCs would be convinced.If several VCs are interested in you, they will sometimes be willing\nto split the deal between them. They're more likely to do this if\nthey're close in the VC pecking order. Such deals may be a net win\nfor founders, because you get multiple VCs interested in your\nsuccess, and you can ask each for advice about the other. One\nfounder I know wrote:\n\n Two-firm deals are great. It costs you a little more equity, but\n being able to play the two firms off each other (as well as ask\n one if the other is being out of line) is invaluable.\n\nWhen you do negotiate with VCs, remember that they've done this a\nlot more than you have. They've invested in dozens of startups,\nwhereas this is probably the first you've founded. But don't let\nthem or the situation intimidate you. The average founder is smarter\nthan the average VC. So just do what you'd do in any complex,\nunfamiliar situation: proceed deliberately, and question anything\nthat seems odd.It is, unfortunately, common for VCs to put terms in an agreement\nwhose consequences surprise founders later, and also common for VCs\nto defend things they do by saying that they're standard in the\nindustry. Standard, schmandard; the whole industry is only a few\ndecades old, and rapidly evolving. The concept of \"standard\" is a\nuseful one when you're operating on a small scale (Y Combinator\nuses identical terms for every deal because for tiny seed-stage\ninvestments it's not worth the overhead of negotiating individual\ndeals), but it doesn't apply at the VC level. On that scale, every\nnegotiation is unique.Most successful startups get money from more than one of the preceding\nfive sources. \n[6]\nAnd, confusingly, the names of funding sources\nalso tend to be used as the names of different rounds. The best\nway to explain how it all works is to follow the case of a hypothetical\nstartup.Stage 1: Seed RoundOur startup begins when a group of three friends have an idea--\neither an idea for something they might build, or simply the idea\n\"let's start a company.\" Presumably they already have some source\nof food and shelter. But if you have food and shelter, you probably\nalso have something you're supposed to be working on: either\nclasswork, or a job. So if you want to work full-time on a startup,\nyour money situation will probably change too.A lot of startup founders say they started the company without any\nidea of what they planned to do. This is actually less common than\nit seems: many have to claim they thought of the idea after quitting\nbecause otherwise their former employer would own it.The three friends decide to take the leap. Since most startups are\nin competitive businesses, you not only want to work full-time on\nthem, but more than full-time. So some or all of the friends quit\ntheir jobs or leave school. (Some of the founders in a startup can\nstay in grad school, but at least one has to make the company his\nfull-time job.)They're going to run the company out of one of their apartments at\nfirst, and since they don't have any users they don't have to pay\nmuch for infrastructure. Their main expenses are setting up the\ncompany, which costs a couple thousand dollars in legal work and\nregistration fees, and the living expenses of the founders.The phrase \"seed investment\" covers a broad range. To some VC firms\nit means $500,000, but to most startups it means several months'\nliving expenses. We'll suppose our group of friends start with\n$15,000 from their friend's rich uncle, who they give 5% of the\ncompany in return. There's only common stock at this stage. They\nleave 20% as an options pool for later employees (but they set\nthings up so that they can issue this stock to themselves if they\nget bought early and most is still unissued), and the three founders\neach get 25%.By living really cheaply they think they can make the remaining\nmoney last five months. When you have five months' runway left,\nhow soon do you need to start looking for your next round? Answer:\nimmediately. It takes time to find investors, and time (always\nmore than you expect) for the deal to close even after they say\nyes. So if our group of founders know what they're doing they'll\nstart sniffing around for angel investors right away. But of course\ntheir main job is to build version 1 of their software.The friends might have liked to have more money in this first phase,\nbut being slightly underfunded teaches them an important lesson.\nFor a startup, cheapness is power. The lower your costs, the more\noptions you have—not just at this stage, but at every point till\nyou're profitable. When you have a high \"burn rate,\" you're always\nunder time pressure, which means (a) you don't have time for your\nideas to evolve, and (b) you're often forced to take deals you don't\nlike.Every startup's rule should be: spend little, and work fast.After ten weeks' work the three friends have built a prototype that\ngives one a taste of what their product will do. It's not what\nthey originally set out to do—in the process of writing it, they\nhad some new ideas. And it only does a fraction of what the finished\nproduct will do, but that fraction includes stuff that no one else\nhas done before.They've also written at least a skeleton business plan, addressing\nthe five fundamental questions: what they're going to do, why users\nneed it, how large the market is, how they'll make money, and who\nthe competitors are and why this company is going to beat them.\n(That last has to be more specific than \"they suck\" or \"we'll work\nreally hard.\")If you have to choose between spending time on the demo or the\nbusiness plan, spend most on the demo. Software is not only more\nconvincing, but a better way to explore ideas.Stage 2: Angel RoundWhile writing the prototype, the group has been traversing their\nnetwork of friends in search of angel investors. They find some\njust as the prototype is demoable. When they demo it, one of the\nangels is willing to invest. Now the group is looking for more\nmoney: they want enough to last for a year, and maybe to hire a\ncouple friends. So they're going to raise $200,000.The angel agrees to invest at a pre-money valuation of $1 million.\nThe company issues $200,000 worth of new shares to the angel; if\nthere were 1000 shares before the deal, this means 200 additional\nshares. The angel now owns 200/1200 shares, or a sixth of the\ncompany, and all the previous shareholders' percentage ownership\nis diluted by a sixth. After the deal, the capitalization table\nlooks like this:\n\nshareholder shares percent\n-------------------------------\nangel 200 16.7\nuncle 50 4.2\neach founder 250 20.8\noption pool 200 16.7\n ---- -----\ntotal 1200 100\n\nTo keep things simple, I had the angel do a straight cash for stock\ndeal. In reality the angel might be more likely to make the\ninvestment in the form of a convertible loan. A convertible loan\nis a loan that can be converted into stock later; it works out the\nsame as a stock purchase in the end, but gives the angel more\nprotection against being squashed by VCs in future rounds.Who pays the legal bills for this deal? The startup, remember,\nonly has a couple thousand left. In practice this turns out to be\na sticky problem that usually gets solved in some improvised way.\nMaybe the startup can find lawyers who will do it cheaply in the\nhope of future work if the startup succeeds. Maybe someone has a\nlawyer friend. Maybe the angel pays for his lawyer to represent\nboth sides. (Make sure if you take the latter route that the lawyer\nis representing you rather than merely advising you, or his\nonly duty is to the investor.)An angel investing $200k would probably expect a seat on the board\nof directors. He might also want preferred stock, meaning a special\nclass of stock that has some additional rights over the common stock\neveryone else has. Typically these rights include vetoes over major\nstrategic decisions, protection against being diluted in future\nrounds, and the right to get one's investment back first if the\ncompany is sold.Some investors might expect the founders to accept vesting for a\nsum this size, and others wouldn't. VCs are more likely to require\nvesting than angels. At Viaweb we managed to raise $2.5 million\nfrom angels without ever accepting vesting, largely because we were\nso inexperienced that we were appalled at the idea. In practice\nthis turned out to be good, because it made us harder to push around.Our experience was unusual; vesting is the norm for amounts that\nsize. Y Combinator doesn't require vesting, because (a) we invest\nsuch small amounts, and (b) we think it's unnecessary, and that the\nhope of getting rich is enough motivation to keep founders at work.\nBut maybe if we were investing millions we would think differently.I should add that vesting is also a way for founders to protect\nthemselves against one another. It solves the problem of what to\ndo if one of the founders quits. So some founders impose it on\nthemselves when they start the company.The angel deal takes two weeks to close, so we are now three months\ninto the life of the company.The point after you get the first big chunk of angel money will\nusually be the happiest phase in a startup's life. It's a lot like\nbeing a postdoc: you have no immediate financial worries, and few\nresponsibilities. You get to work on juicy kinds of work, like\ndesigning software. You don't have to spend time on bureaucratic\nstuff, because you haven't hired any bureaucrats yet. Enjoy it\nwhile it lasts, and get as much done as you can, because you will\nnever again be so productive.With an apparently inexhaustible sum of money sitting safely in the\nbank, the founders happily set to work turning their prototype into\nsomething they can release. They hire one of their friends—at\nfirst just as a consultant, so they can try him out—and then a\nmonth later as employee #1. They pay him the smallest salary he can\nlive on, plus 3% of the company in restricted stock, vesting over\nfour years. (So after this the option pool is down to 13.7%). \n[7]\nThey also spend a little money on a freelance graphic designer.How much stock do you give early employees? That varies so much\nthat there's no conventional number. If you get someone really\ngood, really early, it might be wise to give him as much stock as\nthe founders. The one universal rule is that the amount of stock\nan employee gets decreases polynomially with the age of the company.\nIn other words, you get rich as a power of how early you were. So\nif some friends want you to come work for their startup, don't wait\nseveral months before deciding.A month later, at the end of month four, our group of founders have\nsomething they can launch. Gradually through word of mouth they\nstart to get users. Seeing the system in use by real users—people\nthey don't know—gives them lots of new ideas. Also they find\nthey now worry obsessively about the status of their server. (How\nrelaxing founders' lives must have been when startups wrote VisiCalc.)By the end of month six, the system is starting to have a solid\ncore of features, and a small but devoted following. People start\nto write about it, and the founders are starting to feel like experts\nin their field.We'll assume that their startup is one that could put millions more\nto use. Perhaps they need to spend a lot on marketing, or build\nsome kind of expensive infrastructure, or hire highly paid salesmen.\nSo they decide to start talking to VCs. They get introductions to\nVCs from various sources: their angel investor connects them with\na couple; they meet a few at conferences; a couple VCs call them\nafter reading about them.Step 3: Series A RoundArmed with their now somewhat fleshed-out business plan and able\nto demo a real, working system, the founders visit the VCs they\nhave introductions to. They find the VCs intimidating and inscrutable.\nThey all ask the same question: who else have you pitched to? (VCs\nare like high school girls: they're acutely aware of their position\nin the VC pecking order, and their interest in a company is a\nfunction of the interest other VCs show in it.)One of the VC firms says they want to invest and offers the founders\na term sheet. A term sheet is a summary of what the deal terms\nwill be when and if they do a deal; lawyers will fill in the details\nlater. By accepting the term sheet, the startup agrees to turn\naway other VCs for some set amount of time while this firm does the\n\"due diligence\" required for the deal. Due diligence is the corporate\nequivalent of a background check: the purpose is to uncover any\nhidden bombs that might sink the company later, like serious design\nflaws in the product, pending lawsuits against the company,\nintellectual property issues, and so on. VCs' legal and financial\ndue diligence is pretty thorough, but the technical due diligence\nis generally a joke. \n[8]The due diligence discloses no ticking bombs, and six weeks later\nthey go ahead with the deal. Here are the terms: a $2 million\ninvestment at a pre-money valuation of $4 million, meaning that\nafter the deal closes the VCs will own a third of the company (2 /\n(4 + 2)). The VCs also insist that prior to the deal the option\npool be enlarged by an additional hundred shares. So the total\nnumber of new shares issued is 750, and the cap table becomes:\n\nshareholder shares percent\n-------------------------------\nVCs 650 33.3\nangel 200 10.3\nuncle 50 2.6\neach founder 250 12.8\nemployee 36* 1.8 *unvested\noption pool 264 13.5\n ---- -----\ntotal 1950 100\n\nThis picture is unrealistic in several respects. For example, while\nthe percentages might end up looking like this, it's unlikely that\nthe VCs would keep the existing numbers of shares. In fact, every\nbit of the startup's paperwork would probably be replaced, as if\nthe company were being founded anew. Also, the money might come\nin several tranches, the later ones subject to various \nconditions—though this is apparently more common in deals with lower-tier VCs\n(whose lot in life is to fund more dubious startups) than with the\ntop firms.And of course any VCs reading this are probably rolling on the floor\nlaughing at how my hypothetical VCs let the angel keep his 10.3 of\nthe company. I admit, this is the Bambi version; in simplifying\nthe picture, I've also made everyone nicer. In the real world, VCs\nregard angels the way a jealous husband feels about his wife's\nprevious boyfriends. To them the company didn't exist before they\ninvested in it. \n[9]I don't want to give the impression you have to do an angel round\nbefore going to VCs. In this example I stretched things out to\nshow multiple sources of funding in action. Some startups could go\ndirectly from seed funding to a VC round; several of the companies\nwe've funded have.The founders are required to vest their shares over four years, and\nthe board is now reconstituted to consist of two VCs, two founders,\nand a fifth person acceptable to both. The angel investor cheerfully\nsurrenders his board seat.At this point there is nothing new our startup can teach us about\nfunding—or at least, nothing good. \n[10]\nThe startup will almost\ncertainly hire more people at this point; those millions must be\nput to work, after all. The company may do additional funding\nrounds, presumably at higher valuations. They may if they are\nextraordinarily fortunate do an IPO, which we should remember is\nalso in principle a round of funding, regardless of its de facto\npurpose. But that, if not beyond the bounds of possibility, is\nbeyond the scope of this article.Deals Fall ThroughAnyone who's been through a startup will find the preceding portrait\nto be missing something: disasters. If there's one thing all\nstartups have in common, it's that something is always going wrong.\nAnd nowhere more than in matters of funding.For example, our hypothetical startup never spent more than half\nof one round before securing the next. That's more ideal than\ntypical. Many startups—even successful ones—come close to\nrunning out of money at some point. Terrible things happen to\nstartups when they run out of money, because they're designed for\ngrowth, not adversity.But the most unrealistic thing about the series of deals I've\ndescribed is that they all closed. In the startup world, closing\nis not what deals do. What deals do is fall through. If you're\nstarting a startup you would do well to remember that. Birds fly;\nfish swim; deals fall through.Why? Partly the reason deals seem to fall through so often is that\nyou lie to yourself. You want the deal to close, so you start to\nbelieve it will. But even correcting for this, startup deals fall\nthrough alarmingly often—far more often than, say, deals to buy\nreal estate. The reason is that it's such a risky environment.\nPeople about to fund or acquire a startup are prone to wicked cases\nof buyer's remorse. They don't really grasp the risk they're taking\ntill the deal's about to close. And then they panic. And not just\ninexperienced angel investors, but big companies too.So if you're a startup founder wondering why some angel investor\nisn't returning your phone calls, you can at least take comfort in\nthe thought that the same thing is happening to other deals a hundred\ntimes the size.The example of a startup's history that I've presented is like a\nskeleton—accurate so far as it goes, but needing to be fleshed\nout to be a complete picture. To get a complete picture, just add\nin every possible disaster.A frightening prospect? In a way. And yet also in a way encouraging.\nThe very uncertainty of startups frightens away almost everyone.\nPeople overvalue stability—especially young\npeople, who ironically need it least. And so in starting a startup,\nas in any really bold undertaking, merely deciding to do it gets\nyou halfway there. On the day of the race, most of the other runners\nwon't show up.\nNotes[1]\nThe aim of such regulations is to protect widows and orphans\nfrom crooked investment schemes; people with a million dollars in\nliquid assets are assumed to be able to protect themselves.\nThe unintended consequence is that the investments that generate\nthe highest returns, like hedge funds, are available only to the\nrich.[2]\nConsulting is where product companies go to die. IBM is the\nmost famous example. So starting as a consulting company is like\nstarting out in the grave and trying to work your way up into the\nworld of the living.[3]\nIf \"near you\" doesn't mean the Bay Area, Boston, or Seattle,\nconsider moving. It's not a coincidence you haven't heard of many\nstartups from Philadelphia.[4]\nInvestors are often compared to sheep. And they are like sheep,\nbut that's a rational response to their situation. Sheep act the\nway they do for a reason. If all the other sheep head for a certain\nfield, it's probably good grazing. And when a wolf appears, is he\ngoing to eat a sheep in the middle of the flock, or one near the\nedge?[5]\nThis was partly confidence, and partly simple ignorance. We\ndidn't know ourselves which VC firms were the impressive ones. We\nthought software was all that mattered. But that turned out to be\nthe right direction to be naive in: it's much better to overestimate\nthan underestimate the importance of making a good product.[6]\nI've omitted one source: government grants. I don't think\nthese are even worth thinking about for the average startup.\nGovernments may mean well when they set up grant programs to encourage\nstartups, but what they give with one hand they take away with the\nother: the process of applying is inevitably so arduous, and the\nrestrictions on what you can do with the money so burdensome, that\nit would be easier to take a job to get the money.\nYou should be especially suspicious of grants whose purpose is some\nkind of social engineering-- e.g. to encourage more startups to be\nstarted in Mississippi. Free money to start a startup in a place\nwhere few succeed is hardly free.Some government agencies run venture funding groups, which make\ninvestments rather than giving grants. For example, the CIA runs\na venture fund called In-Q-Tel that is modelled on private sector\nfunds and apparently generates good returns. They would probably\nbe worth approaching—if you don't mind taking money from the CIA.[7]\nOptions have largely been replaced with restricted stock, which\namounts to the same thing. Instead of earning the right to buy\nstock, the employee gets the stock up front, and earns the right\nnot to have to give it back. The shares set aside for this purpose\nare still called the \"option pool.\"[8]\nFirst-rate technical people do not generally hire themselves\nout to do due diligence for VCs. So the most difficult\npart for startup founders is often responding politely to the inane\nquestions of the \"expert\" they send to look you over.[9]\nVCs regularly wipe out angels by issuing arbitrary amounts of\nnew stock. They seem to have a standard piece of casuistry for\nthis situation: that the angels are no longer working to help the\ncompany, and so don't deserve to keep their stock. This of course\nreflects a willful misunderstanding of what investment means; like\nany investor, the angel is being compensated for risks he took\nearlier. By a similar logic, one could argue that the VCs should\nbe deprived of their shares when the company goes public.[10]\nOne new thing the company might encounter is a down\nround, or a funding round at valuation lower than the previous\nround. Down rounds are bad news; it is generally the common stock\nholders who take the hit. Some of the most fearsome provisions in\nVC deal terms have to do with down rounds—like \"full ratchet\nanti-dilution,\" which is as frightening as it sounds.Founders are tempted to ignore these clauses, because they think\nthe company will either be a big success or a complete bust. VCs\nknow otherwise: it's not uncommon for startups to have moments of\nadversity before they ultimately succeed. So it's worth negotiating\nanti-dilution provisions, even though you don't think you need to,\nand VCs will try to make you feel that you're being gratuitously\ntroublesome.Thanks to Sam Altman, Hutch Fishman, Steve Huffman, Jessica\nLivingston, Sesha Pratap, Stan Reiss, Andy Singleton, Zak Stone,\nand Aaron Swartz for reading drafts of this." }, { "path": "data/PaulGrahamEssays/startuphubs.txt", "content": "October 2007After the last \ntalk I gave, one of the organizers \ngot up on the\nstage to deliver an impromptu rebuttal. That never happened before.\nI only heard the first few sentences, but that was enough to tell\nwhat I said that upset him: that startups would do better if they\nmoved to Silicon Valley.This conference was in London, and most of the audience seemed to\nbe from the UK. So saying startups should move to Silicon Valley\nseemed like a nationalistic remark: an obnoxious American telling\nthem that if they wanted to do things right they should all just\nmove to America.Actually I'm less American than I seem. I didn't say so, but I'm\nBritish by birth. And just as Jews are ex officio allowed to tell\nJewish jokes, I don't feel like I have to bother being diplomatic\nwith a British audience.The idea that startups would do better to move to Silicon Valley\nis not even a nationalistic one.\n[1]\nIt's the same thing I say to\nstartups in the US. Y Combinator alternates between coasts every\n6 months. Every other funding cycle is in Boston. And even though\nBoston is the second biggest startup hub in the US (and the world),\nwe tell the startups from those cycles that their best bet is to\nmove to Silicon Valley. If that's true of Boston, it's even more\ntrue of every other city.This is about cities, not countries.And I think I can prove I'm right. You can easily reduce the\nopposing argument ad what most people would agree was absurdum.\nFew would be willing to claim that it doesn't matter at all where\na startup is—that a startup operating out of a small agricultural\ntown wouldn't benefit from moving to a startup hub. Most people\ncould see how it might be helpful to be in a place where there was\ninfrastructure for startups, accumulated knowledge about how to\nmake them work, and other people trying to do it. And yet whatever\nargument you use to prove that startups don't need to move from\nLondon to Silicon Valley could equally well be used to prove startups\ndon't need to move from smaller towns to London.The difference between cities is a matter of degree. And if, as\nnearly everyone who knows agrees, startups are better off in Silicon\nValley than Boston, then they're better off in Silicon Valley than\neverywhere else too.I realize I might seem to have a vested interest in this conclusion,\nbecause startups that move to the US might do it through Y Combinator.\nBut the American startups we've funded will attest that I say the\nsame thing to them.I'm not claiming of course that every startup has to go to Silicon\nValley to succeed. Just that all other things being equal, the\nmore of a startup hub a place is, the better startups will do there.\nBut other considerations can outweigh the advantages of moving.\nI'm not saying founders with families should uproot them to move\nhalfway around the world; that might be too much of a distraction.Immigration difficulties might be another reason to stay put.\nDealing with immigration problems is like raising money: for some\nreason it seems to consume all your attention. A startup can't\nafford much of that. One Canadian startup we funded spent about 6\nmonths working on moving to the US. Eventually they just gave up,\nbecause they couldn't afford to take so much time away from working\non their software.(If another country wanted to establish a rival to Silicon Valley,\nthe single best thing they could do might be to create a special\nvisa for startup founders. US immigration policy is one of Silicon \nValley's biggest weaknesses.)If your startup is connected to a specific industry, you may be\nbetter off in one of its centers. A startup doing something related\nto entertainment might want to be in New York or LA.And finally, if a good investor has committed to fund\nyou if you stay where you are, you should probably stay. Finding\ninvestors is hard. You generally shouldn't pass up a definite\nfunding offer to move.\n[2]In fact, the quality of the investors may be the main advantage of\nstartup hubs. Silicon Valley investors are noticeably more aggressive\nthan Boston ones. Over and over, I've seen startups we've funded\nsnatched by west coast investors out from under the noses of Boston\ninvestors who saw them first but acted too slowly. At this year's\nBoston Demo Day, I told the audience that this happened every year,\nso if they saw a startup they liked, they should make them an offer.\nAnd yet within a month it had happened again: an aggressive west\ncoast VC who had met the founder of a YC-funded startup a week\nbefore beat out a Boston VC who had known him for years. By the\ntime the Boston VC grasped what was happening, the deal was already\ngone.Boston investors will admit they're more conservative. Some want\nto believe this comes from the city's prudent Yankee character.\nBut Occam's razor suggests the truth is less flattering. Boston\ninvestors are probably more conservative than Silicon Valley investors\nfor the same reason Chicago investors are more conservative than\nBoston ones. They don't understand startups as well.West coast investors aren't bolder because they're irresponsible\ncowboys, or because the good weather makes them optimistic. They're\nbolder because they know what they're doing. They're the skiers\nwho ski on the diamond slopes. Boldness is the essence of venture\ninvesting. The way you get big returns is not by trying to avoid\nlosses, but by trying to ensure you get some of the big hits. And\nthe big hits often look risky at first.Like Facebook. Facebook was started in Boston. Boston VCs had the\nfirst shot at them. But they said no, so Facebook moved to Silicon\nValley and raised money there. The partner who turned them down\nnow says that \"may turn out to have been a mistake.\"Empirically, boldness wins. If the aggressive ways of west coast\ninvestors are going to come back to bite them, it has been a long\ntime coming. Silicon Valley has been pulling ahead of Boston since\nthe 1970s. If there was going to be a comeuppance for the west\ncoast investors, the bursting of the Bubble would have been it.\nBut since then the west coast has just pulled further ahead.West coast investors are confident enough of their judgement to act\nboldly; east coast investors, not so much; but anyone who thinks\neast coast investors act that way out of prudence should see the\nfrantic reactions of an east coast VC in the process of losing a\ndeal to a west coast one.In addition to the concentration that comes from specialization,\nstartup hubs are also markets. And markets are usually centralized.\nEven now, when traders could be anywhere, they cluster in a few\ncities. It's hard to say exactly what it is about face to face\ncontact that makes deals happen, but whatever it is, it hasn't yet\nbeen duplicated by technology.Walk down University Ave at the right time, and you might overhear\nfive different people talking on the phone about deals. In fact,\nthis is part of the reason Y Combinator is in Boston half the time:\nit's hard to stand that year round. But though it can sometimes\nbe annoying to be surrounded by people who only think about one\nthing, it's the place to be if that one thing is what you're trying\nto do.I was talking recently to someone who works on search at Google.\nHe knew a lot of people at Yahoo, so he was in a good position to\ncompare the two companies. I asked him why Google was better at\nsearch. He said it wasn't anything specific Google did, but simply\nthat they understood search so much better.And that's why startups thrive in startup hubs like Silicon Valley.\nStartups are a very specialized business, as specialized as diamond\ncutting. And in startup hubs they understand it.\nNotes[1]\nThe nationalistic idea is the converse: that startups should\nstay in a certain city because of the country it's in. If you\nreally have a \"one world\" viewpoint, deciding to move from London\nto Silicon Valley is no different from deciding to move from Chicago\nto Silicon Valley.[2]\nAn investor who merely seems like he will fund you, however,\nyou can ignore. Seeming like they will fund you one day is the way\ninvestors say No.Thanks to Sam Altman, Jessica Livingston, Harjeet Taggar, and Kulveer\nTaggar for reading drafts of this.\nComment on this essay." }, { "path": "data/PaulGrahamEssays/startupideas.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nNovember 2012The way to get startup ideas is not to try to think of startup\nideas. It's to look for problems, preferably problems you have\nyourself.The very best startup ideas tend to have three things in common:\nthey're something the founders themselves want, that they themselves\ncan build, and that few others realize are worth doing. Microsoft,\nApple, Yahoo, Google, and Facebook all began this way.\nProblemsWhy is it so important to work on a problem you have? Among other\nthings, it ensures the problem really exists. It sounds obvious\nto say you should only work on problems that exist. And yet by far\nthe most common mistake startups make is to solve problems no one\nhas.I made it myself. In 1995 I started a company to put art galleries\nonline. But galleries didn't want to be online. It's not how the\nart business works. So why did I spend 6 months working on this\nstupid idea? Because I didn't pay attention to users. I invented\na model of the world that didn't correspond to reality, and worked\nfrom that. I didn't notice my model was wrong until I tried\nto convince users to pay for what we'd built. Even then I took\nembarrassingly long to catch on. I was attached to my model of the\nworld, and I'd spent a lot of time on the software. They had to\nwant it!Why do so many founders build things no one wants? Because they\nbegin by trying to think of startup ideas. That m.o. is doubly\ndangerous: it doesn't merely yield few good ideas; it yields bad\nideas that sound plausible enough to fool you into working on them.At YC we call these \"made-up\" or \"sitcom\" startup ideas. Imagine\none of the characters on a TV show was starting a startup. The\nwriters would have to invent something for it to do. But coming\nup with good startup ideas is hard. It's not something you can do\nfor the asking. So (unless they got amazingly lucky) the writers\nwould come up with an idea that sounded plausible, but was actually\nbad.For example, a social network for pet owners. It doesn't sound\nobviously mistaken. Millions of people have pets. Often they care\na lot about their pets and spend a lot of money on them. Surely\nmany of these people would like a site where they could talk to\nother pet owners. Not all of them perhaps, but if just 2 or 3\npercent were regular visitors, you could have millions of users.\nYou could serve them targeted offers, and maybe charge for premium\nfeatures. \n[1]The danger of an idea like this is that when you run it by your\nfriends with pets, they don't say \"I would never use this.\" They\nsay \"Yeah, maybe I could see using something like that.\" Even when\nthe startup launches, it will sound plausible to a lot of people.\nThey don't want to use it themselves, at least not right now, but\nthey could imagine other people wanting it. Sum that reaction\nacross the entire population, and you have zero users. \n[2]\nWellWhen a startup launches, there have to be at least some users who\nreally need what they're making — not just people who could see\nthemselves using it one day, but who want it urgently. Usually\nthis initial group of users is small, for the simple reason that\nif there were something that large numbers of people urgently needed\nand that could be built with the amount of effort a startup usually\nputs into a version one, it would probably already exist. Which\nmeans you have to compromise on one dimension: you can either build\nsomething a large number of people want a small amount, or something\na small number of people want a large amount. Choose the latter.\nNot all ideas of that type are good startup ideas, but nearly all\ngood startup ideas are of that type.Imagine a graph whose x axis represents all the people who might\nwant what you're making and whose y axis represents how much they\nwant it. If you invert the scale on the y axis, you can envision\ncompanies as holes. Google is an immense crater: hundreds of\nmillions of people use it, and they need it a lot. A startup just\nstarting out can't expect to excavate that much volume. So you\nhave two choices about the shape of hole you start with. You can\neither dig a hole that's broad but shallow, or one that's narrow\nand deep, like a well.Made-up startup ideas are usually of the first type. Lots of people\nare mildly interested in a social network for pet owners.Nearly all good startup ideas are of the second type. Microsoft\nwas a well when they made Altair Basic. There were only a couple\nthousand Altair owners, but without this software they were programming\nin machine language. Thirty years later Facebook had the same\nshape. Their first site was exclusively for Harvard students, of\nwhich there are only a few thousand, but those few thousand users\nwanted it a lot.When you have an idea for a startup, ask yourself: who wants this\nright now? Who wants this so much that they'll use it even when\nit's a crappy version one made by a two-person startup they've never\nheard of? If you can't answer that, the idea is probably bad. \n[3]You don't need the narrowness of the well per se. It's depth you\nneed; you get narrowness as a byproduct of optimizing for depth\n(and speed). But you almost always do get it. In practice the\nlink between depth and narrowness is so strong that it's a good\nsign when you know that an idea will appeal strongly to a specific\ngroup or type of user.But while demand shaped like a well is almost a necessary condition\nfor a good startup idea, it's not a sufficient one. If Mark\nZuckerberg had built something that could only ever have appealed\nto Harvard students, it would not have been a good startup idea.\nFacebook was a good idea because it started with a small market\nthere was a fast path out of. Colleges are similar enough that if\nyou build a facebook that works at Harvard, it will work at any\ncollege. So you spread rapidly through all the colleges. Once you\nhave all the college students, you get everyone else simply by\nletting them in.Similarly for Microsoft: Basic for the Altair; Basic for other\nmachines; other languages besides Basic; operating systems;\napplications; IPO.\nSelfHow do you tell whether there's a path out of an idea? How do you\ntell whether something is the germ of a giant company, or just a\nniche product? Often you can't. The founders of Airbnb didn't\nrealize at first how big a market they were tapping. Initially\nthey had a much narrower idea. They were going to let hosts rent\nout space on their floors during conventions. They didn't foresee\nthe expansion of this idea; it forced itself upon them gradually.\nAll they knew at first is that they were onto something. That's\nprobably as much as Bill Gates or Mark Zuckerberg knew at first.Occasionally it's obvious from the beginning when there's a path\nout of the initial niche. And sometimes I can see a path that's\nnot immediately obvious; that's one of our specialties at YC. But\nthere are limits to how well this can be done, no matter how much\nexperience you have. The most important thing to understand about\npaths out of the initial idea is the meta-fact that these are hard\nto see.So if you can't predict whether there's a path out of an idea, how\ndo you choose between ideas? The truth is disappointing but\ninteresting: if you're the right sort of person, you have the right\nsort of hunches. If you're at the leading edge of a field that's\nchanging fast, when you have a hunch that something is worth doing,\nyou're more likely to be right.In Zen and the Art of Motorcycle Maintenance, Robert Pirsig says:\n\n You want to know how to paint a perfect painting? It's easy. Make\n yourself perfect and then just paint naturally.\n\nI've wondered about that passage since I read it in high school.\nI'm not sure how useful his advice is for painting specifically,\nbut it fits this situation well. Empirically, the way to have good\nstartup ideas is to become the sort of person who has them.Being at the leading edge of a field doesn't mean you have to be\none of the people pushing it forward. You can also be at the leading\nedge as a user. It was not so much because he was a programmer\nthat Facebook seemed a good idea to Mark Zuckerberg as because he\nused computers so much. If you'd asked most 40 year olds in 2004\nwhether they'd like to publish their lives semi-publicly on the\nInternet, they'd have been horrified at the idea. But Mark already\nlived online; to him it seemed natural.Paul Buchheit says that people at the leading edge of a rapidly\nchanging field \"live in the future.\" Combine that with Pirsig and\nyou get:\n\n Live in the future, then build what's missing.\n\nThat describes the way many if not most of the biggest startups got\nstarted. Neither Apple nor Yahoo nor Google nor Facebook were even\nsupposed to be companies at first. They grew out of things their\nfounders built because there seemed a gap in the world.If you look at the way successful founders have had their ideas,\nit's generally the result of some external stimulus hitting a\nprepared mind. Bill Gates and Paul Allen hear about the Altair and\nthink \"I bet we could write a Basic interpreter for it.\" Drew Houston\nrealizes he's forgotten his USB stick and thinks \"I really need to\nmake my files live online.\" Lots of people heard about the Altair.\nLots forgot USB sticks. The reason those stimuli caused those\nfounders to start companies was that their experiences had prepared\nthem to notice the opportunities they represented.The verb you want to be using with respect to startup ideas is not\n\"think up\" but \"notice.\" At YC we call ideas that grow naturally\nout of the founders' own experiences \"organic\" startup ideas. The\nmost successful startups almost all begin this way.That may not have been what you wanted to hear. You may have\nexpected recipes for coming up with startup ideas, and instead I'm\ntelling you that the key is to have a mind that's prepared in the\nright way. But disappointing though it may be, this is the truth.\nAnd it is a recipe of a sort, just one that in the worst case takes\na year rather than a weekend.If you're not at the leading edge of some rapidly changing field,\nyou can get to one. For example, anyone reasonably smart can\nprobably get to an edge of programming (e.g. building mobile apps)\nin a year. Since a successful startup will consume at least 3-5\nyears of your life, a year's preparation would be a reasonable\ninvestment. Especially if you're also looking for a cofounder.\n[4]You don't have to learn programming to be at the leading edge of a\ndomain that's changing fast. Other domains change fast. But while\nlearning to hack is not necessary, it is for the forseeable future\nsufficient. As Marc Andreessen put it, software is eating the world,\nand this trend has decades left to run.Knowing how to hack also means that when you have ideas, you'll be\nable to implement them. That's not absolutely necessary (Jeff Bezos\ncouldn't) but it's an advantage. It's a big advantage, when you're\nconsidering an idea like putting a college facebook online, if\ninstead of merely thinking \"That's an interesting idea,\" you can\nthink instead \"That's an interesting idea. I'll try building an\ninitial version tonight.\" It's even better when you're both a\nprogrammer and the target user, because then the cycle of generating\nnew versions and testing them on users can happen inside one head.\nNoticingOnce you're living in the future in some respect, the way to notice\nstartup ideas is to look for things that seem to be missing. If\nyou're really at the leading edge of a rapidly changing field, there\nwill be things that are obviously missing. What won't be obvious\nis that they're startup ideas. So if you want to find startup\nideas, don't merely turn on the filter \"What's missing?\" Also turn\noff every other filter, particularly \"Could this be a big company?\"\nThere's plenty of time to apply that test later. But if you're\nthinking about that initially, it may not only filter out lots\nof good ideas, but also cause you to focus on bad ones.Most things that are missing will take some time to see. You almost\nhave to trick yourself into seeing the ideas around you.But you know the ideas are out there. This is not one of those\nproblems where there might not be an answer. It's impossibly\nunlikely that this is the exact moment when technological progress\nstops. You can be sure people are going to build things in the\nnext few years that will make you think \"What did I do before x?\"And when these problems get solved, they will probably seem flamingly\nobvious in retrospect. What you need to do is turn off the filters\nthat usually prevent you from seeing them. The most powerful is\nsimply taking the current state of the world for granted. Even the\nmost radically open-minded of us mostly do that. You couldn't get\nfrom your bed to the front door if you stopped to question everything.But if you're looking for startup ideas you can sacrifice some of\nthe efficiency of taking the status quo for granted and start to\nquestion things. Why is your inbox overflowing? Because you get\na lot of email, or because it's hard to get email out of your inbox?\nWhy do you get so much email? What problems are people trying to\nsolve by sending you email? Are there better ways to solve them?\nAnd why is it hard to get emails out of your inbox? Why do you\nkeep emails around after you've read them? Is an inbox the optimal\ntool for that?Pay particular attention to things that chafe you. The advantage\nof taking the status quo for granted is not just that it makes life\n(locally) more efficient, but also that it makes life more tolerable.\nIf you knew about all the things we'll get in the next 50 years but\ndon't have yet, you'd find present day life pretty constraining,\njust as someone from the present would if they were sent back 50\nyears in a time machine. When something annoys you, it could be\nbecause you're living in the future.When you find the right sort of problem, you should probably be\nable to describe it as obvious, at least to you. When we started\nViaweb, all the online stores were built by hand, by web designers\nmaking individual HTML pages. It was obvious to us as programmers\nthat these sites would have to be generated by software.\n[5]Which means, strangely enough, that coming up with startup ideas\nis a question of seeing the obvious. That suggests how weird this\nprocess is: you're trying to see things that are obvious, and yet\nthat you hadn't seen.Since what you need to do here is loosen up your own mind, it may\nbe best not to make too much of a direct frontal attack on the\nproblem — i.e. to sit down and try to think of ideas. The best\nplan may be just to keep a background process running, looking for\nthings that seem to be missing. Work on hard problems, driven\nmainly by curiosity, but have a second self watching over your\nshoulder, taking note of gaps and anomalies. \n[6]Give yourself some time. You have a lot of control over the rate\nat which you turn yours into a prepared mind, but you have less\ncontrol over the stimuli that spark ideas when they hit it. If\nBill Gates and Paul Allen had constrained themselves to come up\nwith a startup idea in one month, what if they'd chosen a month\nbefore the Altair appeared? They probably would have worked on a\nless promising idea. Drew Houston did work on a less promising\nidea before Dropbox: an SAT prep startup. But Dropbox was a much\nbetter idea, both in the absolute sense and also as a match for his\nskills.\n[7]A good way to trick yourself into noticing ideas is to work on\nprojects that seem like they'd be cool. If you do that, you'll\nnaturally tend to build things that are missing. It wouldn't seem\nas interesting to build something that already existed.Just as trying to think up startup ideas tends to produce bad ones,\nworking on things that could be dismissed as \"toys\" often produces\ngood ones. When something is described as a toy, that means it has\neverything an idea needs except being important. It's cool; users\nlove it; it just doesn't matter. But if you're living in the future\nand you build something cool that users love, it may matter more\nthan outsiders think. Microcomputers seemed like toys when Apple\nand Microsoft started working on them. I'm old enough to remember\nthat era; the usual term for people with their own microcomputers\nwas \"hobbyists.\" BackRub seemed like an inconsequential science\nproject. The Facebook was just a way for undergrads to stalk one\nanother.At YC we're excited when we meet startups working on things that\nwe could imagine know-it-alls on forums dismissing as toys. To us\nthat's positive evidence an idea is good.If you can afford to take a long view (and arguably you can't afford\nnot to), you can turn \"Live in the future and build what's missing\"\ninto something even better:\n\n Live in the future and build what seems interesting.\n\nSchoolThat's what I'd advise college students to do, rather than trying\nto learn about \"entrepreneurship.\" \"Entrepreneurship\" is something\nyou learn best by doing it. The examples of the most successful\nfounders make that clear. What you should be spending your time\non in college is ratcheting yourself into the future. College is\nan incomparable opportunity to do that. What a waste to sacrifice\nan opportunity to solve the hard part of starting a startup — becoming \nthe sort of person who can have organic startup ideas — by \nspending time learning about the easy part. Especially since\nyou won't even really learn about it, any more than you'd learn\nabout sex in a class. All you'll learn is the words for things.The clash of domains is a particularly fruitful source of ideas.\nIf you know a lot about programming and you start learning about\nsome other field, you'll probably see problems that software could\nsolve. In fact, you're doubly likely to find good problems in\nanother domain: (a) the inhabitants of that domain are not as likely\nas software people to have already solved their problems with\nsoftware, and (b) since you come into the new domain totally ignorant,\nyou don't even know what the status quo is to take it for granted.So if you're a CS major and you want to start a startup, instead\nof taking a class on entrepreneurship you're better off taking a\nclass on, say, genetics. Or better still, go work for a biotech\ncompany. CS majors normally get summer jobs at computer hardware\nor software companies. But if you want to find startup ideas, you\nmight do better to get a summer job in some unrelated field. \n[8]Or don't take any extra classes, and just build things. It's no\ncoincidence that Microsoft and Facebook both got started in January.\nAt Harvard that is (or was) Reading Period, when students have no\nclasses to attend because they're supposed to be studying for finals.\n[9]But don't feel like you have to build things that will become startups. That's\npremature optimization. Just build things. Preferably with other\nstudents. It's not just the classes that make a university such a\ngood place to crank oneself into the future. You're also surrounded\nby other people trying to do the same thing. If you work together\nwith them on projects, you'll end up producing not just organic\nideas, but organic ideas with organic founding teams — and that,\nempirically, is the best combination.Beware of research. If an undergrad writes something all his friends\nstart using, it's quite likely to represent a good startup idea.\nWhereas a PhD dissertation is extremely unlikely to. For some\nreason, the more a project has to count as research, the less likely\nit is to be something that could be turned into a startup.\n[10]\nI think the reason is that the subset of ideas that count as research\nis so narrow that it's unlikely that a project that satisfied that\nconstraint would also satisfy the orthogonal constraint of solving\nusers' problems. Whereas when students (or professors) build\nsomething as a side-project, they automatically gravitate toward\nsolving users' problems — perhaps even with an additional energy\nthat comes from being freed from the constraints of research.\nCompetitionBecause a good idea should seem obvious, when you have one you'll\ntend to feel that you're late. Don't let that deter you. Worrying\nthat you're late is one of the signs of a good idea. Ten minutes\nof searching the web will usually settle the question. Even if you\nfind someone else working on the same thing, you're probably not\ntoo late. It's exceptionally rare for startups to be killed by\ncompetitors — so rare that you can almost discount the possibility.\nSo unless you discover a competitor with the sort of lock-in that\nwould prevent users from choosing you, don't discard the idea.If you're uncertain, ask users. The question of whether you're too\nlate is subsumed by the question of whether anyone urgently needs\nwhat you plan to make. If you have something that no competitor\ndoes and that some subset of users urgently need, you have a\nbeachhead. \n[11]The question then is whether that beachhead is big enough. Or more\nimportantly, who's in it: if the beachhead consists of people doing\nsomething lots more people will be doing in the future, then it's\nprobably big enough no matter how small it is. For example, if\nyou're building something differentiated from competitors by the\nfact that it works on phones, but it only works on the newest phones,\nthat's probably a big enough beachhead.Err on the side of doing things where you'll face competitors.\nInexperienced founders usually give competitors more credit than\nthey deserve. Whether you succeed depends far more on you than on\nyour competitors. So better a good idea with competitors than a\nbad one without.You don't need to worry about entering a \"crowded market\" so long\nas you have a thesis about what everyone else in it is overlooking.\nIn fact that's a very promising starting point. Google was that\ntype of idea. Your thesis has to be more precise than \"we're going\nto make an x that doesn't suck\" though. You have to be able to\nphrase it in terms of something the incumbents are overlooking.\nBest of all is when you can say that they didn't have the courage\nof their convictions, and that your plan is what they'd have done\nif they'd followed through on their own insights. Google was that\ntype of idea too. The search engines that preceded them shied away\nfrom the most radical implications of what they were doing — particularly \nthat the better a job they did, the faster users would\nleave.A crowded market is actually a good sign, because it means both\nthat there's demand and that none of the existing solutions are\ngood enough. A startup can't hope to enter a market that's obviously\nbig and yet in which they have no competitors. So any startup that\nsucceeds is either going to be entering a market with existing\ncompetitors, but armed with some secret weapon that will get them\nall the users (like Google), or entering a market that looks small\nbut which will turn out to be big (like Microsoft). \n[12]\nFiltersThere are two more filters you'll need to turn off if you want to\nnotice startup ideas: the unsexy filter and the schlep filter.Most programmers wish they could start a startup by just writing\nsome brilliant code, pushing it to a server, and having users pay\nthem lots of money. They'd prefer not to deal with tedious problems\nor get involved in messy ways with the real world. Which is a\nreasonable preference, because such things slow you down. But this\npreference is so widespread that the space of convenient startup\nideas has been stripped pretty clean. If you let your mind wander\na few blocks down the street to the messy, tedious ideas, you'll\nfind valuable ones just sitting there waiting to be implemented.The schlep filter is so dangerous that I wrote a separate essay\nabout the condition it induces, which I called \nschlep blindness.\nI gave Stripe as an example of a startup that benefited from turning\noff this filter, and a pretty striking example it is. Thousands\nof programmers were in a position to see this idea; thousands of\nprogrammers knew how painful it was to process payments before\nStripe. But when they looked for startup ideas they didn't see\nthis one, because unconsciously they shrank from having to deal\nwith payments. And dealing with payments is a schlep for Stripe,\nbut not an intolerable one. In fact they might have had net less\npain; because the fear of dealing with payments kept most people\naway from this idea, Stripe has had comparatively smooth sailing\nin other areas that are sometimes painful, like user acquisition.\nThey didn't have to try very hard to make themselves heard by users,\nbecause users were desperately waiting for what they were building.The unsexy filter is similar to the schlep filter, except it keeps\nyou from working on problems you despise rather than ones you fear.\nWe overcame this one to work on Viaweb. There were interesting\nthings about the architecture of our software, but we weren't\ninterested in ecommerce per se. We could see the problem was one\nthat needed to be solved though.Turning off the schlep filter is more important than turning off\nthe unsexy filter, because the schlep filter is more likely to be\nan illusion. And even to the degree it isn't, it's a worse form\nof self-indulgence. Starting a successful startup is going to be\nfairly laborious no matter what. Even if the product doesn't entail\na lot of schleps, you'll still have plenty dealing with investors,\nhiring and firing people, and so on. So if there's some idea you\nthink would be cool but you're kept away from by fear of the schleps\ninvolved, don't worry: any sufficiently good idea will have as many.The unsexy filter, while still a source of error, is not as entirely\nuseless as the schlep filter. If you're at the leading edge of a\nfield that's changing rapidly, your ideas about what's sexy will\nbe somewhat correlated with what's valuable in practice. Particularly\nas you get older and more experienced. Plus if you find an idea\nsexy, you'll work on it more enthusiastically. \n[13]\nRecipesWhile the best way to discover startup ideas is to become the sort\nof person who has them and then build whatever interests you,\nsometimes you don't have that luxury. Sometimes you need an idea\nnow. For example, if you're working on a startup and your initial\nidea turns out to be bad.For the rest of this essay I'll talk about tricks for coming up\nwith startup ideas on demand. Although empirically you're better\noff using the organic strategy, you could succeed this way. You\njust have to be more disciplined. When you use the organic method,\nyou don't even notice an idea unless it's evidence that something\nis truly missing. But when you make a conscious effort to think\nof startup ideas, you have to replace this natural constraint with\nself-discipline. You'll see a lot more ideas, most of them bad,\nso you need to be able to filter them.One of the biggest dangers of not using the organic method is the\nexample of the organic method. Organic ideas feel like inspirations.\nThere are a lot of stories about successful startups that began\nwhen the founders had what seemed a crazy idea but \"just knew\" it\nwas promising. When you feel that about an idea you've had while\ntrying to come up with startup ideas, you're probably mistaken.When searching for ideas, look in areas where you have some expertise.\nIf you're a database expert, don't build a chat app for teenagers\n(unless you're also a teenager). Maybe it's a good idea, but you\ncan't trust your judgment about that, so ignore it. There have to\nbe other ideas that involve databases, and whose quality you can\njudge. Do you find it hard to come up with good ideas involving\ndatabases? That's because your expertise raises your standards.\nYour ideas about chat apps are just as bad, but you're giving\nyourself a Dunning-Kruger pass in that domain.The place to start looking for ideas is things you need. There\nmust be things you need.\n[14]One good trick is to ask yourself whether in your previous job you\never found yourself saying \"Why doesn't someone make x? If someone\nmade x we'd buy it in a second.\" If you can think of any x people\nsaid that about, you probably have an idea. You know there's demand,\nand people don't say that about things that are impossible to build.More generally, try asking yourself whether there's something unusual\nabout you that makes your needs different from most other people's.\nYou're probably not the only one. It's especially good if you're\ndifferent in a way people will increasingly be.If you're changing ideas, one unusual thing about you is the idea\nyou'd previously been working on. Did you discover any needs while\nworking on it? Several well-known startups began this way. Hotmail\nbegan as something its founders wrote to talk about their previous\nstartup idea while they were working at their day jobs. \n[15]A particularly promising way to be unusual is to be young. Some\nof the most valuable new ideas take root first among people in their\nteens and early twenties. And while young founders are at a\ndisadvantage in some respects, they're the only ones who really\nunderstand their peers. It would have been very hard for someone\nwho wasn't a college student to start Facebook. So if you're a\nyoung founder (under 23 say), are there things you and your friends\nwould like to do that current technology won't let you?The next best thing to an unmet need of your own is an unmet need\nof someone else. Try talking to everyone you can about the gaps\nthey find in the world. What's missing? What would they like to\ndo that they can't? What's tedious or annoying, particularly in\ntheir work? Let the conversation get general; don't be trying too\nhard to find startup ideas. You're just looking for something to\nspark a thought. Maybe you'll notice a problem they didn't consciously\nrealize they had, because you know how to solve it.When you find an unmet need that isn't your own, it may be somewhat\nblurry at first. The person who needs something may not know exactly\nwhat they need. In that case I often recommend that founders act\nlike consultants — that they do what they'd do if they'd been\nretained to solve the problems of this one user. People's problems\nare similar enough that nearly all the code you write this way will\nbe reusable, and whatever isn't will be a small price to start out\ncertain that you've reached the bottom of the well.\n[16]One way to ensure you do a good job solving other people's problems\nis to make them your own. When Rajat Suri of E la Carte decided\nto write software for restaurants, he got a job as a waiter to learn\nhow restaurants worked. That may seem like taking things to extremes,\nbut startups are extreme. We love it when founders do such things.In fact, one strategy I recommend to people who need a new idea is\nnot merely to turn off their schlep and unsexy filters, but to seek\nout ideas that are unsexy or involve schleps. Don't try to start\nTwitter. Those ideas are so rare that you can't find them by looking\nfor them. Make something unsexy that people will pay you for.A good trick for bypassing the schlep and to some extent the unsexy\nfilter is to ask what you wish someone else would build, so that\nyou could use it. What would you pay for right now?Since startups often garbage-collect broken companies and industries,\nit can be a good trick to look for those that are dying, or deserve\nto, and try to imagine what kind of company would profit from their\ndemise. For example, journalism is in free fall at the moment.\nBut there may still be money to be made from something like journalism.\nWhat sort of company might cause people in the future to say \"this\nreplaced journalism\" on some axis?But imagine asking that in the future, not now. When one company\nor industry replaces another, it usually comes in from the side.\nSo don't look for a replacement for x; look for something that\npeople will later say turned out to be a replacement for x. And\nbe imaginative about the axis along which the replacement occurs.\nTraditional journalism, for example, is a way for readers to get\ninformation and to kill time, a way for writers to make money and\nto get attention, and a vehicle for several different types of\nadvertising. It could be replaced on any of these axes (it has\nalready started to be on most).When startups consume incumbents, they usually start by serving\nsome small but important market that the big players ignore. It's\nparticularly good if there's an admixture of disdain in the big\nplayers' attitude, because that often misleads them. For example,\nafter Steve Wozniak built the computer that became the Apple I, he\nfelt obliged to give his then-employer Hewlett-Packard the option\nto produce it. Fortunately for him, they turned it down, and one\nof the reasons they did was that it used a TV for a monitor, which\nseemed intolerably déclassé to a high-end hardware company like HP\nwas at the time. \n[17]Are there groups of \nscruffy \nbut sophisticated users like the early\nmicrocomputer \"hobbyists\" that are currently being ignored by the\nbig players? A startup with its sights set on bigger things can\noften capture a small market easily by expending an effort that\nwouldn't be justified by that market alone.Similarly, since the most successful startups generally ride some\nwave bigger than themselves, it could be a good trick to look for\nwaves and ask how one could benefit from them. The prices of gene\nsequencing and 3D printing are both experiencing Moore's Law-like\ndeclines. What new things will we be able to do in the new world\nwe'll have in a few years? What are we unconsciously ruling out\nas impossible that will soon be possible?\nOrganicBut talking about looking explicitly for waves makes it clear that\nsuch recipes are plan B for getting startup ideas. Looking for\nwaves is essentially a way to simulate the organic method. If\nyou're at the leading edge of some rapidly changing field, you don't\nhave to look for waves; you are the wave.Finding startup ideas is a subtle business, and that's why most\npeople who try fail so miserably. It doesn't work well simply to\ntry to think of startup ideas. If you do that, you get bad ones\nthat sound dangerously plausible. The best approach is more indirect:\nif you have the right sort of background, good startup ideas will\nseem obvious to you. But even then, not immediately. It takes\ntime to come across situations where you notice something missing.\nAnd often these gaps won't seem to be ideas for companies, just\nthings that would be interesting to build. Which is why it's good\nto have the time and the inclination to build things just because\nthey're interesting.Live in the future and build what seems interesting. Strange as\nit sounds, that's the real recipe.\nNotes[1]\nThis form of bad idea has been around as long as the web. It\nwas common in the 1990s, except then people who had it used to say\nthey were going to create a portal for x instead of a social network\nfor x. Structurally the idea is stone soup: you post a sign saying\n\"this is the place for people interested in x,\" and all those people\nshow up and you make money from them. What lures founders into\nthis sort of idea are statistics about the millions of people who\nmight be interested in each type of x. What they forget is that\nany given person might have 20 affinities by this standard, and no\none is going to visit 20 different communities regularly.[2]\nI'm not saying, incidentally, that I know for sure a social\nnetwork for pet owners is a bad idea. I know it's a bad idea the\nway I know randomly generated DNA would not produce a viable organism.\nThe set of plausible sounding startup ideas is many times larger\nthan the set of good ones, and many of the good ones don't even\nsound that plausible. So if all you know about a startup idea is\nthat it sounds plausible, you have to assume it's bad.[3]\nMore precisely, the users' need has to give them sufficient\nactivation energy to start using whatever you make, which can vary\na lot. For example, the activation energy for enterprise software\nsold through traditional channels is very high, so you'd have to\nbe a lot better to get users to switch. Whereas the activation\nenergy required to switch to a new search engine is low. Which in\nturn is why search engines are so much better than enterprise\nsoftware.[4]\nThis gets harder as you get older. While the space of ideas\ndoesn't have dangerous local maxima, the space of careers does.\nThere are fairly high walls between most of the paths people take\nthrough life, and the older you get, the higher the walls become.[5]\nIt was also obvious to us that the web was going to be a big\ndeal. Few non-programmers grasped that in 1995, but the programmers\nhad seen what GUIs had done for desktop computers.[6]\nMaybe it would work to have this second self keep a journal,\nand each night to make a brief entry listing the gaps and anomalies\nyou'd noticed that day. Not startup ideas, just the raw gaps and\nanomalies.[7]\nSam Altman points out that taking time to come up with an\nidea is not merely a better strategy in an absolute sense, but also\nlike an undervalued stock in that so few founders do it.There's comparatively little competition for the best ideas, because\nfew founders are willing to put in the time required to notice them.\nWhereas there is a great deal of competition for mediocre ideas,\nbecause when people make up startup ideas, they tend to make up the\nsame ones.[8]\nFor the computer hardware and software companies, summer jobs\nare the first phase of the recruiting funnel. But if you're good\nyou can skip the first phase. If you're good you'll have no trouble\ngetting hired by these companies when you graduate, regardless of\nhow you spent your summers.[9]\nThe empirical evidence suggests that if colleges want to help\ntheir students start startups, the best thing they can do is leave\nthem alone in the right way.[10]\nI'm speaking here of IT startups; in biotech things are different.[11]\nThis is an instance of a more general rule: focus on users,\nnot competitors. The most important information about competitors\nis what you learn via users anyway.[12]\nIn practice most successful startups have elements of both.\nAnd you can describe each strategy in terms of the other by adjusting\nthe boundaries of what you call the market. But it's useful to\nconsider these two ideas separately.[13]\nI almost hesitate to raise that point though. Startups are\nbusinesses; the point of a business is to make money; and with that\nadditional constraint, you can't expect you'll be able to spend all\nyour time working on what interests you most.[14]\nThe need has to be a strong one. You can retroactively\ndescribe any made-up idea as something you need. But do you really\nneed that recipe site or local event aggregator as much as Drew\nHouston needed Dropbox, or Brian Chesky and Joe Gebbia needed Airbnb?Quite often at YC I find myself asking founders \"Would you use this\nthing yourself, if you hadn't written it?\" and you'd be surprised\nhow often the answer is no.[15]\nPaul Buchheit points out that trying to sell something bad\ncan be a source of better ideas:\"The best technique I've found for dealing with YC companies that\nhave bad ideas is to tell them to go sell the product ASAP (before\nwasting time building it). Not only do they learn that nobody\nwants what they are building, they very often come back with a\nreal idea that they discovered in the process of trying to sell\nthe bad idea.\"[16]\nHere's a recipe that might produce the next Facebook, if\nyou're college students. If you have a connection to one of the\nmore powerful sororities at your school, approach the queen bees\nthereof and offer to be their personal IT consultants, building\nanything they could imagine needing in their social lives that\ndidn't already exist. Anything that got built this way would be\nvery promising, because such users are not just the most demanding\nbut also the perfect point to spread from.I have no idea whether this would work.[17]\nAnd the reason it used a TV for a monitor is that Steve Wozniak\nstarted out by solving his own problems. He, like most of his\npeers, couldn't afford a monitor.Thanks to Sam Altman, Mike Arrington, Paul Buchheit, John Collison,\nPatrick Collison, Garry Tan, and Harj Taggar for reading drafts of\nthis, and Marc Andreessen, Joe Gebbia, Reid Hoffman, Shel Kaphan,\nMike Moritz and Kevin Systrom for answering my questions about\nstartup history." }, { "path": "data/PaulGrahamEssays/startuplessons.txt", "content": "April 2006(This essay is derived from a talk at the 2006 \nStartup School.)The startups we've funded so far are pretty quick, but they seem\nquicker to learn some lessons than others. I think it's because\nsome things about startups are kind of counterintuitive.We've now \ninvested \nin enough companies that I've learned a trick\nfor determining which points are the counterintuitive ones:\nthey're the ones I have to keep repeating.So I'm going to number these points, and maybe with future startups\nI'll be able to pull off a form of Huffman coding. I'll make them\nall read this, and then instead of nagging them in detail, I'll\njust be able to say: number four!\n1. Release Early.The thing I probably repeat most is this recipe for a startup: get\na version 1 out fast, then improve it based on users' reactions.By \"release early\" I don't mean you should release something full\nof bugs, but that you should release something minimal. Users hate\nbugs, but they don't seem to mind a minimal version 1, if there's\nmore coming soon.There are several reasons it pays to get version 1 done fast. One\nis that this is simply the right way to write software, whether for\na startup or not. I've been repeating that since 1993, and I haven't seen much since to\ncontradict it. I've seen a lot of startups die because they were\ntoo slow to release stuff, and none because they were too quick.\n[1]One of the things that will surprise you if you build something\npopular is that you won't know your users. Reddit now has almost half a million\nunique visitors a month. Who are all those people? They have no\nidea. No web startup does. And since you don't know your users,\nit's dangerous to guess what they'll like. Better to release\nsomething and let them tell you.Wufoo took this to heart and released\ntheir form-builder before the underlying database. You can't even\ndrive the thing yet, but 83,000 people came to sit in the driver's\nseat and hold the steering wheel. And Wufoo got valuable feedback\nfrom it: Linux users complained they used too much Flash, so they\nrewrote their software not to. If they'd waited to release everything\nat once, they wouldn't have discovered this problem till it was\nmore deeply wired in.Even if you had no users, it would still be important to release\nquickly, because for a startup the initial release acts as a shakedown\ncruise. If anything major is broken-- if the idea's no good,\nfor example, or the founders hate one another-- the stress of getting\nthat first version out will expose it. And if you have such problems\nyou want to find them early.Perhaps the most important reason to release early, though, is that\nit makes you work harder. When you're working on something that\nisn't released, problems are intriguing. In something that's out\nthere, problems are alarming. There is a lot more urgency once you\nrelease. And I think that's precisely why people put it off. They\nknow they'll have to work a lot harder once they do. \n[2]\n2. Keep Pumping Out Features.Of course, \"release early\" has a second component, without which\nit would be bad advice. If you're going to start with something\nthat doesn't do much, you better improve it fast.What I find myself repeating is \"pump out features.\" And this rule\nisn't just for the initial stages. This is something all startups\nshould do for as long as they want to be considered startups.I don't mean, of course, that you should make your application ever\nmore complex. By \"feature\" I mean one unit of hacking-- one quantum\nof making users' lives better.As with exercise, improvements beget improvements. If you run every\nday, you'll probably feel like running tomorrow. But if you skip\nrunning for a couple weeks, it will be an effort to drag yourself\nout. So it is with hacking: the more ideas you implement, the more\nideas you'll have. You should make your system better at least in\nsome small way every day or two.This is not just a good way to get development done; it is also a\nform of marketing. Users love a site that's constantly improving.\nIn fact, users expect a site to improve. Imagine if you visited a\nsite that seemed very good, and then returned two months later and\nnot one thing had changed. Wouldn't it start to seem lame? \n[3]They'll like you even better when you improve in response to their\ncomments, because customers are used to companies ignoring them.\nIf you're the rare exception-- a company that actually listens--\nyou'll generate fanatical loyalty. You won't need to advertise,\nbecause your users will do it for you.This seems obvious too, so why do I have to keep repeating it? I\nthink the problem here is that people get used to how things are.\nOnce a product gets past the stage where it has glaring flaws, you\nstart to get used to it, and gradually whatever features it happens\nto have become its identity. For example, I doubt many people at\nYahoo (or Google for that matter) realized how much better web mail\ncould be till Paul Buchheit showed them.I think the solution is to assume that anything you've made is far\nshort of what it could be. Force yourself, as a sort of intellectual\nexercise, to keep thinking of improvements. Ok, sure, what you\nhave is perfect. But if you had to change something, what would\nit be?If your product seems finished, there are two possible explanations:\n(a) it is finished, or (b) you lack imagination. Experience suggests\n(b) is a thousand times more likely.\n3. Make Users Happy.Improving constantly is an instance of a more general rule: make\nusers happy. One thing all startups have in common is that they\ncan't force anyone to do anything. They can't force anyone to use\ntheir software, and they can't force anyone to do deals with them.\nA startup has to sing for its supper. That's why the successful\nones make great things. They have to, or die.When you're running a startup you feel like a little bit of debris\nblown about by powerful winds. The most powerful wind is users.\nThey can either catch you and loft you up into the sky, as they did\nwith Google, or leave you flat on the pavement, as they do with\nmost startups. Users are a fickle wind, but more powerful than any\nother. If they take you up, no competitor can keep you down.As a little piece of debris, the rational thing for you to do is\nnot to lie flat, but to curl yourself into a shape the wind will\ncatch.I like the wind metaphor because it reminds you how impersonal the\nstream of traffic is. The vast majority of people who visit your\nsite will be casual visitors. It's them you have to design your\nsite for. The people who really care will find what they want by\nthemselves.The median visitor will arrive with their finger poised on the Back\nbutton. Think about your own experience: most links you\nfollow lead to something lame. Anyone who has used the web for\nmore than a couple weeks has been trained to click on Back after\nfollowing a link. So your site has to say \"Wait! Don't click on\nBack. This site isn't lame. Look at this, for example.\"There are two things you have to do to make people pause. The most\nimportant is to explain, as concisely as possible, what the hell\nyour site is about. How often have you visited a site that seemed\nto assume you already knew what they did? For example, the corporate\nsite that says the\ncompany makes\n\n enterprise content management solutions for business that enable\n organizations to unify people, content and processes to minimize\n business risk, accelerate time-to-value and sustain lower total\n cost of ownership.\n\nAn established company may get away with such an opaque description,\nbut no startup can. A startup\nshould be able to explain in one or two sentences exactly what it\ndoes. \n[4]\nAnd not just to users. You need this for everyone:\ninvestors, acquirers, partners, reporters, potential employees, and\neven current employees. You probably shouldn't even start a company\nto do something that can't be described compellingly in one or two\nsentences.The other thing I repeat is to give people everything you've got,\nright away. If you have something impressive, try to put it on the\nfront page, because that's the only one most visitors will see.\nThough indeed there's a paradox here: the more you push the good\nstuff toward the front, the more likely visitors are to explore\nfurther. \n[5]In the best case these two suggestions get combined: you tell\nvisitors what your site is about by showing them. One of the\nstandard pieces of advice in fiction writing is \"show, don't tell.\"\nDon't say that a character's angry; have him grind his teeth, or\nbreak his pencil in half. Nothing will explain what your site does\nso well as using it.The industry term here is \"conversion.\" The job of your site is\nto convert casual visitors into users-- whatever your definition\nof a user is. You can measure this in your growth rate. Either\nyour site is catching on, or it isn't, and you must know which. If\nyou have decent growth, you'll win in the end, no matter how obscure\nyou are now. And if you don't, you need to fix something.\n4. Fear the Right Things.Another thing I find myself saying a lot is \"don't worry.\" Actually,\nit's more often \"don't worry about this; worry about that instead.\"\nStartups are right to be paranoid, but they sometimes fear the wrong\nthings.Most visible disasters are not so alarming as they seem. Disasters\nare normal in a startup: a founder quits, you discover a patent\nthat covers what you're doing, your servers keep crashing, you run\ninto an insoluble technical problem, you have to change your name,\na deal falls through-- these are all par for the course. They won't\nkill you unless you let them.Nor will most competitors. A lot of startups worry \"what if Google\nbuilds something like us?\" Actually big companies are not the ones\nyou have to worry about-- not even Google. The people at Google\nare smart, but no smarter than you; they're not as motivated, because\nGoogle is not going to go out of business if this one product fails;\nand even at Google they have a lot of bureaucracy to slow them down.What you should fear, as a startup, is not the established players,\nbut other startups you don't know exist yet. They're way more\ndangerous than Google because, like you, they're cornered animals.Looking just at existing competitors can give you a false sense of\nsecurity. You should compete against what someone else could be\ndoing, not just what you can see people doing. A corollary is that\nyou shouldn't relax just because you have no visible competitors\nyet. No matter what your idea, there's someone else out there\nworking on the same thing.That's the downside of it being easier to start a startup: more people\nare doing it. But I disagree with Caterina Fake when she says that\nmakes this a bad time to start a startup. More people are starting\nstartups, but not as many more as could. Most college graduates\nstill think they have to get a job. The average person can't ignore\nsomething that's been beaten into their head since they were three\njust because serving web pages recently got a lot cheaper.And in any case, competitors are not the biggest threat. Way more\nstartups hose themselves than get crushed by competitors. There\nare a lot of ways to do it, but the three main ones are internal\ndisputes, inertia, and ignoring users. Each is, by itself, enough\nto kill you. But if I had to pick the worst, it would be ignoring\nusers. If you want a recipe for a startup that's going to die,\nhere it is: a couple of founders who have some great idea they know\neveryone is going to love, and that's what they're going to build,\nno matter what.Almost everyone's initial plan is broken. If companies stuck to\ntheir initial plans, Microsoft would be selling programming languages,\nand Apple would be selling printed circuit boards. In both cases\ntheir customers told them what their business should be-- and they\nwere smart enough to listen.As Richard Feynman said, the imagination of nature is greater than\nthe imagination of man. You'll find more interesting things by\nlooking at the world than you could ever produce just by thinking.\nThis principle is very powerful. It's why the best abstract painting\nstill falls short of Leonardo, for example. And it applies to\nstartups too. No idea for a product could ever be so clever as the\nones you can discover by smashing a beam of prototypes into a beam\nof users.\n5. Commitment Is a Self-Fulfilling Prophecy.I now have enough experience with startups to be able to say what\nthe most important quality is in a startup founder, and it's not\nwhat you might think. The most important quality in a startup\nfounder is determination. Not intelligence-- determination.This is a little depressing. I'd like to believe Viaweb succeeded\nbecause we were smart, not merely determined. A lot of people in\nthe startup world want to believe that. Not just founders, but\ninvestors too. They like the idea of inhabiting a world ruled by\nintelligence. And you can tell they really believe this, because\nit affects their investment decisions.Time after time VCs invest in startups founded by eminent professors.\nThis may work in biotech, where a lot of startups simply commercialize\nexisting research, but in software you want to invest in students,\nnot professors. Microsoft, Yahoo, and Google were all founded by\npeople who dropped out of school to do it. What students lack in\nexperience they more than make up in dedication.Of course, if you want to get rich, it's not enough merely to be\ndetermined. You have to be smart too, right? I'd like to think\nso, but I've had an experience that convinced me otherwise: I spent\nseveral years living in New York.You can lose quite a lot in the brains department and it won't kill\nyou. But lose even a little bit in the commitment department, and\nthat will kill you very rapidly.Running a startup is like walking on your hands: it's possible, but\nit requires extraordinary effort. If an ordinary employee were\nasked to do the things a startup founder has to, he'd be very\nindignant. Imagine if you were hired at some big company, and in\naddition to writing software ten times faster than you'd ever had\nto before, they expected you to answer support calls, administer\nthe servers, design the web site, cold-call customers, find the\ncompany office space, and go out and get everyone lunch.And to do all this not in the calm, womb-like atmosphere of a big\ncompany, but against a backdrop of constant disasters. That's the\npart that really demands determination. In a startup, there's\nalways some disaster happening. So if you're the least bit inclined\nto find an excuse to quit, there's always one right there.But if you lack commitment, chances are it will have been hurting\nyou long before you actually quit. Everyone who deals with startups\nknows how important commitment is, so if they sense you're ambivalent,\nthey won't give you much attention. If you lack commitment, you'll\njust find that for some mysterious reason good things happen to\nyour competitors but not to you. If you lack commitment, it will\nseem to you that you're unlucky.Whereas if you're determined to stick around, people will pay\nattention to you, because odds are they'll have to deal with you\nlater. You're a local, not just a tourist, so everyone has to come\nto terms with you.At Y Combinator we sometimes mistakenly fund teams who have the\nattitude that they're going to give this startup thing a shot for\nthree months, and if something great happens, they'll stick with\nit-- \"something great\" meaning either that someone wants to buy\nthem or invest millions of dollars in them. But if this is your\nattitude, \"something great\" is very unlikely to happen to you,\nbecause both acquirers and investors judge you by your level of\ncommitment.If an acquirer thinks you're going to stick around no matter what,\nthey'll be more likely to buy you, because if they don't and you\nstick around, you'll probably grow, your price will go up, and\nthey'll be left wishing they'd bought you earlier. Ditto for\ninvestors. What really motivates investors, even big VCs, is not\nthe hope of good returns, but the fear of missing out. \n[6]\nSo if\nyou make it clear you're going to succeed no matter what, and the only\nreason you need them is to make it happen a little faster, you're\nmuch more likely to get money.You can't fake this. The only way to convince everyone that you're\nready to fight to the death is actually to be ready to.You have to be the right kind of determined, though. I carefully\nchose the word determined rather than stubborn, because stubbornness\nis a disastrous quality in a startup. You have to be determined,\nbut flexible, like a running back. A successful running back doesn't\njust put his head down and try to run through people. He improvises:\nif someone appears in front of him, he runs around them; if someone\ntries to grab him, he spins out of their grip; he'll even run in\nthe wrong direction briefly if that will help. The one thing he'll\nnever do is stand still. \n[7]\n6. There Is Always Room.I was talking recently to a startup founder about whether it might\nbe good to add a social component to their software. He said he\ndidn't think so, because the whole social thing was tapped out.\nReally? So in a hundred years the only social networking sites\nwill be the Facebook, MySpace, Flickr, and Del.icio.us? Not likely.There is always room for new stuff. At every point in history,\neven the darkest bits of the dark ages, people were discovering\nthings that made everyone say \"why didn't anyone think of that\nbefore?\" We know this continued to be true up till 2004, when the\nFacebook was founded-- though strictly speaking someone else did\nthink of that.The reason we don't see the opportunities all around us is that we\nadjust to however things are, and assume that's how things have to\nbe. For example, it would seem crazy to most people to try to make\na better search engine than Google. Surely that field, at least,\nis tapped out. Really? In a hundred years-- or even twenty-- are\npeople still going to search for information using something like\nthe current Google? Even Google probably doesn't think that.In particular, I don't think there's any limit to the number of\nstartups. Sometimes you hear people saying \"All these guys starting\nstartups now are going to be disappointed. How many little startups\nare Google and Yahoo going to buy, after all?\" That sounds cleverly\nskeptical, but I can prove it's mistaken. No one proposes that\nthere's some limit to the number of people who can be employed in\nan economy consisting of big, slow-moving companies with a couple\nthousand people each. Why should there be any limit to the number\nwho could be employed by small, fast-moving companies with ten each?\nIt seems to me the only limit would be the number of people who\nwant to work that hard.The limit on the number of startups is not the number that can get\nacquired by Google and Yahoo-- though it seems even that should\nbe unlimited, if the startups were actually worth buying-- but the\namount of wealth that can be created. And I don't think there's\nany limit on that, except cosmological ones.So for all practical purposes, there is no limit to the number of\nstartups. Startups make wealth, which means they make things people\nwant, and if there's a limit on the number of things people want,\nwe are nowhere near it. I still don't even have a flying car.\n7. Don't Get Your Hopes Up.This is another one I've been repeating since long before Y Combinator.\nIt was practically the corporate motto at Viaweb.Startup founders are naturally optimistic. They wouldn't do it\notherwise. But you should treat your optimism the way you'd treat\nthe core of a nuclear reactor: as a source of power that's also\nvery dangerous. You have to build a shield around it, or it will\nfry you.The shielding of a reactor is not uniform; the reactor would be\nuseless if it were. It's pierced in a few places to let pipes in.\nAn optimism shield has to be pierced too. I think the place to\ndraw the line is between what you expect of yourself, and what you\nexpect of other people. It's ok to be optimistic about what you\ncan do, but assume the worst about machines and other people.This is particularly necessary in a startup, because you tend to\nbe pushing the limits of whatever you're doing. So things don't\nhappen in the smooth, predictable way they do in the rest of the\nworld. Things change suddenly, and usually for the worse.Shielding your optimism is nowhere more important than with deals.\nIf your startup is doing a deal, just assume it's not going to\nhappen. The VCs who say they're going to invest in you aren't.\nThe company that says they're going to buy you isn't. The big\ncustomer who wants to use your system in their whole company won't.\nThen if things work out you can be pleasantly surprised.The reason I warn startups not to get their hopes up is not to save\nthem from being disappointed when things fall through. It's\nfor a more practical reason: to prevent them from leaning their\ncompany against something that's going to fall over, taking them\nwith it.For example, if someone says they want to invest in you, there's a\nnatural tendency to stop looking for other investors. That's why\npeople proposing deals seem so positive: they want you to\nstop looking. And you want to stop too, because doing deals is a\npain. Raising money, in particular, is a huge time sink. So you\nhave to consciously force yourself to keep looking.Even if you ultimately do the first deal, it will be to your advantage\nto have kept looking, because you'll get better terms. Deals are\ndynamic; unless you're negotiating with someone unusually honest,\nthere's not a single point where you shake hands and the deal's\ndone. There are usually a lot of subsidiary questions to be cleared\nup after the handshake, and if the other side senses weakness-- if\nthey sense you need this deal-- they will be very tempted to screw\nyou in the details.VCs and corp dev guys are professional negotiators. They're trained\nto take advantage of weakness. \n[8]\nSo while they're often nice\nguys, they just can't help it. And as pros they do this more than\nyou. So don't even try to bluff them. The only way a startup can\nhave any leverage in a deal is genuinely not to need it. And if\nyou don't believe in a deal, you'll be less likely to depend on it.So I want to plant a hypnotic suggestion in your heads: when you\nhear someone say the words \"we want to invest in you\" or \"we want\nto acquire you,\" I want the following phrase to appear automatically\nin your head: don't get your hopes up. Just continue running\nyour company as if this deal didn't exist. Nothing is more likely\nto make it close.The way to succeed in a startup is to focus on the goal of getting\nlots of users, and keep walking swiftly toward it while investors\nand acquirers scurry alongside trying to wave money in your face.\nSpeed, not MoneyThe way I've described it, starting a startup sounds pretty stressful.\nIt is. When I talk to the founders of the companies we've funded,\nthey all say the same thing: I knew it would be hard, but I didn't\nrealize it would be this hard.So why do it? It would be worth enduring a lot of pain and stress\nto do something grand or heroic, but just to make money? Is making\nmoney really that important?No, not really. It seems ridiculous to me when people take business\ntoo seriously. I regard making money as a boring errand to be got\nout of the way as soon as possible. There is nothing grand or\nheroic about starting a startup per se.So why do I spend so much time thinking about startups? I'll tell\nyou why. Economically, a startup is best seen not as a way to get\nrich, but as a way to work faster. You have to make a living, and\na startup is a way to get that done quickly, instead of letting it\ndrag on through your whole life.\n[9]We take it for granted most of the time, but human life is fairly\nmiraculous. It is also palpably short. You're given this marvellous\nthing, and then poof, it's taken away. You can see why people\ninvent gods to explain it. But even to people who don't believe\nin gods, life commands respect. There are times in most of our\nlives when the days go by in a blur, and almost everyone has a\nsense, when this happens, of wasting something precious. As Ben\nFranklin said, if you love life, don't waste time, because time is\nwhat life is made of.So no, there's nothing particularly grand about making money. That's\nnot what makes startups worth the trouble. What's important about\nstartups is the speed. By compressing the dull but necessary task\nof making a living into the smallest possible time, you show respect\nfor life, and there is something grand about that.Notes[1]\nStartups can die from releasing something full of bugs, and not\nfixing them fast enough, but I don't know of any that died from\nreleasing something stable but minimal very early, then promptly\nimproving it.[2]\nI know this is why I haven't released Arc. The moment I do,\nI'll have people nagging me for features.[3]\nA web site is different from a book or movie or desktop application\nin this respect. Users judge a site not as a single snapshot, but\nas an animation with multiple frames. Of the two, I'd say the rate of\nimprovement is more important to users than where you currently\nare.[4]\nIt should not always tell this to users, however. For example,\nMySpace is basically a replacement mall for mallrats. But it was\nwiser for them, initially, to pretend that the site was about bands.[5]\nSimilarly, don't make users register to try your site. Maybe\nwhat you have is so valuable that visitors should gladly register\nto get at it. But they've been trained to expect the opposite.\nMost of the things they've tried on the web have sucked-- and\nprobably especially those that made them register.[6]\nVCs have rational reasons for behaving this way. They don't\nmake their money (if they make money) off their median investments.\nIn a typical fund, half the companies fail, most of the rest generate\nmediocre returns, and one or two \"make the fund\" by succeeding\nspectacularly. So if they miss just a few of the most promising\nopportunities, it could hose the whole fund.[7]\nThe attitude of a running back doesn't translate to soccer.\nThough it looks great when a forward dribbles past multiple defenders,\na player who persists in trying such things will do worse in the\nlong term than one who passes.[8]\nThe reason Y Combinator never negotiates valuations\nis that we're not professional negotiators, and don't want to turn\ninto them.[9]\nThere are two ways to do \nwork you love: (a) to make money, then work\non what you love, or (b) to get a job where you get paid to work on\nstuff you love. In practice the first phases of both\nconsist mostly of unedifying schleps, and in (b) the second phase is less\nsecure.Thanks to Sam Altman, Trevor Blackwell, Beau Hartshorne, Jessica \nLivingston, and Robert Morris for reading drafts of this." }, { "path": "data/PaulGrahamEssays/startupmistakes.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nOctober 2006In the Q & A period after a recent talk, someone asked what made\nstartups fail. After standing there gaping for a few seconds I\nrealized this was kind of a trick question. It's equivalent to\nasking how to make a startup succeed — if you avoid every cause of\nfailure, you succeed — and that's too big a question to answer on\nthe fly.Afterwards I realized it could be helpful to look at the problem\nfrom this direction. If you have a list of all the things you\nshouldn't do, you can turn that into a recipe for succeeding just\nby negating. And this form of list may be more useful in practice.\nIt's easier to catch yourself doing something you shouldn't than\nalways to remember to do something you should.\n[1]In a sense there's just one mistake that kills startups: not making\nsomething users want. If you make something users want, you'll\nprobably be fine, whatever else you do or don't do. And if you\ndon't make something users want, then you're dead, whatever else\nyou do or don't do. So really this is a list of 18 things that\ncause startups not to make something users want. Nearly all failure\nfunnels through that.1. Single FounderHave you ever noticed how few successful startups were founded by\njust one person? Even companies you think of as having one founder,\nlike Oracle, usually turn out to have more. It seems unlikely this\nis a coincidence.What's wrong with having one founder? To start with, it's a vote\nof no confidence. It probably means the founder couldn't talk any\nof his friends into starting the company with him. That's pretty\nalarming, because his friends are the ones who know him best.But even if the founder's friends were all wrong and the company\nis a good bet, he's still at a disadvantage. Starting a startup\nis too hard for one person. Even if you could do all the work\nyourself, you need colleagues to brainstorm with, to talk you out\nof stupid decisions, and to cheer you up when things go wrong.The last one might be the most important. The low points in a\nstartup are so low that few could bear them alone. When you have\nmultiple founders, esprit de corps binds them together in a way\nthat seems to violate conservation laws. Each thinks \"I can't let\nmy friends down.\" This is one of the most powerful forces in human\nnature, and it's missing when there's just one founder.2. Bad LocationStartups prosper in some places and not others. Silicon Valley\ndominates, then Boston, then Seattle, Austin, Denver, and New York. After\nthat there's not much. Even in New York the number of startups per\ncapita is probably a 20th of what it is in Silicon Valley. In towns\nlike Houston and Chicago and Detroit it's too small to measure.Why is the falloff so sharp? Probably for the same reason it is\nin other industries. What's the sixth largest fashion center in\nthe US? The sixth largest center for oil, or finance, or publishing?\nWhatever they are they're probably so far from the top that it would\nbe misleading even to call them centers.It's an interesting question why cities \nbecome startup hubs, but\nthe reason startups prosper in them is probably the same as it is\nfor any industry: that's where the experts are. Standards are\nhigher; people are more sympathetic to what you're doing; the kind\nof people you want to hire want to live there; supporting industries\nare there; the people you run into in chance meetings are in the\nsame business. Who knows exactly how these factors combine to boost\nstartups in Silicon Valley and squish them in Detroit, but it's\nclear they do from the number of startups per capita in each.3. Marginal NicheMost of the groups that apply to Y Combinator suffer from a common\nproblem: choosing a small, obscure niche in the hope of avoiding\ncompetition.If you watch little kids playing sports, you notice that below a\ncertain age they're afraid of the ball. When the ball comes near\nthem their instinct is to avoid it. I didn't make a lot of catches\nas an eight year old outfielder, because whenever a fly ball came\nmy way, I used to close my eyes and hold my glove up more for\nprotection than in the hope of catching it.Choosing a marginal project is the startup equivalent of my eight\nyear old strategy for dealing with fly balls. If you make anything\ngood, you're going to have competitors, so you may as well face\nthat. You can only avoid competition by avoiding good ideas.I think this shrinking from big problems is mostly unconscious.\nIt's not that people think of grand ideas but decide to pursue\nsmaller ones because they seem safer. Your unconscious won't even\nlet you think of grand ideas. So the solution may be to think about\nideas without involving yourself. What would be a great idea for\nsomeone else to do as a startup?4. Derivative IdeaMany of the applications we get are imitations of some existing\ncompany. That's one source of ideas, but not the best. If you\nlook at the origins of successful startups, few were started in\nimitation of some other startup. Where did they get their ideas?\nUsually from some specific, unsolved problem the founders identified.Our startup made software for making online stores. When we started\nit, there wasn't any; the few sites you could order from were\nhand-made at great expense by web consultants. We knew that if\nonline shopping ever took off, these sites would have to be generated\nby software, so we wrote some. Pretty straightforward.It seems like the best problems to solve are ones that affect you\npersonally. Apple happened because Steve Wozniak wanted a computer,\nGoogle because Larry and Sergey couldn't find stuff online, Hotmail\nbecause Sabeer Bhatia and Jack Smith couldn't exchange email at\nwork.So instead of copying the Facebook, with some variation that the\nFacebook rightly ignored, look for ideas from the other direction.\nInstead of starting from companies and working back to the problems\nthey solved, look for problems and imagine the company that might\nsolve them. \n[2]\nWhat do people complain about? What do you wish there was?5. ObstinacyIn some fields the way to succeed is to have a vision of what you\nwant to achieve, and to hold true to it no matter what setbacks you\nencounter. Starting startups is not one of them. The stick-to-your-vision\napproach works for something like winning an Olympic gold medal,\nwhere the problem is well-defined. Startups are more like science,\nwhere you need to follow the trail wherever it leads.So don't get too attached to your original plan, because it's\nprobably wrong. Most successful startups end up doing something\ndifferent than they originally intended — often so different that\nit doesn't even seem like the same company. You have to be prepared\nto see the better idea when it arrives. And the hardest part of\nthat is often discarding your old idea.But openness to new ideas has to be tuned just right. Switching\nto a new idea every week will be equally fatal. Is there some kind\nof external test you can use? One is to ask whether the ideas\nrepresent some kind of progression. If in each new idea you're\nable to re-use most of what you built for the previous ones, then\nyou're probably in a process that converges. Whereas if you keep\nrestarting from scratch, that's a bad sign.Fortunately there's someone you can ask for advice: your users. If\nyou're thinking about turning in some new direction and your users\nseem excited about it, it's probably a good bet.6. Hiring Bad ProgrammersI forgot to include this in the early versions of the list,\nbecause nearly all the founders I know are programmers. This is\nnot a serious problem for them. They might accidentally hire someone\nbad, but it's not going to kill the company. In a pinch they can\ndo whatever's required themselves.But when I think about what killed most of the startups in the\ne-commerce business back in the 90s, it was bad programmers. A lot\nof those companies were started by business guys who thought the\nway startups worked was that you had some clever idea and then hired\nprogrammers to implement it. That's actually much harder than it\nsounds — almost impossibly hard in fact — because business guys\ncan't tell which are the good programmers. They don't even get a\nshot at the best ones, because no one really good wants a job\nimplementing the vision of a business guy.In practice what happens is that the business guys choose people\nthey think are good programmers (it says here on his resume that\nhe's a Microsoft Certified Developer) but who aren't. Then they're\nmystified to find that their startup lumbers along like a World War\nII bomber while their competitors scream past like jet fighters.\nThis kind of startup is in the same position as a big company,\nbut without the advantages.So how do you pick good programmers if you're not a programmer? I\ndon't think there's an answer. I was about to say you'd have to\nfind a good programmer to help you hire people. But if you can't\nrecognize good programmers, how would you even do that?7. Choosing the Wrong PlatformA related problem (since it tends to be done by bad programmers)\nis choosing the wrong platform. For example, I think a lot of\nstartups during the Bubble killed themselves by deciding to build\nserver-based applications on Windows. Hotmail was still running\non FreeBSD for years after Microsoft bought it, presumably because\nWindows couldn't handle the load. If Hotmail's founders\nhad chosen to use Windows, they would have been swamped.PayPal only just dodged this bullet. After they merged with X.com,\nthe new CEO wanted to switch to Windows — even after PayPal cofounder\nMax Levchin showed that their software scaled only 1% as well on\nWindows as Unix. Fortunately for PayPal they switched CEOs instead.Platform is a vague word. It could mean an operating system, or a\nprogramming language, or a \"framework\" built on top of a programming\nlanguage. It implies something that both supports and limits, like\nthe foundation of a house.The scary thing about platforms is that there are always some that\nseem to outsiders to be fine, responsible choices and yet, like\nWindows in the 90s, will destroy you if you choose them. Java\napplets were probably the most spectacular example. This was\nsupposed to be the new way of delivering applications. Presumably\nit killed just about 100% of the startups who believed that.How do you pick the right platforms? The usual way is to hire good\nprogrammers and let them choose. But there is a trick you could\nuse if you're not a programmer: visit a top computer science\ndepartment and see what they use in research projects.8. Slowness in LaunchingCompanies of all sizes have a hard time getting software done. It's\nintrinsic to the medium; software is always 85% done. It takes an\neffort of will to push through this and get something released to\nusers.\n[3]Startups make all kinds of excuses for delaying their launch. Most\nare equivalent to the ones people use for procrastinating in everyday\nlife. There's something that needs to happen first. Maybe. But\nif the software were 100% finished and ready to launch at the push\nof a button, would they still be waiting?One reason to launch quickly is that it forces you to actually\nfinish some quantum of work. Nothing is truly finished till it's\nreleased; you can see that from the rush of work that's always\ninvolved in releasing anything, no matter how finished you thought\nit was. The other reason you need to launch is that it's only by\nbouncing your idea off users that you fully understand it.Several distinct problems manifest themselves as delays in launching:\nworking too slowly; not truly understanding the problem; fear of\nhaving to deal with users; fear of being judged; working on too\nmany different things; excessive perfectionism. Fortunately you\ncan combat all of them by the simple expedient of forcing yourself\nto launch something fairly quickly.9. Launching Too EarlyLaunching too slowly has probably killed a hundred times more\nstartups than launching too fast, but it is possible to launch too\nfast. The danger here is that you ruin your reputation. You launch\nsomething, the early adopters try it out, and if it's no good they\nmay never come back.So what's the minimum you need to launch? We suggest startups think\nabout what they plan to do, identify a core that's both (a) useful\non its own and (b) something that can be incrementally expanded\ninto the whole project, and then get that done as soon as possible.This is the same approach I (and many other programmers) use for\nwriting software. Think about the overall goal, then start by\nwriting the smallest subset of it that does anything useful. If\nit's a subset, you'll have to write it anyway, so in the worst case\nyou won't be wasting your time. But more likely you'll find that\nimplementing a working subset is both good for morale and helps you\nsee more clearly what the rest should do.The early adopters you need to impress are fairly tolerant. They\ndon't expect a newly launched product to do everything; it just has\nto do something.10. Having No Specific User in MindYou can't build things users like without understanding them. I\nmentioned earlier that the most successful startups seem to have\nbegun by trying to solve a problem their founders had. Perhaps\nthere's a rule here: perhaps you create wealth in proportion to how\nwell you understand the problem you're solving, and the problems\nyou understand best are your own. \n[4]That's just a theory. What's not a theory is the converse: if\nyou're trying to solve problems you don't understand, you're hosed.And yet a surprising number of founders seem willing to\nassume that someone, they're not sure exactly who, will want what\nthey're building. Do the founders want it? No, they're not the\ntarget market. Who is? Teenagers. People interested in local\nevents (that one is a perennial tarpit). Or \"business\" users. What\nbusiness users? Gas stations? Movie studios? Defense contractors?You can of course build something for users other than yourself.\nWe did. But you should realize you're stepping into dangerous\nterritory. You're flying on instruments, in effect, so you should\n(a) consciously shift gears, instead of assuming you can rely on\nyour intuitions as you ordinarily would, and (b) look at the\ninstruments.In this case the instruments are the users. When designing for\nother people you have to be empirical. You can no longer guess\nwhat will work; you have to find users and measure their responses.\nSo if you're going to make something for teenagers or \"business\"\nusers or some other group that doesn't include you, you have to be\nable to talk some specific ones into using what you're making. If\nyou can't, you're on the wrong track.11. Raising Too Little MoneyMost successful startups take funding at some point. Like having\nmore than one founder, it seems a good bet statistically. How much\nshould you take, though?Startup funding is measured in time. Every startup that isn't\nprofitable (meaning nearly all of them, initially) has a certain\namount of time left before the money runs out and they have to stop.\nThis is sometimes referred to as runway, as in \"How much runway do\nyou have left?\" It's a good metaphor because it reminds you that\nwhen the money runs out you're going to be airborne or dead.Too little money means not enough to get airborne. What airborne\nmeans depends on the situation. Usually you have to advance to a\nvisibly higher level: if all you have is an idea, a working prototype;\nif you have a prototype, launching; if you're launched, significant\ngrowth. It depends on investors, because until you're profitable\nthat's who you have to convince.So if you take money from investors, you have to take enough to get\nto the next step, whatever that is.\n[5]\nFortunately you have some\ncontrol over both how much you spend and what the next step is. We\nadvise startups to set both low, initially: spend practically\nnothing, and make your initial goal simply to build a solid prototype.\nThis gives you maximum flexibility.12. Spending Too MuchIt's hard to distinguish spending too much from raising too little.\nIf you run out of money, you could say either was the cause. The\nonly way to decide which to call it is by comparison with other\nstartups. If you raised five million and ran out of money, you\nprobably spent too much.Burning through too much money is not as common as it used to be.\nFounders seem to have learned that lesson. Plus it keeps getting\ncheaper to start a startup. So as of this writing few startups\nspend too much. None of the ones we've funded have. (And not just\nbecause we make small investments; many have gone on to raise further\nrounds.)The classic way to burn through cash is by hiring a lot of people.\nThis bites you twice: in addition to increasing your costs, it slows\nyou down—so money that's getting consumed faster has to last\nlonger. Most hackers understand why that happens; Fred Brooks\nexplained it in The Mythical Man-Month.We have three general suggestions about hiring: (a) don't do it if\nyou can avoid it, (b) pay people with equity rather than salary,\nnot just to save money, but because you want the kind of people who\nare committed enough to prefer that, and (c) only hire people who\nare either going to write code or go out and get users, because\nthose are the only things you need at first.13. Raising Too Much MoneyIt's obvious how too little money could kill you, but is there such\na thing as having too much?Yes and no. The problem is not so much the money itself as what\ncomes with it. As one VC who spoke at Y Combinator said, \"Once you\ntake several million dollars of my money, the clock is ticking.\"\nIf VCs fund you, they're not going to let you just put the money\nin the bank and keep operating as two guys living on ramen. They\nwant that money to go to work. \n[6]\nAt the very least you'll move\ninto proper office space and hire more people. That will change\nthe atmosphere, and not entirely for the better. Now most of your\npeople will be employees rather than founders. They won't be as\ncommitted; they'll need to be told what to do; they'll start to\nengage in office politics.When you raise a lot of money, your company moves to the suburbs\nand has kids.Perhaps more dangerously, once you take a lot of money it gets\nharder to change direction. Suppose your initial plan was to sell\nsomething to companies. After taking VC money you hire a sales\nforce to do that. What happens now if you realize you should be\nmaking this for consumers instead of businesses? That's a completely\ndifferent kind of selling. What happens, in practice, is that you\ndon't realize that. The more people you have, the more you stay\npointed in the same direction.Another drawback of large investments is the time they take. The\ntime required to raise money grows with the amount.\n[7]\nWhen the\namount rises into the millions, investors get very cautious. VCs\nnever quite say yes or no; they just engage you in an apparently\nendless conversation. Raising VC scale investments is thus a huge\ntime sink — more work, probably, than the startup itself. And you\ndon't want to be spending all your time talking to investors while\nyour competitors are spending theirs building things.We advise founders who go on to seek VC money to take the first\nreasonable deal they get. If you get an offer from a reputable\nfirm at a reasonable valuation with no unusually onerous terms,\njust take it and get on with building the company.\n[8]\nWho cares\nif you could get a 30% better deal elsewhere? Economically, startups\nare an all-or-nothing game. Bargain-hunting among investors is a\nwaste of time.14. Poor Investor ManagementAs a founder, you have to manage your investors. You shouldn't\nignore them, because they may have useful insights. But neither\nshould you let them run the company. That's supposed to be your\njob. If investors had sufficient vision to run the companies\nthey fund, why didn't they start them?Pissing off investors by ignoring them is probably less dangerous\nthan caving in to them. In our startup, we erred on the ignoring\nside. A lot of our energy got drained\naway in disputes with investors instead of going into the product.\nBut this was less costly than giving in, which would probably have\ndestroyed the company. If the founders know what they're doing,\nit's better to have half their attention focused on the product\nthan the full attention of investors who don't.How hard you have to work on managing investors usually depends on\nhow much money you've taken. When you raise VC-scale money, the\ninvestors get a great deal of control. If they have a board majority,\nthey're literally your bosses. In the more common case, where\nfounders and investors are equally represented and the deciding\nvote is cast by neutral outside directors, all the investors have\nto do is convince the outside directors and they control the company.If things go well, this shouldn't matter. So long as you seem to\nbe advancing rapidly, most investors will leave you alone. But\nthings don't always go smoothly in startups. Investors have made\ntrouble even for the most successful companies. One of the most\nfamous examples is Apple, whose board made a nearly fatal blunder\nin firing Steve Jobs. Apparently even Google got a lot of grief\nfrom their investors early on.15. Sacrificing Users to (Supposed) ProfitWhen I said at the beginning that if you make something users want,\nyou'll be fine, you may have noticed I didn't mention anything about\nhaving the right business model. That's not because making money\nis unimportant. I'm not suggesting that founders start companies\nwith no chance of making money in the hope of unloading them before\nthey tank. The reason we tell founders not to worry about the\nbusiness model initially is that making something people want is\nso much harder.I don't know why it's so hard to make something people want. It\nseems like it should be straightforward. But you can tell it must\nbe hard by how few startups do it.Because making something people want is so much harder than making\nmoney from it, you should leave business models for later, just as\nyou'd leave some trivial but messy feature for version 2. In version\n1, solve the core problem. And the core problem in a startup is\nhow to create wealth \n(= how much people want something x the number\nwho want it), not how to convert that wealth into money.The companies that win are the ones that put users first. Google,\nfor example. They made search work, then worried about how to make\nmoney from it. And yet some startup founders still think it's\nirresponsible not to focus on the business model from the beginning.\nThey're often encouraged in this by investors whose experience comes\nfrom less malleable industries.It is irresponsible not to think about business models. It's\njust ten times more irresponsible not to think about the product.16. Not Wanting to Get Your Hands DirtyNearly all programmers would rather spend their time writing code\nand have someone else handle the messy business of extracting money\nfrom it. And not just the lazy ones. Larry and Sergey apparently\nfelt this way too at first. After developing their new search\nalgorithm, the first thing they tried was to get some other company\nto buy it.Start a company? Yech. Most hackers would rather just have ideas.\nBut as Larry and Sergey found, there's not much of a market for\nideas. No one trusts an idea till you embody it in a product and\nuse that to grow a user base. Then they'll pay big time.Maybe this will change, but I doubt it will change much. There's\nnothing like users for convincing acquirers. It's not just that\nthe risk is decreased. The acquirers are human, and they have a\nhard time paying a bunch of young guys millions of dollars just for\nbeing clever. When the idea is embodied in a company with a lot\nof users, they can tell themselves they're buying the users rather\nthan the cleverness, and this is easier for them to swallow.\n[9]If you're going to attract users, you'll probably have to get up\nfrom your computer and go find some. It's unpleasant work, but if\nyou can make yourself do it you have a much greater chance of\nsucceeding. In the first batch of startups we funded, in the summer\nof 2005, most of the founders spent all their time building their\napplications. But there was one who was away half the time talking\nto executives at cell phone companies, trying to arrange deals.\nCan you imagine anything more painful for a hacker?\n[10]\nBut it\npaid off, because this startup seems the most successful of that\ngroup by an order of magnitude.If you want to start a startup, you have to face the fact that you\ncan't just hack. At least one hacker will have to spend some of\nthe time doing business stuff.17. Fights Between FoundersFights between founders are surprisingly common. About 20% of the\nstartups we've funded have had a founder leave. It happens so often\nthat we've reversed our attitude to vesting. We still don't require\nit, but now we advise founders to vest so there will be an orderly\nway for people to quit.A founder leaving doesn't necessarily kill a startup, though. Plenty\nof successful startups have had that happen. \n[11]\nFortunately it's\nusually the least committed founder who leaves. If there are three\nfounders and one who was lukewarm leaves, big deal. If you have\ntwo and one leaves, or a guy with critical technical skills leaves,\nthat's more of a problem. But even that is survivable. Blogger\ngot down to one person, and they bounced back.Most of the disputes I've seen between founders could have been\navoided if they'd been more careful about who they started a company\nwith. Most disputes are not due to the situation but the people.\nWhich means they're inevitable. And most founders who've been\nburned by such disputes probably had misgivings, which they suppressed,\nwhen they started the company. Don't suppress misgivings. It's\nmuch easier to fix problems before the company is started than\nafter. So don't include your housemate in your startup because\nhe'd feel left out otherwise. Don't start a company with someone\nyou dislike because they have some skill you need and you worry you\nwon't find anyone else. The people are the most important ingredient\nin a startup, so don't compromise there.18. A Half-Hearted EffortThe failed startups you hear most about are the spectacular\nflameouts. Those are actually the elite of failures. The most\ncommon type is not the one that makes spectacular mistakes, but the\none that doesn't do much of anything — the one we never even hear\nabout, because it was some project a couple guys started on the\nside while working on their day jobs, but which never got anywhere\nand was gradually abandoned.Statistically, if you want to avoid failure, it would seem like the\nmost important thing is to quit your day job. Most founders of\nfailed startups don't quit their day jobs, and most founders of\nsuccessful ones do. If startup failure were a disease, the CDC\nwould be issuing bulletins warning people to avoid day jobs.Does that mean you should quit your day job? Not necessarily. I'm\nguessing here, but I'd guess that many of these would-be founders\nmay not have the kind of determination it takes to start a company,\nand that in the back of their minds, they know it. The reason they\ndon't invest more time in their startup is that they know it's a\nbad investment.\n[12]I'd also guess there's some band of people who could have succeeded\nif they'd taken the leap and done it full-time, but didn't. I have\nno idea how wide this band is, but if the winner/borderline/hopeless\nprogression has the sort of distribution you'd expect, the number\nof people who could have made it, if they'd quit their day job, is\nprobably an order of magnitude larger than the number who do make\nit.\n[13]If that's true, most startups that could succeed fail because the\nfounders don't devote their whole efforts to them. That certainly\naccords with what I see out in the world. Most startups fail because\nthey don't make something people want, and the reason most don't\nis that they don't try hard enough.In other words, starting startups is just like everything else.\nThe biggest mistake you can make is not to try hard enough. To the\nextent there's a secret to success, it's not to be in denial about\nthat.\nNotes[1]\nThis is not a complete list of the causes of failure,\njust those you can control. There are also several you can't,\nnotably ineptitude and bad luck.[2]\nIronically, one variant of the Facebook that might work is a\nfacebook exclusively for college students.[3]\nSteve Jobs tried to motivate people by saying \"Real artists\nship.\" This is a fine sentence, but unfortunately not true. Many\nfamous works of art are unfinished. It's true in fields that have\nhard deadlines, like architecture and filmmaking, but even there\npeople tend to be tweaking stuff till it's yanked out of their\nhands.[4]\nThere's probably also a second factor: startup founders tend\nto be at the leading edge of technology, so problems they face are\nprobably especially valuable.[5]\nYou should take more than you think you'll need, maybe 50% to\n100% more, because software takes longer to write and deals longer\nto close than you expect.[6]\nSince people sometimes call us VCs, I should add that we're\nnot. VCs invest large amounts of other people's money. We invest\nsmall amounts of our own, like angel investors.[7]\nNot linearly of course, or it would take forever to raise five\nmillion dollars. In practice it just feels like it takes forever.Though if you include the cases where VCs don't invest, it would\nliterally take forever in the median case. And maybe we should,\nbecause the danger of chasing large investments is not just that\nthey take a long time. That's the best case. The real danger\nis that you'll expend a lot of time and get nothing.[8]\nSome VCs will offer you an artificially low valuation to see\nif you have the balls to ask for more. It's lame that VCs play\nsuch games, but some do. If you're dealing with one of those you\nshould push back on the valuation a bit.[9]\nSuppose YouTube's founders had gone to Google in 2005 and told\nthem \"Google Video is badly designed. Give us $10 million and we'll\ntell you all the mistakes you made.\" They would have gotten\nthe royal raspberry. Eighteen months later Google paid $1.6 billion\nfor the same lesson, partly because they could then tell themselves\nthat they were buying a phenomenon, or a community, or some vague\nthing like that.I don't mean to be hard on Google. They did better than their\ncompetitors, who may have now missed the video boat entirely.[10]\nYes, actually: dealing with the government. But phone companies\nare up there.[11]\nMany more than most people realize, because companies don't advertise\nthis. Did you know Apple originally had three founders?[12]\nI'm not dissing these people. I don't have the determination\nmyself. I've twice come close to starting startups since Viaweb,\nand both times I bailed because I realized that without the spur\nof poverty I just wasn't willing to endure the stress of a startup.[13]\nSo how do you know whether you're in the category of people\nwho should quit their day job, or the presumably larger one who\nshouldn't? I got to the point of saying that this was hard to judge\nfor yourself and that you should seek outside advice, before realizing\nthat that's what we do. We think of ourselves as investors, but\nviewed from the other direction Y Combinator is a service for\nadvising people whether or not to quit their day job. We could be\nmistaken, and no doubt often are, but we do at least bet money on\nour conclusions.Thanks to Sam Altman, Jessica Livingston, Greg McAdoo, and Robert Morris \nfor reading drafts of this.\n" }, { "path": "data/PaulGrahamEssays/stuff.txt", "content": "July 2007I have too much stuff. Most people in America do. In fact, the\npoorer people are, the more stuff they seem to have. Hardly anyone\nis so poor that they can't afford a front yard full of old cars.It wasn't always this way. Stuff used to be rare and valuable.\nYou can still see evidence of that if you look for it. For example,\nin my house in Cambridge, which was built in 1876, the bedrooms\ndon't have closets. In those days people's stuff fit in a chest\nof drawers. Even as recently as a few decades ago there was a lot\nless stuff. When I look back at photos from the 1970s, I'm surprised\nhow empty houses look. As a kid I had what I thought was a huge\nfleet of toy cars, but they'd be dwarfed by the number of toys my\nnephews have. All together my Matchboxes and Corgis took up about\na third of the surface of my bed. In my nephews' rooms the bed is\nthe only clear space.Stuff has gotten a lot cheaper, but our attitudes toward it haven't\nchanged correspondingly. We overvalue stuff.That was a big problem\nfor me when I had no money. I felt poor, and stuff seemed valuable,\nso almost instinctively I accumulated it. Friends would leave\nsomething behind when they moved, or I'd see something as I was\nwalking down the street on trash night (beware of anything you find\nyourself describing as \"perfectly good\"), or I'd find something in\nalmost new condition for a tenth its retail price at a garage sale.\nAnd pow, more stuff.In fact these free or nearly free things weren't bargains, because\nthey were worth even less than they cost. Most of the stuff I\naccumulated was worthless, because I didn't need it.What I didn't understand was that the value of some new acquisition\nwasn't the difference between its retail price and what I paid for\nit. It was the value I derived from it. Stuff is an extremely\nilliquid asset. Unless you have some plan for selling that valuable\nthing you got so cheaply, what difference does it make what it's\n\"worth?\" The only way you're ever going to extract any value from\nit is to use it. And if you don't have any immediate use for it,\nyou probably never will.Companies that sell stuff have spent huge sums training us to think\nstuff is still valuable. But it would be closer to the truth to\ntreat stuff as worthless.In fact, worse than worthless, because once you've accumulated a\ncertain amount of stuff, it starts to own you rather than the other\nway around. I know of one couple who couldn't retire to the town\nthey preferred because they couldn't afford a place there big enough\nfor all their stuff. Their house isn't theirs; it's their stuff's.And unless you're extremely organized, a house full of stuff can\nbe very depressing. A cluttered room saps one's spirits. One\nreason, obviously, is that there's less room for people in a room\nfull of stuff. But there's more going on than that. I think humans\nconstantly scan their environment to build a mental model of what's\naround them. And the harder a scene is to parse, the less energy\nyou have left for conscious thoughts. A cluttered room is literally\nexhausting.(This could explain why clutter doesn't seem to bother kids as much\nas adults. Kids are less perceptive. They build a coarser model\nof their surroundings, and this consumes less energy.)I first realized the worthlessness of stuff when I lived in Italy\nfor a year. All I took with me was one large backpack of stuff.\nThe rest of my stuff I left in my landlady's attic back in the US.\nAnd you know what? All I missed were some of the books. By the\nend of the year I couldn't even remember what else I had stored in\nthat attic.And yet when I got back I didn't discard so much as a box of it.\nThrow away a perfectly good rotary telephone? I might need that\none day.The really painful thing to recall is not just that I accumulated\nall this useless stuff, but that I often spent money I desperately\nneeded on stuff that I didn't.Why would I do that? Because the people whose job is to sell you\nstuff are really, really good at it. The average 25 year old is\nno match for companies that have spent years figuring out how to\nget you to spend money on stuff. They make the experience of buying\nstuff so pleasant that \"shopping\" becomes a leisure activity.How do you protect yourself from these people? It can't be easy.\nI'm a fairly skeptical person, and their tricks worked on me well\ninto my thirties. But one thing that might work is to ask yourself,\nbefore buying something, \"is this going to make my life noticeably\nbetter?\"A friend of mine cured herself of a clothes buying habit by asking\nherself before she bought anything \"Am I going to wear this all the\ntime?\" If she couldn't convince herself that something she was\nthinking of buying would become one of those few things she wore\nall the time, she wouldn't buy it. I think that would work for any\nkind of purchase. Before you buy anything, ask yourself: will this\nbe something I use constantly? Or is it just something nice? Or\nworse still, a mere bargain?The worst stuff in this respect may be stuff you don't use much\nbecause it's too good. Nothing owns you like fragile stuff. For\nexample, the \"good china\" so many households have, and whose defining\nquality is not so much that it's fun to use, but that one must be\nespecially careful not to break it.Another way to resist acquiring stuff is to think of the overall\ncost of owning it. The purchase price is just the beginning. You're\ngoing to have to think about that thing for years—perhaps for\nthe rest of your life. Every thing you own takes energy away from\nyou. Some give more than they take. Those are the only things\nworth having.I've now stopped accumulating stuff. Except books—but books are\ndifferent. Books are more like a fluid than individual objects.\nIt's not especially inconvenient to own several thousand books,\nwhereas if you owned several thousand random possessions you'd be\na local celebrity. But except for books, I now actively avoid\nstuff. If I want to spend money on some kind of treat, I'll take\nservices over \ngoods any day.I'm not claiming this is because I've achieved some kind of zenlike\ndetachment from material things. I'm talking about something more\nmundane. A historical change has taken place, and I've now realized\nit. Stuff used to be valuable, and now it's not.In industrialized countries the same thing happened with food in\nthe middle of the twentieth century. As food got cheaper (or we\ngot richer; they're indistinguishable), eating too much started to\nbe a bigger danger than eating too little. We've now reached that\npoint with stuff. For most people, rich or poor, stuff has become\na burden.The good news is, if you're carrying a burden without knowing it,\nyour life could be better than you realize. Imagine walking around\nfor years with five pound ankle weights, then suddenly having them\nremoved.\n" }, { "path": "data/PaulGrahamEssays/submarine.txt", "content": "April 2005\"Suits make a corporate comeback,\" says the New\nYork Times. Why does this sound familiar? Maybe because\nthe suit was also back in February,\n\nSeptember\n2004, June\n2004, March\n2004, September\n2003, \n\nNovember\n2002, \nApril 2002,\nand February\n2002.\n\nWhy do the media keep running stories saying suits are back? Because\nPR firms tell \nthem to. One of the most surprising things I discovered\nduring my brief business career was the existence of the PR industry,\nlurking like a huge, quiet submarine beneath the news. Of the\nstories you read in traditional media that aren't about politics,\ncrimes, or disasters, more than half probably come from PR firms.I know because I spent years hunting such \"press hits.\" Our startup spent\nits entire marketing budget on PR: at a time when we were assembling\nour own computers to save money, we were paying a PR firm $16,000\na month. And they were worth it. PR is the news equivalent of\nsearch engine optimization; instead of buying ads, which readers\nignore, you get yourself inserted directly into the stories. [1]Our PR firm\nwas one of the best in the business. In 18 months, they got press\nhits in over 60 different publications. \nAnd we weren't the only ones they did great things for. \nIn 1997 I got a call from another\nstartup founder considering hiring them to promote his company. I\ntold him they were PR gods, worth every penny of their outrageous \nfees. But I remember thinking his company's name was odd.\nWhy call an auction site \"eBay\"?\nSymbiosisPR is not dishonest. Not quite. In fact, the reason the best PR\nfirms are so effective is precisely that they aren't dishonest.\nThey give reporters genuinely valuable information. A good PR firm\nwon't bug reporters just because the client tells them to; they've\nworked hard to build their credibility with reporters, and they\ndon't want to destroy it by feeding them mere propaganda.If anyone is dishonest, it's the reporters. The main reason PR \nfirms exist is that reporters are lazy. Or, to put it more nicely,\noverworked. Really they ought to be out there digging up stories\nfor themselves. But it's so tempting to sit in their offices and\nlet PR firms bring the stories to them. After all, they know good\nPR firms won't lie to them.A good flatterer doesn't lie, but tells his victim selective truths\n(what a nice color your eyes are). Good PR firms use the same\nstrategy: they give reporters stories that are true, but whose truth\nfavors their clients.For example, our PR firm often pitched stories about how the Web \nlet small merchants compete with big ones. This was perfectly true.\nBut the reason reporters ended up writing stories about this\nparticular truth, rather than some other one, was that small merchants\nwere our target market, and we were paying the piper.Different publications vary greatly in their reliance on PR firms.\nAt the bottom of the heap are the trade press, who make most of\ntheir money from advertising and would give the magazines away for\nfree if advertisers would let them. [2] The average\ntrade publication is a bunch of ads, glued together by just enough\narticles to make it look like a magazine. They're so desperate for\n\"content\" that some will print your press releases almost verbatim,\nif you take the trouble to write them to read like articles.At the other extreme are publications like the New York Times\nand the Wall Street Journal. Their reporters do go out and\nfind their own stories, at least some of the time. They'll listen \nto PR firms, but briefly and skeptically. We managed to get press \nhits in almost every publication we wanted, but we never managed \nto crack the print edition of the Times. [3]The weak point of the top reporters is not laziness, but vanity.\nYou don't pitch stories to them. You have to approach them as if\nyou were a specimen under their all-seeing microscope, and make it\nseem as if the story you want them to run is something they thought \nof themselves.Our greatest PR coup was a two-part one. We estimated, based on\nsome fairly informal math, that there were about 5000 stores on the\nWeb. We got one paper to print this number, which seemed neutral \nenough. But once this \"fact\" was out there in print, we could quote\nit to other publications, and claim that with 1000 users we had 20%\nof the online store market.This was roughly true. We really did have the biggest share of the\nonline store market, and 5000 was our best guess at its size. But\nthe way the story appeared in the press sounded a lot more definite.Reporters like definitive statements. For example, many of the\nstories about Jeremy Jaynes's conviction say that he was one of the\n10 worst spammers. This \"fact\" originated in Spamhaus's ROKSO list,\nwhich I think even Spamhaus would admit is a rough guess at the top\nspammers. The first stories about Jaynes cited this source, but\nnow it's simply repeated as if it were part of the indictment. \n[4]All you can say with certainty about Jaynes is that he was a fairly\nbig spammer. But reporters don't want to print vague stuff like\n\"fairly big.\" They want statements with punch, like \"top ten.\" And\nPR firms give them what they want.\nWearing suits, we're told, will make us \n3.6\npercent more productive.BuzzWhere the work of PR firms really does get deliberately misleading is in\nthe generation of \"buzz.\" They usually feed the same story to \nseveral different publications at once. And when readers see similar\nstories in multiple places, they think there is some important trend\nafoot. Which is exactly what they're supposed to think.When Windows 95 was launched, people waited outside stores\nat midnight to buy the first copies. None of them would have been\nthere without PR firms, who generated such a buzz in\nthe news media that it became self-reinforcing, like a nuclear chain\nreaction.I doubt PR firms realize it yet, but the Web makes it possible to \ntrack them at work. If you search for the obvious phrases, you\nturn up several efforts over the years to place stories about the \nreturn of the suit. For example, the Reuters article \n\nthat got picked up by USA\nToday in September 2004. \"The suit is back,\" it begins.Trend articles like this are almost always the work of\nPR firms. Once you know how to read them, it's straightforward to\nfigure out who the client is. With trend stories, PR firms usually\nline up one or more \"experts\" to talk about the industry generally. \nIn this case we get three: the NPD Group, the creative director of\nGQ, and a research director at Smith Barney. [5] When\nyou get to the end of the experts, look for the client. And bingo, \nthere it is: The Men's Wearhouse.Not surprising, considering The Men's Wearhouse was at that moment \nrunning ads saying \"The Suit is Back.\" Talk about a successful\npress hit-- a wire service article whose first sentence is your own\nad copy.The secret to finding other press hits from a given pitch\nis to realize that they all started from the same document back at\nthe PR firm. Search for a few key phrases and the names of the\nclients and the experts, and you'll turn up other variants of this \nstory.Casual\nfridays are out and dress codes are in writes Diane E. Lewis\nin The Boston Globe. In a remarkable coincidence, Ms. Lewis's\nindustry contacts also include the creative director of GQ.Ripped jeans and T-shirts are out, writes Mary Kathleen Flynn in\nUS News & World Report. And she too knows the \ncreative director of GQ.Men's suits\nare back writes Nicole Ford in Sexbuzz.Com (\"the ultimate men's\nentertainment magazine\").Dressing\ndown loses appeal as men suit up at the office writes Tenisha\nMercer of The Detroit News.\nNow that so many news articles are online, I suspect you could find\na similar pattern for most trend stories placed by PR firms. I\npropose we call this new sport \"PR diving,\" and I'm sure there are\nfar more striking examples out there than this clump of five stories.OnlineAfter spending years chasing them, it's now second nature\nto me to recognize press hits for what they are. But before we\nhired a PR firm I had no idea where articles in the mainstream media\ncame from. I could tell a lot of them were crap, but I didn't\nrealize why.Remember the exercises in critical reading you did in school, where\nyou had to look at a piece of writing and step back and ask whether\nthe author was telling the whole truth? If you really want to be\na critical reader, it turns out you have to step back one step\nfurther, and ask not just whether the author is telling the truth,\nbut why he's writing about this subject at all.Online, the answer tends to be a lot simpler. Most people who\npublish online write what they write for the simple reason that\nthey want to. You\ncan't see the fingerprints of PR firms all over the articles, as\nyou can in so many print publications-- which is one of the reasons,\nthough they may not consciously realize it, that readers trust\nbloggers more than Business Week.I was talking recently to a friend who works for a\nbig newspaper. He thought the print media were in serious trouble,\nand that they were still mostly in denial about it. \"They think\nthe decline is cyclic,\" he said. \"Actually it's structural.\"In other words, the readers are leaving, and they're not coming\nback.\nWhy? I think the main reason is that the writing online is more honest.\nImagine how incongruous the New York Times article about\nsuits would sound if you read it in a blog:\n The urge to look corporate-- sleek, commanding,\n prudent, yet with just a touch of hubris on your well-cut sleeve--\n is an unexpected development in a time of business disgrace.\n \nThe problem\nwith this article is not just that it originated in a PR firm.\nThe whole tone is bogus. This is the tone of someone writing down\nto their audience.Whatever its flaws, the writing you find online\nis authentic. It's not mystery meat cooked up\nout of scraps of pitch letters and press releases, and pressed into \nmolds of zippy\njournalese. It's people writing what they think.I didn't realize, till there was an alternative, just how artificial\nmost of the writing in the mainstream media was. I'm not saying\nI used to believe what I read in Time and Newsweek. Since high\nschool, at least, I've thought of magazines like that more as\nguides to what ordinary people were being\ntold to think than as \nsources of information. But I didn't realize till the last \nfew years that writing for publication didn't have to mean writing\nthat way. I didn't realize you could write as candidly and\ninformally as you would if you were writing to a friend.Readers aren't the only ones who've noticed the\nchange. The PR industry has too.\nA hilarious article\non the site of the PR Society of America gets to the heart of the \nmatter:\n Bloggers are sensitive about becoming mouthpieces\n for other organizations and companies, which is the reason they\n began blogging in the first place. \nPR people fear bloggers for the same reason readers\nlike them. And that means there may be a struggle ahead. As\nthis new kind of writing draws readers away from traditional media, we\nshould be prepared for whatever PR mutates into to compensate. \nWhen I think \nhow hard PR firms work to score press hits in the traditional \nmedia, I can't imagine they'll work any less hard to feed stories\nto bloggers, if they can figure out how.\nNotes[1] PR has at least \none beneficial feature: it favors small companies. If PR didn't \nwork, the only alternative would be to advertise, and only big\ncompanies can afford that.[2] Advertisers pay \nless for ads in free publications, because they assume readers \nignore something they get for free. This is why so many trade\npublications nominally have a cover price and yet give away free\nsubscriptions with such abandon.[3] Different sections\nof the Times vary so much in their standards that they're\npractically different papers. Whoever fed the style section reporter\nthis story about suits coming back would have been sent packing by\nthe regular news reporters.[4] The most striking\nexample I know of this type is the \"fact\" that the Internet worm \nof 1988 infected 6000 computers. I was there when it was cooked up,\nand this was the recipe: someone guessed that there were about\n60,000 computers attached to the Internet, and that the worm might\nhave infected ten percent of them.Actually no one knows how many computers the worm infected, because\nthe remedy was to reboot them, and this destroyed all traces. But\npeople like numbers. And so this one is now replicated\nall over the Internet, like a little worm of its own.[5] Not all were\nnecessarily supplied by the PR firm. Reporters sometimes call a few\nadditional sources on their own, like someone adding a few fresh \nvegetables to a can of soup.\nThanks to Ingrid Basset, Trevor Blackwell, Sarah Harlin, Jessica \nLivingston, Jackie McDonough, Robert Morris, and Aaron Swartz (who\nalso found the PRSA article) for reading drafts of this.Correction: Earlier versions used a recent\nBusiness Week article mentioning del.icio.us as an example\nof a press hit, but Joshua Schachter tells me \nit was spontaneous." }, { "path": "data/PaulGrahamEssays/sun.txt", "content": "September 2017The most valuable insights are both general and surprising. \nF = ma for example. But general and surprising is a hard\ncombination to achieve. That territory tends to be picked\nclean, precisely because those insights are so valuable.Ordinarily, the best that people can do is one without the\nother: either surprising without being general (e.g.\ngossip), or general without being surprising (e.g.\nplatitudes).Where things get interesting is the moderately valuable\ninsights. You get those from small additions of whichever\nquality was missing. The more common case is a small\naddition of generality: a piece of gossip that's more than\njust gossip, because it teaches something interesting about\nthe world. But another less common approach is to focus on\nthe most general ideas and see if you can find something new\nto say about them. Because these start out so general, you\nonly need a small delta of novelty to produce a useful\ninsight.A small delta of novelty is all you'll be able to get most\nof the time. Which means if you take this route, your ideas\nwill seem a lot like ones that already exist. Sometimes\nyou'll find you've merely rediscovered an idea that did\nalready exist. But don't be discouraged. Remember the huge\nmultiplier that kicks in when you do manage to think of\nsomething even a little new.Corollary: the more general the ideas you're talking about,\nthe less you should worry about repeating yourself. If you\nwrite enough, it's inevitable you will. Your brain is much\nthe same from year to year and so are the stimuli that hit\nit. I feel slightly bad when I find I've said something\nclose to what I've said before, as if I were plagiarizing\nmyself. But rationally one shouldn't. You won't say\nsomething exactly the same way the second time, and that\nvariation increases the chance you'll get that tiny but\ncritical delta of novelty.And of course, ideas beget ideas. (That sounds \nfamiliar.)\nAn idea with a small amount of novelty could lead to one\nwith more. But only if you keep going. So it's doubly\nimportant not to let yourself be discouraged by people who\nsay there's not much new about something you've discovered.\n\"Not much new\" is a real achievement when you're talking\nabout the most general ideas. It's not true that there's nothing new under the sun. There\nare some domains where there's almost nothing new. But\nthere's a big difference between nothing and almost nothing,\nwhen it's multiplied by the area under the sun.\nThanks to Sam Altman, Patrick Collison, and Jessica\nLivingston for reading drafts of this." }, { "path": "data/PaulGrahamEssays/superangels.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nOctober 2010After barely changing at all for decades, the startup funding\nbusiness is now in what could, at least by comparison, be called\nturmoil. At Y Combinator we've seen dramatic changes in the funding\nenvironment for startups. Fortunately one of them is much higher\nvaluations.The trends we've been seeing are probably not YC-specific. I wish\nI could say they were, but the main cause is probably just that we\nsee trends first—partly because the startups we fund are very\nplugged into the Valley and are quick to take advantage of anything\nnew, and partly because we fund so many that we have enough data\npoints to see patterns clearly.What we're seeing now, everyone's probably going to be seeing in\nthe next couple years. So I'm going to explain what we're seeing,\nand what that will mean for you if you try to raise money.Super-AngelsLet me start by describing what the world of startup funding used\nto look like. There used to be two sharply differentiated types\nof investors: angels and venture capitalists. Angels are individual\nrich people who invest small amounts of their own money, while VCs\nare employees of funds that invest large amounts of other people's.For decades there were just those two types of investors, but now\na third type has appeared halfway between them: the so-called\nsuper-angels. \n[1]\n And VCs have been provoked by their arrival\ninto making a lot of angel-style investments themselves. So the\npreviously sharp line between angels and VCs has become hopelessly\nblurred.There used to be a no man's land between angels and VCs. Angels\nwould invest $20k to $50k apiece, and VCs usually a million or more.\nSo an angel round meant a collection of angel investments that\ncombined to maybe $200k, and a VC round meant a series A round in\nwhich a single VC fund (or occasionally two) invested $1-5 million.The no man's land between angels and VCs was a very inconvenient\none for startups, because it coincided with the amount many wanted\nto raise. Most startups coming out of Demo Day wanted to raise\naround $400k. But it was a pain to stitch together that much out\nof angel investments, and most VCs weren't interested in investments\nso small. That's the fundamental reason the super-angels have\nappeared. They're responding to the market.The arrival of a new type of investor is big news for startups,\nbecause there used to be only two and they rarely competed with one\nanother. Super-angels compete with both angels and VCs. That's\ngoing to change the rules about how to raise money. I don't know\nyet what the new rules will be, but it looks like most of the changes\nwill be for the better.A super-angel has some of the qualities of an angel, and some of\nthe qualities of a VC. They're usually individuals, like angels.\nIn fact many of the current super-angels were initially angels of\nthe classic type. But like VCs, they invest other people's money.\nThis allows them to invest larger amounts than angels: a typical\nsuper-angel investment is currently about $100k. They make investment\ndecisions quickly, like angels. And they make a lot more investments\nper partner than VCs—up to 10 times as many.The fact that super-angels invest other people's money makes them\ndoubly alarming to VCs. They don't just compete for startups; they\nalso compete for investors. What super-angels really are is a new\nform of fast-moving, lightweight VC fund. And those of us in the\ntechnology world know what usually happens when something comes\nalong that can be described in terms like that. Usually it's the\nreplacement.Will it be? As of now, few of the startups that take money from\nsuper-angels are ruling out taking VC money. They're just postponing\nit. But that's still a problem for VCs. Some of the startups that\npostpone raising VC money may do so well on the angel money they\nraise that they never bother to raise more. And those who do raise\nVC rounds will be able to get higher valuations when they do. If\nthe best startups get 10x higher valuations when they raise series\nA rounds, that would cut VCs' returns from winners at least tenfold.\n[2]So I think VC funds are seriously threatened by the super-angels.\nBut one thing that may save them to some extent is the uneven\ndistribution of startup outcomes: practically all the returns are\nconcentrated in a few big successes. The expected value of a startup\nis the percentage chance it's Google. So to the extent that winning\nis a matter of absolute returns, the super-angels could win practically\nall the battles for individual startups and yet lose the war, if\nthey merely failed to get those few big winners. And there's a\nchance that could happen, because the top VC funds have better\nbrands, and can also do more for their portfolio companies. \n[3]Because super-angels make more investments per partner, they have\nless partner per investment. They can't pay as much attention to\nyou as a VC on your board could. How much is that extra attention\nworth? It will vary enormously from one partner to another. There's\nno consensus yet in the general case. So for now this is something\nstartups are deciding individually.Till now, VCs' claims about how much value they added were sort of\nlike the government's. Maybe they made you feel better, but you\nhad no choice in the matter, if you needed money on the scale only\nVCs could supply. Now that VCs have competitors, that's going to\nput a market price on the help they offer. The interesting thing\nis, no one knows yet what it will be.Do startups that want to get really big need the sort of advice and\nconnections only the top VCs can supply? Or would super-angel money\ndo just as well? The VCs will say you need them, and the super-angels\nwill say you don't. But the truth is, no one knows yet, not even\nthe VCs and super-angels themselves. All the super-angels know\nis that their new model seems promising enough to be worth trying,\nand all the VCs know is that it seems promising enough to worry\nabout.RoundsWhatever the outcome, the conflict between VCs and super-angels is\ngood news for founders. And not just for the obvious reason that\nmore competition for deals means better terms. The whole shape of\ndeals is changing.One of the biggest differences between angels and VCs is the amount\nof your company they want. VCs want a lot. In a series A round\nthey want a third of your company, if they can get it. They don't\ncare much how much they pay for it, but they want a lot because the\nnumber of series A investments they can do is so small. In a\ntraditional series A investment, at least one partner from the VC\nfund takes a seat on your board. \n[4]\n Since board seats last about\n5 years and each partner can't handle more than about 10 at once,\nthat means a VC fund can only do about 2 series A deals per partner\nper year. And that means they need to get as much of the company\nas they can in each one. You'd have to be a very promising startup\nindeed to get a VC to use up one of his 10 board seats for only a\nfew percent of you.Since angels generally don't take board seats, they don't have this\nconstraint. They're happy to buy only a few percent of you. And\nalthough the super-angels are in most respects mini VC funds, they've\nretained this critical property of angels. They don't take board\nseats, so they don't need a big percentage of your company.Though that means you'll get correspondingly less attention from\nthem, it's good news in other respects. Founders never really liked\ngiving up as much equity as VCs wanted. It was a lot of the company\nto give up in one shot. Most founders doing series A deals would\nprefer to take half as much money for half as much stock, and then\nsee what valuation they could get for the second half of the stock\nafter using the first half of the money to increase its value. But\nVCs never offered that option.Now startups have another alternative. Now it's easy to raise angel\nrounds about half the size of series A rounds. Many of the startups\nwe fund are taking this route, and I predict that will be true of\nstartups in general.A typical big angel round might be $600k on a convertible note with\na valuation cap of $4 million premoney. Meaning that when the note\nconverts into stock (in a later round, or upon acquisition), the\ninvestors in that round will get .6 / 4.6, or 13% of the company.\nThat's a lot less than the 30 to 40% of the company you usually\ngive up in a series A round if you do it so early. \n[5]But the advantage of these medium-sized rounds is not just that\nthey cause less dilution. You also lose less control. After an\nangel round, the founders almost always still have control of the\ncompany, whereas after a series A round they often don't. The\ntraditional board structure after a series A round is two founders,\ntwo VCs, and a (supposedly) neutral fifth person. Plus series A\nterms usually give the investors a veto over various kinds of\nimportant decisions, including selling the company. Founders usually\nhave a lot of de facto control after a series A, as long as things\nare going well. But that's not the same as just being able to do\nwhat you want, like you could before.A third and quite significant advantage of angel rounds is that\nthey're less stressful to raise. Raising a traditional series A\nround has in the past taken weeks, if not months. When a VC firm\ncan only do 2 deals per partner per year, they're careful about\nwhich they do. To get a traditional series A round you have to go\nthrough a series of meetings, culminating in a full partner meeting\nwhere the firm as a whole says yes or no. That's the really scary\npart for founders: not just that series A rounds take so long, but\nat the end of this long process the VCs might still say no. The\nchance of getting rejected after the full partner meeting averages\nabout 25%. At some firms it's over 50%.Fortunately for founders, VCs have been getting a lot faster.\nNowadays Valley VCs are more likely to take 2 weeks than 2 months.\nBut they're still not as fast as angels and super-angels, the most\ndecisive of whom sometimes decide in hours.Raising an angel round is not only quicker, but you get feedback\nas it progresses. An angel round is not an all or nothing thing\nlike a series A. It's composed of multiple investors with varying\ndegrees of seriousness, ranging from the upstanding ones who commit\nunequivocally to the jerks who give you lines like \"come back to\nme to fill out the round.\" You usually start collecting money from\nthe most committed investors and work your way out toward the\nambivalent ones, whose interest increases as the round fills up.But at each point you know how you're doing. If investors turn\ncold you may have to raise less, but when investors in an angel\nround turn cold the process at least degrades gracefully, instead\nof blowing up in your face and leaving you with nothing, as happens\nif you get rejected by a VC fund after a full partner meeting.\nWhereas if investors seem hot, you can not only close the round\nfaster, but now that convertible notes are becoming the norm,\nactually raise the price to reflect demand.ValuationHowever, the VCs have a weapon they can use against the super-angels,\nand they have started to use it. VCs have started making angel-sized\ninvestments too. The term \"angel round\" doesn't mean that all the\ninvestors in it are angels; it just describes the structure of the\nround. Increasingly the participants include VCs making investments\nof a hundred thousand or two. And when VCs invest in angel rounds\nthey can do things that super-angels don't like. VCs are quite\nvaluation-insensitive in angel rounds—partly because they are\nin general, and partly because they don't care that much about the\nreturns on angel rounds, which they still view mostly as a way to\nrecruit startups for series A rounds later. So VCs who invest in\nangel rounds can blow up the valuations for angels and super-angels\nwho invest in them. \n[6]Some super-angels seem to care about valuations. Several turned\ndown YC-funded startups after Demo Day because their valuations\nwere too high. This was not a problem for the startups; by definition\na high valuation means enough investors were willing to accept it.\nBut it was mysterious to me that the super-angels would quibble\nabout valuations. Did they not understand that the big returns\ncome from a few big successes, and that it therefore mattered far\nmore which startups you picked than how much you paid for them?After thinking about it for a while and observing certain other\nsigns, I have a theory that explains why the super-angels may be\nsmarter than they seem. It would make sense for super-angels to\nwant low valuations if they're hoping to invest in startups that\nget bought early. If you're hoping to hit the next Google, you\nshouldn't care if the valuation is 20 million. But if you're looking\nfor companies that are going to get bought for 30 million, you care.\nIf you invest at 20 and the company gets bought for 30, you only\nget 1.5x. You might as well buy Apple.So if some of the super-angels were looking for companies that could\nget acquired quickly, that would explain why they'd care about\nvaluations. But why would they be looking for those? Because\ndepending on the meaning of \"quickly,\" it could actually be very\nprofitable. A company that gets acquired for 30 million is a failure\nto a VC, but it could be a 10x return for an angel, and moreover,\na quick 10x return. Rate of return is what matters in\ninvesting—not the multiple you get, but the multiple per year.\nIf a super-angel gets 10x in one year, that's a higher rate of\nreturn than a VC could ever hope to get from a company that took 6\nyears to go public. To get the same rate of return, the VC would\nhave to get a multiple of 10^6—one million x. Even Google\ndidn't come close to that.So I think at least some super-angels are looking for companies\nthat will get bought. That's the only rational explanation for\nfocusing on getting the right valuations, instead of the right\ncompanies. And if so they'll be different to deal with than VCs.\nThey'll be tougher on valuations, but more accommodating if you want\nto sell early.PrognosisWho will win, the super-angels or the VCs? I think the answer to\nthat is, some of each. They'll each become more like one another.\nThe super-angels will start to invest larger amounts, and the VCs\nwill gradually figure out ways to make more, smaller investments\nfaster. A decade from now the players will be hard to tell apart,\nand there will probably be survivors from each group.What does that mean for founders? One thing it means is that the\nhigh valuations startups are presently getting may not last forever.\nTo the extent that valuations are being driven up by price-insensitive\nVCs, they'll fall again if VCs become more like super-angels and\nstart to become more miserly about valuations. Fortunately if this\ndoes happen it will take years.The short term forecast is more competition between investors, which\nis good news for you. The super-angels will try to undermine the\nVCs by acting faster, and the VCs will try to undermine the\nsuper-angels by driving up valuations. Which for founders will\nresult in the perfect combination: funding rounds that close fast,\nwith high valuations.But remember that to get that combination, your startup will have\nto appeal to both super-angels and VCs. If you don't seem like you\nhave the potential to go public, you won't be able to use VCs to\ndrive up the valuation of an angel round.There is a danger of having VCs in an angel round: the so-called\nsignalling risk. If VCs are only doing it in the hope of investing\nmore later, what happens if they don't? That's a signal to everyone\nelse that they think you're lame.How much should you worry about that? The seriousness of signalling\nrisk depends on how far along you are. If by the next time you\nneed to raise money, you have graphs showing rising revenue or\ntraffic month after month, you don't have to worry about any signals\nyour existing investors are sending. Your results will speak for\nthemselves. \n[7]Whereas if the next time you need to raise money you won't yet have\nconcrete results, you may need to think more about the message your\ninvestors might send if they don't invest more. I'm not sure yet\nhow much you have to worry, because this whole phenomenon of VCs\ndoing angel investments is so new. But my instincts tell me you\ndon't have to worry much. Signalling risk smells like one of those\nthings founders worry about that's not a real problem. As a rule,\nthe only thing that can kill a good startup is the startup itself.\nStartups hurt themselves way more often than competitors hurt them,\nfor example. I suspect signalling risk is in this category too.One thing YC-funded startups have been doing to mitigate the risk\nof taking money from VCs in angel rounds is not to take too much\nfrom any one VC. Maybe that will help, if you have the luxury of\nturning down money.Fortunately, more and more startups will. After decades of competition\nthat could best be described as intramural, the startup funding\nbusiness is finally getting some real competition. That should\nlast several years at least, and maybe a lot longer. Unless there's\nsome huge market crash, the next couple years are going to be a\ngood time for startups to raise money. And that's exciting because\nit means lots more startups will happen.\nNotes[1]\nI've also heard them called \"Mini-VCs\" and \"Micro-VCs.\" I\ndon't know which name will stick.There were a couple predecessors. Ron Conway had angel funds\nstarting in the 1990s, and in some ways First Round Capital is closer to a\nsuper-angel than a VC fund.[2]\nIt wouldn't cut their overall returns tenfold, because investing\nlater would probably (a) cause them to lose less on investments\nthat failed, and (b) not allow them to get as large a percentage\nof startups as they do now. So it's hard to predict precisely what\nwould happen to their returns.[3]\nThe brand of an investor derives mostly from the success of\ntheir portfolio companies. The top VCs thus have a big brand\nadvantage over the super-angels. They could make it self-perpetuating\nif they used it to get all the best new startups. But I don't think\nthey'll be able to. To get all the best startups, you have to do\nmore than make them want you. You also have to want them; you have\nto recognize them when you see them, and that's much harder.\nSuper-angels will snap up stars that VCs miss. And that will cause\nthe brand gap between the top VCs and the super-angels gradually\nto erode.[4]\nThough in a traditional series A round VCs put two partners\non your board, there are signs now that VCs may begin to conserve\nboard seats by switching to what used to be considered an angel-round\nboard, consisting of two founders and one VC. Which is also to the\nfounders' advantage if it means they still control the company.[5]\nIn a series A round, you usually have to give up more than\nthe actual amount of stock the VCs buy, because they insist you\ndilute yourselves to set aside an \"option pool\" as well. I predict\nthis practice will gradually disappear though.[6]\nThe best thing for founders, if they can get it, is a convertible\nnote with no valuation cap at all. In that case the money invested\nin the angel round just converts into stock at the valuation of the\nnext round, no matter how large. Angels and super-angels tend not\nto like uncapped notes. They have no idea how much of the company\nthey're buying. If the company does well and the valuation of the\nnext round is high, they may end up with only a sliver of it. So\nby agreeing to uncapped notes, VCs who don't care about valuations\nin angel rounds can make offers that super-angels hate to match.[7]\nObviously signalling risk is also not a problem if you'll\nnever need to raise more money. But startups are often mistaken\nabout that.Thanks to Sam Altman, John Bautista, Patrick Collison, James\nLindenbaum, Reid Hoffman, Jessica Livingston and Harj Taggar\nfor reading drafts\nof this." }, { "path": "data/PaulGrahamEssays/swan.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nSeptember 2012I've done several types of work over the years but I don't know\nanother as counterintuitive as startup investing.The two most important things to understand about startup investing,\nas a business, are (1) that effectively all the returns are\nconcentrated in a few big winners, and (2) that the best ideas look\ninitially like bad ideas.The first rule I knew intellectually, but didn't really grasp till\nit happened to us. The total value of the companies we've funded\nis around 10 billion, give or take a few. But just two companies,\nDropbox and Airbnb, account for about three quarters of it.In startups, the big winners are big to a degree that violates our\nexpectations about variation. I don't know whether these expectations\nare innate or learned, but whatever the cause, we are just not\nprepared for the 1000x variation in outcomes that one finds in\nstartup investing.That yields all sorts of strange consequences. For example, in\npurely financial terms, there is probably at most one company in\neach YC batch that will have a significant effect on our returns,\nand the rest are just a cost of doing business. \n[1]\nI haven't\nreally assimilated that fact, partly because it's so counterintuitive,\nand partly because we're not doing this just for financial reasons;\nYC would be a pretty lonely place if we only had one company per\nbatch. And yet it's true.To succeed in a domain that violates your intuitions, you need to\nbe able to turn them off the way a pilot does when flying through\nclouds. \n[2]\n You need to do what you know intellectually to be\nright, even though it feels wrong.It's a constant battle for us. It's hard to make ourselves take\nenough risks. When you interview a startup and think \"they seem\nlikely to succeed,\" it's hard not to fund them. And yet, financially\nat least, there is only one kind of success: they're either going\nto be one of the really big winners or not, and if not it doesn't\nmatter whether you fund them, because even if they succeed the\neffect on your returns will be insignificant. In the same day of\ninterviews you might meet some smart 19 year olds who aren't even\nsure what they want to work on. Their chances of succeeding seem\nsmall. But again, it's not their chances of succeeding that matter\nbut their chances of succeeding really big. The probability that\nany group will succeed really big is microscopically small, but the\nprobability that those 19 year olds will might be higher than that\nof the other, safer group.The probability that a startup will make it big is not simply a\nconstant fraction of the probability that they will succeed at all.\nIf it were, you could fund everyone who seemed likely to succeed\nat all, and you'd get that fraction of big hits. Unfortunately\npicking winners is harder than that. You have to ignore the elephant\nin front of you, the likelihood they'll succeed, and focus instead\non the separate and almost invisibly intangible question of whether\nthey'll succeed really big.HarderThat's made harder by the fact that the best startup ideas seem at\nfirst like bad ideas. I've written about this before: if a good\nidea were obviously good, someone else would already have done it.\nSo the most successful founders tend to work on ideas that few\nbeside them realize are good. Which is not that far from a description\nof insanity, till you reach the point where you see results.The first time Peter Thiel spoke at YC he drew a Venn diagram that\nillustrates the situation perfectly. He drew two intersecting\ncircles, one labelled \"seems like a bad idea\" and the other \"is a\ngood idea.\" The intersection is the sweet spot for startups.This concept is a simple one and yet seeing it as a Venn diagram\nis illuminating. It reminds you that there is an intersection—that\nthere are good ideas that seem bad. It also reminds you that the\nvast majority of ideas that seem bad are bad.The fact that the best ideas seem like bad ideas makes it even\nharder to recognize the big winners. It means the probability of\na startup making it really big is not merely not a constant fraction\nof the probability that it will succeed, but that the startups with\na high probability of the former will seem to have a disproportionately\nlow probability of the latter.History tends to get rewritten by big successes, so that in retrospect\nit seems obvious they were going to make it big. For that reason\none of my most valuable memories is how lame Facebook sounded to\nme when I first heard about it. A site for college students to\nwaste time? It seemed the perfect bad idea: a site (1) for a niche\nmarket (2) with no money (3) to do something that didn't matter.One could have described Microsoft and Apple in exactly the same\nterms.\n[3]Harder StillWait, it gets worse. You not only have to solve this hard problem,\nbut you have to do it with no indication of whether you're succeeding.\nWhen you pick a big winner, you won't know it for two years.Meanwhile, the one thing you can measure is dangerously\nmisleading. The one thing we can track precisely is how well the\nstartups in each batch do at fundraising after Demo Day. But we\nknow that's the wrong metric. There's no correlation between the\npercentage of startups that raise money and the metric that does\nmatter financially, whether that batch of startups contains a big\nwinner or not.Except an inverse one. That's the scary thing: fundraising is not\nmerely a useless metric, but positively misleading. We're in a\nbusiness where we need to pick unpromising-looking outliers, and\nthe huge scale of the successes means we can afford to spread our\nnet very widely. The big winners could generate 10,000x returns.\nThat means for each big winner we could pick a thousand companies\nthat returned nothing and still end up 10x ahead.If we ever got to the point where 100% of the startups we funded\nwere able to raise money after Demo Day, it would almost certainly\nmean we were being too conservative.\n[4]It takes a conscious effort not to do that too. After 15 cycles\nof preparing startups for investors and then watching how they do,\nI can now look at a group we're interviewing through Demo Day\ninvestors' eyes. But those are the wrong eyes to look through!We can afford to take at least 10x as much risk as Demo Day investors.\nAnd since risk is usually proportionate to reward, if you can afford\nto take more risk you should. What would it mean to take 10x more\nrisk than Demo Day investors? We'd have to be willing to fund 10x\nmore startups than they would. Which means that even if we're\ngenerous to ourselves and assume that YC can on average triple a\nstartup's expected value, we'd be taking the right amount of risk\nif only 30% of the startups were able to raise significant funding\nafter Demo Day.I don't know what fraction of them currently raise more after Demo\nDay. I deliberately avoid calculating that number, because if you\nstart measuring something you start optimizing it, and I know it's\nthe wrong thing to optimize.\n[5]\nBut the percentage is certainly\nway over 30%. And frankly the thought of a 30% success rate at\nfundraising makes my stomach clench. A Demo Day where only 30% of\nthe startups were fundable would be a shambles. Everyone would\nagree that YC had jumped the shark. We ourselves would feel that\nYC had jumped the shark. And yet we'd all be wrong.For better or worse that's never going to be more than a thought\nexperiment. We could never stand it. How about that for\ncounterintuitive? I can lay out what I know to be the right thing\nto do, and still not do it. I can make up all sorts of plausible\njustifications. It would hurt YC's brand (at least among the\ninnumerate) if we invested in huge numbers of risky startups that\nflamed out. It might dilute the value of the alumni network.\nPerhaps most convincingly, it would be demoralizing for us to be\nup to our chins in failure all the time. But I know the real reason\nwe're so conservative is that we just haven't assimilated the fact\nof 1000x variation in returns.We'll probably never be able to bring ourselves to take risks\nproportionate to the returns in this business. The best we can\nhope for is that when we interview a group and find ourselves\nthinking \"they seem like good founders, but what are investors going\nto think of this crazy idea?\" we'll continue to be able to say \"who\ncares what investors think?\" That's what we thought about Airbnb,\nand if we want to fund more Airbnbs we have to stay good at thinking\nit.Notes[1]\nI'm not saying that the big winners are all that matters, just\nthat they're all that matters financially for investors. Since\nwe're not doing YC mainly for financial reasons, the big winners\naren't all that matters to us. We're delighted to have funded\nReddit, for example. Even though we made comparatively little from\nit, Reddit has had a big effect on the world, and it introduced us\nto Steve Huffman and Alexis Ohanian, both of whom have become good\nfriends.Nor do we push founders to try to become one of the big winners if\nthey don't want to. We didn't \"swing for the fences\" in our own\nstartup (Viaweb, which was acquired for $50 million), and it would\nfeel pretty bogus to press founders to do something we didn't do.\nOur rule is that it's up to the founders. Some want to take over\nthe world, and some just want that first few million. But we invest\nin so many companies that we don't have to sweat any one outcome.\nIn fact, we don't have to sweat whether startups have exits at all.\nThe biggest exits are the only ones that matter financially, and\nthose are guaranteed in the sense that if a company becomes big\nenough, a market for its shares will inevitably arise. Since the\nremaining outcomes don't have a significant effect on returns, it's\ncool with us if the founders want to sell early for a small amount,\nor grow slowly and never sell (i.e. become a so-called lifestyle\nbusiness), or even shut the company down. We're sometimes disappointed\nwhen a startup we had high hopes for doesn't do well, but this\ndisappointment is mostly the ordinary variety that anyone feels\nwhen that happens.[2]\nWithout visual cues (e.g. the horizon) you can't distinguish\nbetween gravity and acceleration. Which means if you're flying\nthrough clouds you can't tell what the attitude of\nthe aircraft is. You could feel like you're flying straight and\nlevel while in fact you're descending in a spiral. The solution\nis to ignore what your body is telling you and listen only to your\ninstruments. But it turns out to be very hard to ignore what your\nbody is telling you. Every pilot knows about this \nproblem and yet\nit is still a leading cause of accidents.[3]\nNot all big hits follow this pattern though. The reason Google\nseemed a bad idea was that there were already lots of search engines\nand there didn't seem to be room for another.[4]\nA startup's success at fundraising is a function of two things:\nwhat they're selling and how good they are at selling it. And while\nwe can teach startups a lot about how to appeal to investors, even\nthe most convincing pitch can't sell an idea that investors don't\nlike. I was genuinely worried that Airbnb, for example, would not\nbe able to raise money after Demo Day. I couldn't convince Fred Wilson to fund them. They might not\nhave raised money at all but for the coincidence that Greg McAdoo,\nour contact at Sequoia, was one of a handful of VCs who understood\nthe vacation rental business, having spent much of the previous two\nyears investigating it.[5]\nI calculated it once for the last batch before a consortium of\ninvestors started offering investment automatically to every startup\nwe funded, summer 2010. At the time it was 94% (33 of 35 companies\nthat tried to raise money succeeded, and one didn't try because\nthey were already profitable). Presumably it's lower now because\nof that investment; in the old days it was raise after Demo Day or\ndie.Thanks to Sam Altman, Paul Buchheit, Patrick Collison, Jessica\nLivingston, Geoff Ralston, and Harj Taggar for reading drafts of\nthis." }, { "path": "data/PaulGrahamEssays/tablets.txt", "content": "December 2010I was thinking recently how inconvenient it was not to have a general\nterm for iPhones, iPads, and the corresponding things running\nAndroid. The closest to a general term seems to be \"mobile devices,\"\nbut that (a) applies to any mobile phone, and (b) doesn't really\ncapture what's distinctive about the iPad.After a few seconds it struck me that what we'll end up calling\nthese things is tablets. The only reason we even consider calling\nthem \"mobile devices\" is that the iPhone preceded the iPad. If the\niPad had come first, we wouldn't think of the iPhone as a phone;\nwe'd think of it as a tablet small enough to hold up to your ear.The iPhone isn't so much a phone as a replacement for a phone.\nThat's an important distinction, because it's an early instance of\nwhat will become a common pattern. Many if not most of the\nspecial-purpose objects around us are going to be replaced by apps\nrunning on tablets.This is already clear in cases like GPSes, music players, and\ncameras. But I think it will surprise people how many things are\ngoing to get replaced. We funded one startup that's \nreplacing keys.\nThe fact that you can change font sizes easily means the iPad\neffectively replaces reading glasses. I wouldn't be surprised if\nby playing some clever tricks with the accelerometer you could even\nreplace the bathroom scale.The advantages of doing things in software on a single device are\nso great that everything that can get turned into software will.\nSo for the next couple years, a good recipe for startups\nwill be to look around you for things that people haven't realized\nyet can be made unnecessary by a tablet app.In 1938 Buckminster Fuller coined the term ephemeralization to\ndescribe the increasing tendency of physical machinery to be replaced\nby what we would now call software. The reason tablets are going\nto take over the world is not (just) that Steve Jobs and Co are\nindustrial design wizards, but because they have this force behind\nthem. The iPhone and the iPad have effectively drilled a hole that\nwill allow ephemeralization to flow into a lot of new areas. No one\nwho has studied the history of technology would want to underestimate\nthe power of that force.I worry about the power Apple could have with this force behind\nthem. I don't want to see another era of client monoculture like\nthe Microsoft one in the 80s and 90s. But if ephemeralization is\none of the main forces driving the spread of tablets, that suggests\na way to compete with Apple: be a better platform for it.It has turned out to be a great thing that Apple tablets have\naccelerometers in them. Developers have used the accelerometer in\nways Apple could never have imagined. That's the nature of platforms.\nThe more versatile the tool, the less you can predict how people\nwill use it. So tablet makers should be thinking: what else can\nwe put in there? Not merely hardware, but software too. What else\ncan we give developers access to? Give hackers an inch and they'll\ntake you a mile.\nThanks to Sam Altman, Paul Buchheit, Jessica Livingston, and\nRobert Morris for reading drafts of this." }, { "path": "data/PaulGrahamEssays/talk.txt", "content": "October 2015Here's a simple trick for getting more people to read what you\nwrite: write in spoken language.Something comes over most people when they start writing. They write\nin a different language than they'd use if they were talking to a\nfriend. The sentence structure and even the words are different.\nNo one uses \"pen\" as a verb in spoken English. You'd feel like an\nidiot using \"pen\" instead of \"write\" in a conversation with a friend.The last straw for me was a sentence I read a couple days ago:\n\n The mercurial Spaniard himself declared: \"After Altamira, all is\n decadence.\"\n\nIt's from Neil Oliver's A History of Ancient Britain. I feel bad\nmaking an example of this book, because it's no worse than lots of\nothers. But just imagine calling Picasso \"the mercurial Spaniard\" when\ntalking to a friend. Even one\nsentence of this would raise eyebrows in conversation. And yet\npeople write whole books of it.Ok, so written and spoken language are different. Does that make\nwritten language worse?If you want people to read and understand what you write, yes.\nWritten language is more complex, which makes it more work to read.\nIt's also more formal and distant, which gives the reader's attention\npermission to drift. But perhaps worst of all, the complex sentences\nand fancy words give you, the writer, the false impression that\nyou're saying more than you actually are.You don't need complex sentences to express complex ideas. When\nspecialists in some abstruse topic talk to one another about ideas\nin their field, they don't use sentences any more complex than they\ndo when talking about what to have for lunch. They use different\nwords, certainly. But even those they use no more than necessary.\nAnd in my experience, the harder the subject, the more informally\nexperts speak. Partly, I think, because they have less to prove,\nand partly because the harder the ideas you're talking about, the\nless you can afford to let language get in the way.Informal language is the athletic clothing of ideas.I'm not saying spoken language always works best. Poetry is as much\nmusic as text, so you can say things you wouldn't say in conversation.\nAnd there are a handful of writers who can get away with using fancy\nlanguage in prose. And then of course there are cases where writers\ndon't want to make it easy to understand what they're saying—in\ncorporate announcements of bad news, for example, or at the more\nbogus end of the humanities. But for nearly everyone else, spoken\nlanguage is better.It seems to be hard for most people to write in spoken language.\nSo perhaps the best solution is to write your first draft the way\nyou usually would, then afterward look at each sentence and ask \"Is\nthis the way I'd say this if I were talking to a friend?\" If it\nisn't, imagine what you would say, and use that instead. After a\nwhile this filter will start to operate as you write. When you write\nsomething you wouldn't say, you'll hear the clank as it hits the\npage.Before I publish a new essay, I read it out loud and fix everything\nthat doesn't sound like conversation. I even fix bits that are\nphonetically awkward; I don't know if that's necessary, but it\ndoesn't cost much.This trick may not always be enough. I've seen writing so far\nremoved from spoken language that it couldn't be fixed sentence by\nsentence. For cases like that there's a more drastic solution.\nAfter writing the first draft, try explaining to a friend what you\njust wrote. Then replace the draft with what you said to your friend.People often tell me how much my essays sound like me talking.\nThe fact that this seems worthy of comment shows how rarely people\nmanage to write in spoken language. Otherwise everyone's writing\nwould sound like them talking.If you simply manage to write in spoken language, you'll be ahead\nof 95% of writers. And it's so easy to do: just don't let a sentence\nthrough unless it's the way you'd say it to a friend.Thanks to Patrick Collison and Jessica Livingston for reading drafts of this." }, { "path": "data/PaulGrahamEssays/taste.txt", "content": "February 2002\n\n\n\n\"...Copernicus'\naesthetic objections to [equants] provided one essential\nmotive for his rejection of the Ptolemaic system....\"- Thomas Kuhn, The Copernican Revolution\"All of us had been trained by Kelly Johnson and believed\nfanatically in his insistence that an airplane that looked\nbeautiful would fly the same way.\"- Ben Rich, Skunk Works\"Beauty is the first test: there is no permanent place in this\nworld for ugly mathematics.\"- G. H. Hardy, A Mathematician's Apology\n\n\nI was talking recently to a friend who teaches\nat MIT. His field is hot now and\nevery year he is inundated by applications from\nwould-be graduate students. \"A lot of them seem smart,\"\nhe said. \"What I can't tell is whether they have any kind\nof taste.\"Taste. You don't hear that word much now.\nAnd yet we still need the underlying\nconcept, whatever we call it. What my friend meant was\nthat he wanted students who were not just good technicians,\nbut who could use their technical knowledge to\ndesign beautiful things.Mathematicians call good work \"beautiful,\"\nand so, either now or in the past, have\nscientists, engineers, musicians, architects, designers,\nwriters, and painters.\nIs it just a coincidence that they used the same word, or is \nthere some overlap in what they meant? If there\nis an overlap, can we use one field's discoveries\nabout beauty to help us in another?For those of us who design things, these are not just\ntheoretical questions. If there is such a thing as\nbeauty, we need to be able to recognize it. We need\ngood taste to make good things.\nInstead of\ntreating beauty as an airy abstraction, to be either blathered\nabout or avoided depending on how one feels about airy\nabstractions, let's try considering it as a practical question:\nhow do you make good stuff?If you mention taste nowadays, a lot of people will tell\nyou that \"taste is subjective.\"\nThey believe this because it really feels that\nway to them. When they like something, they have no idea\nwhy. It could be because it's beautiful, or because their\nmother had one, or because they saw a movie star with one\nin a magazine, or because they know it's expensive.\nTheir thoughts are a tangle of unexamined impulses.Most of us are encouraged, as children, to leave this tangle\nunexamined. If you make fun of your little brother for\ncoloring people green in his coloring book, your\nmother is likely to tell you something like \"you like to\ndo it your way and he likes to do it his way.\"Your mother at this point is not trying to teach you\nimportant truths about aesthetics. She's trying to get\nthe two of you to stop bickering.Like many of the half-truths adults tell us, this one\ncontradicts other things they tell us. After dinning\ninto you that taste is merely a matter of personal preference,\nthey take you to the museum and tell you that you should\npay attention because Leonardo is a great artist.What goes through the kid's head at this point? What does\nhe think \"great artist\" means? After having been\ntold for years that everyone just likes to do\nthings their own way, he is\nunlikely to head straight for the conclusion that a great\nartist is someone whose work is better than the others'.\nA far more likely theory, in his Ptolemaic model of\nthe universe, is that a great artist is something that's\ngood for you, like broccoli, because someone said so in a book.Saying that taste is just personal preference is a good way\nto prevent disputes. The trouble is, it's not true.\nYou feel this when you start to design things.Whatever job people do, they naturally want to do better.\nFootball players\nlike to win games. CEOs like to increase earnings. It's\na matter of pride, and a real pleasure, to get better at\nyour job. But if\nyour job is to design things, and there is no such thing\nas beauty, then there is no way to get better at your job.\nIf taste is just personal preference, then everyone's is \nalready perfect: you like whatever you like, and that's it.As in any job, as you continue to design things, you'll get\nbetter at it. Your tastes will change. And, like anyone\nwho gets better at their job, you'll know you're getting\nbetter. If so,\nyour old tastes were\nnot merely different, but worse. Poof goes the axiom that\ntaste can't be wrong.Relativism is fashionable at the moment, and that may hamper\nyou from thinking about taste, even as yours grows.\nBut if you come out of the closet and admit, at least to yourself,\nthat there is such a thing as good and bad design, then you\ncan start to study good design in detail.\nHow has\nyour taste changed? When you made mistakes, what\ncaused you to make them? What have other people learned about\ndesign?Once you start to examine the question, it's surprising how\nmuch different fields' ideas of beauty have in common. The same\nprinciples of good design crop up again and again.Good design is simple. You hear this from math to\npainting. In math it means that a shorter proof tends to be\na better one. Where axioms are concerned, especially,\nless is more. It means much the same thing in programming.\nFor architects and designers it means that beauty should\ndepend on a few carefully chosen structural elements\nrather than a profusion of superficial ornament. (Ornament\nis not in itself bad, only when it's camouflage on insipid\nform.) Similarly, in painting, a\nstill life of a few carefully observed and solidly\nmodelled objects will tend to be more interesting than a\nstretch of flashy\nbut mindlessly repetitive painting of, say, a lace collar.\nIn writing it means: say what you mean\nand say it briefly.It seems strange to have to emphasize simplicity.\nYou'd think simple would be the default. Ornate\nis more work. But something seems to come over people\nwhen they try to be creative. Beginning writers adopt \na pompous tone that doesn't sound anything like the way \nthey speak. Designers trying to be artistic resort to\nswooshes and curlicues. Painters discover that they're expressionists.\nIt's all evasion.\nUnderneath\nthe long words or the \"expressive\" brush strokes, there\nis not much going on, and that's frightening.When you're\nforced to be simple, you're forced to face the real problem.\nWhen you can't deliver ornament, you have to deliver\nsubstance.Good design is timeless.\nIn math, every proof is timeless unless it contains a mistake.\nSo what does Hardy mean when he says there is no permanent \nplace for ugly mathematics? He means the same thing Kelly Johnson did:\nif something is ugly, it can't be the best solution. There\nmust be a better one, and eventually\nsomeone will discover it.Aiming at timelessness is a way to make\nyourself find the best answer:\nif you can imagine someone surpassing you, you should do it yourself.\nSome of the greatest masters did this so well that they\nleft little room for those who came after.\nEvery engraver since Durer has had to live in his shadow.Aiming at timelessness is also a way to evade\nthe grip of fashion. Fashions almost by definition\nchange with time, so if you can make something that\nwill still look good far into the future, then its\nappeal must derive more from merit and less from fashion.Strangely enough, if you want to make something that will \nappeal to future generations, one way to do it is to\ntry to appeal to past generations. It's hard to guess what\nthe future will be like, but we can be sure it will be\nlike the past in caring nothing for present fashions.\nSo if you can make something that appeals to people today\nand would also have appealed to people in 1500, there is a good\nchance it will appeal to people in 2500.Good design solves the right problem. The typical\nstove has four burners arranged in a square, and a dial\nto control each. How do you arrange the dials? The\nsimplest answer is to put them in a row. But this is a\nsimple answer to the wrong question.\nThe dials are for humans to use, and if you put them in a row,\nthe unlucky human will have to stop and think each time\nabout which dial matches which burner. Better to arrange the dials\nin a square like the burners.A lot of bad design is industrious, but misguided.\nIn the mid twentieth century there was a vogue for\nsetting text in sans-serif fonts.\nThese fonts are closer to the pure, underlying letterforms.\nBut in text that's not the problem you're trying to solve. \nFor legibility it's more important that letters be easy\nto tell apart.\nIt may look Victorian, but a Times Roman lowercase g is\neasy to tell from a lowercase y.Problems can be improved as well as solutions.\nIn software, an intractable problem can usually be replaced\nby an equivalent one that's easy to solve.\nPhysics progressed faster as the problem became\npredicting observable behavior, instead of reconciling it\nwith scripture.Good design is suggestive.\nJane Austen's novels contain almost no\ndescription; instead of telling you how\neverything looks, she tells her story so well that you \nenvision the scene for yourself.\nLikewise, a painting that suggests is usually more engaging\nthan one that tells. Everyone makes up their own story about the\nMona Lisa.In architecture and design, this\nprinciple means that a building or object should let you \nuse it how you want: a good building, for example, will\nserve as a backdrop for whatever life people want to lead in it, instead\nof making them live as if they were executing a program\nwritten by the architect.In software, it means you should give users a few\nbasic elements that they can combine as they wish, like Lego. \nIn math it means a proof that\nbecomes the basis for a lot of new work is\npreferable to a proof that was difficult,\nbut doesn't lead to future discoveries; in the\nsciences generally, citation is considered a rough\nindicator of merit.Good design is often slightly funny. This one\nmay not always be true. But Durer's \nengravings\nand Saarinen's \nwomb chair and the \nPantheon and the\noriginal Porsche 911 all seem\nto me slightly funny. Godel's incompleteness theorem\nseems like a practical joke.I think it's because humor is related to strength.\nTo have a sense of humor is to be strong:\nto keep one's sense of humor is to shrug off misfortunes,\nand to lose one's sense of humor is to be wounded by them.\nAnd so the mark-- or at least the prerogative-- of strength\nis not to take\noneself too seriously.\nThe confident will often, like\nswallows, seem to be making fun of the whole process slightly,\nas Hitchcock does in his films or Bruegel in his paintings-- or\nShakespeare, for that matter.Good design may not have to be funny, but it's hard to\nimagine something that could be called humorless also being\ngood design.Good design is hard. If you look at the people who've\ndone great work, one thing they all seem to have in common is that they\nworked very hard. If you're not working hard,\nyou're probably wasting your time.Hard problems call for great\nefforts. In math, difficult proofs require ingenious solutions,\nand those tend to be interesting. Ditto in engineering.When you\nhave to climb a mountain you toss everything unnecessary\nout of your pack. And so an architect who has to build\non a difficult site, or a small budget, will find that he\nis forced to produce an elegant design. Fashions and\nflourishes get knocked aside by the difficult business\nof solving the problem at all.Not every kind of hard is good. There is good pain and bad pain.\nYou want the kind of pain you get from going running, not the\nkind you get from stepping on a nail.\nA difficult\nproblem could be good for a designer, but a fickle client or unreliable\nmaterials would not be.In art, the highest place has traditionally been given to\npaintings of people. There is something to this tradition,\nand not just because pictures of faces get to press\nbuttons in our brains that other pictures don't. We are \nso good at looking at faces that we force anyone who\ndraws them to work hard to satisfy us. If you\ndraw a tree and you change the angle of a branch\nfive degrees, no one will know. When you change the angle\nof someone's eye five degrees, people notice.When Bauhaus designers adopted Sullivan's \"form follows function,\"\nwhat they meant was, form should follow function. And\nif function is hard enough, form is forced to follow it,\nbecause there is no effort to spare for error. Wild animals\nare beautiful because they have hard lives.Good design looks easy. Like great athletes,\ngreat designers make it look easy. Mostly this is\nan illusion. The easy, conversational tone of good\nwriting comes only on the eighth rewrite.In science and engineering, some of the greatest\ndiscoveries seem so simple that you say to yourself,\nI could have thought of that. The discoverer is\nentitled to reply, why didn't you?Some Leonardo heads are just a few lines. You look\nat them and you think, all you have to do is get eight\nor ten lines in the right place and you've made this beautiful\nportrait. Well, yes, but you have to get them in\nexactly the right place. The slightest error\nwill make the whole thing collapse.Line drawings are in fact the most difficult visual\nmedium, because they demand near perfection.\nIn math terms, they are a closed-form solution; lesser \nartists literally solve the same problems by successive\napproximation. One of the reasons kids give up drawing\nat ten or so is that they decide to start\ndrawing like grownups, and one of the first things\nthey try is a line drawing of a face. Smack!In most fields the appearance of ease seems to come with\npractice. Perhaps what practice does is train your\nunconscious mind to handle tasks that used to\nrequire conscious thought. In some cases\nyou literally train your body. An expert pianist can\nplay notes faster than the brain can send signals to\nhis hand. \nLikewise an artist, after a while, can\nmake visual perception flow in through his eye and\nout through his hand as automatically as someone tapping his foot to\na beat.When people talk about being in\n\"the zone,\" I think what they mean is that the\nspinal cord has the situation under control.\nYour spinal cord is less hesitant, and\nit frees conscious thought for the hard problems.\nGood design uses symmetry.\nI think symmetry may just\nbe one way to achieve simplicity, but it's important enough\nto be mentioned on its own.\nNature uses it a lot, which is a good sign.There are two kinds of symmetry, repetition and recursion.\nRecursion means repetition in subelements, like the\npattern of veins in a leaf.Symmetry is unfashionable in some fields now, in reaction to\nexcesses in the past. Architects started consciously\nmaking buildings asymmetric in Victorian times and by the\n1920s asymmetry was an explicit premise of modernist architecture.\nEven these buildings only tended to be asymmetric\nabout major axes, though; there were hundreds of minor symmetries.In writing you find symmetry at every level, from the phrases\nin a sentence to the plot of a novel. You find the same\nin music and art.\nMosaics (and some Cezannes) get extra visual punch by making\nthe whole picture out of the same atoms. Compositional \nsymmetry yields some of the most memorable paintings, \nespecially when two halves react to one another, as in \nthe Creation of Adam or \nAmerican Gothic.In math and engineering, recursion, especially, is a big win.\nInductive proofs are wonderfully short. In software,\na problem that can be solved by recursion is nearly always\nbest solved that way. The Eiffel Tower looks striking partly\nbecause it is a recursive solution, a tower on a tower.The danger of symmetry, and repetition especially, is that\nit can be used as a substitute for thought.Good design resembles nature. It's not so much that\nresembling nature is intrinsically good as that nature\nhas had a long time to work on the\nproblem. It's a good sign when your answer resembles nature's.It's not cheating to copy.\nFew would deny that a story should be like life.\nWorking from life is a valuable tool in painting too, though its\nrole has often been misunderstood.\nThe aim is not simply to make a record.\nThe point of painting from life is\nthat it gives your mind something to chew on: when your\neyes are looking at something, your hand will do more\ninteresting work.Imitating nature also works in engineering. Boats have\nlong had spines and ribs like an animal's ribcage.\nIn some cases we may have to wait for better technology:\nearly aircraft designers were mistaken to\ndesign aircraft that looked like birds, because they didn't\nhave materials or power sources light enough (the Wrights' engine\nweighed 152 lbs. and\ngenerated only 12 hp.) or control systems sophisticated\nenough for machines that flew like birds, but I could\nimagine little unmanned reconnaissance planes flying\nlike birds in fifty years.Now that we have enough computer power, we can imitate nature's \nmethod as well as its results. Genetic algorithms may let us\ncreate things too complex to design in the ordinary\nsense.Good design is redesign. It's rare to get things right\nthe first time. Experts expect to throw away some early work.\nThey plan for plans to change.It takes confidence to throw work away. You have to be able \nto think, there's more where that came from. \nWhen people first start drawing, for example,\nthey're often reluctant to redo parts that aren't\nright; they feel they've been lucky to get that far, \nand if they try to redo something, it will turn out worse. Instead\nthey convince themselves that the drawing is not that bad,\nreally-- in fact, maybe they meant it to look that way.Dangerous territory, that; if anything you should\ncultivate dissatisfaction.\nIn Leonardo's drawings there are often five\nor six attempts to get a line right.\nThe distinctive back of the Porsche\n911 only appeared in the redesign of an awkward \nprototype.\nIn Wright's early plans for the \nGuggenheim,\nthe right half was a ziggurat; he inverted it to get the\npresent shape.Mistakes are natural. Instead of treating them\nas disasters, make them easy to acknowledge and easy to fix.\nLeonardo more or less invented the sketch, as a\nway to make drawing bear a greater weight of exploration.\nOpen-source software has fewer bugs because it admits the\npossibility of bugs.It helps to have a medium that makes change easy.\nWhen oil paint replaced tempera in the fifteenth century,\nit helped\npainters to deal with difficult subjects like the human \nfigure because, unlike tempera, oil can be blended and overpainted.\nGood design can copy. Attitudes to copying\noften make a round trip. A novice\nimitates without knowing it; next he tries\nconsciously to be original; finally, he decides it's\nmore important to be right than original.Unknowing imitation is almost a recipe for bad design.\nIf you don't know where your ideas are coming from,\nyou're probably imitating an imitator.\nRaphael so pervaded mid-nineteenth century taste that almost \nanyone who tried to draw was imitating him, often at several\nremoves.\nIt was this, more than Raphael's own work, that bothered\nthe Pre-Raphaelites.The ambitious are not content to imitate. The\nsecond phase in the growth of taste is a conscious\nattempt at originality.I think the\ngreatest masters go on to achieve a kind of selflessness.\nThey just want to get the right answer, and if part of the\nright answer has already been discovered by someone else,\nthat's no reason not to use it.\nThey're confident enough to take from anyone without\nfeeling that their own vision will be lost in the process.\nGood design is often strange. Some of the very best work\nhas an uncanny quality: Euler's \nFormula, \nBruegel's\nHunters in the Snow, the \nSR-71, Lisp. They're not just\nbeautiful, but strangely beautiful.I'm not sure why. It may just be my own stupidity. A\ncan-opener must seem miraculous to a dog. Maybe if I were smart\nenough it would seem the most natural thing in the world that\nei*pi = -1. It is after all necessarily true.Most of the qualities I've mentioned are things that can be\ncultivated, but I don't think it works to cultivate strangeness.\nThe best you can do is not squash it if it starts to appear.\nEinstein didn't try to make relativity strange.\nHe tried to make it true, and the truth turned out to be strange.At an art school where I once studied, the students wanted\nmost of all to develop a personal style.\nBut if you just try to make good things, you'll \ninevitably do it in a distinctive way, just as each person\nwalks in a distinctive way. Michelangelo was not trying\nto paint like Michelangelo. He was just trying to paint\nwell; he couldn't help painting like Michelangelo.The only style worth having is the one you can't help.\nAnd this is especially true for strangeness. There is no\nshortcut to it. The Northwest Passage that the Mannerists,\nthe Romantics, and two generations of American high school\nstudents have searched for does not seem to exist. The\nonly way to get there is to go through good and come out\nthe other side.\nGood design happens in chunks. The inhabitants\nof fifteenth century Florence included Brunelleschi, Ghiberti,\nDonatello, Masaccio, Filippo Lippi, \nFra Angelico, Verrocchio, Botticelli, Leonardo, and Michelangelo.\nMilan at the time was as big as Florence.\nHow many fifteenth century Milanese artists can you name?Something was happening in Florence in the fifteenth century.\nAnd it can't have been heredity, because it isn't happening now.\nYou have to assume that whatever\ninborn ability Leonardo and Michelangelo had, there were\npeople born in Milan with just as much. What happened to\nthe Milanese Leonardo?There are roughly a thousand times\nas many people alive in the US right now as lived in\nFlorence during the fifteenth century. A thousand Leonardos\nand a thousand Michelangelos walk among us.\nIf DNA ruled, we should be greeted daily by artistic\nmarvels. We aren't, and the reason is that to make Leonardo\nyou need more than his innate ability. You also need Florence \nin 1450.Nothing is more powerful\nthan a community of talented people working on related\nproblems. Genes count for little by comparison: being a genetic\nLeonardo was not enough to compensate for having been born \nnear Milan instead of Florence.\nToday we move around more, but great work still comes\ndisproportionately from a few hotspots:\nthe Bauhaus, the Manhattan Project, the New Yorker,\nLockheed's Skunk Works, Xerox Parc.At any given time there are a\nfew hot topics and a few groups doing great work on them,\nand it's nearly impossible to do\ngood work yourself if you're too far removed from one\nof these centers. You can push or pull these trends\nto some extent, but you can't break away from them.\n(Maybe you can, but the Milanese Leonardo couldn't.)\nGood design is often daring. At every period \nof history, people have believed things that were just \nridiculous, and believed them so strongly that you risked \nostracism or even violence by saying otherwise.If our own time were any different, that would be remarkable.\nAs far as I can tell it isn't.This problem afflicts not just every\nera, but in some degree every field.\nMuch Renaissance art was in its time considered shockingly secular:\naccording to Vasari, Botticelli repented and gave up painting, and\nFra Bartolommeo and Lorenzo di Credi actually burned some of their\nwork.\nEinstein's theory of relativity offended many contemporary physicists,\nand was not fully accepted for decades-- in France, not until the\n1950s.Today's experimental error is tomorrow's new theory. If\nyou want to discover great new things, then instead of turning\na blind eye to the places where conventional wisdom and\ntruth don't quite meet, you should pay particular attention \nto them.As a practical matter, I think it's easier to see ugliness\nthan to imagine beauty. Most of the people who've made beautiful\nthings seem to have done it by fixing something that they \nthought ugly. Great work usually seems to happen because someone sees\nsomething and thinks, I could do better than that. Giotto\nsaw traditional Byzantine madonnas painted according to a\nformula that had satisfied everyone for centuries, and to him\nthey looked wooden and unnatural.\nCopernicus was so troubled by a hack that all his contemporaries\ncould tolerate that he felt there must be a better solution.Intolerance for ugliness is not in itself enough. You have to\nunderstand a field well before you develop a good nose for\nwhat needs fixing. You have to do your homework. But as\nyou become expert in a field, you'll start to hear little\nvoices saying, What a hack! There must be a better way.\nDon't ignore those voices. Cultivate them. The recipe for\ngreat work is: very exacting taste, plus the ability\nto gratify it.NotesSullivan\n actually said \"form ever follows function,\" but \nI think the usual misquotation is closer to what modernist\narchitects meant.\nStephen G. Brush, \"Why was Relativity Accepted?\"\nPhys. Perspect. 1 (1999) 184-214." }, { "path": "data/PaulGrahamEssays/think.txt", "content": "November 2020There are some kinds of work that you can't do well without thinking\ndifferently from your peers. To be a successful scientist, for\nexample, it's not enough just to be correct. Your ideas have to be\nboth correct and novel. You can't publish papers saying things other\npeople already know. You need to say things no one else has realized\nyet.The same is true for investors. It's not enough for a public market\ninvestor to predict correctly how a company will do. If a lot of\nother people make the same prediction, the stock price will already\nreflect it, and there's no room to make money. The only valuable\ninsights are the ones most other investors don't share.You see this pattern with startup founders too. You don't want to\nstart a startup to do something that everyone agrees is a good idea,\nor there will already be other companies doing it. You have to do\nsomething that sounds to most other people like a bad idea, but\nthat you know isn't — like writing software for a tiny computer\nused by a few thousand hobbyists, or starting a site to let people\nrent airbeds on strangers' floors.Ditto for essayists. An essay that told people things they already\nknew would be boring. You have to tell them something new.But this pattern isn't universal. In fact, it doesn't hold for most\nkinds of work. In most kinds of work — to be an administrator, for\nexample — all you need is the first half. All you need is to be\nright. It's not essential that everyone else be wrong.There's room for a little novelty in most kinds of work, but in\npractice there's a fairly sharp distinction between the kinds of\nwork where it's essential to be independent-minded, and the kinds\nwhere it's not.I wish someone had told me about this distinction when I was a kid,\nbecause it's one of the most important things to think about when\nyou're deciding what kind of work you want to do. Do you want to\ndo the kind of work where you can only win by thinking differently\nfrom everyone else? I suspect most people's unconscious mind will\nanswer that question before their conscious mind has a chance to.\nI know mine does.Independent-mindedness seems to be more a matter of nature than\nnurture. Which means if you pick the wrong type of work, you're\ngoing to be unhappy. If you're naturally independent-minded, you're\ngoing to find it frustrating to be a middle manager. And if you're\nnaturally conventional-minded, you're going to be sailing into a\nheadwind if you try to do original research.One difficulty here, though, is that people are often mistaken about\nwhere they fall on the spectrum from conventional- to independent-minded.\nConventional-minded people don't like to think of themselves as\nconventional-minded. And in any case, it genuinely feels to them\nas if they make up their own minds about everything. It's just a\ncoincidence that their beliefs are identical to their peers'. And\nthe independent-minded, meanwhile, are often unaware how different\ntheir ideas are from conventional ones, at least till they state\nthem publicly.\n[1]By the time they reach adulthood, most people know roughly how smart\nthey are (in the narrow sense of ability to solve pre-set problems),\nbecause they're constantly being tested and ranked according to it.\nBut schools generally ignore independent-mindedness, except to the\nextent they try to suppress it. So we don't get anything like the\nsame kind of feedback about how independent-minded we are.There may even be a phenomenon like Dunning-Kruger at work, where\nthe most conventional-minded people are confident that they're\nindependent-minded, while the genuinely independent-minded worry\nthey might not be independent-minded enough.\n___________\nCan you make yourself more independent-minded? I think so. This\nquality may be largely inborn, but there seem to be ways to magnify\nit, or at least not to suppress it.One of the most effective techniques is one practiced unintentionally\nby most nerds: simply to be less aware what conventional beliefs\nare. It's hard to be a conformist if you don't know what you're\nsupposed to conform to. Though again, it may be that such people\nalready are independent-minded. A conventional-minded person would\nprobably feel anxious not knowing what other people thought, and\nmake more effort to find out.It matters a lot who you surround yourself with. If you're surrounded\nby conventional-minded people, it will constrain which ideas you\ncan express, and that in turn will constrain which ideas you have.\nBut if you surround yourself with independent-minded people, you'll\nhave the opposite experience: hearing other people say surprising\nthings will encourage you to, and to think of more.Because the independent-minded find it uncomfortable to be surrounded\nby conventional-minded people, they tend to self-segregate once\nthey have a chance to. The problem with high school is that they\nhaven't yet had a chance to. Plus high school tends to be an\ninward-looking little world whose inhabitants lack confidence, both\nof which magnify the forces of conformism. So high school is\noften a bad time for the\nindependent-minded. But there is some advantage even here: it\nteaches you what to avoid. If you later find yourself in a situation\nthat makes you think \"this is like high school,\" you know you should\nget out.\n[2]Another place where the independent- and conventional-minded are\nthrown together is in successful startups. The founders and early\nemployees are almost always independent-minded; otherwise the startup\nwouldn't be successful. But conventional-minded people greatly\noutnumber independent-minded ones, so as the company grows, the\noriginal spirit of independent-mindedness is inevitably diluted.\nThis causes all kinds of problems besides the obvious one that the\ncompany starts to suck. One of the strangest is that the founders\nfind themselves able to speak more freely with founders of other\ncompanies than with their own employees.\n[3]Fortunately you don't have to spend all your time with independent-minded\npeople. It's enough to have one or two you can talk to regularly.\nAnd once you find them, they're usually as eager to talk as you\nare; they need you too. Although universities no longer have the\nkind of monopoly they used to have on education, good universities\nare still an excellent way to meet independent-minded people. Most\nstudents will still be conventional-minded, but you'll at least\nfind clumps of independent-minded ones, rather than the near zero\nyou may have found in high school.It also works to go in the other direction: as well as cultivating\na small collection of independent-minded friends, to try to meet\nas many different types of people as you can. It will decrease the\ninfluence of your immediate peers if you have several other groups\nof peers. Plus if you're part of several different worlds, you can\noften import ideas from one to another.But by different types of people, I don't mean demographically\ndifferent. For this technique to work, they have to think differently.\nSo while it's an excellent idea to go and visit other countries,\nyou can probably find people who think differently right around the\ncorner. When I meet someone who knows a lot about something unusual\n(which includes practically everyone, if you dig deep enough), I\ntry to learn what they know that other people don't. There are\nalmost always surprises here. It's a good way to make conversation\nwhen you meet strangers, but I don't do it to make conversation.\nI really want to know.You can expand the source of influences in time as well as space,\nby reading history. When I read history I do it not just to learn\nwhat happened, but to try to get inside the heads of people who\nlived in the past. How did things look to them? This is hard to do,\nbut worth the effort for the same reason it's worth travelling far\nto triangulate a point.You can also take more explicit measures to prevent yourself from\nautomatically adopting conventional opinions. The most general is\nto cultivate an attitude of skepticism. When you hear someone say\nsomething, stop and ask yourself \"Is that true?\" Don't say it out\nloud. I'm not suggesting that you impose on everyone who talks to\nyou the burden of proving what they say, but rather that you take\nupon yourself the burden of evaluating what they say.Treat it as a puzzle. You know that some accepted ideas will later\nturn out to be wrong. See if you can guess which. The end goal is\nnot to find flaws in the things you're told, but to find the new\nideas that had been concealed by the broken ones. So this game\nshould be an exciting quest for novelty, not a boring protocol for\nintellectual hygiene. And you'll be surprised, when you start asking\n\"Is this true?\", how often the answer is not an immediate yes. If\nyou have any imagination, you're more likely to have too many leads\nto follow than too few.More generally your goal should be not to let anything into your\nhead unexamined, and things don't always enter your head in the\nform of statements. Some of the most powerful influences are implicit.\nHow do you even notice these? By standing back and watching how\nother people get their ideas.When you stand back at a sufficient distance, you can see ideas\nspreading through groups of people like waves. The most obvious are\nin fashion: you notice a few people wearing a certain kind of shirt,\nand then more and more, until half the people around you are wearing\nthe same shirt. You may not care much what you wear, but there are\nintellectual fashions too, and you definitely don't want to participate\nin those. Not just because you want sovereignty over your own\nthoughts, but because unfashionable\nideas are disproportionately likely to lead somewhere interesting.\nThe best place to find undiscovered ideas is where no one else is\nlooking.\n[4]\n___________\nTo go beyond this general advice, we need to look at the internal\nstructure of independent-mindedness — at the individual muscles\nwe need to exercise, as it were. It seems to me that it has three\ncomponents: fastidiousness about truth, resistance to being told\nwhat to think, and curiosity.Fastidiousness about truth means more than just not believing things\nthat are false. It means being careful about degree of belief. For\nmost people, degree of belief rushes unexamined toward the extremes:\nthe unlikely becomes impossible, and the probable becomes certain.\n[5]\nTo the independent-minded, this seems unpardonably sloppy.\nThey're willing to have anything in their heads, from highly\nspeculative hypotheses to (apparent) tautologies, but on subjects\nthey care about, everything has to be labelled with a carefully\nconsidered degree of belief.\n[6]The independent-minded thus have a horror of ideologies, which\nrequire one to accept a whole collection of beliefs at once, and\nto treat them as articles of faith. To an independent-minded person\nthat would seem revolting, just as it would seem to someone fastidious\nabout food to take a bite of a submarine sandwich filled with a\nlarge variety of ingredients of indeterminate age and provenance.Without this fastidiousness about truth, you can't be truly\nindependent-minded. It's not enough just to have resistance to being\ntold what to think. Those kind of people reject conventional ideas\nonly to replace them with the most random conspiracy theories. And\nsince these conspiracy theories have often been manufactured to\ncapture them, they end up being less independent-minded than ordinary\npeople, because they're subject to a much more exacting master than\nmere convention.\n[7]Can you increase your fastidiousness about truth? I would think so.\nIn my experience, merely thinking about something you're fastidious\nabout causes that fastidiousness to grow. If so, this is one of\nthose rare virtues we can have more of merely by wanting it. And\nif it's like other forms of fastidiousness, it should also be\npossible to encourage in children. I certainly got a strong dose\nof it from my father.\n[8]The second component of independent-mindedness, resistance to being\ntold what to think, is the most visible of the three. But even this\nis often misunderstood. The big mistake people make about it is to\nthink of it as a merely negative quality. The language we use\nreinforces that idea. You're unconventional. You don't care\nwhat other people think. But it's not just a kind of immunity. In\nthe most independent-minded people, the desire not to be told what\nto think is a positive force. It's not mere skepticism, but an\nactive delight in ideas that subvert\nthe conventional wisdom, the more counterintuitive the better.Some of the most novel ideas seemed at the time almost like practical\njokes. Think how often your reaction to a novel idea is to laugh.\nI don't think it's because novel ideas are funny per se, but because\nnovelty and humor share a certain kind of surprisingness. But while\nnot identical, the two are close enough that there is a definite\ncorrelation between having a sense of humor and being independent-minded\n— just as there is between being humorless and being conventional-minded.\n[9]I don't think we can significantly increase our resistance to being\ntold what to think. It seems the most innate of the three components\nof independent-mindedness; people who have this quality as adults\nusually showed all too visible signs of it as children. But if we\ncan't increase our resistance to being told what to think, we can\nat least shore it up, by surrounding ourselves with other\nindependent-minded people.The third component of independent-mindedness, curiosity, may be\nthe most interesting. To the extent that we can give a brief answer\nto the question of where novel ideas come from, it's curiosity. That's\nwhat people are usually feeling before having them.In my experience, independent-mindedness and curiosity predict one\nanother perfectly. Everyone I know who's independent-minded is\ndeeply curious, and everyone I know who's conventional-minded isn't.\nExcept, curiously, children. All small children are curious. Perhaps\nthe reason is that even the conventional-minded have to be curious\nin the beginning, in order to learn what the conventions are. Whereas\nthe independent-minded are the gluttons of curiosity, who keep\neating even after they're full.\n[10]The three components of independent-mindedness work in concert:\nfastidiousness about truth and resistance to being told what to\nthink leave space in your brain, and curiosity finds new ideas to\nfill it.Interestingly, the three components can substitute for one another\nin much the same way muscles can. If you're sufficiently fastidious\nabout truth, you don't need to be as resistant to being told what\nto think, because fastidiousness alone will create sufficient gaps\nin your knowledge. And either one can compensate for curiosity,\nbecause if you create enough space in your brain, your discomfort\nat the resulting vacuum will add force to your curiosity. Or curiosity\ncan compensate for them: if you're sufficiently curious, you don't\nneed to clear space in your brain, because the new ideas you discover\nwill push out the conventional ones you acquired by default.Because the components of independent-mindedness are so interchangeable,\nyou can have them to varying degrees and still get the same result.\nSo there is not just a single model of independent-mindedness. Some\nindependent-minded people are openly subversive, and others are\nquietly curious. They all know the secret handshake though.Is there a way to cultivate curiosity? To start with, you want to\navoid situations that suppress it. How much does the work you're\ncurrently doing engage your curiosity? If the answer is \"not much,\"\nmaybe you should change something.The most important active step you can take to cultivate your\ncuriosity is probably to seek out the topics that engage it. Few\nadults are equally curious about everything, and it doesn't seem\nas if you can choose which topics interest you. So it's up to you\nto find them. Or invent them, if\nnecessary.Another way to increase your curiosity is to indulge it, by\ninvestigating things you're interested in. Curiosity is unlike\nmost other appetites in this respect: indulging it tends to increase\nrather than to sate it. Questions lead to more questions.Curiosity seems to be more individual than fastidiousness about\ntruth or resistance to being told what to think. To the degree\npeople have the latter two, they're usually pretty general, whereas\ndifferent people can be curious about very different things. So\nperhaps curiosity is the compass here. Perhaps, if your goal is to\ndiscover novel ideas, your motto should not be \"do what you love\"\nso much as \"do what you're curious about.\"Notes[1]\nOne convenient consequence of the fact that no one identifies\nas conventional-minded is that you can say what you like about\nconventional-minded people without getting in too much trouble.\nWhen I wrote \"The Four Quadrants of\nConformism\" I expected a firestorm of rage from the\naggressively conventional-minded, but in fact it was quite muted.\nThey sensed that there was something about the essay that they\ndisliked intensely, but they had a hard time finding a specific\npassage to pin it on.[2]\nWhen I ask myself what in my life is like high school, the\nanswer is Twitter. It's not just full of conventional-minded people,\nas anything its size will inevitably be, but subject to violent\nstorms of conventional-mindedness that remind me of descriptions\nof Jupiter. But while it probably is a net loss to spend time there,\nit has at least made me think more about the distinction between\nindependent- and conventional-mindedness, which I probably wouldn't\nhave done otherwise.[3]\nThe decrease in independent-mindedness in growing startups is\nstill an open problem, but there may be solutions.Founders can delay the problem by making a conscious effort only\nto hire independent-minded people. Which of course also has the\nancillary benefit that they have better ideas.Another possible solution is to create policies that somehow disrupt\nthe force of conformism, much as control rods slow chain reactions,\nso that the conventional-minded aren't as dangerous. The physical\nseparation of Lockheed's Skunk Works may have had this as a side\nbenefit. Recent examples suggest employee forums like Slack may not\nbe an unmitigated good.The most radical solution would be to grow revenues without growing\nthe company. You think hiring that junior PR person will be cheap,\ncompared to a programmer, but what will be the effect on the average\nlevel of independent-mindedness in your company? (The growth in\nstaff relative to faculty seems to have had a similar effect on\nuniversities.) Perhaps the rule about outsourcing work that's not\nyour \"core competency\" should be augmented by one about outsourcing\nwork done by people who'd ruin your culture as employees.Some investment firms already seem to be able to grow revenues\nwithout growing the number of employees. Automation plus the ever\nincreasing articulation of the \"tech stack\" suggest this may one\nday be possible for product companies.[4]\nThere are intellectual fashions in every field, but their\ninfluence varies. One of the reasons politics, for example, tends\nto be boring is that it's so extremely subject to them. The threshold\nfor having opinions about politics is much lower than the one for having\nopinions about set theory. So while there are some ideas in politics,\nin practice they tend to be swamped by waves of intellectual fashion.[5]\nThe conventional-minded are often fooled by the strength of\ntheir opinions into believing that they're independent-minded. But\nstrong convictions are not a sign of independent-mindedness. Rather\nthe opposite.[6]\nFastidiousness about truth doesn't imply that an independent-minded\nperson won't be dishonest, but that he won't be deluded. It's sort\nof like the definition of a gentleman as someone who is never\nunintentionally rude.[7]\nYou see this especially among political extremists. They think\nthemselves nonconformists, but actually they're niche conformists.\nTheir opinions may be different from the average person's, but they\nare often more influenced by their peers' opinions than the average\nperson's are.[8]\nIf we broaden the concept of fastidiousness about truth so that\nit excludes pandering, bogusness, and pomposity as well as falsehood\nin the strict sense, our model of independent-mindedness can expand\nfurther into the arts.[9]\nThis correlation is far from perfect, though. Gödel and Dirac\ndon't seem to have been very strong in the humor department. But\nsomeone who is both \"neurotypical\" and humorless is very likely to\nbe conventional-minded.[10]\nException: gossip. Almost everyone is curious about gossip.\nThanks to Trevor Blackwell, Paul Buchheit, Patrick Collison, Jessica\nLivingston, Robert Morris, Harj Taggar, and Peter Thiel for reading\ndrafts of this." }, { "path": "data/PaulGrahamEssays/todo.txt", "content": "April 2012A palliative care nurse called Bronnie Ware made a list of the\nbiggest regrets\nof the dying. Her list seems plausible. I could see\nmyself — can see myself — making at least 4 of these\n5 mistakes.If you had to compress them into a single piece of advice, it might\nbe: don't be a cog. The 5 regrets paint a portrait of post-industrial\nman, who shrinks himself into a shape that fits his circumstances,\nthen turns dutifully till he stops.The alarming thing is, the mistakes that produce these regrets are\nall errors of omission. You forget your dreams, ignore your family,\nsuppress your feelings, neglect your friends, and forget to be\nhappy. Errors of omission are a particularly dangerous type of\nmistake, because you make them by default.I would like to avoid making these mistakes. But how do you avoid\nmistakes you make by default? Ideally you transform your life so\nit has other defaults. But it may not be possible to do that\ncompletely. As long as these mistakes happen by default, you probably\nhave to be reminded not to make them. So I inverted the 5 regrets,\nyielding a list of 5 commands\n\n Don't ignore your dreams; don't work too much; say what you\n think; cultivate friendships; be happy.\n\nwhich I then put at the top of the file I use as a todo list." }, { "path": "data/PaulGrahamEssays/top.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nJuly 2010I realized recently that what one thinks about in the shower in the\nmorning is more important than I'd thought. I knew it was a good\ntime to have ideas. Now I'd go further: now I'd say it's hard to\ndo a really good job on anything you don't think about in the shower.Everyone who's worked on difficult problems is probably familiar\nwith the phenomenon of working hard to figure something out, failing,\nand then suddenly seeing the answer a bit later while doing something\nelse. There's a kind of thinking you do without trying to. I'm\nincreasingly convinced this type of thinking is not merely helpful\nin solving hard problems, but necessary. The tricky part is, you\ncan only control it indirectly.\n[1]I think most people have one top idea in their mind at any given\ntime. That's the idea their thoughts will drift toward when they're\nallowed to drift freely. And this idea will thus tend to get all\nthe benefit of that type of thinking, while others are starved of\nit. Which means it's a disaster to let the wrong idea become the\ntop one in your mind.What made this clear to me was having an idea I didn't want as the\ntop one in my mind for two long stretches.I'd noticed startups got way less done when they started raising\nmoney, but it was not till we ourselves raised money that I understood\nwhy. The problem is not the actual time it takes to meet with\ninvestors. The problem is that once you start raising money, raising\nmoney becomes the top idea in your mind. That becomes what you\nthink about when you take a shower in the morning. And that means\nother questions aren't.I'd hated raising money when I was running Viaweb, but I'd forgotten\nwhy I hated it so much. When we raised money for Y Combinator, I\nremembered. Money matters are particularly likely to become the\ntop idea in your mind. The reason is that they have to be. It's\nhard to get money. It's not the sort of thing that happens by\ndefault. It's not going to happen unless you let it become the\nthing you think about in the shower. And then you'll make little\nprogress on anything else you'd rather be working on.\n[2](I hear similar complaints from friends who are professors. Professors\nnowadays seem to have become professional fundraisers who do a\nlittle research on the side. It may be time to fix that.)The reason this struck me so forcibly is that for most of the\npreceding 10 years I'd been able to think about what I wanted. So\nthe contrast when I couldn't was sharp. But I don't think this\nproblem is unique to me, because just about every startup I've seen\ngrinds to a halt when they start raising money — or talking\nto acquirers.You can't directly control where your thoughts drift. If you're\ncontrolling them, they're not drifting. But you can control them\nindirectly, by controlling what situations you let yourself get\ninto. That has been the lesson for me: be careful what you let\nbecome critical to you. Try to get yourself into situations where\nthe most urgent problems are ones you want to think about.You don't have complete control, of course. An emergency could\npush other thoughts out of your head. But barring emergencies you\nhave a good deal of indirect control over what becomes the top idea\nin your mind.I've found there are two types of thoughts especially worth\navoiding — thoughts like the Nile Perch in the way they push\nout more interesting ideas. One I've already mentioned: thoughts\nabout money. Getting money is almost by definition an attention\nsink.\nThe other is disputes. These too are engaging in the\nwrong way: they have the same velcro-like shape as genuinely\ninteresting ideas, but without the substance. So avoid disputes\nif you want to get real work done.\n[3]Even Newton fell into this trap. After publishing his theory of\ncolors in 1672 he found himself distracted by disputes for years,\nfinally concluding that the only solution was to stop publishing:\n\n I see I have made myself a slave to Philosophy, but if I get free\n of Mr Linus's business I will resolutely bid adew to it eternally,\n excepting what I do for my privat satisfaction or leave to come\n out after me. For I see a man must either resolve to put out\n nothing new or become a slave to defend it.\n[4]\n\nLinus and his students at Liege were among the more tenacious\ncritics. Newton's biographer Westfall seems to feel he was\noverreacting:\n\n Recall that at the time he wrote, Newton's \"slavery\" consisted\n of five replies to Liege, totalling fourteen printed pages, over\n the course of a year.\n\nI'm more sympathetic to Newton. The problem was not the 14 pages,\nbut the pain of having this stupid controversy constantly reintroduced\nas the top idea in a mind that wanted so eagerly to think about\nother things.Turning the other cheek turns out to have selfish advantages.\nSomeone who does you an injury hurts you twice: first by the injury\nitself, and second by taking up your time afterward thinking about\nit. If you learn to ignore injuries you can at least avoid the\nsecond half. I've found I can to some extent avoid thinking about\nnasty things people have done to me by telling myself: this doesn't\ndeserve space in my head. I'm always delighted to find I've forgotten\nthe details of disputes, because that means I hadn't been thinking\nabout them. My wife thinks I'm more forgiving than she is, but my\nmotives are purely selfish.I suspect a lot of people aren't sure what's the top idea in their\nmind at any given time. I'm often mistaken about it. I tend to\nthink it's the idea I'd want to be the top one, rather than the one\nthat is. But it's easy to figure this out: just take a shower.\nWhat topic do your thoughts keep returning to? If it's not what\nyou want to be thinking about, you may want to change something.Notes[1]\nNo doubt there are already names for this type of thinking, but\nI call it \"ambient thought.\"[2]\nThis was made particularly clear in our case, because neither\nof the funds we raised was difficult, and yet in both cases the\nprocess dragged on for months. Moving large amounts of money around\nis never something people treat casually. The attention required\nincreases with the amount—maybe not linearly, but definitely\nmonotonically.[3]\nCorollary: Avoid becoming an administrator, or your job will\nconsist of dealing with money and disputes.[4]\nLetter to Oldenburg, quoted in Westfall, Richard, Life of\nIsaac Newton, p. 107.Thanks to Sam Altman, Patrick Collison, Jessica Livingston,\nand Robert Morris for reading drafts of this." }, { "path": "data/PaulGrahamEssays/trolls.txt", "content": "February 2008A user on Hacker News recently posted a\ncomment\nthat set me thinking:\n\n Something about hacker culture that never really set well with\n me was this — the nastiness. ... I just don't understand why people\n troll like they do.\n\nI've thought a lot over the last couple years about the problem of\ntrolls. It's an old one, as old as forums, but\nwe're still just learning what the causes are and how to address\nthem.There are two senses of the word \"troll.\" In the original sense\nit meant someone, usually an outsider, who deliberately stirred up\nfights in a forum by saying controversial things.\n[1]\nFor example,\nsomeone who didn't use a certain programming language might go to\na forum for users of that language and make disparaging remarks\nabout it, then sit back and watch as people rose to the bait. This\nsort of trolling was in the nature of a practical joke, like letting\na bat loose in a room full of people.The definition then spread to people who behaved like assholes in\nforums, whether intentionally or not. Now when people talk about\ntrolls they usually mean this broader sense of the word. Though\nin a sense this is historically inaccurate, it is in other ways\nmore accurate, because when someone is being an asshole it's usually\nuncertain even in their own mind how much is deliberate.\nThat is arguably one of the defining qualities of an asshole.I think trolling in the broader sense has four causes. The most\nimportant is distance. People will say things in anonymous forums\nthat they'd never dare say to someone's face, just as they'll do\nthings in cars that they'd never do as pedestrians — like tailgate\npeople, or honk at them, or cut them off.Trolling tends to be particularly bad in forums related to computers,\nand I think that's due to the kind of people you find there. Most\nof them (myself included) are more comfortable dealing with abstract\nideas than with people. Hackers can be abrupt even in person. Put\nthem on an anonymous forum, and the problem gets worse.The third cause of trolling is incompetence. If you disagree with\nsomething, it's easier to say \"you suck\" than to figure out and\nexplain exactly what you disagree with. You're also safe that way\nfrom refutation. In this respect trolling is a lot like graffiti.\nGraffiti happens at the intersection of ambition and incompetence:\npeople want to make their mark on the world, but have no other way\nto do it than literally making a mark on the world.\n[2]The final contributing factor is the culture of the forum. Trolls\nare like children (many are children) in that they're capable of\na wide range of behavior depending on what they think will be\ntolerated. In a place where rudeness isn't tolerated, most can be\npolite. But vice versa as well.There's a sort of Gresham's Law of trolls: trolls are willing to\nuse a forum with a lot of thoughtful people in it, but thoughtful\npeople aren't willing to use a forum with a lot of trolls in it.\nWhich means that once trolling takes hold, it tends to become the\ndominant culture. That had already happened to Slashdot and Digg by\nthe time I paid attention to comment threads there, but I watched\nit happen to Reddit.News.YC is, among other things, an experiment to see if this fate\ncan be avoided. The sites's guidelines\nexplicitly ask people not to say things they wouldn't say face to\nface. If someone starts being rude, other users will step in and\ntell them to stop. And when people seem to be deliberately trolling,\nwe ban them ruthlessly.Technical tweaks may also help. On Reddit, votes on your comments\ndon't affect your karma score, but they do on News.YC. And it does\nseem to influence people when they can see their reputation in the\neyes of their peers drain away after making an asshole remark.\nOften users have second thoughts and delete such comments.One might worry this would prevent people from expressing controversial\nideas, but empirically that doesn't seem to be what happens. When\npeople say something substantial that gets modded down, they\nstubbornly leave it up. What people delete are wisecracks, because\nthey have less invested in them.So far the experiment seems to be working. The level of conversation\non News.YC is as high as on any forum I've seen. But we still only\nhave about 8,000 uniques a day. The conversations on Reddit were\ngood when it was that small. The challenge is whether we can keep\nthings this way.I'm optimistic we will. We're not depending just on technical\ntricks. The core users of News.YC are mostly refugees from other\nsites that were overrun by trolls. They feel about trolls roughly\nthe way refugees from Cuba or Eastern Europe feel about dictatorships.\nSo there are a lot of people working to keep this from happening\nagain.\nNotes[1]\nI mean forum in the general sense of a place to exchange views.\nThe original Internet forums were not web sites but Usenet newsgroups.[2]\nI'm talking here about everyday tagging. Some graffiti is\nquite impressive (anything becomes art if you do it well enough)\nbut the median tag is just visual spam." }, { "path": "data/PaulGrahamEssays/twitter.txt", "content": "April 2009Om Malik is the most recent of many people\nto ask why Twitter is such a big deal.The reason is that it's a new messaging \nprotocol, where you don't specify the recipients.\nNew protocols are rare. Or more precisely, new\nprotocols that take off are.\nThere are only a handful of commonly used ones: TCP/IP \n(the Internet), SMTP (email), HTTP (the web), and so on. So any\nnew protocol is a big deal. But Twitter is a protocol owned\nby a private company. That's even rarer.Curiously, the fact that the founders of Twitter \nhave been slow to monetize it may in the long run\nprove to be an advantage. Because they haven't tried\nto control it too much, Twitter feels to everyone like\nprevious protocols. One forgets it's owned by a\nprivate company. That must have made it easier for\nTwitter to spread." }, { "path": "data/PaulGrahamEssays/unions.txt", "content": "May 2007People who worry about the increasing gap between rich and poor\ngenerally look back on the mid twentieth century as a golden age.\nIn those days we had a large number of high-paying union manufacturing\njobs that boosted the median income. I wouldn't quite call the\nhigh-paying union job a myth, but I think people who dwell on it\nare reading too much into it.Oddly enough, it was working with startups that made me realize\nwhere the high-paying union job came from. In a rapidly growing\nmarket, you don't worry too much about efficiency. It's more\nimportant to grow fast. If there's some mundane problem getting\nin your way, and there's a simple solution that's somewhat expensive,\njust take it and get on with more important things. EBay didn't\nwin by paying less for servers than their competitors.Difficult though it may be to imagine now, manufacturing was a\ngrowth industry in the mid twentieth century. This was an era when\nsmall firms making everything from cars to candy were getting\nconsolidated into a new kind of corporation with national reach and\nhuge economies of scale. You had to grow fast or die. Workers\nwere for these companies what servers are for an Internet startup.\nA reliable supply was more important than low cost.If you looked in the head of a 1950s auto executive, the attitude\nmust have been: sure, give 'em whatever they ask for, so long as\nthe new model isn't delayed.In other words, those workers were not paid what their work was\nworth. Circumstances being what they were, companies would have\nbeen stupid to insist on paying them so little.If you want a less controversial example of this phenomenon, ask\nanyone who worked as a consultant building web sites during the\nInternet Bubble. In the late nineties you could get paid huge sums\nof money for building the most trivial things. And yet does anyone\nwho was there have any expectation those days will ever return? I\ndoubt it. Surely everyone realizes that was just a temporary\naberration.The era of labor unions seems to have been the same kind of aberration, \njust spread\nover a longer period, and mixed together with a lot of ideology\nthat prevents people from viewing it with as cold an eye as they\nwould something like consulting during the Bubble.Basically, unions were just Razorfish.People who think the labor movement was the creation of heroic union\norganizers have a problem to explain: why are unions shrinking now?\nThe best they can do is fall back on the default explanation of\npeople living in fallen civilizations. Our ancestors were giants.\nThe workers of the early twentieth century must have had a moral\ncourage that's lacking today.In fact there's a simpler explanation. The early twentieth century\nwas just a fast-growing startup overpaying for infrastructure. And\nwe in the present are not a fallen people, who have abandoned\nwhatever mysterious high-minded principles produced the high-paying\nunion job. We simply live in a time when the fast-growing companies\noverspend on different things." }, { "path": "data/PaulGrahamEssays/usa.txt", "content": "November 2004(This is a new essay for the Japanese edition of \nHackers \n& Painters.\nIt tries to explain why Americans make some things well \nand others badly.)A few years ago an Italian friend of mine travelled by train from\nBoston to Providence. She had only been in America for a\ncouple weeks and hadn't seen much of the country yet. She arrived\nlooking astonished. \"It's so ugly!\"People from other rich countries can scarcely imagine\nthe squalor of the man-made bits of America. In travel books\nthey show you mostly natural environments: the Grand Canyon,\nwhitewater rafting, horses in a field. If you see\npictures with man-made things in them, it will be either a\nview of the New York skyline shot from a discreet distance,\nor a carefully cropped image of a seacoast town in Maine.How can it be, visitors must wonder. How can the richest country\nin the world look like this?Oddly enough, it may not be a coincidence. Americans are good\nat some things and bad at others. We're good at making\nmovies and software, and bad at making cars and cities.\nAnd I think we may be good at what we're good at for the same\nreason we're bad at what we're bad at. We're impatient.\nIn America, if you want to do something, you don't worry that\nit might come out badly, or upset delicate social balances, or\nthat people might think you're getting above yourself. If you\nwant to do something, as Nike says, just do it.This works well in some fields and badly in others. I suspect\nit works in movies and software because they're both messy \nprocesses. \"Systematic\"\nis the last word I'd use to describe the way \ngood programmers write software.\nCode is not something they assemble painstakingly after\ncareful planning, like the pyramids. It's something they\nplunge into, working fast and constantly changing their minds,\nlike a charcoal sketch.In software, paradoxical\nas it sounds, good craftsmanship means working fast.\nIf you work slowly and meticulously,\nyou merely end up with a very fine implementation of your initial,\nmistaken idea.\nWorking slowly and meticulously is\npremature optimization. Better to get a\nprototype done fast, and see what new ideas\nit gives you.It sounds like making movies works a lot like making software.\nEvery movie is a Frankenstein, full of imperfections\nand usually quite different from what was originally envisioned. \nBut interesting, and finished fairly quickly. I think we get away with this in movies and software\nbecause they're both malleable mediums. Boldness pays.\n\nAnd if at the last minute two parts don't quite \nfit, you can figure out some hack that will at least conceal\nthe problem.Not so with cars, or cities. They are all too physical.\nIf the car business worked like software or movies, you'd\nsurpass your competitors by making a car that weighed only\nfifty pounds, or folded up to the size of a motorcycle when \nyou wanted to park it. But with physical products there are\nmore constraints. You don't win by dramatic innovations\nso much as by good taste and attention to detail.The trouble is, the very word \"taste\"\nsounds slightly ridiculous to American ears.\nIt seems pretentious, or frivolous, or even effeminate.\nBlue staters think it's \"subjective,\" and red staters \nthink it's for sissies. So anyone in America\nwho really cares about design will be sailing upwind.Twenty years ago we used to hear that the problem with\nthe US car industry was the workers.\nWe don't hear that any more now that Japanese companies\nare building cars in the US. The problem with\nAmerican cars is bad design. You can see that just by\nlooking at them.All that extra sheet metal on the AMC Matador wasn't\nadded by the workers. The problem\nwith this car, as with American cars today, is that it was\ndesigned by marketing people instead of designers.Why do the Japanese make better cars than us? Some say it's\nbecause their culture encourages cooperation. That may come\ninto it. But in this case it seems more to the point that\ntheir culture prizes design and craftsmanship.For centuries the Japanese have made finer things than we\nhave in the West. When you look at swords they\nmade in 1200, you just can't believe the date on the label\nis right.\nPresumably their cars fit together more \nprecisely than ours for the same reason their joinery always has.\nThey're obsessed with making things well.Not us.\nWhen we make something in America, our aim is just to get the \njob done. Once we reach that point, we take one of two routes.\nWe can stop there, and have something crude but\nserviceable, like a Vise-grip. Or we can improve it,\nwhich usually means encrusting it with gratuitous ornament.\nWhen we want to make a car \"better,\"\nwe stick tail fins on it, or make it \nlonger, or make the \nwindows smaller, depending on the current fashion.Ditto for houses. In America you can have either a flimsy box banged\ntogether out of two by fours and drywall, or a McMansion-- a\nflimsy box banged together out of two by fours and drywall,\nbut larger, more dramatic-looking, and full of expensive fittings.\nRich people don't get better design or craftsmanship;\nthey just get a larger, more conspicuous version of the\nstandard house.We don't especially prize design or craftsmanship here. What\nwe like is speed, and we're willing to do something in an ugly\nway to get it done fast. In some\nfields, like software or movies, this is a net win. \nBut it's not just that software and movies are malleable mediums.\nIn those businesses, the designers (though they're\nnot generally called that) have more power. \nSoftware companies, at least successful ones, tend to be run\nby programmers. And in the film industry, though producers\nmay second-guess directors, the director controls most of\nwhat appears on the screen.\nAnd so American software and movies, and Japanese cars, all\nhave this in common: the people in charge care about\ndesign-- the former because the designers are in charge, and the latter\nbecause the whole culture cares about design.I think most Japanese executives would be horrified at\nthe idea of making a bad car. Whereas American executives,\nin their hearts, still believe the most important thing about\na car is the image it projects.\nMake a good car? What's \"good?\" It's so subjective.\nIf you want to know how to design a car, ask a focus group.Instead of relying on their own internal design compass\n(like Henry Ford did),\nAmerican car companies try to make what marketing people\nthink consumers want. But it isn't working. American cars continue\nto lose market share. And the reason is that the customer\ndoesn't want what he thinks he wants.Letting focus groups design your cars for you \nonly wins in the short term. In the long term, it pays\nto bet on good design. The focus group may say they want the\nmeretricious feature du jour, but what they want even more is\nto imitate sophisticated buyers, and they, though a\nsmall minority, really do care about good design.\nEventually the\npimps and drug dealers notice that the doctors and lawyers\nhave switched from Cadillac to Lexus, and do the same.Apple is an interesting counterexample to the general\nAmerican trend. If you want to buy a nice CD player, you'll\nprobably buy a Japanese one. But if you want to buy an\nMP3 player, you'll probably buy an iPod. What happened?\nWhy doesn't Sony dominate MP3 players? Because Apple is\nin the consumer electronics business now, and unlike\nother American companies, they're obsessed with good design. \nOr more precisely, their CEO is.I just got an iPod, and it's not just nice. It's \nsurprisingly nice. For it to surprise me, it must be\nsatisfying expectations I didn't know I had. No focus\ngroup is going to discover those. Only a great \ndesigner can.Cars aren't the worst thing we make in America.\nWhere the just-do-it model fails most dramatically is in our cities-- or\nrather, exurbs.\nIf real estate developers operated on a large enough scale, if\nthey built whole towns, market forces would compel\nthem to build towns that didn't suck. But they only build a\ncouple office buildings or suburban streets at a time, and the\nresult is so depressing that the inhabitants consider it a great\ntreat to fly to Europe and spend a couple weeks living what\nis, for people there, just everyday life. [1]But the just-do-it model does have advantages. It seems the clear\nwinner for generating wealth and technical innovations\n(which are practically the same thing). I think speed is the reason.\nIt's hard to create wealth by making a commodity. The\nreal value is in things that are new, and if you want to\nbe the first to make something, it helps to work fast.\nFor better or worse, the just-do-it model is fast,\nwhether you're Dan Bricklin writing the prototype of VisiCalc in\na weekend, or a real estate developer\nbuilding a block of shoddy condos in a month.If I had to choose between the just-do-it model and the\ncareful model, I'd probably choose just-do-it.\nBut do we have to choose? Could we have it both ways?\nCould Americans have nice\nplaces to live without undermining the impatient, individualistic spirit\nthat makes us good at software? Could other countries\nintroduce more individualism into their technology companies\nand research labs without having it metastasize as strip malls?\nI'm optimistic. It's harder to\nsay about other countries, but in the US, at least, I think \nwe can have both.Apple is an encouraging example. They've managed to preserve\nenough of the impatient, hackerly spirit you need to write\nsoftware. And yet when\nyou pick up a new Apple laptop, well, it doesn't\nseem American. It's too perfect. It seems as if it\nmust have been made by a Swedish or a Japanese company.In many technologies, version 2 has higher resolution. Why\nnot in design generally? I think we'll gradually see\nnational characters superseded\nby occupational characters: hackers in Japan will be allowed\nto behave with a willfulness \nthat would now seem unJapanese,\nand products in America will be designed with an\ninsistence on taste that would now seem unAmerican.\nPerhaps the most successful countries, in the future, will be\nthose most willing to ignore what are now considered\nnational characters, and do each kind of work in the way\nthat works best. Race you.Notes[1] Japanese cities are ugly too, but for different reasons.\nJapan is prone to earthquakes, so buildings are traditionally\nseen as temporary; there is no grand tradition of city planning\nlike the one Europeans inherited from Rome. The other cause is\nthe notoriously corrupt relationship between the government\nand construction companies.Thanks to Trevor Blackwell, Barry Eisler, Sarah Harlin,\nShiro Kawai, Jessica Livingston, Jackie McDonough, Robert Morris, \nand Eric Raymond\nfor reading drafts of this." }, { "path": "data/PaulGrahamEssays/useful.txt", "content": "February 2020What should an essay be? Many people would say persuasive. That's\nwhat a lot of us were taught essays should be. But I think we can\naim for something more ambitious: that an essay should be useful.To start with, that means it should be correct. But it's not enough\nmerely to be correct. It's easy to make a statement correct by\nmaking it vague. That's a common flaw in academic writing, for\nexample. If you know nothing at all about an issue, you can't go\nwrong by saying that the issue is a complex one, that there are\nmany factors to be considered, that it's a mistake to take too\nsimplistic a view of it, and so on.Though no doubt correct, such statements tell the reader nothing.\nUseful writing makes claims that are as strong as they can be made\nwithout becoming false.For example, it's more useful to say that Pike's Peak is near the\nmiddle of Colorado than merely somewhere in Colorado. But if I say\nit's in the exact middle of Colorado, I've now gone too far, because\nit's a bit east of the middle.Precision and correctness are like opposing forces. It's easy to\nsatisfy one if you ignore the other. The converse of vaporous\nacademic writing is the bold, but false, rhetoric of demagogues.\nUseful writing is bold, but true.It's also two other things: it tells people something important,\nand that at least some of them didn't already know.Telling people something they didn't know doesn't always mean\nsurprising them. Sometimes it means telling them something they\nknew unconsciously but had never put into words. In fact those may\nbe the more valuable insights, because they tend to be more\nfundamental.Let's put them all together. Useful writing tells people something\ntrue and important that they didn't already know, and tells them\nas unequivocally as possible.Notice these are all a matter of degree. For example, you can't\nexpect an idea to be novel to everyone. Any insight that you have\nwill probably have already been had by at least one of the world's\n7 billion people. But it's sufficient if an idea is novel to a lot\nof readers.Ditto for correctness, importance, and strength. In effect the four\ncomponents are like numbers you can multiply together to get a score\nfor usefulness. Which I realize is almost awkwardly reductive, but\nnonetheless true._____\nHow can you ensure that the things you say are true and novel and\nimportant? Believe it or not, there is a trick for doing this. I\nlearned it from my friend Robert Morris, who has a horror of saying\nanything dumb. His trick is not to say anything unless he's sure\nit's worth hearing. This makes it hard to get opinions out of him,\nbut when you do, they're usually right.Translated into essay writing, what this means is that if you write\na bad sentence, you don't publish it. You delete it and try again.\nOften you abandon whole branches of four or five paragraphs. Sometimes\na whole essay.You can't ensure that every idea you have is good, but you can\nensure that every one you publish is, by simply not publishing the\nones that aren't.In the sciences, this is called publication bias, and is considered\nbad. When some hypothesis you're exploring gets inconclusive results,\nyou're supposed to tell people about that too. But with essay\nwriting, publication bias is the way to go.My strategy is loose, then tight. I write the first draft of an\nessay fast, trying out all kinds of ideas. Then I spend days rewriting\nit very carefully.I've never tried to count how many times I proofread essays, but\nI'm sure there are sentences I've read 100 times before publishing\nthem. When I proofread an essay, there are usually passages that\nstick out in an annoying way, sometimes because they're clumsily\nwritten, and sometimes because I'm not sure they're true. The\nannoyance starts out unconscious, but after the tenth reading or\nso I'm saying \"Ugh, that part\" each time I hit it. They become like\nbriars that catch your sleeve as you walk past. Usually I won't\npublish an essay till they're all gone — till I can read through\nthe whole thing without the feeling of anything catching.I'll sometimes let through a sentence that seems clumsy, if I can't\nthink of a way to rephrase it, but I will never knowingly let through\none that doesn't seem correct. You never have to. If a sentence\ndoesn't seem right, all you have to do is ask why it doesn't, and\nyou've usually got the replacement right there in your head.This is where essayists have an advantage over journalists. You\ndon't have a deadline. You can work for as long on an essay as you\nneed to get it right. You don't have to publish the essay at all,\nif you can't get it right. Mistakes seem to lose courage in the\nface of an enemy with unlimited resources. Or that's what it feels\nlike. What's really going on is that you have different expectations\nfor yourself. You're like a parent saying to a child \"we can sit\nhere all night till you eat your vegetables.\" Except you're the\nchild too.I'm not saying no mistake gets through. For example, I added condition\n(c) in \"A Way to Detect Bias\" \nafter readers pointed out that I'd\nomitted it. But in practice you can catch nearly all of them.There's a trick for getting importance too. It's like the trick I\nsuggest to young founders for getting startup ideas: to make something\nyou yourself want. You can use yourself as a proxy for the reader.\nThe reader is not completely unlike you, so if you write about\ntopics that seem important to you, they'll probably seem important\nto a significant number of readers as well.Importance has two factors. It's the number of people something\nmatters to, times how much it matters to them. Which means of course\nthat it's not a rectangle, but a sort of ragged comb, like a Riemann\nsum.The way to get novelty is to write about topics you've thought about\na lot. Then you can use yourself as a proxy for the reader in this\ndepartment too. Anything you notice that surprises you, who've\nthought about the topic a lot, will probably also surprise a\nsignificant number of readers. And here, as with correctness and\nimportance, you can use the Morris technique to ensure that you\nwill. If you don't learn anything from writing an essay, don't\npublish it.You need humility to measure novelty, because acknowledging the\nnovelty of an idea means acknowledging your previous ignorance of\nit. Confidence and humility are often seen as opposites, but in\nthis case, as in many others, confidence helps you to be humble.\nIf you know you're an expert on some topic, you can freely admit\nwhen you learn something you didn't know, because you can be confident\nthat most other people wouldn't know it either.The fourth component of useful writing, strength, comes from two\nthings: thinking well, and the skillful use of qualification. These\ntwo counterbalance each other, like the accelerator and clutch in\na car with a manual transmission. As you try to refine the expression\nof an idea, you adjust the qualification accordingly. Something\nyou're sure of, you can state baldly with no qualification at all,\nas I did the four components of useful writing. Whereas points that\nseem dubious have to be held at arm's length with perhapses.As you refine an idea, you're pushing in the direction of less\nqualification. But you can rarely get it down to zero. Sometimes\nyou don't even want to, if it's a side point and a fully refined\nversion would be too long.Some say that qualifications weaken writing. For example, that you\nshould never begin a sentence in an essay with \"I think,\" because\nif you're saying it, then of course you think it. And it's true\nthat \"I think x\" is a weaker statement than simply \"x.\" Which is\nexactly why you need \"I think.\" You need it to express your degree\nof certainty.But qualifications are not scalars. They're not just experimental\nerror. There must be 50 things they can express: how broadly something\napplies, how you know it, how happy you are it's so, even how it\ncould be falsified. I'm not going to try to explore the structure\nof qualification here. It's probably more complex than the whole\ntopic of writing usefully. Instead I'll just give you a practical\ntip: Don't underestimate qualification. It's an important skill in\nits own right, not just a sort of tax you have to pay in order to\navoid saying things that are false. So learn and use its full range.\nIt may not be fully half of having good ideas, but it's part of\nhaving them.There's one other quality I aim for in essays: to say things as\nsimply as possible. But I don't think this is a component of\nusefulness. It's more a matter of consideration for the reader. And\nit's a practical aid in getting things right; a mistake is more\nobvious when expressed in simple language. But I'll admit that the\nmain reason I write simply is not for the reader's sake or because\nit helps get things right, but because it bothers me to use more\nor fancier words than I need to. It seems inelegant, like a program\nthat's too long.I realize florid writing works for some people. But unless you're\nsure you're one of them, the best advice is to write as simply as\nyou can._____\nI believe the formula I've given you, importance + novelty +\ncorrectness + strength, is the recipe for a good essay. But I should\nwarn you that it's also a recipe for making people mad.The root of the problem is novelty. When you tell people something\nthey didn't know, they don't always thank you for it. Sometimes the\nreason people don't know something is because they don't want to\nknow it. Usually because it contradicts some cherished belief. And\nindeed, if you're looking for novel ideas, popular but mistaken\nbeliefs are a good place to find them. Every popular mistaken belief\ncreates a dead zone of ideas around \nit that are relatively unexplored because they contradict it.The strength component just makes things worse. If there's anything\nthat annoys people more than having their cherished assumptions\ncontradicted, it's having them flatly contradicted.Plus if you've used the Morris technique, your writing will seem\nquite confident. Perhaps offensively confident, to people who\ndisagree with you. The reason you'll seem confident is that you are\nconfident: you've cheated, by only publishing the things you're\nsure of. It will seem to people who try to disagree with you that\nyou never admit you're wrong. In fact you constantly admit you're\nwrong. You just do it before publishing instead of after.And if your writing is as simple as possible, that just makes things\nworse. Brevity is the diction of command. If you watch someone\ndelivering unwelcome news from a position of inferiority, you'll\nnotice they tend to use lots of words, to soften the blow. Whereas\nto be short with someone is more or less to be rude to them.It can sometimes work to deliberately phrase statements more weakly\nthan you mean. To put \"perhaps\" in front of something you're actually\nquite sure of. But you'll notice that when writers do this, they\nusually do it with a wink.I don't like to do this too much. It's cheesy to adopt an ironic\ntone for a whole essay. I think we just have to face the fact that\nelegance and curtness are two names for the same thing.You might think that if you work sufficiently hard to ensure that\nan essay is correct, it will be invulnerable to attack. That's sort\nof true. It will be invulnerable to valid attacks. But in practice\nthat's little consolation.In fact, the strength component of useful writing will make you\nparticularly vulnerable to misrepresentation. If you've stated an\nidea as strongly as you could without making it false, all anyone\nhas to do is to exaggerate slightly what you said, and now it is\nfalse.Much of the time they're not even doing it deliberately. One of the\nmost surprising things you'll discover, if you start writing essays,\nis that people who disagree with you rarely disagree with what\nyou've actually written. Instead they make up something you said\nand disagree with that.For what it's worth, the countermove is to ask someone who does\nthis to quote a specific sentence or passage you wrote that they\nbelieve is false, and explain why. I say \"for what it's worth\"\nbecause they never do. So although it might seem that this could\nget a broken discussion back on track, the truth is that it was\nnever on track in the first place.Should you explicitly forestall likely misinterpretations? Yes, if\nthey're misinterpretations a reasonably smart and well-intentioned\nperson might make. In fact it's sometimes better to say something\nslightly misleading and then add the correction than to try to get\nan idea right in one shot. That can be more efficient, and can also\nmodel the way such an idea would be discovered.But I don't think you should explicitly forestall intentional\nmisinterpretations in the body of an essay. An essay is a place to\nmeet honest readers. You don't want to spoil your house by putting\nbars on the windows to protect against dishonest ones. The place\nto protect against intentional misinterpretations is in end-notes.\nBut don't think you can predict them all. People are as ingenious\nat misrepresenting you when you say something they don't want to\nhear as they are at coming up with rationalizations for things they\nwant to do but know they shouldn't. I suspect it's the same skill._____\nAs with most other things, the way to get better at writing essays\nis to practice. But how do you start? Now that we've examined the\nstructure of useful writing, we can rephrase that question more\nprecisely. Which constraint do you relax initially? The answer is,\nthe first component of importance: the number of people who care\nabout what you write.If you narrow the topic sufficiently, you can probably find something\nyou're an expert on. Write about that to start with. If you only\nhave ten readers who care, that's fine. You're helping them, and\nyou're writing. Later you can expand the breadth of topics you write\nabout.The other constraint you can relax is a little surprising: publication.\nWriting essays doesn't have to mean publishing them. That may seem\nstrange now that the trend is to publish every random thought, but\nit worked for me. I wrote what amounted to essays in notebooks for\nabout 15 years. I never published any of them and never expected\nto. I wrote them as a way of figuring things out. But when the web\ncame along I'd had a lot of practice.Incidentally, \nSteve \nWozniak did the same thing. In high school he\ndesigned computers on paper for fun. He couldn't build them because\nhe couldn't afford the components. But when Intel launched 4K DRAMs\nin 1975, he was ready._____\nHow many essays are there left to write though? The answer to that\nquestion is probably the most exciting thing I've learned about\nessay writing. Nearly all of them are left to write.Although the essay \nis an old form, it hasn't been assiduously\ncultivated. In the print era, publication was expensive, and there\nwasn't enough demand for essays to publish that many. You could\npublish essays if you were already well known for writing something\nelse, like novels. Or you could write book reviews that you took\nover to express your own ideas. But there was not really a direct\npath to becoming an essayist. Which meant few essays got written,\nand those that did tended to be about a narrow range of subjects.Now, thanks to the internet, there's a path. Anyone can publish\nessays online. You start in obscurity, perhaps, but at least you\ncan start. You don't need anyone's permission.It sometimes happens that an area of knowledge sits quietly for\nyears, till some change makes it explode. Cryptography did this to\nnumber theory. The internet is doing it to the essay.The exciting thing is not that there's a lot left to write, but\nthat there's a lot left to discover. There's a certain kind of idea\nthat's best discovered by writing essays. If most essays are still\nunwritten, most such ideas are still undiscovered.Notes[1] Put railings on the balconies, but don't put bars on the windows.[2] Even now I sometimes write essays that are not meant for\npublication. I wrote several to figure out what Y Combinator should\ndo, and they were really helpful.Thanks to Trevor Blackwell, Daniel Gackle, Jessica Livingston, and\nRobert Morris for reading drafts of this." }, { "path": "data/PaulGrahamEssays/users.txt", "content": "September 2022I recently told applicants to Y Combinator that the best advice I\ncould give for getting in, per word, was \n\n Explain what you've learned from users.\n\nThat tests a lot of things: whether you're paying attention to\nusers, how well you understand them, and even how much they need\nwhat you're making.Afterward I asked myself the same question. What have I learned\nfrom YC's users, the startups we've funded?The first thing that came to mind was that most startups have the\nsame problems. No two have exactly the same problems, but it's\nsurprising how much the problems remain the same, regardless of\nwhat they're making. Once you've advised 100 startups all doing\ndifferent things, you rarely encounter problems you haven't seen\nbefore.This fact is one of the things that makes YC work. But I didn't\nknow it when we started YC. I only had a few data points: our own\nstartup, and those started by friends. It was a surprise to me how\noften the same problems recur in different forms. Many later stage\ninvestors might never realize this, because later stage investors\nmight not advise 100 startups in their whole career, but a YC partner\nwill get this much experience in the first year or two.That's one advantage of funding large numbers of early stage companies\nrather than smaller numbers of later-stage ones. You get a lot of\ndata. Not just because you're looking at more companies, but also\nbecause more goes wrong.But knowing (nearly) all the problems startups can encounter doesn't\nmean that advising them can be automated, or reduced to a formula.\nThere's no substitute for individual office hours with a YC partner.\nEach startup is unique, which means they have to be advised\nby specific partners who know them well.\n[1]We learned that the hard way, in the notorious \"batch that broke\nYC\" in the summer of 2012. Up till that point we treated the partners\nas a pool. When a startup requested office hours, they got the next\navailable slot posted by any partner. That meant every partner had\nto know every startup. This worked fine up to 60 startups, but when\nthe batch grew to 80, everything broke. The founders probably didn't\nrealize anything was wrong, but the partners were confused and\nunhappy because halfway through the batch they still didn't know\nall the companies yet.\n[2]At first I was puzzled. How could things be fine at 60 startups and\nbroken at 80? It was only a third more. Then I realized what had\nhappened. We were using an O(n2) algorithm. So of course it blew\nup.The solution we adopted was the classic one in these situations.\nWe sharded the batch into smaller groups of startups, each overseen\nby a dedicated group of partners. That fixed the problem, and has\nworked fine ever since. But the batch that broke YC was a powerful\ndemonstration of how individualized the process of advising startups\nhas to be.Another related surprise is how bad founders can be at realizing\nwhat their problems are. Founders will sometimes come in to talk\nabout some problem, and we'll discover another much bigger one in\nthe course of the conversation. For example (and this case is all\ntoo common), founders will come in to talk about the difficulties\nthey're having raising money, and after digging into their situation,\nit turns out the reason is that the company is doing badly, and\ninvestors can tell. Or founders will come in worried that they still\nhaven't cracked the problem of user acquisition, and the reason turns out\nto be that their product isn't good enough. There have been times\nwhen I've asked \"Would you use this yourself, if you hadn't built\nit?\" and the founders, on thinking about it, said \"No.\" Well, there's\nthe reason you're having trouble getting users.Often founders know what their problems are, but not their relative\nimportance.\n[3]\nThey'll come in to talk about three problems\nthey're worrying about. One is of moderate importance, one doesn't\nmatter at all, and one will kill the company if it isn't addressed\nimmediately. It's like watching one of those horror movies where\nthe heroine is deeply upset that her boyfriend cheated on her, and\nonly mildly curious about the door that's mysteriously ajar. You\nwant to say: never mind about your boyfriend, think about that door!\nFortunately in office hours you can. So while startups still die\nwith some regularity, it's rarely because they wandered into a room\ncontaining a murderer. The YC partners can warn them where the\nmurderers are.Not that founders listen. That was another big surprise: how often\nfounders don't listen to us. A couple weeks ago I talked to a partner\nwho had been working for YC for a couple batches and was starting\nto see the pattern. \"They come back a year later,\" she said, \"and\nsay 'We wish we'd listened to you.'\"It took me a long time to figure out why founders don't listen. At\nfirst I thought it was mere stubbornness. That's part of the reason,\nbut another and probably more important reason is that so much about\nstartups is counterintuitive. \nAnd when you tell someone something\ncounterintuitive, what it sounds to them is wrong. So the reason\nfounders don't listen to us is that they don't believe us. At\nleast not till experience teaches them otherwise.\n[4]The reason startups are so counterintuitive is that they're so\ndifferent from most people's other experiences. No one knows what\nit's like except those who've done it. Which is why YC partners\nshould usually have been founders themselves. But strangely enough,\nthe counterintuitiveness of startups turns out to be another of the\nthings that make YC work. If it weren't counterintuitive, founders\nwouldn't need our advice about how to do it.Focus is doubly important for early stage startups, because not\nonly do they have a hundred different problems, they don't have\nanyone to work on them except the founders. If the founders focus\non things that don't matter, there's no one focusing on the things\nthat do. So the essence of what happens at YC is to figure out which\nproblems matter most, then cook up ideas for solving them — ideally\nat a resolution of a week or less — and then try those ideas and\nmeasure how well they worked. The focus is on action, with measurable,\nnear-term results.This doesn't imply that founders should rush forward regardless of\nthe consequences. If you correct course at a high enough frequency,\nyou can be simultaneously decisive at a micro scale and tentative\nat a macro scale. The result is a somewhat winding path, but executed\nvery rapidly, like the path a running back takes downfield. And in\npractice there's less backtracking than you might expect. Founders\nusually guess right about which direction to run in, especially if\nthey have someone experienced like a YC partner to bounce their\nhypotheses off. And when they guess wrong, they notice fast, because\nthey'll talk about the results at office hours the next week.\n[5]A small improvement in navigational ability can make you a lot\nfaster, because it has a double effect: the path is shorter, and\nyou can travel faster along it when you're more certain it's the\nright one. That's where a lot of YC's value lies, in helping founders\nget an extra increment of focus that lets them move faster. And\nsince moving fast is the essence of a startup, YC in effect makes\nstartups more startup-like.Speed defines startups. Focus enables speed. YC improves focus.Why are founders uncertain about what to do? Partly because startups\nalmost by definition are doing something new, which means no one\nknows how to do it yet, or in most cases even what \"it\" is. Partly\nbecause startups are so counterintuitive generally. And partly\nbecause many founders, especially young and ambitious ones, have\nbeen trained to win the wrong way. That took me years to figure\nout. The educational system in most countries trains you to win by\nhacking the test \ninstead of actually doing whatever it's supposed\nto measure. But that stops working when you start a startup. So\npart of what YC does is to retrain founders to stop trying to hack\nthe test. (It takes a surprisingly long time. A year in, you still\nsee them reverting to their old habits.)YC is not simply more experienced founders passing on their knowledge.\nIt's more like specialization than apprenticeship. The knowledge\nof the YC partners and the founders have different shapes: It\nwouldn't be worthwhile for a founder to acquire the encyclopedic\nknowledge of startup problems that a YC partner has, just as it\nwouldn't be worthwhile for a YC partner to acquire the depth of\ndomain knowledge that a founder has. That's why it can still be\nvaluable for an experienced founder to do YC, just as it can still\nbe valuable for an experienced athlete to have a coach.The other big thing YC gives founders is colleagues, and this may\nbe even more important than the advice of partners. If you look at\nhistory, great work clusters around certain places and institutions:\nFlorence in the late 15th century, the University of Göttingen in\nthe late 19th, The New Yorker under Ross, Bell Labs, Xerox PARC.\nHowever good you are, good colleagues make you better. Indeed, very\nambitious people probably need colleagues more than anyone else,\nbecause they're so starved for them in everyday life.Whether or not YC manages one day to be listed alongside those\nfamous clusters, it won't be for lack of trying. We were very aware\nof this historical phenomenon and deliberately designed YC to be\none. By this point it's not bragging to say that it's the biggest\ncluster of great startup founders. Even people trying to attack YC\nconcede that.Colleagues and startup founders are two of the most powerful forces\nin the world, so you'd expect it to have a big effect to combine\nthem. Before YC, to the extent people thought about the question\nat all, most assumed they couldn't be combined — that loneliness\nwas the price of independence. That was how it felt to us when we\nstarted our own startup in Boston in the 1990s. We had a handful\nof older people we could go to for advice (of varying quality), but\nno peers. There was no one we could commiserate with about the\nmisbehavior of investors, or speculate with about the future of\ntechnology. I often tell founders to make something they themselves\nwant, and YC is certainly that: it was designed to be exactly what\nwe wanted when we were starting a startup.One thing we wanted was to be able to get seed funding without\nhaving to make the rounds of random rich people. That has become a\ncommodity now, at least in the US. But great colleagues can never\nbecome a commodity, because the fact that they cluster in some\nplaces means they're proportionally absent from the rest.Something magical happens where they do cluster though. The energy\nin the room at a YC dinner is like nothing else I've experienced.\nWe would have been happy just to have one or two other startups to\ntalk to. When you have a whole roomful it's another thing entirely.YC founders aren't just inspired by one another. They also help one\nanother. That's the happiest thing I've learned about startup\nfounders: how generous they can be in helping one another. We noticed\nthis in the first batch and consciously designed YC to magnify it.\nThe result is something far more intense than, say, a university.\nBetween the partners, the alumni, and their batchmates, founders\nare surrounded by people who want to help them, and can.Notes[1] \nThis is why I've never liked it when people refer to YC as a\n\"bootcamp.\" It's intense like a bootcamp, but the opposite in\nstructure. Instead of everyone doing the same thing, they're each\ntalking to YC partners to figure out what their specific startup\nneeds.[2] \nWhen I say the summer 2012 batch was broken, I mean it felt\nto the partners that something was wrong. Things weren't yet so\nbroken that the startups had a worse experience. In fact that batch\ndid unusually well.[3] \nThis situation reminds me of the research showing that people\nare much better at answering questions than they are at judging how\naccurate their answers are. The two phenomena feel very similar.[4] \nThe Airbnbs were \nparticularly good at listening — partly\nbecause they were flexible and disciplined, but also because they'd\nhad such a rough time during the preceding year. They were ready\nto listen.[5] \nThe optimal unit of decisiveness depends on how long it takes\nto get results, and that depends on the type of problem you're\nsolving. When you're negotiating with investors, it could be a\ncouple days, whereas if you're building hardware it could be months.\nThanks to Trevor Blackwell, Jessica Livingston, \nHarj Taggar, and Garry Tan for reading drafts of this." }, { "path": "data/PaulGrahamEssays/vb.txt", "content": "January 2016Life is short, as everyone knows. When I was a kid I used to wonder\nabout this. Is life actually short, or are we really complaining\nabout its finiteness? Would we be just as likely to feel life was\nshort if we lived 10 times as long?Since there didn't seem any way to answer this question, I stopped\nwondering about it. Then I had kids. That gave me a way to answer\nthe question, and the answer is that life actually is short.Having kids showed me how to convert a continuous quantity, time,\ninto discrete quantities. You only get 52 weekends with your 2 year\nold. If Christmas-as-magic lasts from say ages 3 to 10, you only\nget to watch your child experience it 8 times. And while it's\nimpossible to say what is a lot or a little of a continuous quantity\nlike time, 8 is not a lot of something. If you had a handful of 8\npeanuts, or a shelf of 8 books to choose from, the quantity would\ndefinitely seem limited, no matter what your lifespan was.Ok, so life actually is short. Does it make any difference to know\nthat?It has for me. It means arguments of the form \"Life is too short\nfor x\" have great force. It's not just a figure of speech to say\nthat life is too short for something. It's not just a synonym for\nannoying. If you find yourself thinking that life is too short for\nsomething, you should try to eliminate it if you can.When I ask myself what I've found life is too short for, the word\nthat pops into my head is \"bullshit.\" I realize that answer is\nsomewhat tautological. It's almost the definition of bullshit that\nit's the stuff that life is too short for. And yet bullshit does\nhave a distinctive character. There's something fake about it.\nIt's the junk food of experience.\n[1]If you ask yourself what you spend your time on that's bullshit,\nyou probably already know the answer. Unnecessary meetings, pointless\ndisputes, bureaucracy, posturing, dealing with other people's\nmistakes, traffic jams, addictive but unrewarding pastimes.There are two ways this kind of thing gets into your life: it's\neither forced on you, or it tricks you. To some extent you have to\nput up with the bullshit forced on you by circumstances. You need\nto make money, and making money consists mostly of errands. Indeed,\nthe law of supply and demand insures that: the more rewarding some\nkind of work is, the cheaper people will do it. It may be that\nless bullshit is forced on you than you think, though. There has\nalways been a stream of people who opt out of the default grind and\ngo live somewhere where opportunities are fewer in the conventional\nsense, but life feels more authentic. This could become more common.You can do it on a smaller scale without moving. The amount of\ntime you have to spend on bullshit varies between employers. Most\nlarge organizations (and many small ones) are steeped in it. But\nif you consciously prioritize bullshit avoidance over other factors\nlike money and prestige, you can probably find employers that will\nwaste less of your time.If you're a freelancer or a small company, you can do this at the\nlevel of individual customers. If you fire or avoid toxic customers,\nyou can decrease the amount of bullshit in your life by more than\nyou decrease your income.But while some amount of bullshit is inevitably forced on you, the\nbullshit that sneaks into your life by tricking you is no one's\nfault but your own. And yet the bullshit you choose may be harder\nto eliminate than the bullshit that's forced on you. Things that\nlure you into wasting your time have to be really good at\ntricking you. An example that will be familiar to a lot of people\nis arguing online. When someone\ncontradicts you, they're in a sense attacking you. Sometimes pretty\novertly. Your instinct when attacked is to defend yourself. But\nlike a lot of instincts, this one wasn't designed for the world we\nnow live in. Counterintuitive as it feels, it's better most of\nthe time not to defend yourself. Otherwise these people are literally\ntaking your life.\n[2]Arguing online is only incidentally addictive. There are more\ndangerous things than that. As I've written before, one byproduct\nof technical progress is that things we like tend to become more\naddictive. Which means we will increasingly have to make a conscious\neffort to avoid addictions — to stand outside ourselves and ask \"is\nthis how I want to be spending my time?\"As well as avoiding bullshit, one should actively seek out things\nthat matter. But different things matter to different people, and\nmost have to learn what matters to them. A few are lucky and realize\nearly on that they love math or taking care of animals or writing,\nand then figure out a way to spend a lot of time doing it. But\nmost people start out with a life that's a mix of things that\nmatter and things that don't, and only gradually learn to distinguish\nbetween them.For the young especially, much of this confusion is induced by the\nartificial situations they find themselves in. In middle school and\nhigh school, what the other kids think of you seems the most important\nthing in the world. But when you ask adults what they got wrong\nat that age, nearly all say they cared too much what other kids\nthought of them.One heuristic for distinguishing stuff that matters is to ask\nyourself whether you'll care about it in the future. Fake stuff\nthat matters usually has a sharp peak of seeming to matter. That's\nhow it tricks you. The area under the curve is small, but its shape\njabs into your consciousness like a pin.The things that matter aren't necessarily the ones people would\ncall \"important.\" Having coffee with a friend matters. You won't\nfeel later like that was a waste of time.One great thing about having small children is that they make you\nspend time on things that matter: them. They grab your sleeve as\nyou're staring at your phone and say \"will you play with me?\" And\nodds are that is in fact the bullshit-minimizing option.If life is short, we should expect its shortness to take us by\nsurprise. And that is just what tends to happen. You take things\nfor granted, and then they're gone. You think you can always write\nthat book, or climb that mountain, or whatever, and then you realize\nthe window has closed. The saddest windows close when other people\ndie. Their lives are short too. After my mother died, I wished I'd\nspent more time with her. I lived as if she'd always be there.\nAnd in her typical quiet way she encouraged that illusion. But an\nillusion it was. I think a lot of people make the same mistake I\ndid.The usual way to avoid being taken by surprise by something is to\nbe consciously aware of it. Back when life was more precarious,\npeople used to be aware of death to a degree that would now seem a\nbit morbid. I'm not sure why, but it doesn't seem the right answer\nto be constantly reminding oneself of the grim reaper hovering at\neveryone's shoulder. Perhaps a better solution is to look at the\nproblem from the other end. Cultivate a habit of impatience about\nthe things you most want to do. Don't wait before climbing that\nmountain or writing that book or visiting your mother. You don't\nneed to be constantly reminding yourself why you shouldn't wait.\nJust don't wait.I can think of two more things one does when one doesn't have much\nof something: try to get more of it, and savor what one has. Both\nmake sense here.How you live affects how long you live. Most people could do better.\nMe among them.But you can probably get even more effect by paying closer attention\nto the time you have. It's easy to let the days rush by. The\n\"flow\" that imaginative people love so much has a darker cousin\nthat prevents you from pausing to savor life amid the daily slurry\nof errands and alarms. One of the most striking things I've read\nwas not in a book, but the title of one: James Salter's Burning\nthe Days.It is possible to slow time somewhat. I've gotten better at it.\nKids help. When you have small children, there are a lot of moments\nso perfect that you can't help noticing.It does help too to feel that you've squeezed everything out of\nsome experience. The reason I'm sad about my mother is not just\nthat I miss her but that I think of all the things we could have\ndone that we didn't. My oldest son will be 7 soon. And while I\nmiss the 3 year old version of him, I at least don't have any regrets\nover what might have been. We had the best time a daddy and a 3\nyear old ever had.Relentlessly prune bullshit, don't wait to do things that matter,\nand savor the time you have. That's what you do when life is short.Notes[1]\nAt first I didn't like it that the word that came to mind was\none that had other meanings. But then I realized the other meanings\nare fairly closely related. Bullshit in the sense of things you\nwaste your time on is a lot like intellectual bullshit.[2]\nI chose this example deliberately as a note to self. I get\nattacked a lot online. People tell the craziest lies about me.\nAnd I have so far done a pretty mediocre job of suppressing the\nnatural human inclination to say \"Hey, that's not true!\"Thanks to Jessica Livingston and Geoff Ralston for reading drafts\nof this." }, { "path": "data/PaulGrahamEssays/vcsqueeze.txt", "content": "November 2005In the next few years, venture capital funds will find themselves\nsqueezed from four directions. They're already stuck with a seller's\nmarket, because of the huge amounts they raised at the end of the\nBubble and still haven't invested. This by itself is not the end\nof the world. In fact, it's just a more extreme version of the\nnorm\nin the VC business: too much money chasing too few deals.Unfortunately, those few deals now want less and less money, because\nit's getting so cheap to start a startup. The four causes: open\nsource, which makes software free; Moore's law, which makes hardware\ngeometrically closer to free; the Web, which makes promotion free\nif you're good; and better languages, which make development a lot\ncheaper.When we started our startup in 1995, the first three were our biggest\nexpenses. We had to pay $5000 for the Netscape Commerce Server,\nthe only software that then supported secure http connections. We\npaid $3000 for a server with a 90 MHz processor and 32 meg of\nmemory. And we paid a PR firm about $30,000 to promote our launch.Now you could get all three for nothing. You can get the software\nfor free; people throw away computers more powerful than our first\nserver; and if you make something good you can generate ten times\nas much traffic by word of mouth online than our first PR firm got\nthrough the print media.And of course another big change for the average startup is that\nprogramming languages have improved-- or rather, the median language has. At most startups ten years\nago, software development meant ten programmers writing code in\nC++. Now the same work might be done by one or two using Python\nor Ruby.During the Bubble, a lot of people predicted that startups would\noutsource their development to India. I think a better model for\nthe future is David Heinemeier Hansson, who outsourced his development\nto a more powerful language instead. A lot of well-known applications\nare now, like BaseCamp, written by just one programmer. And one\nguy is more than 10x cheaper than ten, because (a) he won't waste\nany time in meetings, and (b) since he's probably a founder, he can\npay himself nothing.Because starting a startup is so cheap, venture capitalists now\noften want to give startups more money than the startups want to\ntake. VCs like to invest several million at a time. But as one\nVC told me after a startup he funded would only take about half a\nmillion, \"I don't know what we're going to do. Maybe we'll just\nhave to give some of it back.\" Meaning give some of the fund back\nto the institutional investors who supplied it, because it wasn't\ngoing to be possible to invest it all.Into this already bad situation comes the third problem: Sarbanes-Oxley.\nSarbanes-Oxley is a law, passed after the Bubble, that drastically\nincreases the regulatory burden on public companies. And in addition\nto the cost of compliance, which is at least two million dollars a\nyear, the law introduces frightening legal exposure for corporate\nofficers. An experienced CFO I know said flatly: \"I would not\nwant to be CFO of a public company now.\"You might think that responsible corporate governance is an area\nwhere you can't go too far. But you can go too far in any law, and\nthis remark convinced me that Sarbanes-Oxley must have. This CFO\nis both the smartest and the most upstanding money guy I know. If\nSarbanes-Oxley deters people like him from being CFOs of public \ncompanies, that's proof enough that it's broken.Largely because of Sarbanes-Oxley, few startups go public now. For\nall practical purposes, succeeding now equals getting bought. Which\nmeans VCs are now in the business of finding promising little 2-3\nman startups and pumping them up into companies that cost $100\nmillion to acquire. They didn't mean to be in this business; it's\njust what their business has evolved into.Hence the fourth problem: the acquirers have begun to realize they\ncan buy wholesale. Why should they wait for VCs to make the startups\nthey want more expensive? Most of what the VCs add, acquirers don't\nwant anyway. The acquirers already have brand recognition and HR\ndepartments. What they really want is the software and the developers,\nand that's what the startup is in the early phase: concentrated\nsoftware and developers.Google, typically, seems to have been the first to figure this out.\n\"Bring us your startups early,\" said Google's speaker at the Startup School. They're quite\nexplicit about it: they like to acquire startups at just the point\nwhere they would do a Series A round. (The Series A round is the\nfirst round of real VC funding; it usually happens in the first\nyear.) It is a brilliant strategy, and one that other big technology\ncompanies will no doubt try to duplicate. Unless they want to have \nstill more of their lunch eaten by Google.Of course, Google has an advantage in buying startups: a lot of the\npeople there are rich, or expect to be when their options vest.\nOrdinary employees find it very hard to recommend an acquisition;\nit's just too annoying to see a bunch of twenty year olds get rich\nwhen you're still working for salary. Even if it's the right thing \nfor your company to do.The Solution(s)Bad as things look now, there is a way for VCs to save themselves.\nThey need to do two things, one of which won't surprise them, and \nanother that will seem an anathema.Let's start with the obvious one: lobby to get Sarbanes-Oxley \nloosened. This law was created to prevent future Enrons, not to\ndestroy the IPO market. Since the IPO market was practically dead\nwhen it passed, few saw what bad effects it would have. But now \nthat technology has recovered from the last bust, we can see clearly\nwhat a bottleneck Sarbanes-Oxley has become.Startups are fragile plants—seedlings, in fact. These seedlings\nare worth protecting, because they grow into the trees of the\neconomy. Much of the economy's growth is their growth. I think\nmost politicians realize that. But they don't realize just how \nfragile startups are, and how easily they can become collateral\ndamage of laws meant to fix some other problem.Still more dangerously, when you destroy startups, they make very\nlittle noise. If you step on the toes of the coal industry, you'll\nhear about it. But if you inadvertantly squash the startup industry,\nall that happens is that the founders of the next Google stay in \ngrad school instead of starting a company.My second suggestion will seem shocking to VCs: let founders cash \nout partially in the Series A round. At the moment, when VCs invest\nin a startup, all the stock they get is newly issued and all the \nmoney goes to the company. They could buy some stock directly from\nthe founders as well.Most VCs have an almost religious rule against doing this. They\ndon't want founders to get a penny till the company is sold or goes\npublic. VCs are obsessed with control, and they worry that they'll\nhave less leverage over the founders if the founders have any money.This is a dumb plan. In fact, letting the founders sell a little stock\nearly would generally be better for the company, because it would\ncause the founders' attitudes toward risk to be aligned with the\nVCs'. As things currently work, their attitudes toward risk tend\nto be diametrically opposed: the founders, who have nothing, would\nprefer a 100% chance of $1 million to a 20% chance of $10 million,\nwhile the VCs can afford to be \"rational\" and prefer the latter.Whatever they say, the reason founders are selling their companies\nearly instead of doing Series A rounds is that they get paid up\nfront. That first million is just worth so much more than the\nsubsequent ones. If founders could sell a little stock early,\nthey'd be happy to take VC money and bet the rest on a bigger\noutcome.So why not let the founders have that first million, or at least\nhalf million? The VCs would get same number of shares for the \nmoney. So what if some of the money would go to the \nfounders instead of the company?Some VCs will say this is\nunthinkable—that they want all their money to be put to work\ngrowing the company. But the fact is, the huge size of current VC\ninvestments is dictated by the structure\nof VC funds, not the needs of startups. Often as not these large \ninvestments go to work destroying the company rather than growing\nit.The angel investors who funded our startup let the founders sell\nsome stock directly to them, and it was a good deal for everyone. \nThe angels made a huge return on that investment, so they're happy.\nAnd for us founders it blunted the terrifying all-or-nothingness\nof a startup, which in its raw form is more a distraction than a\nmotivator.If VCs are frightened at the idea of letting founders partially\ncash out, let me tell them something still more frightening: you\nare now competing directly with Google.\nThanks to Trevor Blackwell, Sarah Harlin, Jessica\nLivingston, and Robert Morris for reading drafts of this." }, { "path": "data/PaulGrahamEssays/venturecapital.txt", "content": "March 2005A couple months ago I got an email from a recruiter asking if I was\ninterested in being a \"technologist in residence\" at a new venture\ncapital fund. I think the idea was to play Karl Rove to the VCs'\nGeorge Bush.I considered it for about four seconds. Work for a VC fund? Ick.One of my most vivid memories from our startup is going to visit\nGreylock, the famous Boston VCs. They were the most arrogant\npeople I've met in my life. And I've met a lot of arrogant people.\n[1]I'm not alone in feeling this way, of course. Even a VC friend of\nmine dislikes VCs. \"Assholes,\" he says.But lately I've been learning more about how the VC world works,\n\nand a few days ago it hit me that there's a reason VCs are the way\nthey are. It's not so much that the business attracts jerks, or\neven that the power they wield corrupts them. The real problem is\nthe way they're paid.The problem with VC funds is that they're funds. Like the\nmanagers of mutual funds or hedge funds, VCs get paid a percentage\nof the money they manage: about 2% a year in management fees,\nplus a percentage of the gains. So they want\nthe fund to be huge-- hundreds of millions of dollars, if possible.\nBut that means each partner ends up being responsible for investing\na lot of money. And since one person can only manage so many deals,\neach deal has to be for multiple millions of dollars.This turns out to explain nearly all the characteristics of VCs\nthat founders hate.It explains why VCs take so agonizingly long to make up their minds,\nand why their due diligence feels like a body cavity search. [2]\nWith so much at stake, they have to be paranoid.It explains why they steal your ideas. Every founder knows that\nVCs will tell your secrets to your competitors if they end up\ninvesting in them. It's not unheard of for VCs to meet you when\nthey have no intention of funding you, just to pick your brain for\na competitor. This prospect makes naive founders clumsily secretive.\nExperienced founders treat it as a cost of doing business. Either\nway it sucks. But again, the only reason VCs are so sneaky is the\ngiant deals they do. With so much at stake, they have to be devious.It explains why VCs tend to interfere in the companies they invest\nin. They want to be on your board not just so that they can advise\nyou, but so that they can watch you. Often they even install a new\nCEO. Yes, he may have extensive business experience. But he's\nalso their man: these newly installed CEOs always play something \nof the role of a political commissar in a Red Army unit. With\nso much at stake, VCs can't resist micromanaging you.The huge investments themselves are something founders would dislike,\nif they realized how damaging they can be. VCs don't invest $x\nmillion because that's the amount you need, but because that's the\namount the structure of their business requires them to invest. \nLike steroids, these sudden huge investments can do more harm than \ngood. Google survived enormous VC funding because it could\nlegitimately absorb large amounts of money. They had to buy a lot\nof servers and a lot of bandwidth to crawl the whole Web. Less\nfortunate startups just end up hiring armies of people to sit around\nhaving meetings.In principle you could take a huge VC investment, put it in treasury\nbills, and continue to operate frugally. You just try it.And of course giant investments mean giant valuations. They have\nto, or there's not enough stock left to keep the founders interested.\nYou might think a high valuation is a great thing. Many founders \ndo. But you can't eat paper. You can't benefit from a high valuation\nunless you can somehow achieve what those in the business \n\ncall a \"liquidity event,\" and the higher \nyour valuation, the narrower your options for doing that. Many a \nfounder would be happy to sell his company for $15 million, but VCs\nwho've just invested at a pre-money valuation of $8 million won't\nhear of that. You're rolling the dice again, whether you like it\nor not.Back in 1997, one of our competitors raised $20 million in a single \nround of VC funding. This was at the time more than the valuation\nof our entire company. Was I worried? Not at all: I was delighted.\nIt was like watching a car you're chasing turn down a street that\nyou know has no outlet.Their smartest move at that point would have been to take every \npenny of the $20 million and use it to buy us. We would have sold.\nTheir investors would have been furious of course. But I think the \nmain reason they never considered this was that they never imagined\nwe could be had so cheap. They probably assumed we were on the\nsame VC gravy train they were.In fact we only spent about $2 million in our entire existence. \nAnd that gave us flexibility. We could sell ourselves to Yahoo for\n$50 million, and everyone was delighted. If our competitor had\ndone that, the last round of investors would presumably have lost\nmoney. I assume they could have vetoed such a deal. But no one \nthose days was paying a lot more than Yahoo. So unless their\nfounders could pull off an IPO (which would be difficult with Yahoo\nas a competitor), they had no choice but to ride the thing down.The puffed-up companies that went public during the Bubble didn't\ndo it just because they were pulled into it by unscrupulous investment \nbankers. Most were pushed just as hard from the other side by VCs\nwho'd invested at high valuations, leaving an IPO as the only way \nout. The only people dumber were retail investors. So it was\nliterally IPO or bust. Or rather, IPO then bust, or just bust.Add up all the evidence of VCs' behavior, and the resulting personality\nis not attractive. In fact, it's the classic villain: alternately\ncowardly, greedy, sneaky, and overbearing.I used to take it for granted that VCs were like this. Complaining \nthat VCs were jerks used to seem as naive to me as complaining that\nusers didn't read the reference manual. Of course VCs were jerks.\nHow could it be otherwise?But I realize now that they're not intrinsically jerks. VCs are \nlike car salesmen or bureaucrats: the nature of their work\nturns them into jerks.I've met a few VCs I like. Mike Moritz seems a good guy. He even \nhas a sense of humor, which is almost unheard of among VCs. From \nwhat I've read about John Doerr, he sounds like a good guy too, \nalmost a hacker. But they work for the very best VC funds. And \nmy theory explains why they'd tend to be different: just as the\nvery most popular kids don't have to persecute \nnerds, the very best\nVCs don't have to act like VCs. They get the pick of all the best \ndeals. So they don't have to be so paranoid and sneaky, and they \ncan choose those rare companies, like Google, that will actually\nbenefit from the giant sums they're compelled to invest.VCs often complain that in their business there's too much money\nchasing too few deals. Few realize that this also describes a flaw\nin the way funding works at the level of individual firms.Perhaps this was the sort of strategic insight I was supposed to \ncome up with as a \"technologist in residence.\" If so, the good\nnews is that they're getting it for free. The bad news is it\nmeans that if you're not one of the very top funds, you're \ncondemned to be the bad guys.Notes[1] After Greylock booted founder Philip Greenspun out of ArsDigita,\nhe wrote a hilarious but also very informative\nessay about it.\n[2] Since most VCs aren't tech guys, the technology side of their\ndue diligence tends to be like a body cavity search by someone with\na faulty knowledge of human anatomy. After a while we were quite\nsore from VCs attempting to probe our nonexistent database orifice.No, we don't use Oracle. We just store the data in files. Our\nsecret is to use an OS that doesn't lose our data. Which OS?\nFreeBSD. Why do you use that instead of Windows NT? Because it's\nbetter and it doesn't cost anything. What, you're using a\nfreeware OS?How many times that conversation was repeated.\nThen when we got to Yahoo, we found they used FreeBSD and stored\ntheir data in files too." }, { "path": "data/PaulGrahamEssays/vw.txt", "content": "January 2012A few hours before the Yahoo acquisition was announced in June 1998\nI took a snapshot of Viaweb's\nsite. I thought it might be interesting to look at one day.The first thing one notices is is how tiny the pages are. Screens\nwere a lot smaller in 1998. If I remember correctly, our frontpage\nused to just fit in the size window people typically used then.Browsers then (IE 6 was still 3 years in the future) had few fonts\nand they weren't antialiased. If you wanted to make pages that\nlooked good, you had to render display text as images.You may notice a certain similarity between the Viaweb and Y Combinator logos. We did that\nas an inside joke when we started YC. Considering how basic a red\ncircle is, it seemed surprising to me when we started Viaweb how\nfew other companies used one as their logo. A bit later I realized\nwhy.On the Company\npage you'll notice a mysterious individual called John McArtyem.\nRobert Morris (aka Rtm) was so publicity averse after the \nWorm that he\ndidn't want his name on the site. I managed to get him to agree\nto a compromise: we could use his bio but not his name. He has\nsince relaxed a bit\non that point.Trevor graduated at about the same time the acquisition closed, so in the\ncourse of 4 days he went from impecunious grad student to millionaire\nPhD. The culmination of my career as a writer of press releases\nwas one celebrating\nhis graduation, illustrated with a drawing I did of him during\na meeting.(Trevor also appears as Trevino\nBagwell in our directory of web designers merchants could hire\nto build stores for them. We inserted him as a ringer in case some\ncompetitor tried to spam our web designers. We assumed his logo\nwould deter any actual customers, but it did not.)Back in the 90s, to get users you had to get mentioned in magazines\nand newspapers. There were not the same ways to get found online\nthat there are today. So we used to pay a PR\nfirm $16,000 a month to get us mentioned in the press. Fortunately\nreporters liked\nus.In our advice about\ngetting traffic from search engines (I don't think the term SEO\nhad been coined yet), we say there are only 7 that matter: Yahoo,\nAltaVista, Excite, WebCrawler, InfoSeek, Lycos, and HotBot. Notice\nanything missing? Google was incorporated that September.We supported online transactions via a company called \nCybercash,\nsince if we lacked that feature we'd have gotten beaten up in product\ncomparisons. But Cybercash was so bad and most stores' order volumes\nwere so low that it was better if merchants processed orders like phone orders. We had a page in our site trying to talk merchants\nout of doing real time authorizations.The whole site was organized like a funnel, directing people to the\ntest drive.\nIt was a novel thing to be able to try out software online. We put\ncgi-bin in our dynamic urls to fool competitors about how our\nsoftware worked.We had some well\nknown users. Needless to say, Frederick's of Hollywood got the\nmost traffic. We charged a flat fee of $300/month for big stores,\nso it was a little alarming to have users who got lots of traffic.\nI once calculated how much Frederick's was costing us in bandwidth,\nand it was about $300/month.Since we hosted all the stores, which together were getting just\nover 10 million page views per month in June 1998, we consumed what\nat the time seemed a lot of bandwidth. We had 2 T1s (3 Mb/sec)\ncoming into our offices. In those days there was no AWS. Even\ncolocating servers seemed too risky, considering how often things\nwent wrong with them. So we had our servers in our offices. Or\nmore precisely, in Trevor's office. In return for the unique\nprivilege of sharing his office with no other humans, he had to\nshare it with 6 shrieking tower servers. His office was nicknamed\nthe Hot Tub on account of the heat they generated. Most days his\nstack of window air conditioners could keep up.For describing pages, we had a template language called RTML, which\nsupposedly stood for something, but which in fact I named after\nRtm. RTML was Common Lisp augmented by some macros and libraries,\nand concealed under a structure editor that made it look like it\nhad syntax.Since we did continuous releases, our software didn't actually have\nversions. But in those days the trade press expected versions, so\nwe made them up. If we wanted to get lots of attention, we made\nthe version number an\ninteger. That \"version 4.0\" icon was generated by our own\nbutton generator, incidentally. The whole Viaweb site was made\nwith our software, even though it wasn't an online store, because\nwe wanted to experience what our users did.At the end of 1997, we released a general purpose shopping search\nengine called Shopfind. It\nwas pretty advanced for the time. It had a programmable crawler\nthat could crawl most of the different stores online and pick out\nthe products." }, { "path": "data/PaulGrahamEssays/want.txt", "content": "November 2022Since I was about 9 I've been puzzled by the apparent contradiction\nbetween being made of matter that behaves in a predictable way, and\nthe feeling that I could choose to do whatever I wanted. At the\ntime I had a self-interested motive for exploring the question. At\nthat age (like most succeeding ages) I was always in trouble with\nthe authorities, and it seemed to me that there might possibly be\nsome way to get out of trouble by arguing that I wasn't responsible\nfor my actions. I gradually lost hope of that, but the puzzle\nremained: How do you reconcile being a machine made of matter with\nthe feeling that you're free to choose what you do?\n[1]The best way to explain the answer may be to start with a slightly\nwrong version, and then fix it. The wrong version is: You can do\nwhat you want, but you can't want what you want. Yes, you can control\nwhat you do, but you'll do what you want, and you can't control\nthat.The reason this is mistaken is that people do sometimes change what\nthey want. People who don't want to want something — drug addicts,\nfor example — can sometimes make themselves stop wanting it. And\npeople who want to want something — who want to like classical\nmusic, or broccoli — sometimes succeed.So we modify our initial statement: You can do what you want, but\nyou can't want to want what you want.That's still not quite true. It's possible to change what you want\nto want. I can imagine someone saying \"I decided to stop wanting\nto like classical music.\" But we're getting closer to the truth.\nIt's rare for people to change what they want to want, and the more\n\"want to\"s we add, the rarer it gets.We can get arbitrarily close to a true statement by adding more \"want\nto\"s in much the same way we can get arbitrarily close to 1 by adding\nmore 9s to a string of 9s following a decimal point. In practice\nthree or four \"want to\"s must surely be enough. It's hard even to\nenvision what it would mean to change what you want to want to want\nto want, let alone actually do it.So one way to express the correct answer is to use a regular\nexpression. You can do what you want, but there's some statement\nof the form \"you can't (want to)* want what you want\" that's true.\nUltimately you get back to a want that you don't control.\n[2]\nNotes[1]\nI didn't know when I was 9 that matter might behave randomly,\nbut I don't think it affects the problem much. Randomness destroys\nthe ghost in the machine as effectively as determinism.[2]\nIf you don't like using an expression, you can make the same\npoint using higher-order desires: There is some n such that you\ndon't control your nth-order desires.\nThanks to Trevor Blackwell,\nJessica Livingston, Robert Morris, and\nMichael Nielsen for reading drafts of this." }, { "path": "data/PaulGrahamEssays/wealth.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nMay 2004\n(This essay was originally published in Hackers \n& Painters.)\nIf you wanted to get rich, how would you do it? I think your best\nbet would be to start or join a startup. That's been a \nreliable way to get rich for hundreds of years. The word \"startup\" \ndates from the 1960s, but what happens in one is \nvery similar to the venture-backed trading voyages of the\nMiddle Ages.Startups usually involve technology, so much so that the phrase\n\"high-tech startup\" is almost redundant. A startup is a small\ncompany that takes on a hard technical problem.Lots of people get rich knowing nothing more than that.\nYou don't have to know physics to be a good pitcher. But\nI think it could give you an edge to understand the underlying principles.\nWhy do startups have to be small? \nWill a startup inevitably stop being a startup as it\ngrows larger? \nAnd why do they so often work on\ndeveloping new technology? Why are there so many startups\nselling new drugs or computer software, and none selling corn oil\nor laundry detergent?The PropositionEconomically, you can think of a startup as a way to \ncompress your whole working life into a few years. Instead\nof working at a low intensity for forty years, you work as\nhard as you possibly can for four. This pays especially well\nin technology, where you earn a premium for working fast.Here is a brief sketch of the economic proposition. If you're\na good hacker in your mid twenties, you can\nget a job paying about $80,000 per year. So on average \nsuch a hacker must be\nable to do at least $80,000 worth of work per year for the \ncompany just to break even. You could probably\nwork twice as many hours as a corporate employee, and if\nyou focus you can probably get three times as much done in\nan hour. \n[1]\nYou should get another multiple of two, at\nleast, by eliminating the drag \nof the pointy-haired middle\nmanager who would be your boss in a big company.\nThen there is one more multiple: how much smarter are you\nthan your job description expects you to be?\nSuppose another multiple of three. Combine all these multipliers, and I'm\nclaiming you could be 36 times more \nproductive than you're expected to be in a random corporate\njob. \n[2]\n If a fairly good hacker is worth $80,000 a year at a \nbig company, then a smart\nhacker working very hard without any corporate\nbullshit to slow him down should be able to do work worth about\n$3 million a year.Like all back-of-the-envelope calculations, this one\nhas a lot of wiggle room. I wouldn't try to\ndefend the actual numbers. But I stand by the \nstructure of the calculation. I'm not claiming\nthe multiplier is precisely 36, but it is certainly more\nthan 10, and probably rarely as high as 100.If $3 million a year seems\nhigh, remember that we're talking about the limit case:\nthe case where you not only have zero leisure time\nbut indeed work so hard that you endanger your health.Startups are not magic. They don't change the laws of\nwealth creation. They just represent a point at the far end of the curve.\nThere is a conservation law at work here: if\nyou want to make a million dollars, you have to endure a \nmillion dollars' worth of pain. \nFor example, one way to\nmake a million dollars would be to work for the \nPost Office your whole life, and save every penny of your \nsalary. Imagine the stress of working for the Post \nOffice for fifty years. In a startup you compress all\nthis stress into three or four years. You do tend to get a \ncertain \nbulk discount if you buy the economy-size pain,\nbut you can't evade the fundamental conservation law.\nIf starting a startup were easy, everyone would do it.Millions, not BillionsIf $3 million a year seems high to some people, it will seem\nlow to others. Three million? \nHow do I get to be a billionaire, like Bill Gates?So let's get Bill Gates out of the way right now. It's not\na good idea to use famous rich people \nas examples, because the press only \nwrite about the very richest, and these tend to be outliers.\nBill Gates is a smart, determined, and hardworking man,\nbut you need more than\nthat to make as much money as he has. You also need to be\nvery lucky.There is a large random\nfactor in the success of any company. So the guys you end \nup reading about in the papers are the ones who are very \nsmart, totally dedicated, and win the lottery.\nCertainly Bill is smart and dedicated, but Microsoft also \nhappens to have been the beneficiary of one of the most spectacular\nblunders in the history of business: the licensing deal for\nDOS. No doubt Bill did \neverything he could to steer IBM into making that blunder, \nand he has done an excellent job of exploiting it, but if\nthere had been one person with a brain on IBM's side,\nMicrosoft's future would have been very different.\nMicrosoft at that stage had little leverage over IBM.\nThey were effectively a component supplier. If IBM had \nrequired an exclusive license, as they should have, Microsoft\nwould still have signed the deal. It would still have\nmeant a lot of money for them, and IBM\ncould easily have gotten an operating system elsewhere.Instead IBM ended up using all its power in the market\nto give Microsoft control of the PC standard. From \nthat point, all Microsoft had to do was execute. They\nnever had to bet the company on a bold decision. All they\nhad to do was play hardball with licensees and copy more\ninnovative products reasonably promptly.If IBM hadn't made this mistake, Microsoft would\nstill have been a successful company, but it\ncould not have grown so big so fast. \nBill Gates would be rich, but he'd be somewhere\nnear the bottom of the Forbes 400 with the other guys his age.There are a lot of ways to get\nrich, and this essay is about only one of them. This\nessay is about how to make money by creating wealth and\ngetting paid for it. There are plenty of other ways to \nget money, including chance, speculation, marriage, inheritance, \ntheft, extortion, fraud, monopoly,\ngraft, lobbying,\ncounterfeiting, and prospecting. Most of the greatest fortunes\nhave probably involved several of these.The advantage of creating wealth, as a way to get rich,\nis not just that it's more legitimate \n(many of the other methods are now illegal) \nbut that it's more\nstraightforward. You just have to do something people want.Money Is Not WealthIf you want to create wealth, it will help to understand what it is. \nWealth is not the same thing as money. \n[3]\n Wealth is as old as\nhuman history. Far older, in fact; ants have wealth. \nMoney is a comparatively recent invention.Wealth is the fundamental thing. Wealth is stuff we want: food, \nclothes, houses, cars, gadgets, travel to interesting places,\nand so on. You can have wealth without\nhaving money. If you had a magic machine that\ncould on command make you a car or cook you dinner or do your\nlaundry, or do anything else you wanted, you wouldn't need money.\nWhereas if you were in the middle of Antarctica, where there is\nnothing to buy, it wouldn't matter how much money you had.Wealth is what you want, not money. But if wealth is the important\nthing, why does everyone talk about making money? It is\na kind of shorthand: money is a way of moving wealth, and in practice\nthey are usually interchangeable. But they are not the same thing,\nand unless you plan to get rich by counterfeiting, talking about\nmaking money can make it harder to understand how to \nmake money.Money is a side effect of specialization.\nIn a specialized society, most of the\nthings you need, you can't make for yourself. If you want a potato\nor a pencil or a place to live, you have to get it from someone\nelse.How do you get the person who grows the potatoes to give you some?\nBy giving him something he wants in return. But you can't get\nvery far by trading things directly with the people who\nneed them. If you make violins, and none of the local\nfarmers wants one, how will you eat?The solution societies find, as they get more specialized, is to\nmake the trade into a two-step process. Instead of trading violins\ndirectly for potatoes, you trade violins for, say, silver, \nwhich you can then trade again for anything else you need. The\nintermediate stuff-- the medium of exchange-- can be anything that's\nrare and portable. Historically metals have been the most common,\nbut recently we've been using a medium of exchange, called the dollar,\nthat doesn't physically exist. It works as a medium of exchange,\nhowever, because its rarity \nis guaranteed by the U.S. Government.The advantage of a medium of exchange is that it makes trade work.\nThe disadvantage is that it tends to obscure what trade really\nmeans. People think that what a business does is make money.\nBut money is just the intermediate stage-- just\na shorthand-- for whatever people want.\nWhat most businesses really do is make \nwealth. They do something people want. \n[4]The Pie FallacyA surprising number of people retain from childhood the idea\nthat there is a fixed amount of wealth in the world. \nThere is, in any normal family, a fixed amount of money at \nany moment. But that's not the same thing.When wealth is talked about in this context, it is often\ndescribed as a pie. \"You can't make the pie larger,\"\nsay politicians.\nWhen you're\ntalking about the amount of money in one family's bank\naccount, or the amount available to a government from one\nyear's tax revenue, this is true. \nIf one person gets more, someone else has to get less.I can remember believing, as a child, that if a few\nrich people had all the money, it left less for everyone else.\nMany people seem to continue to believe something like this\nwell into adulthood. This fallacy is usually there in the \nbackground when you hear someone talking about how x percent\nof the population have y percent of the wealth. If you plan\nto start a startup, then whether you realize it or not, you're\nplanning to disprove the Pie Fallacy.What leads people astray here is the abstraction of\nmoney. Money is not wealth. It's\njust something we use to move wealth around.\nSo although there may be, in certain specific moments (like\nyour family, this month) a fixed amount of money available to\ntrade with other people for things you want,\nthere is not a fixed amount of wealth in the world. \nYou can make more wealth. Wealth has been getting created and\ndestroyed (but on balance, created) for all of human history.Suppose you own a beat-up old car. \nInstead of sitting on your butt next\nsummer, you could spend the time restoring your car to pristine condition.\nIn doing so you create wealth. The world is-- and\nyou specifically are-- one pristine old car the richer. And not\njust in some metaphorical way. If you sell your car,\nyou'll get more for it.In restoring your old car you have made yourself\nricher. You haven't made anyone else poorer. So there is\nobviously not a fixed pie. And in fact, when you look at \nit this way, you wonder why anyone would think there was. \n[5]Kids know, without knowing they know, that they can create\nwealth. If you need to give someone a present and don't\nhave any money, you make one. But kids are so bad at making\nthings that they consider home-made presents to be a distinct,\ninferior, sort of thing to store-bought ones-- a mere expression\nof the proverbial thought that counts. \nAnd indeed, the lumpy ashtrays\nwe made for our parents did not have much of a resale market.CraftsmenThe people most likely to grasp that wealth can be\ncreated are the ones who are good at making things, the craftsmen.\nTheir hand-made objects become store-bought ones. \nBut with the rise of industrialization there are fewer and\nfewer craftsmen. One of the biggest remaining groups is\ncomputer programmers.A programmer can sit down in front of a computer and\ncreate wealth. A good piece of software is, in itself, \na valuable thing.\nThere is no manufacturing to confuse the issue. Those\ncharacters you type \nare a complete, finished product.\nIf someone sat down and wrote a web\nbrowser that didn't suck (a fine idea, by the way), the world\nwould be that much richer.\n[5b]Everyone in a company works together to create\nwealth, in the sense of making more things people want.\nMany of the employees (e.g. the people in the mailroom or\nthe personnel department) work at one remove from the \nactual making of stuff. Not the programmers. They\nliterally think the product, one line at a time.\nAnd so it's clearer to programmers that wealth is something\nthat's made, rather than being distributed, like slices of a\npie, by some imaginary Daddy.It's also obvious to programmers that there are huge variations\nin the rate at which wealth is created. At Viaweb we had one\nprogrammer who was a sort of monster of productivity. \nI remember watching what he did one long day and estimating that\nhe had added several hundred thousand dollars\nto the market value of the company. \nA great programmer, on a roll, could \ncreate a million dollars worth of wealth in a couple weeks.\nA mediocre programmer over the same period will generate zero or\neven negative wealth (e.g. by introducing bugs).This is\nwhy so many of the best programmers are libertarians.\nIn our world, you sink or swim, and there are no excuses.\nWhen those far removed from the creation of wealth-- undergraduates,\nreporters, politicians-- hear\nthat the richest 5% of the people have \nhalf the total wealth, they tend to think injustice!\nAn experienced programmer would be more likely to think\nis that all? The top 5% of programmers\nprobably write 99% of the good software.Wealth can be created without being sold. Scientists, till\nrecently at least, effectively donated the wealth they \ncreated. We are all richer for knowing about penicillin,\nbecause we're less likely to die from infections. Wealth\nis whatever people want, and not dying is certainly something\nwe want. Hackers often donate their work by \nwriting open source software that anyone can use for free.\nI am much the richer for the operating system\nFreeBSD, which I'm running on the computer I'm using now,\nand so is Yahoo, which runs it on all their servers.What a Job IsIn industrialized countries, people belong to one institution or\nanother at least until their twenties. After all those years you get\nused to the idea of belonging to a group of people who all get up\nin the morning, go to some set of buildings, and do things that they\ndo not, ordinarily, enjoy doing. Belonging to such a group becomes\npart of your identity: name, age, role, institution.\nIf you have to introduce yourself, or\nsomeone else describes you, it will be as something like, John\nSmith, age 10, a student at such and such elementary school, or\nJohn Smith, age 20, a student at such and such college.When John Smith finishes school he is expected to get a job. And\nwhat getting a job seems to mean is joining another institution.\nSuperficially it's a lot like college. You pick the companies you\nwant to work for and apply to join them. If one likes you, you\nbecome a member of this new group. You get up in the morning and\ngo to a new set of buildings, and do things that you do not, ordinarily,\nenjoy doing. There are a few differences: life is not as much fun,\nand you get paid, instead of paying, as you did in college. But\nthe similarities feel greater than the differences. John Smith is\nnow John Smith, 22, a software developer at such and such corporation.In fact John Smith's\nlife has changed more than he realizes. Socially, a company\nlooks much like college, but the deeper you go into the\nunderlying reality, the more different it gets.What a company does, and has to do if it wants to continue to\nexist, is earn money. And the way most companies make money\nis by creating wealth. Companies can be so specialized that this\nsimilarity is concealed, but it is not only manufacturing \ncompanies that create wealth. A big component of wealth is\nlocation. \nRemember that magic machine that could\nmake you cars and cook you dinner and so on? It would not be\nso useful if it delivered your dinner to a random location\nin central Asia. \nIf wealth means what people want, companies that move\nthings also create wealth. Ditto for\nmany other kinds of companies that don't make anything\nphysical. Nearly all companies exist to do something people\nwant.And that's what you do, as well, when you go to work for a company.\nBut here there is another layer that tends to obscure the underlying\nreality. In a company, the work you do is averaged together with\na lot of other people's. \nYou may not even be aware you're doing something people\nwant. Your contribution may be indirect. But the company as a\nwhole must be giving people something they want, or they won't make\nany money. And if they are paying you x dollars a year, then on\naverage you must be contributing at least x dollars a year worth\nof work, or the company will be spending more than it makes,\nand will go out of business.Someone graduating from college thinks, and is told, that he needs\nto get a job, as if the important thing were becoming a member of \nan institution. A more direct way to put it would be: you need to\nstart doing something people want. You don't\nneed to\njoin a company to do that. All a company is is a group of people\nworking together to do something people want. It's doing something people\nwant that matters, not joining the group. \n[6]For most people the \nbest plan probably is to go to work for some existing\ncompany. But it is a good idea to understand what's happening \nwhen you do this. A job means doing something people want,\naveraged together with everyone else in that company.Working HarderThat averaging gets to be a problem.\nI think the single biggest problem afflicting large companies is the \ndifficulty of assigning a value to each person's work. \nFor the most part they punt. In a\nbig company you get paid a fairly predictable salary for working \nfairly hard. You're expected not to be obviously incompetent or\nlazy, but you're not expected to devote your whole life to your\nwork.It turns out, though, that there are economies of scale in how much of your\nlife you devote to your work. In the right kind of business, \nsomeone who really devoted himself to work could generate ten or\neven a hundred times as much wealth as an average\nemployee. A programmer, for example, instead of chugging along\nmaintaining and updating an existing piece of software, could write\na whole new piece of software, and with it create a new source of\nrevenue.Companies are not set up to reward people who want to do this. \nYou can't go to your boss and say, I'd like to start working ten\ntimes as hard, so will you please pay me ten times as much? For\none thing, the official fiction is that you are already working as\nhard as you can. But a more serious problem is that the company\nhas no way of measuring the value of your work.Salesmen are an exception. It's easy \nto measure how much revenue they generate, and they're\nusually paid a percentage of it. If a salesman wants to work harder,\nhe can just start doing it, and he will automatically\nget paid proportionally more.There is one other job besides sales where big companies can\nhire first-rate people: in the top management jobs. \nAnd for the same reason: their performance can\nbe measured. The top managers are\nheld responsible for the performance of the entire company.\nBecause an ordinary employee's performance can't usually\nbe measured, he is not expected to do\nmore than put in a solid effort. Whereas top management, like\nsalespeople, have to actually come up with the numbers.\nThe CEO of a company that tanks cannot plead that he put in \na solid effort. If the company does badly, he's done badly.A company that could pay all its employees so straightforwardly \nwould be enormously successful. Many employees would work harder\nif they could get paid for it. More importantly,\nsuch a company would attract people who wanted to work\nespecially hard. \nIt would crush its competitors.Unfortunately, companies can't pay everyone like salesmen. Salesmen\nwork alone. Most employees' work is tangled together. Suppose\na company makes some kind of consumer gadget. The \nengineers build a reliable gadget with all kinds of new features;\nthe industrial designers design a beautiful case for it; and then\nthe marketing people convince everyone that\nit's something they've got to have. How do you know how much of the\ngadget's sales are due to each group's efforts? Or, for that\nmatter, how much is due to the creators of past gadgets that gave\nthe company a reputation for quality? There's no way to \nuntangle all their contributions. Even if you could read the minds\nof the consumers, you'd find these factors were all blurred together.If you want to go faster, it's a problem to have your work\ntangled together with a large number of other people's. In a \nlarge group, your performance is not separately measurable-- and \nthe rest of the group slows you down.Measurement and LeverageTo get rich you need to get yourself in a situation with two\nthings, measurement and leverage. You need to be in a\nposition where your performance can be measured, or there is\nno way to get paid more by doing more. And you have to\nhave leverage, in the sense that the decisions you make have \na big effect.Measurement alone is not enough. An example of a job with\nmeasurement but not leverage is doing piecework in a\nsweatshop. Your performance is measured and you get paid \naccordingly, but you have no scope for decisions. The only\ndecision you get to make is how fast you work, and that\ncan probably only increase your earnings by a factor\nof two or three.An example of a job with both measurement and leverage would\nbe lead actor in a movie. Your performance can be measured in the\ngross of the movie. And you have leverage in the sense that your\nperformance can make or break it.CEOs also have both measurement and leverage. They're measured,\nin that the performance of the company is their performance.\nAnd they have leverage in that their decisions\nset the whole company moving in one direction or another.I think everyone who gets rich by their own efforts will be\nfound to be in a situation with measurement and leverage. \nEveryone I can think of does: CEOs, movie stars, \nhedge fund managers, professional athletes. A good hint to the\npresence of leverage is the possibility of failure.\nUpside must be balanced by downside, so if there is \nbig potential for gain there must also be a terrifying\npossibility of loss. CEOs, stars, fund managers, and athletes\nall live with the sword hanging over their heads;\nthe moment they start to suck, they're out. If you're in\na job that feels safe, you are not going to get rich,\nbecause if there is no danger there is almost certainly no leverage.But you don't have to become a CEO or a movie star to\nbe in a situation with measurement and leverage. All you \nneed to do is be part of a small group working on a\nhard problem.Smallness = MeasurementIf you can't measure the value of the work done by individual \nemployees, you can get close. You can measure the value\nof the work done by small groups.One level at which you can accurately measure the revenue\ngenerated by employees is at the level of the whole company. \nWhen the company is small, you are thereby fairly close to \nmeasuring the contributions of individual employees. A viable\nstartup might only have ten employees, which puts you within a\nfactor of ten of measuring individual effort.Starting or joining a startup is thus as close as most\npeople can get to saying to one's boss, I want to work ten times\nas hard, so please pay me ten times as much. There are two\ndifferences: you're not saying it to your boss, but directly to the\ncustomers (for whom your boss is only a proxy after all), and\nyou're not doing it individually, but along with a small group\nof other ambitious people.It will, ordinarily, be a group. Except in a few unusual kinds\nof work, like acting or writing books, you can't be a company \nof one person. \nAnd the people you work with had better be good, because it's their work that\nyours is going to be averaged with.A big company is like a giant galley driven by a thousand rowers.\nTwo things keep the speed of the\ngalley down. One is that individual rowers don't see any\nresult from working harder. \nThe other is that, in a group of a\nthousand people, the average rower is likely to be\npretty average.If you took ten people at random out of the big galley and\nput them in a boat by themselves, they could probably go \nfaster. They would have both carrot and stick to motivate \nthem. An energetic rower would be encouraged by the thought\nthat he could have a visible effect on the speed of\nthe boat. And if someone was lazy, the others would be more likely\nto notice and complain.But the real advantage of the ten-man boat shows when \nyou take the ten best rowers out of the big galley\nand put them in a boat together. They will have all\nthe extra motivation that comes from being in a small group.\nBut more importantly, by selecting that small a group\nyou can get the best rowers. Each one will be in\nthe top 1%. It's a much better deal for them to average \ntheir work together with a small group of their peers than to \naverage it with everyone.That's the real point of startups. Ideally, you are getting\ntogether with a group of other people who also want to work\na lot harder, and get paid a lot more, than they would in\na big company. And because startups tend to get founded \nby self-selecting groups of ambitious people who already \nknow one another (at least by reputation), the level of \nmeasurement is more precise than you get from smallness alone.\nA startup is not merely ten people, but ten people like you.Steve Jobs once said that the success or failure of a startup\ndepends on the first ten employees. I agree. If \nanything, it's more like the first five.\nBeing small is not, in itself, what makes startups kick butt, \nbut rather that small groups can be select.\nYou don't want small in the sense of a\nvillage, but small in the sense of an all-star team.The larger a group, the closer its average member will be to the average\nfor the population as a whole. So all other things being\nequal, a very able person in a big company is probably\ngetting a bad deal, because his performance is dragged down by\nthe overall lower performance of the others. Of course,\nall other things often are not equal: the able person may \nnot care about money, or may prefer the stability of a large\ncompany. But a very able person who does care about money\nwill ordinarily do better to go off and work with a small\ngroup of peers.Technology = LeverageStartups offer anyone a way to be in a situation with\nmeasurement and leverage.\nThey allow measurement because they're small,\nand they offer leverage because they\nmake money by inventing new technology.What is technology? It's technique. It's the way \nwe all do things. And when\nyou discover a new way to do things, its value is multiplied\nby all the people who use it. It is the proverbial fishing\nrod, rather than the fish. That's the difference between a\nstartup and a restaurant or a barber shop. You fry eggs or cut \nhair one customer at a time. Whereas if \nyou solve a technical problem that a lot of people care about,\nyou help everyone who uses your solution. \nThat's leverage.If you look at history, it seems that most people\nwho got rich by creating wealth did it by developing\nnew technology. You just can't fry eggs or cut hair fast enough.\nWhat made the Florentines rich in 1200 \nwas the discovery of new techniques for making the high-tech \nproduct of the time, fine woven cloth. What made the\nDutch rich in 1600 was the discovery of shipbuilding and\nnavigation techniques that enabled them to dominate the seas\nof the Far East.Fortunately there is a natural fit between smallness and\nsolving hard problems. The leading edge of technology moves\nfast. Technology that's valuable today could be worthless\nin a couple years. Small companies are more at home in this\nworld, because they don't have layers of bureaucracy to\nslow them down.\nAlso, technical advances tend to come from unorthodox approaches,\nand small companies are less constrained by convention.Big companies can develop technology. They just can't do it\nquickly. Their size makes them slow and prevents\nthem from rewarding employees for the extraordinary\neffort required. So in practice big companies only get to develop \ntechnology in fields where large capital requirements prevent startups from\ncompeting with them, like microprocessors, power plants, \nor passenger aircraft. And even in those fields they depend heavily\non startups for components and ideas.It's obvious that biotech or software startups exist to solve\nhard technical problems, but \nI think it will also be found to be true \nin businesses that don't seem to be about technology. McDonald's,\nfor example, grew big by designing a system, the McDonald's \nfranchise, that could then be reproduced at will all over the \nface of the earth. A McDonald's franchise is controlled by rules\nso precise that it is practically\na piece of software. Write once, run everywhere.\nDitto for Wal-Mart. Sam Walton got rich not by being a \nretailer, but by designing a new kind of store.Use difficulty as a guide not just in selecting the overall\naim of your company, but also at decision points along the way.\nAt Viaweb one of our rules of thumb was run upstairs.\nSuppose you are a little, nimble guy being chased by a big,\nfat, bully. You open a door and find yourself in a \nstaircase. Do you go up or down? I say up. The\nbully can probably run downstairs as fast as you can.\nGoing upstairs his bulk will be more of a disadvantage.\nRunning upstairs is hard for you but even harder for him.What this meant in practice was that we deliberately sought \nhard problems. If there were two features we could add to our\nsoftware, both equally valuable in proportion to their difficulty,\nwe'd always take the harder one. Not just because it was \nmore valuable, but because it was harder.\nWe delighted in forcing bigger, slower competitors\nto follow us over difficult ground.\nLike guerillas, startups prefer the difficult terrain of the\nmountains, where the troops of the central government\ncan't follow. I can remember times when we were just\nexhausted after wrestling all day with some horrible technical\nproblem. And I'd be delighted, because something that was \nhard for us would be impossible for our competitors.This is not just a good way to run a startup. It's what\na startup is.\nVenture capitalists know about this and have a phrase for it:\nbarriers to entry. If you go to a VC with a new \nidea and ask him to invest in it, one of the first things\nhe'll ask is, how hard would this be for someone else to \ndevelop? That is, how much difficult ground\nhave you put between yourself and potential pursuers? \n[7]\nAnd you had better have a convincing explanation of why \nyour technology would be hard to duplicate. Otherwise as\nsoon as some big company becomes aware of it, they'll make\ntheir own, and with their brand name, capital, and\ndistribution clout, they'll take away your market overnight.\nYou'd be like guerillas caught in the open field by regular\narmy forces.One way to put up barriers to entry is through patents. \nBut patents may not provide much protection. \nCompetitors commonly find ways to work around a patent.\nAnd if they can't, they \nmay simply violate it and invite you to sue them.\nA big company is not afraid to be sued; it's an everyday thing\nfor them. They'll make sure that suing them is expensive and\ntakes a long time.\nEver heard of Philo Farnsworth? He invented\ntelevision. The reason you've never\nheard of him is that his company was not the one to make\nmoney from it. \n[8]\nThe company that did was RCA, and\nFarnsworth's reward for his efforts was a decade of\npatent litigation.Here, as so often, the best defense is a good offense. If\nyou can develop technology that's simply too hard for\ncompetitors to duplicate, you don't need to rely on other\ndefenses. Start by picking a hard problem, and\nthen at every decision point, take the harder choice. \n[9]The Catch(es)If it were simply a matter of working harder than \nan ordinary employee and getting paid proportionately, it would\nobviously be a good deal to start a startup. Up to a point it\nwould be more fun. I don't think many people \nlike the slow pace of big companies, the interminable meetings,\nthe water-cooler conversations, the clueless middle managers,\nand so on.Unfortunately there are a couple catches. One is that you\ncan't choose the point on the curve that you want to inhabit.\nYou can't decide, for example, that you'd like to work just\ntwo or three times as hard, and get paid that much more. When\nyou're running a startup, your competitors decide how\nhard you work. And they pretty much all make the same decision:\nas hard as you possibly can.The other catch is that the payoff is only on average proportionate\nto your productivity. There is, as I said before, a large\nrandom multiplier in the success of any company. So in\npractice the deal is not that you're 30 times as productive and get \npaid 30 times as much. It is that you're 30 times as productive,\nand get paid between zero and a thousand times as much.\nIf the mean is 30x, the median is probably zero.\nMost startups tank, and not just the dogfood \nportals we all heard about during\nthe Internet Bubble. It's common for a startup\nto be developing a genuinely good product, take slightly\ntoo long to do it, run out of money, and have to shut down.A startup is like a mosquito. A bear can absorb a hit and a crab\nis armored against one, but a mosquito is designed for one thing:\nto score. No energy is wasted on defense. The defense of mosquitos, \nas a species, is that there are a lot of them, but this is little \nconsolation to the individual mosquito.Startups, like mosquitos, tend to be an all-or-nothing proposition.\nAnd you don't generally know which of the two you're going to\nget till the last minute. \nViaweb came close to tanking several times. Our trajectory\nwas like a sine wave. Fortunately we got bought at\nthe top of the cycle, but it was damned close. While we were\nvisiting Yahoo in California to talk about selling the company\nto them, we had to borrow a conference room to reassure\nan investor who was about to back out of a new round of funding \nthat we needed to stay alive.The all-or-nothing aspect of startups was not something we wanted.\nViaweb's hackers were all extremely risk-averse.\nIf there had been some way just to work super hard and get\npaid for it, without having a lottery mixed in, we would have\nbeen delighted. We would have much preferred a 100% chance of\n$1 million to a 20% chance of $10 million, even though \ntheoretically the second is worth twice as much. Unfortunately,\nthere is not currently any space in the business world where\nyou can get the first deal.The closest you can get is by\nselling your startup in the early stages, giving up upside \n(and risk) for a smaller but guaranteed payoff. We had a \nchance to do this, and stupidly, as we then thought, let it slip by.\nAfter that we became comically eager to sell.\nFor the next year or so,\nif anyone expressed the slightest curiosity about Viaweb\nwe would try to sell them the company. But there were no takers,\nso we had to keep going.It would have been a bargain to \nbuy us at an early stage, but companies doing acquisitions are not\nlooking for bargains. A company big enough to acquire \nstartups will be big enough to be fairly conservative, and \nwithin the company the people in charge of acquisitions will\nbe among the more conservative, because they are likely to be\nbusiness school types who joined the company late. \nThey would rather overpay for a safe choice. So\nit is easier to sell an established startup, even at a large\npremium, than an early-stage one.Get UsersI think it's a good idea to get bought, if you can. Running a\nbusiness is different from growing one.\nIt is just as well to let a big company take over once you reach \ncruising altitude. It's\nalso financially wiser, because selling allows you to diversify.\nWhat would you think of a financial advisor who put all his\nclient's assets into one volatile stock?How do you get bought? Mostly by doing the same things \nyou'd do if you didn't intend to sell the company. Being \nprofitable, for example. But getting bought is also an art\nin its own right, and one that we spent a lot of time trying\nto master.Potential buyers will\nalways delay if they can. The hard part about getting\nbought is getting them to act. For most people, the most powerful motivator\nis not the hope of gain, but the fear of loss. For potential\nacquirers, the most powerful motivator is the prospect that \none of their competitors will buy you. This, as we found, \ncauses CEOs to take red-eyes. \nThe second biggest is the worry that, if they don't buy you \nnow, you'll continue to grow rapidly and will cost more to\nacquire later, or even become a competitor.In both cases, what it all comes down to is users. \nYou'd think that a company about to buy you would do a lot of\nresearch and decide for themselves how valuable your technology\nwas. Not at all. What they go by is the number of users you\nhave.In effect, acquirers assume the customers know who has the\nbest technology. And this is not as stupid as it sounds. Users \nare the only real proof that you've created wealth. Wealth is \nwhat people want, and if people aren't using your software,\nmaybe it's not just because you're bad at marketing. Maybe it's\nbecause you haven't made what they want.Venture capitalists have a list of danger signs to watch out for.\nNear the top is the company run by techno-weenies who are \nobsessed with solving interesting technical problems, instead\nof making users happy. In a startup, you're not just trying to\nsolve problems. You're trying to solve problems that \nusers care about.So I think you should make users the test, just as \nacquirers do. Treat a startup as an optimization problem \nin which performance is measured by number of users. As anyone\nwho has tried to optimize software knows, the key is measurement.\nWhen you try to guess where your program is slow, and what would\nmake it faster, you almost always guess wrong.Number of users may not be the perfect test, but it will \nbe very close. It's what acquirers care about. It's what \nrevenues depend on. \nIt's what makes competitors unhappy.\nIt's what impresses reporters, and potential\nnew users. Certainly it's a better test than your a priori\nnotions of what problems are important to solve, no matter how\ntechnically adept you are.Among other things, treating a startup as an optimization\nproblem will help you avoid another\npitfall that VCs worry about, and rightly-- taking a long time\nto develop a product. Now we can recognize this as something\nhackers already know to avoid: premature optimization. Get a version \n1.0 out there as soon as you can. Until you have some users to\nmeasure, you're optimizing based on guesses.The ball you need to keep your eye on here is the underlying\nprinciple that wealth is what people want. If you plan to get \nrich by creating wealth, you have to know what people want. \nSo few businesses really pay attention to making customers happy.\nHow often do you walk into a store, or call a company on the\nphone, with a feeling of dread in the back of your mind?\nWhen you hear \"your call is important to us, please stay on\nthe line,\" do you think, oh good, now everything will be all right?A restaurant can afford to serve the occasional burnt dinner.\nBut in technology, you cook one thing and that's what everyone\neats. So any difference between what people want and what\nyou deliver is multiplied. \nYou please or annoy\ncustomers wholesale. The closer you can get to what they want,\nthe more wealth you generate.Wealth and PowerMaking wealth is not the only way to get rich. For most of\nhuman history it has not even been the most common. Until\na few centuries ago,\nthe main sources of wealth were mines, slaves and serfs,\nland, and cattle,\nand the only ways to acquire these rapidly were by inheritance,\nmarriage, conquest, or confiscation. \nNaturally wealth had a bad reputation.Two things changed. The first was the rule of law. For most of the world's\nhistory, if you did somehow accumulate a fortune, the ruler or his \nhenchmen \nwould find a way to steal it.\nBut in medieval Europe something new happened.\nA new class of merchants and manufacturers\nbegan to collect in towns. \n[10]\nTogether they were able to withstand the local feudal\nlord. So \nfor the first time in our history, the bullies stopped stealing the\nnerds' lunch money.\nThis was naturally a great incentive,\nand possibly indeed the main cause of the second big change,\nindustrialization.A great deal has been written about the causes of the Industrial \nRevolution. But surely a necessary, if not sufficient, condition\nwas that people who made fortunes be able to enjoy them in peace.\n[11]\nOne piece of evidence is what happened to countries\nthat tried to return to the old model, like the Soviet\nUnion, and to a lesser extent Britain under the labor\ngovernments of the 1960s and early 1970s. Take away the incentive\nof wealth, and technical innovation grinds to a halt.Remember what a startup is, economically: \na way of saying, I want to work faster. Instead of accumulating\nmoney slowly by being paid a regular wage for fifty years, I \nwant to get it over with as soon as possible. So governments\nthat forbid you to accumulate wealth are in effect decreeing\nthat you work slowly. They're willing to let you earn $3 million over\nfifty years, but they're not willing to let you work so hard that\nyou can do it in two. They are like\nthe corporate boss that you can't go to and say, I want to work\nten times as hard, so please pay me ten times a much.\nExcept this is not a boss you can escape by starting your own\ncompany.The problem with working slowly is not just that technical\ninnovation happens slowly. It's that it tends not to happen at all.\nIt's only when you're deliberately looking for hard problems,\nas a way to use speed to the greatest advantage, that you take\non this kind of project. Developing new technology is a \npain in the ass. It is, as Edison said, one percent \ninspiration and ninety-nine percent perspiration. \nWithout the incentive of wealth, no one wants to do it.\nEngineers will work on sexy projects like fighter planes and moon\nrockets for ordinary salaries, but more mundane technologies\nlike light bulbs or semiconductors have to be developed by entrepreneurs.Startups\nare not just something that happened in Silicon Valley in \nthe last couple decades. Since it became possible to\nget rich by creating wealth, everyone who has done it has\nused essentially the same recipe: measurement and leverage,\nwhere measurement comes from working with a small\ngroup, and leverage from developing new techniques.\nThe recipe was the same in Florence in 1200 as it is \nin Santa Clara today.Understanding this may help to answer an important question:\nwhy Europe grew so powerful.\nWas it something about the geography of \nEurope? Was it that Europeans are somehow racially superior?\nWas it their religion? The answer (or at least\nthe proximate cause) may be that the\nEuropeans \nrode on the crest of a powerful new idea: allowing those who\nmade a lot of money to keep it.Once you're allowed to do that, \npeople who want to get rich can do it by generating\nwealth instead of stealing it.\nThe resulting technological growth translates not only \ninto wealth but into military power. The theory that led to\nthe stealth plane was developed by a Soviet mathematician.\nBut because the Soviet Union didn't have a computer industry,\nit remained for them a theory;\nthey didn't have hardware capable of executing the calculations\nfast enough to design an actual airplane.In that respect the Cold War teaches the same lesson as\nWorld War II and, for that matter, most wars in recent history.\nDon't let a ruling\nclass of warriors and politicians squash the entrepreneurs.\nThe same recipe that makes individuals rich\nmakes countries powerful. Let the nerds keep their lunch\nmoney, and you rule the world.Notes[1]\nOne valuable thing you tend to get only in startups is\nuninterruptability. Different kinds of\nwork have different time quanta. Someone proofreading a\nmanuscript\ncould probably be interrupted every fifteen minutes\nwith little loss of productivity. But the time quantum for\nhacking is very long: it might take an hour just to load\na problem into your head. So the\ncost of having someone from personnel\ncall you about a form you forgot to fill out can be huge.This is why hackers give you such a baleful stare as they\nturn from their screen to answer your question. Inside\ntheir heads a giant house of cards is tottering.The mere possibility of being interrupted deters hackers\nfrom starting hard projects. This is why they\ntend to work late at night, and why it's next to impossible\nto write great software in a cubicle (except late at night).One great advantage of startups is that they don't yet have\nany of the people who interrupt you. There is no personnel\ndepartment, and thus no form nor anyone to call you about it.[2]\nFaced with the idea that people working for startups might be\n20 or 30 times as productive as those working for large companies,\nexecutives at large companies will naturally wonder, how could\nI get the people working for me to do that? The answer is\nsimple: pay them to.Internally most companies are run like Communist states.\nIf you believe in free markets, why not turn your company into one?Hypothesis: A company will be maximally profitable when each\nemployee is paid in proportion to the wealth they generate.[3]\nUntil recently even governments sometimes didn't grasp the\ndistinction between money and wealth. Adam\nSmith (Wealth of Nations, v:i) mentions several\nthat tried to preserve their\n\"wealth\" by forbidding the export of gold or silver.\nBut having more of the medium of exchange would not make\na country richer; if you have more money chasing the same\namount of material wealth, the only result is higher prices.[4]\nThere are many senses of the word \"wealth,\" not all of\nthem material. I'm not trying to make a deep philosophical\npoint here about which\nis the true kind. I'm writing about one specific,\nrather technical sense of the word \"wealth.\" What\npeople will give you money for.\nThis is an interesting sort of wealth to study, because\nit is the kind that prevents you from starving.\nAnd what people will give you money for depends on them,\nnot you.When you're starting a business,\nit's easy to slide into thinking that customers\nwant what you do. During the Internet Bubble I talked\nto a woman who, because she liked the outdoors, was\nstarting an \"outdoor portal.\" You know what\nkind of business you should start if you like\nthe outdoors? One to recover data from crashed hard disks.What's the connection? None at all. Which is precisely my point.\nIf you want\nto create wealth (in the narrow technical sense of not\nstarving) then you should be especially skeptical about any\nplan that centers on things you like doing.\nThat is where your idea of what's valuable is least\nlikely to coincide with other people's.[5]\nIn the average car restoration you probably do make everyone\nelse microscopically poorer, by doing a small amount of damage to\nthe environment. While environmental costs should be taken\ninto account, they don't\nmake wealth a zero-sum game. For example, if you repair\na machine that's broken because a part has come unscrewed,\nyou create wealth with no environmental cost.[5b]\nThis essay was written before Firefox.[6]\nMany people feel confused and depressed in\ntheir early twenties. Life seemed so much more fun in college.\nWell, of course it was. Don't be fooled by the surface similarities.\nYou've gone from guest to servant.\nIt's possible to have fun in this new world. \nAmong other things, you now get to go behind the doors that say\n\"authorized personnel only.\"\nBut the change is a shock at first, and all the worse\nif you're not consciously aware of it.[7]\nWhen VCs asked us how long it would take another startup\nto duplicate our software, we used to reply that they probably\nwouldn't be able to at all. I think this made us seem naive,\nor liars.[8]\nFew technologies have one clear inventor. So as\na rule, if you know the \"inventor\" of something\n(the telephone, the assembly line, the airplane, \nthe light bulb, the transistor) it is because their\ncompany made money from it, and the company's PR people worked\nhard to spread the story. If you don't know who invented\nsomething (the automobile, the television, the computer,\nthe jet engine, the laser), it's because other companies\nmade all the money.[9]\nThis is a good plan for life in general.\nIf you have two choices, choose the harder.\nIf you're trying to decide whether to go out running or\nsit home and watch TV, go running.\nProbably the reason this trick works so well is that\nwhen you have two choices and one is harder, the\nonly reason you're even considering the other is laziness.\nYou know in the back of your mind what's the right thing\nto do, and this trick merely forces you to acknowledge it.[10]\nIt is probably no accident that the middle class\nfirst appeared in northern Italy and the low countries,\nwhere there were no strong central governments. These two\nregions were the richest of their time and became the twin\ncenters from which Renaissance civilization radiated.\nIf they no longer play that role, it is because\nother places, like the United States, have been truer to the\nprinciples they discovered.[11]\nIt may indeed be a sufficient condition. But if so, why didn't\nthe Industrial Revolution happen earlier? Two possible (and\nnot incompatible) answers: (a) It did. \nThe Industrial Revolution was one in a series.\n(b) Because in medieval towns, monopolies\nand guild regulations initially slowed the development of new means\nof production.\n\nComment on this essay." }, { "path": "data/PaulGrahamEssays/web20.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nNovember 2005Does \"Web 2.0\" mean anything? Till recently I thought it didn't,\nbut the truth turns out to be more complicated. Originally, yes,\nit was meaningless. Now it seems to have acquired a meaning. And\nyet those who dislike the term are probably right, because if it\nmeans what I think it does, we don't need it.I first heard the phrase \"Web 2.0\" in the name of the Web 2.0\nconference in 2004. At the time it was supposed to mean using \"the\nweb as a platform,\" which I took to refer to web-based applications.\n[1]So I was surprised at a conference this summer when Tim O'Reilly\nled a session intended to figure out a definition of \"Web 2.0.\"\nDidn't it already mean using the web as a platform? And if it\ndidn't already mean something, why did we need the phrase at all?OriginsTim says the phrase \"Web 2.0\" first\narose in \"a brainstorming session between\nO'Reilly and Medialive International.\" What is Medialive International?\n\"Producers of technology tradeshows and conferences,\" according to\ntheir site. So presumably that's what this brainstorming session\nwas about. O'Reilly wanted to organize a conference about the web,\nand they were wondering what to call it.I don't think there was any deliberate plan to suggest there was a\nnew version of the web. They just wanted to make the point\nthat the web mattered again. It was a kind of semantic deficit\nspending: they knew new things were coming, and the \"2.0\" referred\nto whatever those might turn out to be.And they were right. New things were coming. But the new version\nnumber led to some awkwardness in the short term. In the process\nof developing the pitch for the first conference, someone must have\ndecided they'd better take a stab at explaining what that \"2.0\"\nreferred to. Whatever it meant, \"the web as a platform\" was at\nleast not too constricting.The story about \"Web 2.0\" meaning the web as a platform didn't live\nmuch past the first conference. By the second conference, what\n\"Web 2.0\" seemed to mean was something about democracy. At least,\nit did when people wrote about it online. The conference itself\ndidn't seem very grassroots. It cost $2800, so the only people who\ncould afford to go were VCs and people from big companies.And yet, oddly enough, Ryan Singel's article\nabout the conference in Wired News spoke of \"throngs of\ngeeks.\" When a friend of mine asked Ryan about this, it was news\nto him. He said he'd originally written something like \"throngs\nof VCs and biz dev guys\" but had later shortened it just to \"throngs,\"\nand that this must have in turn been expanded by the editors into\n\"throngs of geeks.\" After all, a Web 2.0 conference would presumably\nbe full of geeks, right?Well, no. There were about 7. Even Tim O'Reilly was wearing a \nsuit, a sight so alien I couldn't parse it at first. I saw\nhim walk by and said to one of the O'Reilly people \"that guy looks\njust like Tim.\"\"Oh, that's Tim. He bought a suit.\"\nI ran after him, and sure enough, it was. He explained that he'd\njust bought it in Thailand.The 2005 Web 2.0 conference reminded me of Internet trade shows\nduring the Bubble, full of prowling VCs looking for the next hot\nstartup. There was that same odd atmosphere created by a large \nnumber of people determined not to miss out. Miss out on what?\nThey didn't know. Whatever was going to happen—whatever Web 2.0\nturned out to be.I wouldn't quite call it \"Bubble 2.0\" just because VCs are eager\nto invest again. The Internet is a genuinely big deal. The bust\nwas as much an overreaction as\nthe boom. It's to be expected that once we started to pull out of\nthe bust, there would be a lot of growth in this area, just as there\nwas in the industries that spiked the sharpest before the Depression.The reason this won't turn into a second Bubble is that the IPO\nmarket is gone. Venture investors\nare driven by exit strategies. The reason they were funding all \nthose laughable startups during the late 90s was that they hoped\nto sell them to gullible retail investors; they hoped to be laughing\nall the way to the bank. Now that route is closed. Now the default\nexit strategy is to get bought, and acquirers are less prone to\nirrational exuberance than IPO investors. The closest you'll get \nto Bubble valuations is Rupert Murdoch paying $580 million for \nMyspace. That's only off by a factor of 10 or so.1. AjaxDoes \"Web 2.0\" mean anything more than the name of a conference\nyet? I don't like to admit it, but it's starting to. When people\nsay \"Web 2.0\" now, I have some idea what they mean. And the fact\nthat I both despise the phrase and understand it is the surest proof\nthat it has started to mean something.One ingredient of its meaning is certainly Ajax, which I can still\nonly just bear to use without scare quotes. Basically, what \"Ajax\"\nmeans is \"Javascript now works.\" And that in turn means that\nweb-based applications can now be made to work much more like desktop\nones.As you read this, a whole new generation\nof software is being written to take advantage of Ajax. There\nhasn't been such a wave of new applications since microcomputers\nfirst appeared. Even Microsoft sees it, but it's too late for them\nto do anything more than leak \"internal\" \ndocuments designed to give the impression they're on top of this\nnew trend.In fact the new generation of software is being written way too\nfast for Microsoft even to channel it, let alone write their own\nin house. Their only hope now is to buy all the best Ajax startups\nbefore Google does. And even that's going to be hard, because\nGoogle has as big a head start in buying microstartups as it did\nin search a few years ago. After all, Google Maps, the canonical\nAjax application, was the result of a startup they bought.So ironically the original description of the Web 2.0 conference\nturned out to be partially right: web-based applications are a big\ncomponent of Web 2.0. But I'm convinced they got this right by \naccident. The Ajax boom didn't start till early 2005, when Google\nMaps appeared and the term \"Ajax\" was coined.2. DemocracyThe second big element of Web 2.0 is democracy. We now have several\nexamples to prove that amateurs can \nsurpass professionals, when they have the right kind of system to \nchannel their efforts. Wikipedia\nmay be the most famous. Experts have given Wikipedia middling\nreviews, but they miss the critical point: it's good enough. And \nit's free, which means people actually read it. On the web, articles\nyou have to pay for might as well not exist. Even if you were \nwilling to pay to read them yourself, you can't link to them. \nThey're not part of the conversation.Another place democracy seems to win is in deciding what counts as\nnews. I never look at any news site now except Reddit.\n[2]\n I know if something major\nhappens, or someone writes a particularly interesting article, it \nwill show up there. Why bother checking the front page of any\nspecific paper or magazine? Reddit's like an RSS feed for the whole\nweb, with a filter for quality. Similar sites include Digg, a technology news site that's\nrapidly approaching Slashdot in popularity, and del.icio.us, the collaborative\nbookmarking network that set off the \"tagging\" movement. And whereas\nWikipedia's main appeal is that it's good enough and free, these\nsites suggest that voters do a significantly better job than human\neditors.The most dramatic example of Web 2.0 democracy is not in the selection\nof ideas, but their production. \nI've noticed for a while that the stuff I read on individual people's\nsites is as good as or better than the stuff I read in newspapers\nand magazines. And now I have independent evidence: the top links\non Reddit are generally links to individual people's sites rather \nthan to magazine articles or news stories.My experience of writing\nfor magazines suggests an explanation. Editors. They control the\ntopics you can write about, and they can generally rewrite whatever\nyou produce. The result is to damp extremes. Editing yields 95th\npercentile writing—95% of articles are improved by it, but 5% are\ndragged down. 5% of the time you get \"throngs of geeks.\"On the web, people can publish whatever they want. Nearly all of\nit falls short of the editor-damped writing in print publications.\nBut the pool of writers is very, very large. If it's large enough,\nthe lack of damping means the best writing online should surpass \nthe best in print.\n[3] \nAnd now that the web has evolved mechanisms\nfor selecting good stuff, the web wins net. Selection beats damping,\nfor the same reason market economies beat centrally planned ones.Even the startups are different this time around. They are to the \nstartups of the Bubble what bloggers are to the print media. During\nthe Bubble, a startup meant a company headed by an MBA that was \nblowing through several million dollars of VC money to \"get big\nfast\" in the most literal sense. Now it means a smaller, younger, more technical group that just \ndecided to make something great. They'll decide later if they want \nto raise VC-scale funding, and if they take it, they'll take it on\ntheir terms.3. Don't Maltreat UsersI think everyone would agree that democracy and Ajax are elements\nof \"Web 2.0.\" I also see a third: not to maltreat users. During\nthe Bubble a lot of popular sites were quite high-handed with users.\nAnd not just in obvious ways, like making them register, or subjecting\nthem to annoying ads. The very design of the average site in the \nlate 90s was an abuse. Many of the most popular sites were loaded\nwith obtrusive branding that made them slow to load and sent the\nuser the message: this is our site, not yours. (There's a physical\nanalog in the Intel and Microsoft stickers that come on some\nlaptops.)I think the root of the problem was that sites felt they were giving\nsomething away for free, and till recently a company giving anything\naway for free could be pretty high-handed about it. Sometimes it\nreached the point of economic sadism: site owners assumed that the\nmore pain they caused the user, the more benefit it must be to them. \nThe most dramatic remnant of this model may be at salon.com, where \nyou can read the beginning of a story, but to get the rest you have\nsit through a movie.At Y Combinator we advise all the startups we fund never to lord\nit over users. Never make users register, unless you need to in\norder to store something for them. If you do make users register, \nnever make them wait for a confirmation link in an email; in fact,\ndon't even ask for their email address unless you need it for some\nreason. Don't ask them any unnecessary questions. Never send them\nemail unless they explicitly ask for it. Never frame pages you\nlink to, or open them in new windows. If you have a free version \nand a pay version, don't make the free version too restricted. And\nif you find yourself asking \"should we allow users to do x?\" just \nanswer \"yes\" whenever you're unsure. Err on the side of generosity.In How to Start a Startup I advised startups\nnever to let anyone fly under them, meaning never to let any other\ncompany offer a cheaper, easier solution. Another way to fly low \nis to give users more power. Let users do what they want. If you \ndon't and a competitor does, you're in trouble.iTunes is Web 2.0ish in this sense. Finally you can buy individual\nsongs instead of having to buy whole albums. The recording industry\nhated the idea and resisted it as long as possible. But it was\nobvious what users wanted, so Apple flew under the labels.\n[4]\nThough really it might be better to describe iTunes as Web 1.5. \nWeb 2.0 applied to music would probably mean individual bands giving\naway DRMless songs for free.The ultimate way to be nice to users is to give them something for\nfree that competitors charge for. During the 90s a lot of people \nprobably thought we'd have some working system for micropayments \nby now. In fact things have gone in the other direction. The most \nsuccessful sites are the ones that figure out new ways to give stuff\naway for free. Craigslist has largely destroyed the classified ad\nsites of the 90s, and OkCupid looks likely to do the same to the\nprevious generation of dating sites.Serving web pages is very, very cheap. If you can make even a \nfraction of a cent per page view, you can make a profit. And\ntechnology for targeting ads continues to improve. I wouldn't be\nsurprised if ten years from now eBay had been supplanted by an \nad-supported freeBay (or, more likely, gBay).Odd as it might sound, we tell startups that they should try to\nmake as little money as possible. If you can figure out a way to\nturn a billion dollar industry into a fifty million dollar industry,\nso much the better, if all fifty million go to you. Though indeed,\nmaking things cheaper often turns out to generate more money in the\nend, just as automating things often turns out to generate more\njobs.The ultimate target is Microsoft. What a bang that balloon is going\nto make when someone pops it by offering a free web-based alternative \nto MS Office.\n[5]\nWho will? Google? They seem to be taking their\ntime. I suspect the pin will be wielded by a couple of 20 year old\nhackers who are too naive to be intimidated by the idea. (How hard\ncan it be?)The Common ThreadAjax, democracy, and not dissing users. What do they all have in \ncommon? I didn't realize they had anything in common till recently,\nwhich is one of the reasons I disliked the term \"Web 2.0\" so much.\nIt seemed that it was being used as a label for whatever happened\nto be new—that it didn't predict anything.But there is a common thread. Web 2.0 means using the web the way\nit's meant to be used. The \"trends\" we're seeing now are simply\nthe inherent nature of the web emerging from under the broken models\nthat got imposed on it during the Bubble.I realized this when I read an interview with\nJoe Kraus, the co-founder of Excite.\n[6]\n\n Excite really never got the business model right at all. We fell \n into the classic problem of how when a new medium comes out it\n adopts the practices, the content, the business models of the old\n medium—which fails, and then the more appropriate models get\n figured out.\n\nIt may have seemed as if not much was happening during the years\nafter the Bubble burst. But in retrospect, something was happening:\nthe web was finding its natural angle of repose. The democracy \ncomponent, for example—that's not an innovation, in the sense of\nsomething someone made happen. That's what the web naturally tends\nto produce.Ditto for the idea of delivering desktop-like applications over the\nweb. That idea is almost as old as the web. But the first time \naround it was co-opted by Sun, and we got Java applets. Java has\nsince been remade into a generic replacement for C++, but in 1996\nthe story about Java was that it represented a new model of software.\nInstead of desktop applications, you'd run Java \"applets\" delivered\nfrom a server.This plan collapsed under its own weight. Microsoft helped kill it,\nbut it would have died anyway. There was no uptake among hackers.\nWhen you find PR firms promoting\nsomething as the next development platform, you can be sure it's\nnot. If it were, you wouldn't need PR firms to tell you, because \nhackers would already be writing stuff on top of it, the way sites \nlike Busmonster used Google Maps as a\nplatform before Google even meant it to be one.The proof that Ajax is the next hot platform is that thousands of \nhackers have spontaneously started building things on top\nof it. Mikey likes it.There's another thing all three components of Web 2.0 have in common.\nHere's a clue. Suppose you approached investors with the following\nidea for a Web 2.0 startup:\n\n Sites like del.icio.us and flickr allow users to \"tag\" content\n with descriptive tokens. But there is also huge source of\n implicit tags that they ignore: the text within web links.\n Moreover, these links represent a social network connecting the \n individuals and organizations who created the pages, and by using\n graph theory we can compute from this network an estimate of the\n reputation of each member. We plan to mine the web for these \n implicit tags, and use them together with the reputation hierarchy\n they embody to enhance web searches.\n\nHow long do you think it would take them on average to realize that\nit was a description of Google?Google was a pioneer in all three components of Web 2.0: their core\nbusiness sounds crushingly hip when described in Web 2.0 terms, \n\"Don't maltreat users\" is a subset of \"Don't be evil,\" and of course\nGoogle set off the whole Ajax boom with Google Maps.Web 2.0 means using the web as it was meant to be used, and Google\ndoes. That's their secret. They're sailing with the wind, instead of sitting \nbecalmed praying for a business model, like the print media, or \ntrying to tack upwind by suing their customers, like Microsoft and \nthe record labels.\n[7]Google doesn't try to force things to happen their way. They try \nto figure out what's going to happen, and arrange to be standing \nthere when it does. That's the way to approach technology—and \nas business includes an ever larger technological component, the\nright way to do business.The fact that Google is a \"Web 2.0\" company shows that, while\nmeaningful, the term is also rather bogus. It's like the word\n\"allopathic.\" It just means doing things right, and it's a bad \nsign when you have a special word for that.\nNotes[1]\nFrom the conference\nsite, June 2004: \"While the first wave of the Web was closely \ntied to the browser, the second wave extends applications across \nthe web and enables a new generation of services and business\nopportunities.\" To the extent this means anything, it seems to be\nabout \nweb-based applications.[2]\nDisclosure: Reddit was funded by \nY Combinator. But although\nI started using it out of loyalty to the home team, I've become a\ngenuine addict. While we're at it, I'm also an investor in\n!MSFT, having sold all my shares earlier this year.[3]\nI'm not against editing. I spend more time editing than\nwriting, and I have a group of picky friends who proofread almost\neverything I write. What I dislike is editing done after the fact \nby someone else.[4]\nObvious is an understatement. Users had been climbing in through \nthe window for years before Apple finally moved the door.[5]\nHint: the way to create a web-based alternative to Office may\nnot be to write every component yourself, but to establish a protocol\nfor web-based apps to share a virtual home directory spread across\nmultiple servers. Or it may be to write it all yourself.[6]\nIn Jessica Livingston's\nFounders at\nWork.[7]\nMicrosoft didn't sue their customers directly, but they seem \nto have done all they could to help SCO sue them.Thanks to Trevor Blackwell, Sarah Harlin, Jessica Livingston, Peter\nNorvig, Aaron Swartz, and Jeff Weiner for reading drafts of this, and to the\nguys at O'Reilly and Adaptive Path for answering my questions." }, { "path": "data/PaulGrahamEssays/webstartups.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nOctober 2007(This essay is derived from a keynote at FOWA in October 2007.)There's something interesting happening right now. Startups are\nundergoing the same transformation that technology does when it becomes\ncheaper.It's a pattern we see over and over in technology. Initially\nthere's some device that's very expensive and made\nin small quantities. Then someone discovers how to make them cheaply; \nmany more get built; and as a result they can be used in new ways.Computers are a familiar example. When I was a kid, computers were\nbig, expensive machines built one at a time. Now they're a commodity.\nNow we can stick computers in everything.This pattern is very old. Most of the turning\npoints in economic history are instances of it. It happened to\nsteel in the 1850s, and to power in the 1780s.\nIt happened to cloth manufacture in the thirteenth century, generating\nthe wealth that later brought about the Renaissance. Agriculture\nitself was an instance of this pattern.Now as well as being produced by startups, this pattern\nis happening to startups. It's so cheap to start web startups\nthat orders of magnitudes more will be started. If the pattern\nholds true, that should cause dramatic changes.1. Lots of StartupsSo my first prediction about the future of web startups is pretty\nstraightforward: there will be a lot of them. When starting a\nstartup was expensive, you had to get the permission of investors\nto do it. Now the only threshold is courage.Even that threshold is getting lower, as people watch others take\nthe plunge and survive. In the last batch of startups we funded,\nwe had several founders who said they'd thought of applying before,\nbut weren't sure and got jobs instead. It was only after hearing\nreports of friends who'd done it that they decided to try it\nthemselves.Starting a startup is hard, but having a 9 to 5 job is hard too,\nand in some ways a worse kind of hard. In a startup you have lots\nof worries, but you don't have that feeling that your life is flying\nby like you do in a big company. Plus in a startup you could make\nmuch more money.As word spreads that startups work, the number may grow\nto a point that would now seem surprising.We now think of it as normal to have a job at a company, but this\nis the thinnest of historical veneers. Just two or three\nlifetimes ago, most people in what are now called industrialized\ncountries lived by farming. So while it may seem surprising to\npropose that large numbers of people will change the way they make\na living, it would be more surprising if they didn't.2. StandardizationWhen technology makes something dramatically cheaper, standardization\nalways follows. When you make things in large volumes you tend\nto standardize everything that doesn't need to change.At Y Combinator we still only have four people, so we try to\nstandardize everything. We could hire employees, but we want to be\nforced to figure out how to scale investing.We often tell startups to release a minimal version one quickly, \nthen let the needs of the users determine what to do\nnext. In essense, let the market design the product. We've\ndone the same thing ourselves. We think of the techniques we're\ndeveloping for dealing with large numbers of startups as like\nsoftware. Sometimes it literally is software, like \nHacker News and\nour application system.One of the most important things we've been working on standardizing\nare investment terms. Till now investment terms have been\nindividually negotiated.\nThis is a problem for founders, because it makes raising money\ntake longer and cost more in legal fees. So as well as using the\nsame paperwork for every deal we do, we've commissioned generic\nangel paperwork that all the startups we fund can use for future\nrounds.Some investors will still want to cook up their own deal terms.\nSeries A rounds, where you raise a million dollars or more, will\nbe custom deals for the forseeable future. But I think angel rounds\nwill start to be done mostly with standardized agreements. An angel\nwho wants to insert a bunch of complicated terms into the agreement\nis probably not one you want anyway.3. New Attitude to AcquisitionAnother thing I see starting to get standardized is acquisitions.\nAs the volume of startups increases, big companies will start to\ndevelop standardized procedures that make acquisitions little\nmore work than hiring someone.Google is the leader here, as in so many areas of technology. They\nbuy a lot of startups— more than most people realize, because they\nonly announce a fraction of them. And being Google, they're\nfiguring out how to do it efficiently.One problem they've solved is how to think about acquisitions. For\nmost companies, acquisitions still carry some stigma of inadequacy.\nCompanies do them because they have to, but there's usually some\nfeeling they shouldn't have to—that their own programmers should\nbe able to build everything they need.Google's example should cure the rest of the world of this idea.\nGoogle has by far the best programmers of any public technology\ncompany. If they don't have a problem doing acquisitions, the\nothers should have even less problem. However many Google does,\nMicrosoft should do ten times as many.One reason Google doesn't have a problem with acquisitions\nis that they know first-hand the quality of the people they can get\nthat way. Larry and Sergey only started Google after making the\nrounds of the search engines trying to sell their idea and finding\nno takers. They've been the guys coming in to visit the big\ncompany, so they know who might be sitting across that conference\ntable from them.4. Riskier Strategies are PossibleRisk is always proportionate to reward. The way to get really big\nreturns is to do things that seem crazy, like starting a new search\nengine in 1998, or turning down a billion dollar acquisition offer.This has traditionally been a problem in venture funding. Founders\nand investors have different attitudes to risk. Knowing that risk\nis on average proportionate to reward, investors like risky strategies,\nwhile founders, who don't have a big enough sample size to care\nwhat's true on average, tend to be more conservative.If startups are easy to start, this conflict goes away, because\nfounders can start them younger, when it's rational to take more\nrisk, and can start more startups total in their careers. When\nfounders can do lots of startups, they can start to look at the\nworld in the same portfolio-optimizing way as investors. And that\nmeans the overall amount of wealth created can be greater, because\nstrategies can be riskier.5. Younger, Nerdier FoundersIf startups become a cheap commodity, more people will be able to\nhave them, just as more people could have computers once microprocessors\nmade them cheap. And in particular, younger and more technical\nfounders will be able to start startups than could before.Back when it cost a lot to start a startup, you had to convince\ninvestors to let you do it. And that required very different skills\nfrom actually doing the startup. If investors were perfect judges,\nthe two would require exactly the same skills. But unfortunately\nmost investors are terrible judges. I know because I see behind\nthe scenes what an enormous amount of work it takes to raise money,\nand the amount of selling required in an industry is always inversely\nproportional to the judgement of the buyers.Fortunately, if startups get cheaper to start, there's another way\nto convince investors. Instead of going to venture capitalists\nwith a business plan and trying to convince them to fund it, you\ncan get a product launched on a few tens of thousands of dollars\nof seed money from us or your uncle, and approach them with a\nworking company instead of a plan for one. Then instead of\nhaving to seem smooth and confident, you can just point them to\nAlexa.This way of convincing investors is better suited to hackers, who\noften went into technology in part because they felt uncomfortable\nwith the amount of fakeness required in other fields.6. Startup Hubs Will PersistIt might seem that if startups get cheap to start, it will mean the\nend of startup hubs like Silicon Valley. If all you need to start\na startup is rent money, you should be able to do it anywhere.This is kind of true and kind of false. It's true that you can now\nstart a startup anywhere. But you have to do more with a\nstartup than just start it. You have to make it succeed. And that\nis more likely to happen in a startup hub.I've thought a lot about this question, and it seems to me the\nincreasing cheapness of web startups will if anything increase the\nimportance of startup hubs. The value of startup hubs, like centers\nfor any kind of business, lies in something very old-fashioned:\nface to face meetings. No technology in the immediate future will\nreplace walking down University Ave and running into a friend who\ntells you how to fix a bug that's been bothering you all weekend,\nor visiting a friend's startup down the street and ending up in a\nconversation with one of their investors.The question of whether to be in a startup hub is like the question\nof whether to take outside investment. The question is not whether\nyou need it, but whether it brings any advantage at all.\nBecause anything that brings an advantage will give your competitors\nan advantage over you if they do it and you don't. So if you hear\nsomeone saying \"we don't need to be in Silicon Valley,\" that use\nof the word \"need\" is a sign they're not even thinking about the\nquestion right.And while startup hubs are as powerful magnets as ever, the increasing\ncheapness of starting a startup means the particles they're attracting\nare getting lighter. A startup now can be just a pair of 22 year\nold guys. A company like that can move much more easily than one\nwith 10 people, half of whom have kids.We know because we make people move for Y Combinator, and it doesn't\nseem to be a problem. The advantage of being able to work together\nface to face for three months outweighs the inconvenience of moving.\nAsk anyone who's done it.The mobility of seed-stage startups means that seed funding is a\nnational business. One of the most common emails we get is from\npeople asking if we can help them set up a local clone of Y Combinator.\nBut this just wouldn't work. Seed funding isn't regional, just as\nbig research universities aren't.Is seed funding not merely national, but international? Interesting\nquestion. There are signs it may be. We've had an ongoing\nstream of founders from outside the US, and they tend to do\nparticularly well, because they're all people who were so determined\nto succeed that they were willing to move to another country to do\nit.The more mobile startups get, the harder it would be to start new \nsilicon valleys. If startups are mobile, the best local talent \nwill go to the real Silicon Valley,\nand all they'll get at the local one will be the people who didn't\nhave the energy to move.This is not a nationalistic idea, incidentally. It's cities that\ncompete, not countries. Atlanta is just as hosed as Munich.7. Better Judgement NeededIf the number of startups increases dramatically, then the people\nwhose job is to judge them are going to have to get better at\nit. I'm thinking particularly of investors and acquirers. We now\nget on the order of 1000 applications a year. What are we going\nto do if we get 10,000?That's actually an alarming idea. But we'll figure out some kind\nof answer. We'll have to. It will probably involve writing some\nsoftware, but fortunately we can do that.Acquirers will also have to get better at picking winners. \nThey generally do better than investors, because they pick\nlater, when there's more performance to measure. But even at the\nmost advanced acquirers, identifying companies to\nbuy is extremely ad hoc, and completing the acquisition often\ninvolves a great deal of unneccessary friction.I think acquirers may eventually have chief acquisition officers\nwho will both identify good acquisitions and make the deals happen.\nAt the moment those two functions are separate. Promising new\nstartups are often discovered by developers. If someone powerful\nenough wants to buy them, the deal is handed over to corp dev guys\nto negotiate. It would be better if both were combined in\none group, headed by someone with a technical background and some\nvision of what they wanted to accomplish. Maybe in the future big\ncompanies will have both a VP of Engineering responsible for\ntechnology developed in-house, and a CAO responsible for bringing\ntechnology in from outside.At the moment, there is no one within big companies who gets in\ntrouble when they buy a startup for $200 million that they could\nhave bought earlier for $20 million. There should start to be\nsomeone who gets in trouble for that.8. College Will ChangeIf the best hackers start their own companies after college\ninstead of getting jobs, that will change what happens in college.\nMost of these changes will be for the better. I think the experience\nof college is warped in a bad way by the expectation that afterward\nyou'll be judged by potential employers.One change will be in the meaning of \"after\ncollege,\" which will switch from when one graduates from college\nto when one leaves it. If you're starting your own company, why\ndo you need a degree? We don't encourage people to start startups\nduring college, but the best founders are certainly\ncapable of it. Some of the most successful companies we've funded\nwere started by undergrads.I grew up in a time where college degrees seemed really important,\nso I'm alarmed to be saying things like this, but there's nothing\nmagical about a degree. There's nothing that magically changes\nafter you take that last exam. The importance of degrees is due\nsolely to the administrative needs of large organizations. These\ncan certainly affect your life—it's hard to get into grad\nschool, or to get a work visa in the US, without an undergraduate\ndegree—but tests like this will matter less and\nless.As well as mattering less whether students get degrees, it will\nalso start to matter less where they go to college. In a startup\nyou're judged by users, and they don't care where you went to\ncollege. So in a world of startups, elite universities will play\nless of a role as gatekeepers. In the US it's a national scandal\nhow easily children of rich parents game college admissions.\nBut the way this problem ultimately gets solved may not be by\nreforming the universities but by going around them. We in the\ntechnology world are used to that sort of solution: you don't beat\nthe incumbents; you redefine the problem to make them irrelevant.The greatest value of universities is not the brand name or perhaps\neven the classes so much as the people you meet. If\nit becomes common to start a startup after college, students may start\ntrying to maximize this. Instead of focusing on getting\ninternships at companies they want to work for, they may start\nto focus on working with other students they want as cofounders.What students do in their classes will change too. Instead of\ntrying to get good grades to impress future employers, students\nwill try to learn things. We're talking about some pretty dramatic\nchanges here.9. Lots of CompetitorsIf it gets easier to start a startup, it's easier for competitors too. \nThat doesn't erase the advantage of\nincreased cheapness, however. You're not all playing a zero-sum\ngame. There's not some fixed number of startups that can succeed,\nregardless of how many are started.In fact, I don't think there's any limit to the number of startups\nthat could succeed. Startups succeed by creating wealth, which is\nthe satisfaction of people's desires. And people's desires seem\nto be effectively infinite, at least in the short term.What the increasing number of startups does mean is that you won't\nbe able to sit on a good idea. Other people have your idea, and\nthey'll be increasingly likely to do something about it.10. Faster AdvancesThere's a good side to that, at least for consumers of\ntechnology. If people get right to work implementing ideas instead\nof sitting on them, technology will evolve faster.Some kinds of innovations happen a company at a time, like the\npunctuated equilibrium model of evolution. There are some kinds\nof ideas that are so threatening that it's hard for big companies\neven to think of them. Look at what a hard time Microsoft is\nhaving discovering web apps. They're like a character in a movie\nthat everyone in the audience can see something bad is about to\nhappen to, but who can't see it himself. The big innovations\nthat happen a company at a time will obviously happen faster if\nthe rate of new companies increases.But in fact there will be a double speed increase. People won't\nwait as long to act on new ideas, but also those ideas will\nincreasingly be developed within startups rather than big companies.\nWhich means technology will evolve faster per company as well.Big companies are just not a good place to make things happen fast.\nI talked recently to a founder whose startup had been acquired by\na big company. He was a precise sort of guy, so he'd measured their\nproductivity before and after. He counted lines of code, which can\nbe a dubious measure, but in this case was meaningful because it\nwas the same group of programmers. He found they were one thirteenth\nas productive after the acquisition.The company that bought them was not a particularly stupid one.\nI think what he was measuring was mostly the cost of bigness. I\nexperienced this myself, and his number sounds about right. There's\nsomething about big companies that just sucks the energy out of\nyou.Imagine what all that energy could do if it were put to use. There\nis an enormous latent capacity in the world's hackers that most\npeople don't even realize is there. That's the main reason we do\nY Combinator: to let loose all this energy by making it easy for\nhackers to start their own startups.A Series of TubesThe process of starting startups is currently like the plumbing in\nan old house. The pipes are narrow and twisty, and there are leaks\nin every joint. In the future this mess will gradually be replaced\nby a single, huge pipe. The water will still have to get from A\nto B, but it will get there faster and without the risk of spraying\nout through some random leak.This will change a lot of things for the better. In a big, straight\npipe like that, the force of being measured by one's performance\nwill propagate back through the whole system. Performance is always\nthe ultimate test, but there are so many kinks in the plumbing now\nthat most people are insulated from it most of the time. So you\nend up with a world in which high school students think they need\nto get good grades to get into elite colleges, and college students\nthink they need to get good grades to impress employers, within\nwhich the employees waste most of their time in political battles,\nand from which consumers have to buy anyway because there are so\nfew choices. Imagine if that sequence became a big, straight pipe.\nThen the effects of being measured by performance would propagate\nall the way back to high school, flushing out all the arbitrary\nstuff people are measured by now. That is the future of web startups.Thanks to Brian Oberkirch and Simon Willison for inviting me to \nspeak, and the crew at Carson Systems for making everything run smoothly." }, { "path": "data/PaulGrahamEssays/weird.txt", "content": "August 2021When people say that in their experience all programming languages\nare basically equivalent, they're making a statement not about\nlanguages but about the kind of programming they've done.99.5% of programming consists of gluing together calls to library\nfunctions. All popular languages are equally good at this. So one\ncan easily spend one's whole career operating in the intersection\nof popular programming languages.But the other .5% of programming is disproportionately interesting.\nIf you want to learn what it consists of, the weirdness of weird\nlanguages is a good clue to follow.Weird languages aren't weird by accident. Not the good ones, at\nleast. The weirdness of the good ones usually implies the existence\nof some form of programming that's not just the usual gluing together\nof library calls.A concrete example: Lisp macros. Lisp macros seem weird even to\nmany Lisp programmers. They're not only not in the intersection of\npopular languages, but by their nature would be hard to implement\nproperly in a language without turning it into a dialect of\nLisp. And macros are definitely evidence of techniques that go\nbeyond glue programming. For example, solving problems by first\nwriting a language for problems of that type, and then writing\nyour specific application in it. Nor is this all you can do with\nmacros; it's just one region in a space of program-manipulating\ntechniques that even now is far from fully explored.So if you want to expand your concept of what programming can be,\none way to do it is by learning weird languages. Pick a language\nthat most programmers consider weird but whose median user is smart,\nand then focus on the differences between this language and the\nintersection of popular languages. What can you say in this language\nthat would be impossibly inconvenient to say in others? In the\nprocess of learning how to say things you couldn't previously say,\nyou'll probably be learning how to think things you couldn't\npreviously think.\nThanks to Trevor Blackwell, Patrick Collison, Daniel Gackle, Amjad\nMasad, and Robert Morris for reading drafts of this.\n" }, { "path": "data/PaulGrahamEssays/whyyc.txt", "content": "March 2006, rev August 2009Yesterday one of the founders we funded asked me why we started \nY\nCombinator. Or more precisely, he asked if we'd started YC mainly\nfor fun.Kind of, but not quite. It is enormously fun to be able to work\nwith Rtm and Trevor again. I missed that after we sold Viaweb, and\nfor all the years after I always had a background process running,\nlooking for something we could do together. There is definitely\nan aspect of a band reunion to Y Combinator. Every couple days I\nslip and call it \"Viaweb.\"Viaweb we started very explicitly to make money. I was sick of\nliving from one freelance project to the next, and decided to just\nwork as hard as I could till I'd made enough to solve the problem\nonce and for all. Viaweb was sometimes fun, but it wasn't designed\nfor fun, and mostly it wasn't. I'd be surprised if any startup is.\nAll startups are mostly schleps.The real reason we started Y Combinator is neither selfish nor\nvirtuous. We didn't start it mainly to make money; we have no idea\nwhat our average returns might be, and won't know for years. Nor\ndid we start YC mainly to help out young would-be founders, though\nwe do like the idea, and comfort ourselves occasionally with the\nthought that if all our investments tank, we will thus have been\ndoing something unselfish. (It's oddly nondeterministic.)The real reason we started Y Combinator is one probably only a\nhacker would understand. We did it because it seems such a great\nhack. There are thousands of smart people who could start companies\nand don't, and with a relatively small amount of force applied at\njust the right place, we can spring on the world a stream of new\nstartups that might otherwise not have existed.In a way this is virtuous, because I think startups are a good\nthing. But really what motivates us is the completely amoral desire\nthat would motivate any hacker who looked at some complex device\nand realized that with a tiny tweak he could make it run more\nefficiently. In this case, the device is the world's economy, which\nfortunately happens to be open source." }, { "path": "data/PaulGrahamEssays/wisdom.txt", "content": "February 2007A few days ago I finally figured out something I've wondered about\nfor 25 years: the relationship between wisdom and intelligence.\nAnyone can see they're not the same by the number of people who are\nsmart, but not very wise. And yet intelligence and wisdom do seem\nrelated. How?What is wisdom? I'd say it's knowing what to do in a lot of\nsituations. I'm not trying to make a deep point here about the\ntrue nature of wisdom, just to figure out how we use the word. A\nwise person is someone who usually knows the right thing to do.And yet isn't being smart also knowing what to do in certain\nsituations? For example, knowing what to do when the teacher tells\nyour elementary school class to add all the numbers from 1 to 100?\n[1]Some say wisdom and intelligence apply to different types of\nproblems—wisdom to human problems and intelligence to abstract\nones. But that isn't true. Some wisdom has nothing to do with\npeople: for example, the wisdom of the engineer who knows certain\nstructures are less prone to failure than others. And certainly\nsmart people can find clever solutions to human problems as well\nas abstract ones. \n[2]Another popular explanation is that wisdom comes from experience\nwhile intelligence is innate. But people are not simply wise in\nproportion to how much experience they have. Other things must\ncontribute to wisdom besides experience, and some may be innate: a\nreflective disposition, for example.Neither of the conventional explanations of the difference between\nwisdom and intelligence stands up to scrutiny. So what is the\ndifference? If we look at how people use the words \"wise\" and\n\"smart,\" what they seem to mean is different shapes of performance.Curve\"Wise\" and \"smart\" are both ways of saying someone knows what to\ndo. The difference is that \"wise\" means one has a high average\noutcome across all situations, and \"smart\" means one does spectacularly\nwell in a few. That is, if you had a graph in which the x axis\nrepresented situations and the y axis the outcome, the graph of the\nwise person would be high overall, and the graph of the smart person\nwould have high peaks.The distinction is similar to the rule that one should judge talent\nat its best and character at its worst. Except you judge intelligence\nat its best, and wisdom by its average. That's how the two are\nrelated: they're the two different senses in which the same curve\ncan be high.So a wise person knows what to do in most situations, while a smart\nperson knows what to do in situations where few others could. We\nneed to add one more qualification: we should ignore cases where\nsomeone knows what to do because they have inside information. \n[3]\nBut aside from that, I don't think we can get much more specific\nwithout starting to be mistaken.Nor do we need to. Simple as it is, this explanation predicts, or\nat least accords with, both of the conventional stories about the\ndistinction between wisdom and intelligence. Human problems are\nthe most common type, so being good at solving those is key in\nachieving a high average outcome. And it seems natural that a\nhigh average outcome depends mostly on experience, but that dramatic\npeaks can only be achieved by people with certain rare, innate\nqualities; nearly anyone can learn to be a good swimmer, but to be\nan Olympic swimmer you need a certain body type.This explanation also suggests why wisdom is such an elusive concept:\nthere's no such thing. \"Wise\" means something—that one is\non average good at making the right choice. But giving the name\n\"wisdom\" to the supposed quality that enables one to do that doesn't\nmean such a thing exists. To the extent \"wisdom\" means anything,\nit refers to a grab-bag of qualities as various as self-discipline,\nexperience, and empathy. \n[4]Likewise, though \"intelligent\" means something, we're asking for\ntrouble if we insist on looking for a single thing called \"intelligence.\"\nAnd whatever its components, they're not all innate. We use the\nword \"intelligent\" as an indication of ability: a smart person can\ngrasp things few others could. It does seem likely there's some\ninborn predisposition to intelligence (and wisdom too), but this\npredisposition is not itself intelligence.One reason we tend to think of intelligence as inborn is that people\ntrying to measure it have concentrated on the aspects of it that\nare most measurable. A quality that's inborn will obviously be\nmore convenient to work with than one that's influenced by experience,\nand thus might vary in the course of a study. The problem comes\nwhen we drag the word \"intelligence\" over onto what they're measuring.\nIf they're measuring something inborn, they can't be measuring\nintelligence. Three year olds aren't smart. When we describe one\nas smart, it's shorthand for \"smarter than other three year olds.\"SplitPerhaps it's a technicality to point out that a predisposition to\nintelligence is not the same as intelligence. But it's an important\ntechnicality, because it reminds us that we can become smarter,\njust as we can become wiser.The alarming thing is that we may have to choose between the two.If wisdom and intelligence are the average and peaks of the same\ncurve, then they converge as the number of points on the curve\ndecreases. If there's just one point, they're identical: the average\nand maximum are the same. But as the number of points increases,\nwisdom and intelligence diverge. And historically the number of\npoints on the curve seems to have been increasing: our ability is\ntested in an ever wider range of situations.In the time of Confucius and Socrates, people seem to have regarded\nwisdom, learning, and intelligence as more closely related than we\ndo. Distinguishing between \"wise\" and \"smart\" is a modern habit.\n[5]\nAnd the reason we do is that they've been diverging. As knowledge\ngets more specialized, there are more points on the curve, and the\ndistinction between the spikes and the average becomes sharper,\nlike a digital image rendered with more pixels.One consequence is that some old recipes may have become obsolete.\nAt the very least we have to go back and figure out if they were\nreally recipes for wisdom or intelligence. But the really striking\nchange, as intelligence and wisdom drift apart, is that we may have\nto decide which we prefer. We may not be able to optimize for both\nsimultaneously.Society seems to have voted for intelligence. We no longer admire\nthe sage—not the way people did two thousand years ago. Now\nwe admire the genius. Because in fact the distinction we began\nwith has a rather brutal converse: just as you can be smart without\nbeing very wise, you can be wise without being very smart. That\ndoesn't sound especially admirable. That gets you James Bond, who\nknows what to do in a lot of situations, but has to rely on Q for\nthe ones involving math.Intelligence and wisdom are obviously not mutually exclusive. In\nfact, a high average may help support high peaks. But there are\nreasons to believe that at some point you have to choose between\nthem. One is the example of very smart people, who are so often\nunwise that in popular culture this now seems to be regarded as the\nrule rather than the exception. Perhaps the absent-minded professor\nis wise in his way, or wiser than he seems, but he's not wise in\nthe way Confucius or Socrates wanted people to be. \n[6]NewFor both Confucius and Socrates, wisdom, virtue, and happiness were\nnecessarily related. The wise man was someone who knew what the\nright choice was and always made it; to be the right choice, it had\nto be morally right; he was therefore always happy, knowing he'd\ndone the best he could. I can't think of many ancient philosophers\nwho would have disagreed with that, so far as it goes.\"The superior man is always happy; the small man sad,\" said Confucius.\n[7]Whereas a few years ago I read an interview with a mathematician\nwho said that most nights he went to bed discontented, feeling he\nhadn't made enough progress. \n[8]\nThe Chinese and Greek words we\ntranslate as \"happy\" didn't mean exactly what we do by it, but\nthere's enough overlap that this remark contradicts them.Is the mathematician a small man because he's discontented? No;\nhe's just doing a kind of work that wasn't very common in Confucius's\nday.Human knowledge seems to grow fractally. Time after time, something\nthat seemed a small and uninteresting area—experimental error,\neven—turns out, when examined up close, to have as much in\nit as all knowledge up to that point. Several of the fractal buds\nthat have exploded since ancient times involve inventing and\ndiscovering new things. Math, for example, used to be something a\nhandful of people did part-time. Now it's the career of thousands.\nAnd in work that involves making new things, some old rules don't\napply.Recently I've spent some time advising people, and there I find the\nancient rule still works: try to understand the situation as well\nas you can, give the best advice you can based on your experience,\nand then don't worry about it, knowing you did all you could. But\nI don't have anything like this serenity when I'm writing an essay.\nThen I'm worried. What if I run out of ideas? And when I'm writing,\nfour nights out of five I go to bed discontented, feeling I didn't\nget enough done.Advising people and writing are fundamentally different types of\nwork. When people come to you with a problem and you have to figure\nout the right thing to do, you don't (usually) have to invent\nanything. You just weigh the alternatives and try to judge which\nis the prudent choice. But prudence can't tell me what sentence\nto write next. The search space is too big.Someone like a judge or a military officer can in much of his work\nbe guided by duty, but duty is no guide in making things. Makers\ndepend on something more precarious: inspiration. And like most\npeople who lead a precarious existence, they tend to be worried,\nnot contented. In that respect they're more like the small man of\nConfucius's day, always one bad harvest (or ruler) away from\nstarvation. Except instead of being at the mercy of weather and\nofficials, they're at the mercy of their own imagination.LimitsTo me it was a relief just to realize it might be ok to be discontented.\nThe idea that a successful person should be happy has thousands of\nyears of momentum behind it. If I was any good, why didn't I have\nthe easy confidence winners are supposed to have? But that, I now\nbelieve, is like a runner asking \"If I'm such a good athlete, why\ndo I feel so tired?\" Good runners still get tired; they just get\ntired at higher speeds.People whose work is to invent or discover things are in the same\nposition as the runner. There's no way for them to do the best\nthey can, because there's no limit to what they could do. The\nclosest you can come is to compare yourself to other people. But\nthe better you do, the less this matters. An undergrad who gets\nsomething published feels like a star. But for someone at the top\nof the field, what's the test of doing well? Runners can at least\ncompare themselves to others doing exactly the same thing; if you\nwin an Olympic gold medal, you can be fairly content, even if you\nthink you could have run a bit faster. But what is a novelist to\ndo?Whereas if you're doing the kind of work in which problems are\npresented to you and you have to choose between several alternatives,\nthere's an upper bound on your performance: choosing the best every\ntime. In ancient societies, nearly all work seems to have been of\nthis type. The peasant had to decide whether a garment was worth\nmending, and the king whether or not to invade his neighbor, but\nneither was expected to invent anything. In principle they could\nhave; the king could have invented firearms, then invaded his\nneighbor. But in practice innovations were so rare that they weren't\nexpected of you, any more than goalkeepers are expected to score\ngoals. \n[9]\nIn practice, it seemed as if there was a correct decision\nin every situation, and if you made it you'd done your job perfectly,\njust as a goalkeeper who prevents the other team from scoring is\nconsidered to have played a perfect game.In this world, wisdom seemed paramount. \n[10]\nEven now, most people\ndo work in which problems are put before them and they have to\nchoose the best alternative. But as knowledge has grown more\nspecialized, there are more and more types of work in which people\nhave to make up new things, and in which performance is therefore\nunbounded. Intelligence has become increasingly important relative\nto wisdom because there is more room for spikes.RecipesAnother sign we may have to choose between intelligence and wisdom\nis how different their recipes are. Wisdom seems to come largely\nfrom curing childish qualities, and intelligence largely from\ncultivating them.Recipes for wisdom, particularly ancient ones, tend to have a\nremedial character. To achieve wisdom one must cut away all the\ndebris that fills one's head on emergence from childhood, leaving\nonly the important stuff. Both self-control and experience have\nthis effect: to eliminate the random biases that come from your own\nnature and from the circumstances of your upbringing respectively.\nThat's not all wisdom is, but it's a large part of it. Much of\nwhat's in the sage's head is also in the head of every twelve year\nold. The difference is that in the head of the twelve year old\nit's mixed together with a lot of random junk.The path to intelligence seems to be through working on hard problems.\nYou develop intelligence as you might develop muscles, through\nexercise. But there can't be too much compulsion here. No amount\nof discipline can replace genuine curiosity. So cultivating\nintelligence seems to be a matter of identifying some bias in one's\ncharacter—some tendency to be interested in certain types of\nthings—and nurturing it. Instead of obliterating your\nidiosyncrasies in an effort to make yourself a neutral vessel for\nthe truth, you select one and try to grow it from a seedling into\na tree.The wise are all much alike in their wisdom, but very smart people\ntend to be smart in distinctive ways.Most of our educational traditions aim at wisdom. So perhaps one\nreason schools work badly is that they're trying to make intelligence\nusing recipes for wisdom. Most recipes for wisdom have an element\nof subjection. At the very least, you're supposed to do what the\nteacher says. The more extreme recipes aim to break down your\nindividuality the way basic training does. But that's not the route\nto intelligence. Whereas wisdom comes through humility, it may\nactually help, in cultivating intelligence, to have a mistakenly\nhigh opinion of your abilities, because that encourages you to keep\nworking. Ideally till you realize how mistaken you were.(The reason it's hard to learn new skills late in life is not just\nthat one's brain is less malleable. Another probably even worse\nobstacle is that one has higher standards.)I realize we're on dangerous ground here. I'm not proposing the\nprimary goal of education should be to increase students' \"self-esteem.\"\nThat just breeds laziness. And in any case, it doesn't really fool\nthe kids, not the smart ones. They can tell at a young age that a\ncontest where everyone wins is a fraud.A teacher has to walk a narrow path: you want to encourage kids to\ncome up with things on their own, but you can't simply applaud\neverything they produce. You have to be a good audience: appreciative,\nbut not too easily impressed. And that's a lot of work. You have\nto have a good enough grasp of kids' capacities at different ages\nto know when to be surprised.That's the opposite of traditional recipes for education. Traditionally\nthe student is the audience, not the teacher; the student's job is\nnot to invent, but to absorb some prescribed body of material. (The\nuse of the term \"recitation\" for sections in some colleges is a\nfossil of this.) The problem with these old traditions is that\nthey're too much influenced by recipes for wisdom.DifferentI deliberately gave this essay a provocative title; of course it's\nworth being wise. But I think it's important to understand the\nrelationship between intelligence and wisdom, and particularly what\nseems to be the growing gap between them. That way we can avoid\napplying rules and standards to intelligence that are really meant\nfor wisdom. These two senses of \"knowing what to do\" are more\ndifferent than most people realize. The path to wisdom is through\ndiscipline, and the path to intelligence through carefully selected\nself-indulgence. Wisdom is universal, and intelligence idiosyncratic.\nAnd while wisdom yields calmness, intelligence much of the time\nleads to discontentment.That's particularly worth remembering. A physicist friend recently\ntold me half his department was on Prozac. Perhaps if we acknowledge\nthat some amount of frustration is inevitable in certain kinds\nof work, we can mitigate its effects. Perhaps we can box it up and\nput it away some of the time, instead of letting it flow together\nwith everyday sadness to produce what seems an alarmingly large\npool. At the very least, we can avoid being discontented about\nbeing discontented.If you feel exhausted, it's not necessarily because there's something\nwrong with you. Maybe you're just running fast.Notes[1]\nGauss was supposedly asked this when he was 10. Instead of\nlaboriously adding together the numbers like the other students,\nhe saw that they consisted of 50 pairs that each summed to 101 (100\n+ 1, 99 + 2, etc), and that he could just multiply 101 by 50 to get\nthe answer, 5050.[2]\nA variant is that intelligence is the ability to solve problems,\nand wisdom the judgement to know how to use those solutions. But\nwhile this is certainly an important relationship between wisdom\nand intelligence, it's not the distinction between them. Wisdom\nis useful in solving problems too, and intelligence can help in\ndeciding what to do with the solutions.[3]\nIn judging both intelligence and wisdom we have to factor out\nsome knowledge. People who know the combination of a safe will be\nbetter at opening it than people who don't, but no one would say\nthat was a test of intelligence or wisdom.But knowledge overlaps with wisdom and probably also intelligence.\nA knowledge of human nature is certainly part of wisdom. So where\ndo we draw the line?Perhaps the solution is to discount knowledge that at some point\nhas a sharp drop in utility. For example, understanding French\nwill help you in a large number of situations, but its value drops\nsharply as soon as no one else involved knows French. Whereas the\nvalue of understanding vanity would decline more gradually.The knowledge whose utility drops sharply is the kind that has\nlittle relation to other knowledge. This includes mere conventions,\nlike languages and safe combinations, and also what we'd call\n\"random\" facts, like movie stars' birthdays, or how to distinguish\n1956 from 1957 Studebakers.[4]\nPeople seeking some single thing called \"wisdom\" have been\nfooled by grammar. Wisdom is just knowing the right thing to do,\nand there are a hundred and one different qualities that help in\nthat. Some, like selflessness, might come from meditating in an\nempty room, and others, like a knowledge of human nature, might\ncome from going to drunken parties.Perhaps realizing this will help dispel the cloud of semi-sacred\nmystery that surrounds wisdom in so many people's eyes. The mystery\ncomes mostly from looking for something that doesn't exist. And\nthe reason there have historically been so many different schools\nof thought about how to achieve wisdom is that they've focused on\ndifferent components of it.When I use the word \"wisdom\" in this essay, I mean no more than\nwhatever collection of qualities helps people make the right choice\nin a wide variety of situations.[5]\nEven in English, our sense of the word \"intelligence\" is\nsurprisingly recent. Predecessors like \"understanding\" seem to\nhave had a broader meaning.[6]\nThere is of course some uncertainty about how closely the remarks\nattributed to Confucius and Socrates resemble their actual opinions.\nI'm using these names as we use the name \"Homer,\" to mean the\nhypothetical people who said the things attributed to them.[7]\nAnalects VII:36, Fung trans.Some translators use \"calm\" instead of \"happy.\" One source of\ndifficulty here is that present-day English speakers have a different\nidea of happiness from many older societies. Every language probably\nhas a word meaning \"how one feels when things are going well,\" but\ndifferent cultures react differently when things go well. We react\nlike children, with smiles and laughter. But in a more reserved\nsociety, or in one where life was tougher, the reaction might be a\nquiet contentment.[8]\nIt may have been Andrew Wiles, but I'm not sure. If anyone\nremembers such an interview, I'd appreciate hearing from you.[9]\nConfucius claimed proudly that he had never invented\nanything—that he had simply passed on an accurate account of\nancient traditions. [Analects VII:1] It's hard for us now to\nappreciate how important a duty it must have been in preliterate\nsocieties to remember and pass on the group's accumulated knowledge.\nEven in Confucius's time it still seems to have been the first duty\nof the scholar.[10]\nThe bias toward wisdom in ancient philosophy may be exaggerated\nby the fact that, in both Greece and China, many of the first\nphilosophers (including Confucius and Plato) saw themselves as\nteachers of administrators, and so thought disproportionately about\nsuch matters. The few people who did invent things, like storytellers,\nmust have seemed an outlying data point that could be ignored.Thanks to Trevor Blackwell, Sarah Harlin, Jessica Livingston,\nand Robert Morris for reading drafts of this." }, { "path": "data/PaulGrahamEssays/word.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nJanuary 2012A year ago I noticed a pattern in the least successful startups\nwe'd funded: they all seemed hard to talk to. It felt as if there\nwas some kind of wall between us. I could never quite tell if they\nunderstood what I was saying.This caught my attention because earlier we'd noticed a pattern\namong the most successful startups, and it seemed to hinge on a\ndifferent quality. We found the startups that did best were the\nones with the sort of founders about whom we'd say \"they can take\ncare of themselves.\" The startups that do best are fire-and-forget\nin the sense that all you have to do is give them a lead, and they'll\nclose it, whatever type of lead it is. When they're raising money,\nfor example, you can do the initial intros knowing that if you\nwanted to you could stop thinking about it at that point. You won't\nhave to babysit the round to make sure it happens. That type of\nfounder is going to come back with the money; the only question is\nhow much on what terms.It seemed odd that the outliers at the two ends of the spectrum\ncould be detected by what appeared to be unrelated tests. You'd\nexpect that if the founders at one end were distinguished by the\npresence of quality x, at the other end they'd be distinguished by\nlack of x. Was there some kind of inverse relation between\nresourcefulness and being hard to talk to?It turns out there is, and the key to the mystery is the old adage\n\"a word to the wise is sufficient.\" Because this phrase is not\nonly overused, but overused in an indirect way (by prepending the\nsubject to some advice), most people who've heard it don't know\nwhat it means. What it means is that if someone is wise, all you\nhave to do is say one word to them, and they'll understand immediately.\nYou don't have to explain in detail; they'll chase down all the\nimplications.In much the same way that all you have to do is give the right sort\nof founder a one line intro to a VC, and he'll chase down the money.\nThat's the connection. Understanding all the implications — even the\ninconvenient implications — of what someone tells you is a subset of\nresourcefulness. It's conversational resourcefulness.Like real world resourcefulness, conversational resourcefulness\noften means doing things you don't want to. Chasing down all the\nimplications of what's said to you can sometimes lead to uncomfortable\nconclusions. The best word to describe the failure to do so is\nprobably \"denial,\" though that seems a bit too narrow. A better\nway to describe the situation would be to say that the unsuccessful\nfounders had the sort of conservatism that comes from weakness.\nThey traversed idea space as gingerly as a very old person\ntraverses the physical world.\n[1]The unsuccessful founders weren't stupid. Intellectually they\nwere as capable as\nthe successful founders of following all the implications of what\none said to them. They just weren't eager to.So being hard to talk to was not what was killing the\nunsuccessful startups. It\nwas a sign of an underlying lack of resourcefulness. That's what\nwas killing them. As well as\nfailing to chase down the implications of what was said to them,\nthe unsuccessful founders would also fail to chase down funding,\nand users, and sources of new ideas. But the most immediate evidence\nI had that something was amiss was that I couldn't talk to them.Notes[1]\nA YC partner wrote:My feeling with the bad groups is that coming into office hours,\nthey've already decided what they're going to do and everything I\nsay is being put through an internal process in their heads, which\neither desperately tries to munge what I've said into something\nthat conforms with their decision or just outright dismisses it and\ncreates a rationalization for doing so. They may not even be conscious\nof this process but that's what I think is happening when you say\nsomething to bad groups and they have that glazed over look. I don't\nthink it's confusion or lack of understanding per se, it's this\ninternal process at work.With the good groups, you can tell that everything you say is being\nlooked at with fresh eyes and even if it's dismissed, it's because\nof some logical reason e.g. \"we already tried that\" or \"from speaking\nto our users that isn't what they'd like,\" etc. Those groups never\nhave that glazed over look.Thanks to Sam Altman, Patrick Collison, Aaron Iba, Jessica Livingston,\nRobert Morris, Harj Taggar, and Garry Tan for reading drafts of\nthis." }, { "path": "data/PaulGrahamEssays/words.txt", "content": "February 2022Writing about something, even something you know well, usually shows\nyou that you didn't know it as well as you thought. Putting ideas\ninto words is a severe test. The first words you choose are usually\nwrong; you have to rewrite sentences over and over to\nget them exactly right. And your ideas won't just be imprecise, but\nincomplete too. Half the ideas that end up in an essay will be ones\nyou thought of while you were writing it. Indeed, that's why I write\nthem.Once you publish something, the convention is that whatever you\nwrote was what you thought before you wrote it. These were your\nideas, and now you've expressed them. But you know this isn't true.\nYou know that putting your ideas into words changed them. And not\njust the ideas you published. Presumably there were others that\nturned out to be too broken to fix, and those you discarded instead.It's not just having to commit your ideas to specific words that\nmakes writing so exacting. The real test is reading what you've\nwritten. You have to pretend to be a neutral reader who knows nothing\nof what's in your head, only what you wrote. When he reads what you\nwrote, does it seem correct? Does it seem complete? If you make an\neffort, you can read your writing as if you were a complete stranger,\nand when you do the news is usually bad. It takes me many cycles\nbefore I can get an essay past the stranger. But the stranger is\nrational, so you always can, if you ask him what he needs. If he's\nnot satisfied because you failed to mention x or didn't qualify\nsome sentence sufficiently, then you mention x or add more\nqualifications. Happy now? It may cost you some nice sentences, but\nyou have to resign yourself to that. You just have to make them as\ngood as you can and still satisfy the stranger.This much, I assume, won't be that controversial. I think it will\naccord with the experience of anyone who has tried to write about\nanything nontrivial. There may exist people whose thoughts are so\nperfectly formed that they just flow straight into words. But I've\nnever known anyone who could do this, and if I met someone who said\nthey could, it would seem evidence of their limitations rather than\ntheir ability. Indeed, this is a trope in movies: the guy who claims\nto have a plan for doing some difficult thing, and who when questioned\nfurther, taps his head and says \"It's all up here.\" Everyone watching\nthe movie knows what that means. At best the plan is vague and\nincomplete. Very likely there's some undiscovered flaw that invalidates\nit completely. At best it's a plan for a plan.In precisely defined domains it's possible to form complete ideas\nin your head. People can play chess in their heads, for example.\nAnd mathematicians can do some amount of math in their heads, though\nthey don't seem to feel sure of a proof over a certain length till\nthey write it down. But this only seems possible with ideas you can\nexpress in a formal language. [1] Arguably what such people are\ndoing is putting ideas into words in their heads. I can to some\nextent write essays in my head. I'll sometimes think of a paragraph\nwhile walking or lying in bed that survives nearly unchanged in the\nfinal version. But really I'm writing when I do this. I'm doing the\nmental part of writing; my fingers just aren't moving as I do it.\n[2]You can know a great deal about something without writing about it.\nCan you ever know so much that you wouldn't learn more from trying\nto explain what you know? I don't think so. I've written about at\nleast two subjects I know well — Lisp hacking and startups\n— and in both cases I learned a lot from writing about them.\nIn both cases there were things I didn't consciously realize till\nI had to explain them. And I don't think my experience was anomalous.\nA great deal of knowledge is unconscious, and experts have if\nanything a higher proportion of unconscious knowledge than beginners.I'm not saying that writing is the best way to explore all ideas.\nIf you have ideas about architecture, presumably the best way to\nexplore them is to build actual buildings. What I'm saying is that\nhowever much you learn from exploring ideas in other ways, you'll\nstill learn new things from writing about them.Putting ideas into words doesn't have to mean writing, of course.\nYou can also do it the old way, by talking. But in my experience,\nwriting is the stricter test. You have to commit to a single, optimal\nsequence of words. Less can go unsaid when you don't have tone of\nvoice to carry meaning. And you can focus in a way that would seem\nexcessive in conversation. I'll often spend 2 weeks on an essay and\nreread drafts 50 times. If you did that in conversation\nit would seem evidence of some kind of\nmental disorder. \nIf you're lazy,\nof course, writing and talking are equally useless. But if you want\nto push yourself to get things right, writing is the steeper hill.\n[3]The reason I've spent so long establishing this rather obvious point\nis that it leads to another that many people will find shocking.\nIf writing down your ideas always makes them more precise and more\ncomplete, then no one who hasn't written about a topic has fully\nformed ideas about it. And someone who never writes has no fully\nformed ideas about anything nontrivial.It feels to them as if they do, especially if they're not in the\nhabit of critically examining their own thinking. Ideas can feel\ncomplete. It's only when you try to put them into words that you\ndiscover they're not. So if you never subject your ideas to that\ntest, you'll not only never have fully formed ideas, but also never\nrealize it.Putting ideas into words is certainly no guarantee that they'll be\nright. Far from it. But though it's not a sufficient condition, it\nis a necessary one.Notes[1] Machinery and\ncircuits are formal languages.[2] I thought of this\nsentence as I was walking down the street in Palo Alto.[3] There are two\nsenses of talking to someone: a strict sense in which the conversation\nis verbal, and a more general sense in which it can take any form,\nincluding writing. In the limit case (e.g. Seneca's letters),\nconversation in the latter sense becomes essay writing.It can be very useful to talk (in either sense) with other people\nas you're writing something. But a verbal conversation will never\nbe more exacting than when you're talking about something you're\nwriting. Thanks to Trevor Blackwell, Patrick\nCollison, and Robert Morris for reading drafts of this. " }, { "path": "data/PaulGrahamEssays/work.txt", "content": "January 2015My father is a mathematician. For most of my childhood he worked\nfor Westinghouse, modelling nuclear reactors.He was one of those lucky people who know early on what they want to\ndo. When you talk to him about his childhood, there's a clear\nwatershed at about age 12, when he \"got interested in maths.\"He\ngrew up in the small Welsh seacoast town of Pwllheli. As we retraced\nhis walk to school on Google Street View, he said that it had been\nnice growing up in the country.\"Didn't it get boring when you got to be about 15?\" I asked.\"No,\" he said, \"by then I was interested in maths.\"In another conversation he told me that what he really liked was\nsolving problems. To me the exercises at the end of each chapter\nin a math textbook represent work, or at best a way to reinforce\nwhat you learned in that chapter. To him the problems were the\nreward. The text of each chapter was just some advice about solving\nthem. He said that as soon as he got a new textbook he'd immediately\nwork out all the problems — to the slight annoyance of his teacher,\nsince the class was supposed to work through the book gradually.Few people know so early or so certainly what they want to work on.\nBut talking to my father reminded me of a heuristic the rest of us\ncan use. If something that seems like work to other people doesn't\nseem like work to you, that's something you're well suited for.\nFor example, a lot of programmers I know, including me, actually\nlike debugging. It's not something people tend to volunteer; one\nlikes it the way one likes popping zits. But you may have to like\ndebugging to like programming, considering the degree to which\nprogramming consists of it.The stranger your tastes seem to other people, the stronger evidence\nthey probably are of what you should do. When I was in college I\nused to write papers for my friends. It was quite interesting to\nwrite a paper for a class I wasn't taking. Plus they were always\nso relieved.It seemed curious that the same task could be painful to one person\nand pleasant to another, but I didn't realize at the time what this\nimbalance implied, because I wasn't looking for it. I didn't realize\nhow hard it can be to decide what you should work on, and that you\nsometimes have to figure it out from subtle clues, like a detective\nsolving a case in a mystery novel. So I bet it would help a lot\nof people to ask themselves about this explicitly. What seems like\nwork to other people that doesn't seem like work to you?\nThanks to Sam Altman, Trevor Blackwell, Jessica Livingston,\nRobert Morris, and my father for reading drafts of this." }, { "path": "data/PaulGrahamEssays/worked.txt", "content": "February 2021Before college the two main things I worked on, outside of school,\r\nwere writing and programming. I didn't write essays. I wrote what\r\nbeginning writers were supposed to write then, and probably still\r\nare: short stories. My stories were awful. They had hardly any plot,\r\njust characters with strong feelings, which I imagined made them\r\ndeep.The first programs I tried writing were on the IBM 1401 that our\r\nschool district used for what was then called \"data processing.\"\r\nThis was in 9th grade, so I was 13 or 14. The school district's\r\n1401 happened to be in the basement of our junior high school, and\r\nmy friend Rich Draves and I got permission to use it. It was like\r\na mini Bond villain's lair down there, with all these alien-looking\r\nmachines — CPU, disk drives, printer, card reader — sitting up\r\non a raised floor under bright fluorescent lights.The language we used was an early version of Fortran. You had to\r\ntype programs on punch cards, then stack them in the card reader\r\nand press a button to load the program into memory and run it. The\r\nresult would ordinarily be to print something on the spectacularly\r\nloud printer.I was puzzled by the 1401. I couldn't figure out what to do with\r\nit. And in retrospect there's not much I could have done with it.\r\nThe only form of input to programs was data stored on punched cards,\r\nand I didn't have any data stored on punched cards. The only other\r\noption was to do things that didn't rely on any input, like calculate\r\napproximations of pi, but I didn't know enough math to do anything\r\ninteresting of that type. So I'm not surprised I can't remember any\r\nprograms I wrote, because they can't have done much. My clearest\r\nmemory is of the moment I learned it was possible for programs not\r\nto terminate, when one of mine didn't. On a machine without\r\ntime-sharing, this was a social as well as a technical error, as\r\nthe data center manager's expression made clear.With microcomputers, everything changed. Now you could have a\r\ncomputer sitting right in front of you, on a desk, that could respond\r\nto your keystrokes as it was running instead of just churning through\r\na stack of punch cards and then stopping. \r\n[1]The first of my friends to get a microcomputer built it himself.\r\nIt was sold as a kit by Heathkit. I remember vividly how impressed\r\nand envious I felt watching him sitting in front of it, typing\r\nprograms right into the computer.Computers were expensive in those days and it took me years of\r\nnagging before I convinced my father to buy one, a TRS-80, in about\r\n1980. The gold standard then was the Apple II, but a TRS-80 was\r\ngood enough. This was when I really started programming. I wrote\r\nsimple games, a program to predict how high my model rockets would\r\nfly, and a word processor that my father used to write at least one\r\nbook. There was only room in memory for about 2 pages of text, so\r\nhe'd write 2 pages at a time and then print them out, but it was a\r\nlot better than a typewriter.Though I liked programming, I didn't plan to study it in college.\r\nIn college I was going to study philosophy, which sounded much more\r\npowerful. It seemed, to my naive high school self, to be the study\r\nof the ultimate truths, compared to which the things studied in\r\nother fields would be mere domain knowledge. What I discovered when\r\nI got to college was that the other fields took up so much of the\r\nspace of ideas that there wasn't much left for these supposed\r\nultimate truths. All that seemed left for philosophy were edge cases\r\nthat people in other fields felt could safely be ignored.I couldn't have put this into words when I was 18. All I knew at\r\nthe time was that I kept taking philosophy courses and they kept\r\nbeing boring. So I decided to switch to AI.AI was in the air in the mid 1980s, but there were two things\r\nespecially that made me want to work on it: a novel by Heinlein\r\ncalled The Moon is a Harsh Mistress, which featured an intelligent\r\ncomputer called Mike, and a PBS documentary that showed Terry\r\nWinograd using SHRDLU. I haven't tried rereading The Moon is a Harsh\r\nMistress, so I don't know how well it has aged, but when I read it\r\nI was drawn entirely into its world. It seemed only a matter of\r\ntime before we'd have Mike, and when I saw Winograd using SHRDLU,\r\nit seemed like that time would be a few years at most. All you had\r\nto do was teach SHRDLU more words.There weren't any classes in AI at Cornell then, not even graduate\r\nclasses, so I started trying to teach myself. Which meant learning\r\nLisp, since in those days Lisp was regarded as the language of AI.\r\nThe commonly used programming languages then were pretty primitive,\r\nand programmers' ideas correspondingly so. The default language at\r\nCornell was a Pascal-like language called PL/I, and the situation\r\nwas similar elsewhere. Learning Lisp expanded my concept of a program\r\nso fast that it was years before I started to have a sense of where\r\nthe new limits were. This was more like it; this was what I had\r\nexpected college to do. It wasn't happening in a class, like it was\r\nsupposed to, but that was ok. For the next couple years I was on a\r\nroll. I knew what I was going to do.For my undergraduate thesis, I reverse-engineered SHRDLU. My God\r\ndid I love working on that program. It was a pleasing bit of code,\r\nbut what made it even more exciting was my belief — hard to imagine\r\nnow, but not unique in 1985 — that it was already climbing the\r\nlower slopes of intelligence.I had gotten into a program at Cornell that didn't make you choose\r\na major. You could take whatever classes you liked, and choose\r\nwhatever you liked to put on your degree. I of course chose \"Artificial\r\nIntelligence.\" When I got the actual physical diploma, I was dismayed\r\nto find that the quotes had been included, which made them read as\r\nscare-quotes. At the time this bothered me, but now it seems amusingly\r\naccurate, for reasons I was about to discover.I applied to 3 grad schools: MIT and Yale, which were renowned for\r\nAI at the time, and Harvard, which I'd visited because Rich Draves\r\nwent there, and was also home to Bill Woods, who'd invented the\r\ntype of parser I used in my SHRDLU clone. Only Harvard accepted me,\r\nso that was where I went.I don't remember the moment it happened, or if there even was a\r\nspecific moment, but during the first year of grad school I realized\r\nthat AI, as practiced at the time, was a hoax. By which I mean the\r\nsort of AI in which a program that's told \"the dog is sitting on\r\nthe chair\" translates this into some formal representation and adds\r\nit to the list of things it knows.What these programs really showed was that there's a subset of\r\nnatural language that's a formal language. But a very proper subset.\r\nIt was clear that there was an unbridgeable gap between what they\r\ncould do and actually understanding natural language. It was not,\r\nin fact, simply a matter of teaching SHRDLU more words. That whole\r\nway of doing AI, with explicit data structures representing concepts,\r\nwas not going to work. Its brokenness did, as so often happens,\r\ngenerate a lot of opportunities to write papers about various\r\nband-aids that could be applied to it, but it was never going to\r\nget us Mike.So I looked around to see what I could salvage from the wreckage\r\nof my plans, and there was Lisp. I knew from experience that Lisp\r\nwas interesting for its own sake and not just for its association\r\nwith AI, even though that was the main reason people cared about\r\nit at the time. So I decided to focus on Lisp. In fact, I decided\r\nto write a book about Lisp hacking. It's scary to think how little\r\nI knew about Lisp hacking when I started writing that book. But\r\nthere's nothing like writing a book about something to help you\r\nlearn it. The book, On Lisp, wasn't published till 1993, but I wrote\r\nmuch of it in grad school.Computer Science is an uneasy alliance between two halves, theory\r\nand systems. The theory people prove things, and the systems people\r\nbuild things. I wanted to build things. I had plenty of respect for\r\ntheory — indeed, a sneaking suspicion that it was the more admirable\r\nof the two halves — but building things seemed so much more exciting.The problem with systems work, though, was that it didn't last.\r\nAny program you wrote today, no matter how good, would be obsolete\r\nin a couple decades at best. People might mention your software in\r\nfootnotes, but no one would actually use it. And indeed, it would\r\nseem very feeble work. Only people with a sense of the history of\r\nthe field would even realize that, in its time, it had been good.There were some surplus Xerox Dandelions floating around the computer\r\nlab at one point. Anyone who wanted one to play around with could\r\nhave one. I was briefly tempted, but they were so slow by present\r\nstandards; what was the point? No one else wanted one either, so\r\noff they went. That was what happened to systems work.I wanted not just to build things, but to build things that would\r\nlast.In this dissatisfied state I went in 1988 to visit Rich Draves at\r\nCMU, where he was in grad school. One day I went to visit the\r\nCarnegie Institute, where I'd spent a lot of time as a kid. While\r\nlooking at a painting there I realized something that might seem\r\nobvious, but was a big surprise to me. There, right on the wall,\r\nwas something you could make that would last. Paintings didn't\r\nbecome obsolete. Some of the best ones were hundreds of years old.And moreover this was something you could make a living doing. Not\r\nas easily as you could by writing software, of course, but I thought\r\nif you were really industrious and lived really cheaply, it had to\r\nbe possible to make enough to survive. And as an artist you could\r\nbe truly independent. You wouldn't have a boss, or even need to get\r\nresearch funding.I had always liked looking at paintings. Could I make them? I had\r\nno idea. I'd never imagined it was even possible. I knew intellectually\r\nthat people made art — that it didn't just appear spontaneously\r\n— but it was as if the people who made it were a different species.\r\nThey either lived long ago or were mysterious geniuses doing strange\r\nthings in profiles in Life magazine. The idea of actually being\r\nable to make art, to put that verb before that noun, seemed almost\r\nmiraculous.That fall I started taking art classes at Harvard. Grad students\r\ncould take classes in any department, and my advisor, Tom Cheatham,\r\nwas very easy going. If he even knew about the strange classes I\r\nwas taking, he never said anything.So now I was in a PhD program in computer science, yet planning to\r\nbe an artist, yet also genuinely in love with Lisp hacking and\r\nworking away at On Lisp. In other words, like many a grad student,\r\nI was working energetically on multiple projects that were not my\r\nthesis.I didn't see a way out of this situation. I didn't want to drop out\r\nof grad school, but how else was I going to get out? I remember\r\nwhen my friend Robert Morris got kicked out of Cornell for writing\r\nthe internet worm of 1988, I was envious that he'd found such a\r\nspectacular way to get out of grad school.Then one day in April 1990 a crack appeared in the wall. I ran into\r\nprofessor Cheatham and he asked if I was far enough along to graduate\r\nthat June. I didn't have a word of my dissertation written, but in\r\nwhat must have been the quickest bit of thinking in my life, I\r\ndecided to take a shot at writing one in the 5 weeks or so that\r\nremained before the deadline, reusing parts of On Lisp where I\r\ncould, and I was able to respond, with no perceptible delay \"Yes,\r\nI think so. I'll give you something to read in a few days.\"I picked applications of continuations as the topic. In retrospect\r\nI should have written about macros and embedded languages. There's\r\na whole world there that's barely been explored. But all I wanted\r\nwas to get out of grad school, and my rapidly written dissertation\r\nsufficed, just barely.Meanwhile I was applying to art schools. I applied to two: RISD in\r\nthe US, and the Accademia di Belli Arti in Florence, which, because\r\nit was the oldest art school, I imagined would be good. RISD accepted\r\nme, and I never heard back from the Accademia, so off to Providence\r\nI went.I'd applied for the BFA program at RISD, which meant in effect that\r\nI had to go to college again. This was not as strange as it sounds,\r\nbecause I was only 25, and art schools are full of people of different\r\nages. RISD counted me as a transfer sophomore and said I had to do\r\nthe foundation that summer. The foundation means the classes that\r\neveryone has to take in fundamental subjects like drawing, color,\r\nand design.Toward the end of the summer I got a big surprise: a letter from\r\nthe Accademia, which had been delayed because they'd sent it to\r\nCambridge England instead of Cambridge Massachusetts, inviting me\r\nto take the entrance exam in Florence that fall. This was now only\r\nweeks away. My nice landlady let me leave my stuff in her attic. I\r\nhad some money saved from consulting work I'd done in grad school;\r\nthere was probably enough to last a year if I lived cheaply. Now\r\nall I had to do was learn Italian.Only stranieri (foreigners) had to take this entrance exam. In\r\nretrospect it may well have been a way of excluding them, because\r\nthere were so many stranieri attracted by the idea of studying\r\nart in Florence that the Italian students would otherwise have been\r\noutnumbered. I was in decent shape at painting and drawing from the\r\nRISD foundation that summer, but I still don't know how I managed\r\nto pass the written exam. I remember that I answered the essay\r\nquestion by writing about Cezanne, and that I cranked up the\r\nintellectual level as high as I could to make the most of my limited\r\nvocabulary. \r\n[2]I'm only up to age 25 and already there are such conspicuous patterns.\r\nHere I was, yet again about to attend some august institution in\r\nthe hopes of learning about some prestigious subject, and yet again\r\nabout to be disappointed. The students and faculty in the painting\r\ndepartment at the Accademia were the nicest people you could imagine,\r\nbut they had long since arrived at an arrangement whereby the\r\nstudents wouldn't require the faculty to teach anything, and in\r\nreturn the faculty wouldn't require the students to learn anything.\r\nAnd at the same time all involved would adhere outwardly to the\r\nconventions of a 19th century atelier. We actually had one of those\r\nlittle stoves, fed with kindling, that you see in 19th century\r\nstudio paintings, and a nude model sitting as close to it as possible\r\nwithout getting burned. Except hardly anyone else painted her besides\r\nme. The rest of the students spent their time chatting or occasionally\r\ntrying to imitate things they'd seen in American art magazines.Our model turned out to live just down the street from me. She made\r\na living from a combination of modelling and making fakes for a\r\nlocal antique dealer. She'd copy an obscure old painting out of a\r\nbook, and then he'd take the copy and maltreat it to make it look\r\nold. \r\n[3]While I was a student at the Accademia I started painting still\r\nlives in my bedroom at night. These paintings were tiny, because\r\nthe room was, and because I painted them on leftover scraps of\r\ncanvas, which was all I could afford at the time. Painting still\r\nlives is different from painting people, because the subject, as\r\nits name suggests, can't move. People can't sit for more than about\r\n15 minutes at a time, and when they do they don't sit very still.\r\nSo the traditional m.o. for painting people is to know how to paint\r\na generic person, which you then modify to match the specific person\r\nyou're painting. Whereas a still life you can, if you want, copy\r\npixel by pixel from what you're seeing. You don't want to stop\r\nthere, of course, or you get merely photographic accuracy, and what\r\nmakes a still life interesting is that it's been through a head.\r\nYou want to emphasize the visual cues that tell you, for example,\r\nthat the reason the color changes suddenly at a certain point is\r\nthat it's the edge of an object. By subtly emphasizing such things\r\nyou can make paintings that are more realistic than photographs not\r\njust in some metaphorical sense, but in the strict information-theoretic\r\nsense. \r\n[4]I liked painting still lives because I was curious about what I was\r\nseeing. In everyday life, we aren't consciously aware of much we're\r\nseeing. Most visual perception is handled by low-level processes\r\nthat merely tell your brain \"that's a water droplet\" without telling\r\nyou details like where the lightest and darkest points are, or\r\n\"that's a bush\" without telling you the shape and position of every\r\nleaf. This is a feature of brains, not a bug. In everyday life it\r\nwould be distracting to notice every leaf on every bush. But when\r\nyou have to paint something, you have to look more closely, and\r\nwhen you do there's a lot to see. You can still be noticing new\r\nthings after days of trying to paint something people usually take\r\nfor granted, just as you can after\r\ndays of trying to write an essay about something people usually\r\ntake for granted.This is not the only way to paint. I'm not 100% sure it's even a\r\ngood way to paint. But it seemed a good enough bet to be worth\r\ntrying.Our teacher, professor Ulivi, was a nice guy. He could see I worked\r\nhard, and gave me a good grade, which he wrote down in a sort of\r\npassport each student had. But the Accademia wasn't teaching me\r\nanything except Italian, and my money was running out, so at the\r\nend of the first year I went back to the US.I wanted to go back to RISD, but I was now broke and RISD was very\r\nexpensive, so I decided to get a job for a year and then return to\r\nRISD the next fall. I got one at a company called Interleaf, which\r\nmade software for creating documents. You mean like Microsoft Word?\r\nExactly. That was how I learned that low end software tends to eat\r\nhigh end software. But Interleaf still had a few years to live yet.\r\n[5]Interleaf had done something pretty bold. Inspired by Emacs, they'd\r\nadded a scripting language, and even made the scripting language a\r\ndialect of Lisp. Now they wanted a Lisp hacker to write things in\r\nit. This was the closest thing I've had to a normal job, and I\r\nhereby apologize to my boss and coworkers, because I was a bad\r\nemployee. Their Lisp was the thinnest icing on a giant C cake, and\r\nsince I didn't know C and didn't want to learn it, I never understood\r\nmost of the software. Plus I was terribly irresponsible. This was\r\nback when a programming job meant showing up every day during certain\r\nworking hours. That seemed unnatural to me, and on this point the\r\nrest of the world is coming around to my way of thinking, but at\r\nthe time it caused a lot of friction. Toward the end of the year I\r\nspent much of my time surreptitiously working on On Lisp, which I\r\nhad by this time gotten a contract to publish.The good part was that I got paid huge amounts of money, especially\r\nby art student standards. In Florence, after paying my part of the\r\nrent, my budget for everything else had been $7 a day. Now I was\r\ngetting paid more than 4 times that every hour, even when I was\r\njust sitting in a meeting. By living cheaply I not only managed to\r\nsave enough to go back to RISD, but also paid off my college loans.I learned some useful things at Interleaf, though they were mostly\r\nabout what not to do. I learned that it's better for technology\r\ncompanies to be run by product people than sales people (though\r\nsales is a real skill and people who are good at it are really good\r\nat it), that it leads to bugs when code is edited by too many people,\r\nthat cheap office space is no bargain if it's depressing, that\r\nplanned meetings are inferior to corridor conversations, that big,\r\nbureaucratic customers are a dangerous source of money, and that\r\nthere's not much overlap between conventional office hours and the\r\noptimal time for hacking, or conventional offices and the optimal\r\nplace for it.But the most important thing I learned, and which I used in both\r\nViaweb and Y Combinator, is that the low end eats the high end:\r\nthat it's good to be the \"entry level\" option, even though that\r\nwill be less prestigious, because if you're not, someone else will\r\nbe, and will squash you against the ceiling. Which in turn means\r\nthat prestige is a danger sign.When I left to go back to RISD the next fall, I arranged to do\r\nfreelance work for the group that did projects for customers, and\r\nthis was how I survived for the next several years. When I came\r\nback to visit for a project later on, someone told me about a new\r\nthing called HTML, which was, as he described it, a derivative of\r\nSGML. Markup language enthusiasts were an occupational hazard at\r\nInterleaf and I ignored him, but this HTML thing later became a big\r\npart of my life.In the fall of 1992 I moved back to Providence to continue at RISD.\r\nThe foundation had merely been intro stuff, and the Accademia had\r\nbeen a (very civilized) joke. Now I was going to see what real art\r\nschool was like. But alas it was more like the Accademia than not.\r\nBetter organized, certainly, and a lot more expensive, but it was\r\nnow becoming clear that art school did not bear the same relationship\r\nto art that medical school bore to medicine. At least not the\r\npainting department. The textile department, which my next door\r\nneighbor belonged to, seemed to be pretty rigorous. No doubt\r\nillustration and architecture were too. But painting was post-rigorous.\r\nPainting students were supposed to express themselves, which to the\r\nmore worldly ones meant to try to cook up some sort of distinctive\r\nsignature style.A signature style is the visual equivalent of what in show business\r\nis known as a \"schtick\": something that immediately identifies the\r\nwork as yours and no one else's. For example, when you see a painting\r\nthat looks like a certain kind of cartoon, you know it's by Roy\r\nLichtenstein. So if you see a big painting of this type hanging in\r\nthe apartment of a hedge fund manager, you know he paid millions\r\nof dollars for it. That's not always why artists have a signature\r\nstyle, but it's usually why buyers pay a lot for such work.\r\n[6]There were plenty of earnest students too: kids who \"could draw\"\r\nin high school, and now had come to what was supposed to be the\r\nbest art school in the country, to learn to draw even better. They\r\ntended to be confused and demoralized by what they found at RISD,\r\nbut they kept going, because painting was what they did. I was not\r\none of the kids who could draw in high school, but at RISD I was\r\ndefinitely closer to their tribe than the tribe of signature style\r\nseekers.I learned a lot in the color class I took at RISD, but otherwise I\r\nwas basically teaching myself to paint, and I could do that for\r\nfree. So in 1993 I dropped out. I hung around Providence for a bit,\r\nand then my college friend Nancy Parmet did me a big favor. A\r\nrent-controlled apartment in a building her mother owned in New\r\nYork was becoming vacant. Did I want it? It wasn't much more than\r\nmy current place, and New York was supposed to be where the artists\r\nwere. So yes, I wanted it!\r\n[7]Asterix comics begin by zooming in on a tiny corner of Roman Gaul\r\nthat turns out not to be controlled by the Romans. You can do\r\nsomething similar on a map of New York City: if you zoom in on the\r\nUpper East Side, there's a tiny corner that's not rich, or at least\r\nwasn't in 1993. It's called Yorkville, and that was my new home.\r\nNow I was a New York artist — in the strictly technical sense of\r\nmaking paintings and living in New York.I was nervous about money, because I could sense that Interleaf was\r\non the way down. Freelance Lisp hacking work was very rare, and I\r\ndidn't want to have to program in another language, which in those\r\ndays would have meant C++ if I was lucky. So with my unerring nose\r\nfor financial opportunity, I decided to write another book on Lisp.\r\nThis would be a popular book, the sort of book that could be used\r\nas a textbook. I imagined myself living frugally off the royalties\r\nand spending all my time painting. (The painting on the cover of\r\nthis book, ANSI Common Lisp, is one that I painted around this\r\ntime.)The best thing about New York for me was the presence of Idelle and\r\nJulian Weber. Idelle Weber was a painter, one of the early\r\nphotorealists, and I'd taken her painting class at Harvard. I've\r\nnever known a teacher more beloved by her students. Large numbers\r\nof former students kept in touch with her, including me. After I\r\nmoved to New York I became her de facto studio assistant.She liked to paint on big, square canvases, 4 to 5 feet on a side.\r\nOne day in late 1994 as I was stretching one of these monsters there\r\nwas something on the radio about a famous fund manager. He wasn't\r\nthat much older than me, and was super rich. The thought suddenly\r\noccurred to me: why don't I become rich? Then I'll be able to work\r\non whatever I want.Meanwhile I'd been hearing more and more about this new thing called\r\nthe World Wide Web. Robert Morris showed it to me when I visited\r\nhim in Cambridge, where he was now in grad school at Harvard. It\r\nseemed to me that the web would be a big deal. I'd seen what graphical\r\nuser interfaces had done for the popularity of microcomputers. It\r\nseemed like the web would do the same for the internet.If I wanted to get rich, here was the next train leaving the station.\r\nI was right about that part. What I got wrong was the idea. I decided\r\nwe should start a company to put art galleries online. I can't\r\nhonestly say, after reading so many Y Combinator applications, that\r\nthis was the worst startup idea ever, but it was up there. Art\r\ngalleries didn't want to be online, and still don't, not the fancy\r\nones. That's not how they sell. I wrote some software to generate\r\nweb sites for galleries, and Robert wrote some to resize images and\r\nset up an http server to serve the pages. Then we tried to sign up\r\ngalleries. To call this a difficult sale would be an understatement.\r\nIt was difficult to give away. A few galleries let us make sites\r\nfor them for free, but none paid us.Then some online stores started to appear, and I realized that\r\nexcept for the order buttons they were identical to the sites we'd\r\nbeen generating for galleries. This impressive-sounding thing called\r\nan \"internet storefront\" was something we already knew how to build.So in the summer of 1995, after I submitted the camera-ready copy\r\nof ANSI Common Lisp to the publishers, we started trying to write\r\nsoftware to build online stores. At first this was going to be\r\nnormal desktop software, which in those days meant Windows software.\r\nThat was an alarming prospect, because neither of us knew how to\r\nwrite Windows software or wanted to learn. We lived in the Unix\r\nworld. But we decided we'd at least try writing a prototype store\r\nbuilder on Unix. Robert wrote a shopping cart, and I wrote a new\r\nsite generator for stores — in Lisp, of course.We were working out of Robert's apartment in Cambridge. His roommate\r\nwas away for big chunks of time, during which I got to sleep in his\r\nroom. For some reason there was no bed frame or sheets, just a\r\nmattress on the floor. One morning as I was lying on this mattress\r\nI had an idea that made me sit up like a capital L. What if we ran\r\nthe software on the server, and let users control it by clicking\r\non links? Then we'd never have to write anything to run on users'\r\ncomputers. We could generate the sites on the same server we'd serve\r\nthem from. Users wouldn't need anything more than a browser.This kind of software, known as a web app, is common now, but at\r\nthe time it wasn't clear that it was even possible. To find out,\r\nwe decided to try making a version of our store builder that you\r\ncould control through the browser. A couple days later, on August\r\n12, we had one that worked. The UI was horrible, but it proved you\r\ncould build a whole store through the browser, without any client\r\nsoftware or typing anything into the command line on the server.Now we felt like we were really onto something. I had visions of a\r\nwhole new generation of software working this way. You wouldn't\r\nneed versions, or ports, or any of that crap. At Interleaf there\r\nhad been a whole group called Release Engineering that seemed to\r\nbe at least as big as the group that actually wrote the software.\r\nNow you could just update the software right on the server.We started a new company we called Viaweb, after the fact that our\r\nsoftware worked via the web, and we got $10,000 in seed funding\r\nfrom Idelle's husband Julian. In return for that and doing the\r\ninitial legal work and giving us business advice, we gave him 10%\r\nof the company. Ten years later this deal became the model for Y\r\nCombinator's. We knew founders needed something like this, because\r\nwe'd needed it ourselves.At this stage I had a negative net worth, because the thousand\r\ndollars or so I had in the bank was more than counterbalanced by\r\nwhat I owed the government in taxes. (Had I diligently set aside\r\nthe proper proportion of the money I'd made consulting for Interleaf?\r\nNo, I had not.) So although Robert had his graduate student stipend,\r\nI needed that seed funding to live on.We originally hoped to launch in September, but we got more ambitious\r\nabout the software as we worked on it. Eventually we managed to\r\nbuild a WYSIWYG site builder, in the sense that as you were creating\r\npages, they looked exactly like the static ones that would be\r\ngenerated later, except that instead of leading to static pages,\r\nthe links all referred to closures stored in a hash table on the\r\nserver.It helped to have studied art, because the main goal of an online\r\nstore builder is to make users look legit, and the key to looking\r\nlegit is high production values. If you get page layouts and fonts\r\nand colors right, you can make a guy running a store out of his\r\nbedroom look more legit than a big company.(If you're curious why my site looks so old-fashioned, it's because\r\nit's still made with this software. It may look clunky today, but\r\nin 1996 it was the last word in slick.)In September, Robert rebelled. \"We've been working on this for a\r\nmonth,\" he said, \"and it's still not done.\" This is funny in\r\nretrospect, because he would still be working on it almost 3 years\r\nlater. But I decided it might be prudent to recruit more programmers,\r\nand I asked Robert who else in grad school with him was really good.\r\nHe recommended Trevor Blackwell, which surprised me at first, because\r\nat that point I knew Trevor mainly for his plan to reduce everything\r\nin his life to a stack of notecards, which he carried around with\r\nhim. But Rtm was right, as usual. Trevor turned out to be a\r\nfrighteningly effective hacker.It was a lot of fun working with Robert and Trevor. They're the two\r\nmost independent-minded people \r\nI know, and in completely different\r\nways. If you could see inside Rtm's brain it would look like a\r\ncolonial New England church, and if you could see inside Trevor's\r\nit would look like the worst excesses of Austrian Rococo.We opened for business, with 6 stores, in January 1996. It was just\r\nas well we waited a few months, because although we worried we were\r\nlate, we were actually almost fatally early. There was a lot of\r\ntalk in the press then about ecommerce, but not many people actually\r\nwanted online stores.\r\n[8]There were three main parts to the software: the editor, which\r\npeople used to build sites and which I wrote, the shopping cart,\r\nwhich Robert wrote, and the manager, which kept track of orders and\r\nstatistics, and which Trevor wrote. In its time, the editor was one\r\nof the best general-purpose site builders. I kept the code tight\r\nand didn't have to integrate with any other software except Robert's\r\nand Trevor's, so it was quite fun to work on. If all I'd had to do\r\nwas work on this software, the next 3 years would have been the\r\neasiest of my life. Unfortunately I had to do a lot more, all of\r\nit stuff I was worse at than programming, and the next 3 years were\r\ninstead the most stressful.There were a lot of startups making ecommerce software in the second\r\nhalf of the 90s. We were determined to be the Microsoft Word, not\r\nthe Interleaf. Which meant being easy to use and inexpensive. It\r\nwas lucky for us that we were poor, because that caused us to make\r\nViaweb even more inexpensive than we realized. We charged $100 a\r\nmonth for a small store and $300 a month for a big one. This low\r\nprice was a big attraction, and a constant thorn in the sides of\r\ncompetitors, but it wasn't because of some clever insight that we\r\nset the price low. We had no idea what businesses paid for things.\r\n$300 a month seemed like a lot of money to us.We did a lot of things right by accident like that. For example,\r\nwe did what's now called \"doing things that \r\ndon't scale,\" although\r\nat the time we would have described it as \"being so lame that we're\r\ndriven to the most desperate measures to get users.\" The most common\r\nof which was building stores for them. This seemed particularly\r\nhumiliating, since the whole raison d'etre of our software was that\r\npeople could use it to make their own stores. But anything to get\r\nusers.We learned a lot more about retail than we wanted to know. For\r\nexample, that if you could only have a small image of a man's shirt\r\n(and all images were small then by present standards), it was better\r\nto have a closeup of the collar than a picture of the whole shirt.\r\nThe reason I remember learning this was that it meant I had to\r\nrescan about 30 images of men's shirts. My first set of scans were\r\nso beautiful too.Though this felt wrong, it was exactly the right thing to be doing.\r\nBuilding stores for users taught us about retail, and about how it\r\nfelt to use our software. I was initially both mystified and repelled\r\nby \"business\" and thought we needed a \"business person\" to be in\r\ncharge of it, but once we started to get users, I was converted,\r\nin much the same way I was converted to \r\nfatherhood once I had kids.\r\nWhatever users wanted, I was all theirs. Maybe one day we'd have\r\nso many users that I couldn't scan their images for them, but in\r\nthe meantime there was nothing more important to do.Another thing I didn't get at the time is that \r\ngrowth rate is the\r\nultimate test of a startup. Our growth rate was fine. We had about\r\n70 stores at the end of 1996 and about 500 at the end of 1997. I\r\nmistakenly thought the thing that mattered was the absolute number\r\nof users. And that is the thing that matters in the sense that\r\nthat's how much money you're making, and if you're not making enough,\r\nyou might go out of business. But in the long term the growth rate\r\ntakes care of the absolute number. If we'd been a startup I was\r\nadvising at Y Combinator, I would have said: Stop being so stressed\r\nout, because you're doing fine. You're growing 7x a year. Just don't\r\nhire too many more people and you'll soon be profitable, and then\r\nyou'll control your own destiny.Alas I hired lots more people, partly because our investors wanted\r\nme to, and partly because that's what startups did during the\r\nInternet Bubble. A company with just a handful of employees would\r\nhave seemed amateurish. So we didn't reach breakeven until about\r\nwhen Yahoo bought us in the summer of 1998. Which in turn meant we\r\nwere at the mercy of investors for the entire life of the company.\r\nAnd since both we and our investors were noobs at startups, the\r\nresult was a mess even by startup standards.It was a huge relief when Yahoo bought us. In principle our Viaweb\r\nstock was valuable. It was a share in a business that was profitable\r\nand growing rapidly. But it didn't feel very valuable to me; I had\r\nno idea how to value a business, but I was all too keenly aware of\r\nthe near-death experiences we seemed to have every few months. Nor\r\nhad I changed my grad student lifestyle significantly since we\r\nstarted. So when Yahoo bought us it felt like going from rags to\r\nriches. Since we were going to California, I bought a car, a yellow\r\n1998 VW GTI. I remember thinking that its leather seats alone were\r\nby far the most luxurious thing I owned.The next year, from the summer of 1998 to the summer of 1999, must\r\nhave been the least productive of my life. I didn't realize it at\r\nthe time, but I was worn out from the effort and stress of running\r\nViaweb. For a while after I got to California I tried to continue\r\nmy usual m.o. of programming till 3 in the morning, but fatigue\r\ncombined with Yahoo's prematurely aged\r\nculture and grim cube farm\r\nin Santa Clara gradually dragged me down. After a few months it\r\nfelt disconcertingly like working at Interleaf.Yahoo had given us a lot of options when they bought us. At the\r\ntime I thought Yahoo was so overvalued that they'd never be worth\r\nanything, but to my astonishment the stock went up 5x in the next\r\nyear. I hung on till the first chunk of options vested, then in the\r\nsummer of 1999 I left. It had been so long since I'd painted anything\r\nthat I'd half forgotten why I was doing this. My brain had been\r\nentirely full of software and men's shirts for 4 years. But I had\r\ndone this to get rich so I could paint, I reminded myself, and now\r\nI was rich, so I should go paint.When I said I was leaving, my boss at Yahoo had a long conversation\r\nwith me about my plans. I told him all about the kinds of pictures\r\nI wanted to paint. At the time I was touched that he took such an\r\ninterest in me. Now I realize it was because he thought I was lying.\r\nMy options at that point were worth about $2 million a month. If I\r\nwas leaving that kind of money on the table, it could only be to\r\ngo and start some new startup, and if I did, I might take people\r\nwith me. This was the height of the Internet Bubble, and Yahoo was\r\nground zero of it. My boss was at that moment a billionaire. Leaving\r\nthen to start a new startup must have seemed to him an insanely,\r\nand yet also plausibly, ambitious plan.But I really was quitting to paint, and I started immediately.\r\nThere was no time to lose. I'd already burned 4 years getting rich.\r\nNow when I talk to founders who are leaving after selling their\r\ncompanies, my advice is always the same: take a vacation. That's\r\nwhat I should have done, just gone off somewhere and done nothing\r\nfor a month or two, but the idea never occurred to me.So I tried to paint, but I just didn't seem to have any energy or\r\nambition. Part of the problem was that I didn't know many people\r\nin California. I'd compounded this problem by buying a house up in\r\nthe Santa Cruz Mountains, with a beautiful view but miles from\r\nanywhere. I stuck it out for a few more months, then in desperation\r\nI went back to New York, where unless you understand about rent\r\ncontrol you'll be surprised to hear I still had my apartment, sealed\r\nup like a tomb of my old life. Idelle was in New York at least, and\r\nthere were other people trying to paint there, even though I didn't\r\nknow any of them.When I got back to New York I resumed my old life, except now I was\r\nrich. It was as weird as it sounds. I resumed all my old patterns,\r\nexcept now there were doors where there hadn't been. Now when I was\r\ntired of walking, all I had to do was raise my hand, and (unless\r\nit was raining) a taxi would stop to pick me up. Now when I walked\r\npast charming little restaurants I could go in and order lunch. It\r\nwas exciting for a while. Painting started to go better. I experimented\r\nwith a new kind of still life where I'd paint one painting in the\r\nold way, then photograph it and print it, blown up, on canvas, and\r\nthen use that as the underpainting for a second still life, painted\r\nfrom the same objects (which hopefully hadn't rotted yet).Meanwhile I looked for an apartment to buy. Now I could actually\r\nchoose what neighborhood to live in. Where, I asked myself and\r\nvarious real estate agents, is the Cambridge of New York? Aided by\r\noccasional visits to actual Cambridge, I gradually realized there\r\nwasn't one. Huh.Around this time, in the spring of 2000, I had an idea. It was clear\r\nfrom our experience with Viaweb that web apps were the future. Why\r\nnot build a web app for making web apps? Why not let people edit\r\ncode on our server through the browser, and then host the resulting\r\napplications for them?\r\n[9]\r\nYou could run all sorts of services\r\non the servers that these applications could use just by making an\r\nAPI call: making and receiving phone calls, manipulating images,\r\ntaking credit card payments, etc.I got so excited about this idea that I couldn't think about anything\r\nelse. It seemed obvious that this was the future. I didn't particularly\r\nwant to start another company, but it was clear that this idea would\r\nhave to be embodied as one, so I decided to move to Cambridge and\r\nstart it. I hoped to lure Robert into working on it with me, but\r\nthere I ran into a hitch. Robert was now a postdoc at MIT, and\r\nthough he'd made a lot of money the last time I'd lured him into\r\nworking on one of my schemes, it had also been a huge time sink.\r\nSo while he agreed that it sounded like a plausible idea, he firmly\r\nrefused to work on it.Hmph. Well, I'd do it myself then. I recruited Dan Giffin, who had\r\nworked for Viaweb, and two undergrads who wanted summer jobs, and\r\nwe got to work trying to build what it's now clear is about twenty\r\ncompanies and several open source projects worth of software. The\r\nlanguage for defining applications would of course be a dialect of\r\nLisp. But I wasn't so naive as to assume I could spring an overt\r\nLisp on a general audience; we'd hide the parentheses, like Dylan\r\ndid.By then there was a name for the kind of company Viaweb was, an\r\n\"application service provider,\" or ASP. This name didn't last long\r\nbefore it was replaced by \"software as a service,\" but it was current\r\nfor long enough that I named this new company after it: it was going\r\nto be called Aspra.I started working on the application builder, Dan worked on network\r\ninfrastructure, and the two undergrads worked on the first two\r\nservices (images and phone calls). But about halfway through the\r\nsummer I realized I really didn't want to run a company — especially\r\nnot a big one, which it was looking like this would have to be. I'd\r\nonly started Viaweb because I needed the money. Now that I didn't\r\nneed money anymore, why was I doing this? If this vision had to be\r\nrealized as a company, then screw the vision. I'd build a subset\r\nthat could be done as an open source project.Much to my surprise, the time I spent working on this stuff was not\r\nwasted after all. After we started Y Combinator, I would often\r\nencounter startups working on parts of this new architecture, and\r\nit was very useful to have spent so much time thinking about it and\r\neven trying to write some of it.The subset I would build as an open source project was the new Lisp,\r\nwhose parentheses I now wouldn't even have to hide. A lot of Lisp\r\nhackers dream of building a new Lisp, partly because one of the\r\ndistinctive features of the language is that it has dialects, and\r\npartly, I think, because we have in our minds a Platonic form of\r\nLisp that all existing dialects fall short of. I certainly did. So\r\nat the end of the summer Dan and I switched to working on this new\r\ndialect of Lisp, which I called Arc, in a house I bought in Cambridge.The following spring, lightning struck. I was invited to give a\r\ntalk at a Lisp conference, so I gave one about how we'd used Lisp\r\nat Viaweb. Afterward I put a postscript file of this talk online,\r\non paulgraham.com, which I'd created years before using Viaweb but\r\nhad never used for anything. In one day it got 30,000 page views.\r\nWhat on earth had happened? The referring urls showed that someone\r\nhad posted it on Slashdot.\r\n[10]Wow, I thought, there's an audience. If I write something and put\r\nit on the web, anyone can read it. That may seem obvious now, but\r\nit was surprising then. In the print era there was a narrow channel\r\nto readers, guarded by fierce monsters known as editors. The only\r\nway to get an audience for anything you wrote was to get it published\r\nas a book, or in a newspaper or magazine. Now anyone could publish\r\nanything.This had been possible in principle since 1993, but not many people\r\nhad realized it yet. I had been intimately involved with building\r\nthe infrastructure of the web for most of that time, and a writer\r\nas well, and it had taken me 8 years to realize it. Even then it\r\ntook me several years to understand the implications. It meant there\r\nwould be a whole new generation of \r\nessays.\r\n[11]In the print era, the channel for publishing essays had been\r\nvanishingly small. Except for a few officially anointed thinkers\r\nwho went to the right parties in New York, the only people allowed\r\nto publish essays were specialists writing about their specialties.\r\nThere were so many essays that had never been written, because there\r\nhad been no way to publish them. Now they could be, and I was going\r\nto write them.\r\n[12]I've worked on several different things, but to the extent there\r\nwas a turning point where I figured out what to work on, it was\r\nwhen I started publishing essays online. From then on I knew that\r\nwhatever else I did, I'd always write essays too.I knew that online essays would be a \r\nmarginal medium at first.\r\nSocially they'd seem more like rants posted by nutjobs on their\r\nGeoCities sites than the genteel and beautifully typeset compositions\r\npublished in The New Yorker. But by this point I knew enough to\r\nfind that encouraging instead of discouraging.One of the most conspicuous patterns I've noticed in my life is how\r\nwell it has worked, for me at least, to work on things that weren't\r\nprestigious. Still life has always been the least prestigious form\r\nof painting. Viaweb and Y Combinator both seemed lame when we started\r\nthem. I still get the glassy eye from strangers when they ask what\r\nI'm writing, and I explain that it's an essay I'm going to publish\r\non my web site. Even Lisp, though prestigious intellectually in\r\nsomething like the way Latin is, also seems about as hip.It's not that unprestigious types of work are good per se. But when\r\nyou find yourself drawn to some kind of work despite its current\r\nlack of prestige, it's a sign both that there's something real to\r\nbe discovered there, and that you have the right kind of motives.\r\nImpure motives are a big danger for the ambitious. If anything is\r\ngoing to lead you astray, it will be the desire to impress people.\r\nSo while working on things that aren't prestigious doesn't guarantee\r\nyou're on the right track, it at least guarantees you're not on the\r\nmost common type of wrong one.Over the next several years I wrote lots of essays about all kinds\r\nof different topics. O'Reilly reprinted a collection of them as a\r\nbook, called Hackers & Painters after one of the essays in it. I\r\nalso worked on spam filters, and did some more painting. I used to\r\nhave dinners for a group of friends every thursday night, which\r\ntaught me how to cook for groups. And I bought another building in\r\nCambridge, a former candy factory (and later, twas said, porn\r\nstudio), to use as an office.One night in October 2003 there was a big party at my house. It was\r\na clever idea of my friend Maria Daniels, who was one of the thursday\r\ndiners. Three separate hosts would all invite their friends to one\r\nparty. So for every guest, two thirds of the other guests would be\r\npeople they didn't know but would probably like. One of the guests\r\nwas someone I didn't know but would turn out to like a lot: a woman\r\ncalled Jessica Livingston. A couple days later I asked her out.Jessica was in charge of marketing at a Boston investment bank.\r\nThis bank thought it understood startups, but over the next year,\r\nas she met friends of mine from the startup world, she was surprised\r\nhow different reality was. And how colorful their stories were. So\r\nshe decided to compile a book of \r\ninterviews with startup founders.When the bank had financial problems and she had to fire half her\r\nstaff, she started looking for a new job. In early 2005 she interviewed\r\nfor a marketing job at a Boston VC firm. It took them weeks to make\r\nup their minds, and during this time I started telling her about\r\nall the things that needed to be fixed about venture capital. They\r\nshould make a larger number of smaller investments instead of a\r\nhandful of giant ones, they should be funding younger, more technical\r\nfounders instead of MBAs, they should let the founders remain as\r\nCEO, and so on.One of my tricks for writing essays had always been to give talks.\r\nThe prospect of having to stand up in front of a group of people\r\nand tell them something that won't waste their time is a great\r\nspur to the imagination. When the Harvard Computer Society, the\r\nundergrad computer club, asked me to give a talk, I decided I would\r\ntell them how to start a startup. Maybe they'd be able to avoid the\r\nworst of the mistakes we'd made.So I gave this talk, in the course of which I told them that the\r\nbest sources of seed funding were successful startup founders,\r\nbecause then they'd be sources of advice too. Whereupon it seemed\r\nthey were all looking expectantly at me. Horrified at the prospect\r\nof having my inbox flooded by business plans (if I'd only known),\r\nI blurted out \"But not me!\" and went on with the talk. But afterward\r\nit occurred to me that I should really stop procrastinating about\r\nangel investing. I'd been meaning to since Yahoo bought us, and now\r\nit was 7 years later and I still hadn't done one angel investment.Meanwhile I had been scheming with Robert and Trevor about projects\r\nwe could work on together. I missed working with them, and it seemed\r\nlike there had to be something we could collaborate on.As Jessica and I were walking home from dinner on March 11, at the\r\ncorner of Garden and Walker streets, these three threads converged.\r\nScrew the VCs who were taking so long to make up their minds. We'd\r\nstart our own investment firm and actually implement the ideas we'd\r\nbeen talking about. I'd fund it, and Jessica could quit her job and\r\nwork for it, and we'd get Robert and Trevor as partners too.\r\n[13]Once again, ignorance worked in our favor. We had no idea how to\r\nbe angel investors, and in Boston in 2005 there were no Ron Conways\r\nto learn from. So we just made what seemed like the obvious choices,\r\nand some of the things we did turned out to be novel.There are multiple components to Y Combinator, and we didn't figure\r\nthem all out at once. The part we got first was to be an angel firm.\r\nIn those days, those two words didn't go together. There were VC\r\nfirms, which were organized companies with people whose job it was\r\nto make investments, but they only did big, million dollar investments.\r\nAnd there were angels, who did smaller investments, but these were\r\nindividuals who were usually focused on other things and made\r\ninvestments on the side. And neither of them helped founders enough\r\nin the beginning. We knew how helpless founders were in some respects,\r\nbecause we remembered how helpless we'd been. For example, one thing\r\nJulian had done for us that seemed to us like magic was to get us\r\nset up as a company. We were fine writing fairly difficult software,\r\nbut actually getting incorporated, with bylaws and stock and all\r\nthat stuff, how on earth did you do that? Our plan was not only to\r\nmake seed investments, but to do for startups everything Julian had\r\ndone for us.YC was not organized as a fund. It was cheap enough to run that we\r\nfunded it with our own money. That went right by 99% of readers,\r\nbut professional investors are thinking \"Wow, that means they got\r\nall the returns.\" But once again, this was not due to any particular\r\ninsight on our part. We didn't know how VC firms were organized.\r\nIt never occurred to us to try to raise a fund, and if it had, we\r\nwouldn't have known where to start.\r\n[14]The most distinctive thing about YC is the batch model: to fund a\r\nbunch of startups all at once, twice a year, and then to spend three\r\nmonths focusing intensively on trying to help them. That part we\r\ndiscovered by accident, not merely implicitly but explicitly due\r\nto our ignorance about investing. We needed to get experience as\r\ninvestors. What better way, we thought, than to fund a whole bunch\r\nof startups at once? We knew undergrads got temporary jobs at tech\r\ncompanies during the summer. Why not organize a summer program where\r\nthey'd start startups instead? We wouldn't feel guilty for being\r\nin a sense fake investors, because they would in a similar sense\r\nbe fake founders. So while we probably wouldn't make much money out\r\nof it, we'd at least get to practice being investors on them, and\r\nthey for their part would probably have a more interesting summer\r\nthan they would working at Microsoft.We'd use the building I owned in Cambridge as our headquarters.\r\nWe'd all have dinner there once a week — on tuesdays, since I was\r\nalready cooking for the thursday diners on thursdays — and after\r\ndinner we'd bring in experts on startups to give talks.We knew undergrads were deciding then about summer jobs, so in a\r\nmatter of days we cooked up something we called the Summer Founders\r\nProgram, and I posted an \r\nannouncement \r\non my site, inviting undergrads\r\nto apply. I had never imagined that writing essays would be a way\r\nto get \"deal flow,\" as investors call it, but it turned out to be\r\nthe perfect source.\r\n[15]\r\nWe got 225 applications for the Summer\r\nFounders Program, and we were surprised to find that a lot of them\r\nwere from people who'd already graduated, or were about to that\r\nspring. Already this SFP thing was starting to feel more serious\r\nthan we'd intended.We invited about 20 of the 225 groups to interview in person, and\r\nfrom those we picked 8 to fund. They were an impressive group. That\r\nfirst batch included reddit, Justin Kan and Emmett Shear, who went\r\non to found Twitch, Aaron Swartz, who had already helped write the\r\nRSS spec and would a few years later become a martyr for open access,\r\nand Sam Altman, who would later become the second president of YC.\r\nI don't think it was entirely luck that the first batch was so good.\r\nYou had to be pretty bold to sign up for a weird thing like the\r\nSummer Founders Program instead of a summer job at a legit place\r\nlike Microsoft or Goldman Sachs.The deal for startups was based on a combination of the deal we did\r\nwith Julian ($10k for 10%) and what Robert said MIT grad students\r\ngot for the summer ($6k). We invested $6k per founder, which in the\r\ntypical two-founder case was $12k, in return for 6%. That had to\r\nbe fair, because it was twice as good as the deal we ourselves had\r\ntaken. Plus that first summer, which was really hot, Jessica brought\r\nthe founders free air conditioners.\r\n[16]Fairly quickly I realized that we had stumbled upon the way to scale\r\nstartup funding. Funding startups in batches was more convenient\r\nfor us, because it meant we could do things for a lot of startups\r\nat once, but being part of a batch was better for the startups too.\r\nIt solved one of the biggest problems faced by founders: the\r\nisolation. Now you not only had colleagues, but colleagues who\r\nunderstood the problems you were facing and could tell you how they\r\nwere solving them.As YC grew, we started to notice other advantages of scale. The\r\nalumni became a tight community, dedicated to helping one another,\r\nand especially the current batch, whose shoes they remembered being\r\nin. We also noticed that the startups were becoming one another's\r\ncustomers. We used to refer jokingly to the \"YC GDP,\" but as YC\r\ngrows this becomes less and less of a joke. Now lots of startups\r\nget their initial set of customers almost entirely from among their\r\nbatchmates.I had not originally intended YC to be a full-time job. I was going\r\nto do three things: hack, write essays, and work on YC. As YC grew,\r\nand I grew more excited about it, it started to take up a lot more\r\nthan a third of my attention. But for the first few years I was\r\nstill able to work on other things.In the summer of 2006, Robert and I started working on a new version\r\nof Arc. This one was reasonably fast, because it was compiled into\r\nScheme. To test this new Arc, I wrote Hacker News in it. It was\r\noriginally meant to be a news aggregator for startup founders and\r\nwas called Startup News, but after a few months I got tired of\r\nreading about nothing but startups. Plus it wasn't startup founders\r\nwe wanted to reach. It was future startup founders. So I changed\r\nthe name to Hacker News and the topic to whatever engaged one's\r\nintellectual curiosity.HN was no doubt good for YC, but it was also by far the biggest\r\nsource of stress for me. If all I'd had to do was select and help\r\nfounders, life would have been so easy. And that implies that HN\r\nwas a mistake. Surely the biggest source of stress in one's work\r\nshould at least be something close to the core of the work. Whereas\r\nI was like someone who was in pain while running a marathon not\r\nfrom the exertion of running, but because I had a blister from an\r\nill-fitting shoe. When I was dealing with some urgent problem during\r\nYC, there was about a 60% chance it had to do with HN, and a 40%\r\nchance it had do with everything else combined.\r\n[17]As well as HN, I wrote all of YC's internal software in Arc. But\r\nwhile I continued to work a good deal in Arc, I gradually stopped\r\nworking on Arc, partly because I didn't have time to, and partly\r\nbecause it was a lot less attractive to mess around with the language\r\nnow that we had all this infrastructure depending on it. So now my\r\nthree projects were reduced to two: writing essays and working on\r\nYC.YC was different from other kinds of work I've done. Instead of\r\ndeciding for myself what to work on, the problems came to me. Every\r\n6 months there was a new batch of startups, and their problems,\r\nwhatever they were, became our problems. It was very engaging work,\r\nbecause their problems were quite varied, and the good founders\r\nwere very effective. If you were trying to learn the most you could\r\nabout startups in the shortest possible time, you couldn't have\r\npicked a better way to do it.There were parts of the job I didn't like. Disputes between cofounders,\r\nfiguring out when people were lying to us, fighting with people who\r\nmaltreated the startups, and so on. But I worked hard even at the\r\nparts I didn't like. I was haunted by something Kevin Hale once\r\nsaid about companies: \"No one works harder than the boss.\" He meant\r\nit both descriptively and prescriptively, and it was the second\r\npart that scared me. I wanted YC to be good, so if how hard I worked\r\nset the upper bound on how hard everyone else worked, I'd better\r\nwork very hard.One day in 2010, when he was visiting California for interviews,\r\nRobert Morris did something astonishing: he offered me unsolicited\r\nadvice. I can only remember him doing that once before. One day at\r\nViaweb, when I was bent over double from a kidney stone, he suggested\r\nthat it would be a good idea for him to take me to the hospital.\r\nThat was what it took for Rtm to offer unsolicited advice. So I\r\nremember his exact words very clearly. \"You know,\" he said, \"you\r\nshould make sure Y Combinator isn't the last cool thing you do.\"At the time I didn't understand what he meant, but gradually it\r\ndawned on me that he was saying I should quit. This seemed strange\r\nadvice, because YC was doing great. But if there was one thing rarer\r\nthan Rtm offering advice, it was Rtm being wrong. So this set me\r\nthinking. It was true that on my current trajectory, YC would be\r\nthe last thing I did, because it was only taking up more of my\r\nattention. It had already eaten Arc, and was in the process of\r\neating essays too. Either YC was my life's work or I'd have to leave\r\neventually. And it wasn't, so I would.In the summer of 2012 my mother had a stroke, and the cause turned\r\nout to be a blood clot caused by colon cancer. The stroke destroyed\r\nher balance, and she was put in a nursing home, but she really\r\nwanted to get out of it and back to her house, and my sister and I\r\nwere determined to help her do it. I used to fly up to Oregon to\r\nvisit her regularly, and I had a lot of time to think on those\r\nflights. On one of them I realized I was ready to hand YC over to\r\nsomeone else.I asked Jessica if she wanted to be president, but she didn't, so\r\nwe decided we'd try to recruit Sam Altman. We talked to Robert and\r\nTrevor and we agreed to make it a complete changing of the guard.\r\nUp till that point YC had been controlled by the original LLC we\r\nfour had started. But we wanted YC to last for a long time, and to\r\ndo that it couldn't be controlled by the founders. So if Sam said\r\nyes, we'd let him reorganize YC. Robert and I would retire, and\r\nJessica and Trevor would become ordinary partners.When we asked Sam if he wanted to be president of YC, initially he\r\nsaid no. He wanted to start a startup to make nuclear reactors.\r\nBut I kept at it, and in October 2013 he finally agreed. We decided\r\nhe'd take over starting with the winter 2014 batch. For the rest\r\nof 2013 I left running YC more and more to Sam, partly so he could\r\nlearn the job, and partly because I was focused on my mother, whose\r\ncancer had returned.She died on January 15, 2014. We knew this was coming, but it was\r\nstill hard when it did.I kept working on YC till March, to help get that batch of startups\r\nthrough Demo Day, then I checked out pretty completely. (I still\r\ntalk to alumni and to new startups working on things I'm interested\r\nin, but that only takes a few hours a week.)What should I do next? Rtm's advice hadn't included anything about\r\nthat. I wanted to do something completely different, so I decided\r\nI'd paint. I wanted to see how good I could get if I really focused\r\non it. So the day after I stopped working on YC, I started painting.\r\nI was rusty and it took a while to get back into shape, but it was\r\nat least completely engaging.\r\n[18]I spent most of the rest of 2014 painting. I'd never been able to\r\nwork so uninterruptedly before, and I got to be better than I had\r\nbeen. Not good enough, but better. Then in November, right in the\r\nmiddle of a painting, I ran out of steam. Up till that point I'd\r\nalways been curious to see how the painting I was working on would\r\nturn out, but suddenly finishing this one seemed like a chore. So\r\nI stopped working on it and cleaned my brushes and haven't painted\r\nsince. So far anyway.I realize that sounds rather wimpy. But attention is a zero sum\r\ngame. If you can choose what to work on, and you choose a project\r\nthat's not the best one (or at least a good one) for you, then it's\r\ngetting in the way of another project that is. And at 50 there was\r\nsome opportunity cost to screwing around.I started writing essays again, and wrote a bunch of new ones over\r\nthe next few months. I even wrote a couple that \r\nweren't about\r\nstartups. Then in March 2015 I started working on Lisp again.The distinctive thing about Lisp is that its core is a language\r\ndefined by writing an interpreter in itself. It wasn't originally\r\nintended as a programming language in the ordinary sense. It was\r\nmeant to be a formal model of computation, an alternative to the\r\nTuring machine. If you want to write an interpreter for a language\r\nin itself, what's the minimum set of predefined operators you need?\r\nThe Lisp that John McCarthy invented, or more accurately discovered,\r\nis an answer to that question.\r\n[19]McCarthy didn't realize this Lisp could even be used to program\r\ncomputers till his grad student Steve Russell suggested it. Russell\r\ntranslated McCarthy's interpreter into IBM 704 machine language,\r\nand from that point Lisp started also to be a programming language\r\nin the ordinary sense. But its origins as a model of computation\r\ngave it a power and elegance that other languages couldn't match.\r\nIt was this that attracted me in college, though I didn't understand\r\nwhy at the time.McCarthy's 1960 Lisp did nothing more than interpret Lisp expressions.\r\nIt was missing a lot of things you'd want in a programming language.\r\nSo these had to be added, and when they were, they weren't defined\r\nusing McCarthy's original axiomatic approach. That wouldn't have\r\nbeen feasible at the time. McCarthy tested his interpreter by\r\nhand-simulating the execution of programs. But it was already getting\r\nclose to the limit of interpreters you could test that way — indeed,\r\nthere was a bug in it that McCarthy had overlooked. To test a more\r\ncomplicated interpreter, you'd have had to run it, and computers\r\nthen weren't powerful enough.Now they are, though. Now you could continue using McCarthy's\r\naxiomatic approach till you'd defined a complete programming language.\r\nAnd as long as every change you made to McCarthy's Lisp was a\r\ndiscoveredness-preserving transformation, you could, in principle,\r\nend up with a complete language that had this quality. Harder to\r\ndo than to talk about, of course, but if it was possible in principle,\r\nwhy not try? So I decided to take a shot at it. It took 4 years,\r\nfrom March 26, 2015 to October 12, 2019. It was fortunate that I\r\nhad a precisely defined goal, or it would have been hard to keep\r\nat it for so long.I wrote this new Lisp, called Bel, \r\nin itself in Arc. That may sound\r\nlike a contradiction, but it's an indication of the sort of trickery\r\nI had to engage in to make this work. By means of an egregious\r\ncollection of hacks I managed to make something close enough to an\r\ninterpreter written in itself that could actually run. Not fast,\r\nbut fast enough to test.I had to ban myself from writing essays during most of this time,\r\nor I'd never have finished. In late 2015 I spent 3 months writing\r\nessays, and when I went back to working on Bel I could barely\r\nunderstand the code. Not so much because it was badly written as\r\nbecause the problem is so convoluted. When you're working on an\r\ninterpreter written in itself, it's hard to keep track of what's\r\nhappening at what level, and errors can be practically encrypted\r\nby the time you get them.So I said no more essays till Bel was done. But I told few people\r\nabout Bel while I was working on it. So for years it must have\r\nseemed that I was doing nothing, when in fact I was working harder\r\nthan I'd ever worked on anything. Occasionally after wrestling for\r\nhours with some gruesome bug I'd check Twitter or HN and see someone\r\nasking \"Does Paul Graham still code?\"Working on Bel was hard but satisfying. I worked on it so intensively\r\nthat at any given time I had a decent chunk of the code in my head\r\nand could write more there. I remember taking the boys to the\r\ncoast on a sunny day in 2015 and figuring out how to deal with some\r\nproblem involving continuations while I watched them play in the\r\ntide pools. It felt like I was doing life right. I remember that\r\nbecause I was slightly dismayed at how novel it felt. The good news\r\nis that I had more moments like this over the next few years.In the summer of 2016 we moved to England. We wanted our kids to\r\nsee what it was like living in another country, and since I was a\r\nBritish citizen by birth, that seemed the obvious choice. We only\r\nmeant to stay for a year, but we liked it so much that we still\r\nlive there. So most of Bel was written in England.In the fall of 2019, Bel was finally finished. Like McCarthy's\r\noriginal Lisp, it's a spec rather than an implementation, although\r\nlike McCarthy's Lisp it's a spec expressed as code.Now that I could write essays again, I wrote a bunch about topics\r\nI'd had stacked up. I kept writing essays through 2020, but I also\r\nstarted to think about other things I could work on. How should I\r\nchoose what to do? Well, how had I chosen what to work on in the\r\npast? I wrote an essay for myself to answer that question, and I\r\nwas surprised how long and messy the answer turned out to be. If\r\nthis surprised me, who'd lived it, then I thought perhaps it would\r\nbe interesting to other people, and encouraging to those with\r\nsimilarly messy lives. So I wrote a more detailed version for others\r\nto read, and this is the last sentence of it.\nNotes[1]\r\nMy experience skipped a step in the evolution of computers:\r\ntime-sharing machines with interactive OSes. I went straight from\r\nbatch processing to microcomputers, which made microcomputers seem\r\nall the more exciting.[2]\r\nItalian words for abstract concepts can nearly always be\r\npredicted from their English cognates (except for occasional traps\r\nlike polluzione). It's the everyday words that differ. So if you\r\nstring together a lot of abstract concepts with a few simple verbs,\r\nyou can make a little Italian go a long way.[3]\r\nI lived at Piazza San Felice 4, so my walk to the Accademia\r\nwent straight down the spine of old Florence: past the Pitti, across\r\nthe bridge, past Orsanmichele, between the Duomo and the Baptistery,\r\nand then up Via Ricasoli to Piazza San Marco. I saw Florence at\r\nstreet level in every possible condition, from empty dark winter\r\nevenings to sweltering summer days when the streets were packed with\r\ntourists.[4]\r\nYou can of course paint people like still lives if you want\r\nto, and they're willing. That sort of portrait is arguably the apex\r\nof still life painting, though the long sitting does tend to produce\r\npained expressions in the sitters.[5]\r\nInterleaf was one of many companies that had smart people and\r\nbuilt impressive technology, and yet got crushed by Moore's Law.\r\nIn the 1990s the exponential growth in the power of commodity (i.e.\r\nIntel) processors rolled up high-end, special-purpose hardware and\r\nsoftware companies like a bulldozer.[6]\r\nThe signature style seekers at RISD weren't specifically\r\nmercenary. In the art world, money and coolness are tightly coupled.\r\nAnything expensive comes to be seen as cool, and anything seen as\r\ncool will soon become equally expensive.[7]\r\nTechnically the apartment wasn't rent-controlled but\r\nrent-stabilized, but this is a refinement only New Yorkers would\r\nknow or care about. The point is that it was really cheap, less\r\nthan half market price.[8]\r\nMost software you can launch as soon as it's done. But when\r\nthe software is an online store builder and you're hosting the\r\nstores, if you don't have any users yet, that fact will be painfully\r\nobvious. So before we could launch publicly we had to launch\r\nprivately, in the sense of recruiting an initial set of users and\r\nmaking sure they had decent-looking stores.[9]\r\nWe'd had a code editor in Viaweb for users to define their\r\nown page styles. They didn't know it, but they were editing Lisp\r\nexpressions underneath. But this wasn't an app editor, because the\r\ncode ran when the merchants' sites were generated, not when shoppers\r\nvisited them.[10]\r\nThis was the first instance of what is now a familiar experience,\r\nand so was what happened next, when I read the comments and found\r\nthey were full of angry people. How could I claim that Lisp was\r\nbetter than other languages? Weren't they all Turing complete?\r\nPeople who see the responses to essays I write sometimes tell me\r\nhow sorry they feel for me, but I'm not exaggerating when I reply\r\nthat it has always been like this, since the very beginning. It\r\ncomes with the territory. An essay must tell readers things they\r\ndon't already know, and some \r\npeople dislike being told such things.[11]\r\nPeople put plenty of stuff on the internet in the 90s of\r\ncourse, but putting something online is not the same as publishing\r\nit online. Publishing online means you treat the online version as\r\nthe (or at least a) primary version.[12]\r\nThere is a general lesson here that our experience with Y\r\nCombinator also teaches: Customs continue to constrain you long\r\nafter the restrictions that caused them have disappeared. Customary\r\nVC practice had once, like the customs about publishing essays,\r\nbeen based on real constraints. Startups had once been much more\r\nexpensive to start, and proportionally rare. Now they could be cheap\r\nand common, but the VCs' customs still reflected the old world,\r\njust as customs about writing essays still reflected the constraints\r\nof the print era.Which in turn implies that people who are independent-minded (i.e.\r\nless influenced by custom) will have an advantage in fields affected\r\nby rapid change (where customs are more likely to be obsolete).Here's an interesting point, though: you can't always predict which\r\nfields will be affected by rapid change. Obviously software and\r\nventure capital will be, but who would have predicted that essay\r\nwriting would be?[13]\r\nY Combinator was not the original name. At first we were\r\ncalled Cambridge Seed. But we didn't want a regional name, in case\r\nsomeone copied us in Silicon Valley, so we renamed ourselves after\r\none of the coolest tricks in the lambda calculus, the Y combinator.I picked orange as our color partly because it's the warmest, and\r\npartly because no VC used it. In 2005 all the VCs used staid colors\r\nlike maroon, navy blue, and forest green, because they were trying\r\nto appeal to LPs, not founders. The YC logo itself is an inside\r\njoke: the Viaweb logo had been a white V on a red circle, so I made\r\nthe YC logo a white Y on an orange square.[14]\r\nYC did become a fund for a couple years starting in 2009,\r\nbecause it was getting so big I could no longer afford to fund it\r\npersonally. But after Heroku got bought we had enough money to go\r\nback to being self-funded.[15]\r\nI've never liked the term \"deal flow,\" because it implies\r\nthat the number of new startups at any given time is fixed. This\r\nis not only false, but it's the purpose of YC to falsify it, by\r\ncausing startups to be founded that would not otherwise have existed.[16]\r\nShe reports that they were all different shapes and sizes,\r\nbecause there was a run on air conditioners and she had to get\r\nwhatever she could, but that they were all heavier than she could\r\ncarry now.[17]\r\nAnother problem with HN was a bizarre edge case that occurs\r\nwhen you both write essays and run a forum. When you run a forum,\r\nyou're assumed to see if not every conversation, at least every\r\nconversation involving you. And when you write essays, people post\r\nhighly imaginative misinterpretations of them on forums. Individually\r\nthese two phenomena are tedious but bearable, but the combination\r\nis disastrous. You actually have to respond to the misinterpretations,\r\nbecause the assumption that you're present in the conversation means\r\nthat not responding to any sufficiently upvoted misinterpretation\r\nreads as a tacit admission that it's correct. But that in turn\r\nencourages more; anyone who wants to pick a fight with you senses\r\nthat now is their chance.[18]\r\nThe worst thing about leaving YC was not working with Jessica\r\nanymore. We'd been working on YC almost the whole time we'd known\r\neach other, and we'd neither tried nor wanted to separate it from\r\nour personal lives, so leaving was like pulling up a deeply rooted\r\ntree.[19]\r\nOne way to get more precise about the concept of invented vs\r\ndiscovered is to talk about space aliens. Any sufficiently advanced\r\nalien civilization would certainly know about the Pythagorean\r\ntheorem, for example. I believe, though with less certainty, that\r\nthey would also know about the Lisp in McCarthy's 1960 paper.But if so there's no reason to suppose that this is the limit of\r\nthe language that might be known to them. Presumably aliens need\r\nnumbers and errors and I/O too. So it seems likely there exists at\r\nleast one path out of McCarthy's Lisp along which discoveredness\r\nis preserved.Thanks to Trevor Blackwell, John Collison, Patrick Collison, Daniel\r\nGackle, Ralph Hazell, Jessica Livingston, Robert Morris, and Harj\r\nTaggar for reading drafts of this." }, { "path": "data/PaulGrahamEssays/writing44.txt", "content": "March 2005\n(In the process\nof answering an email, I accidentally wrote a tiny essay about writing.\nI usually spend weeks on an essay. This one took 67 minutes—23\nof writing, and 44 of rewriting.)I think it's far more important to write well than most people\nrealize. Writing doesn't just communicate ideas; it generates them.\nIf you're bad at writing and don't like to do it, you'll miss out\non most of the ideas writing would have generated.As for how to write well, here's the short version: \nWrite a bad version\n1 as fast as you can; rewrite it over and over; cut out everything\nunnecessary; write in a conversational tone; develop a nose for\nbad writing, so you can see and fix it in yours; imitate writers\nyou like; if you can't get started, tell someone what you plan to\nwrite about, then write down what you said; expect\n80% of the ideas in an essay to happen after you start writing it,\nand 50% of those you start with to be wrong; be confident enough\nto cut; have friends you trust read your stuff and tell you which\nbits are confusing or drag; don't (always) make detailed outlines;\nmull ideas over for a few days before\nwriting; carry a small notebook or scrap paper with you; start writing \nwhen you think of the first \nsentence; if a deadline\nforces you to start before that, just say the most important sentence\nfirst; write about stuff you like; don't try to sound impressive; don't hesitate to change the topic on the fly;\nuse footnotes to contain digressions; use anaphora to knit\nsentences together; read your essays out loud to see (a) where you stumble\nover awkward phrases and (b) which bits are boring (the\nparagraphs you dread reading); try to tell the\nreader something new and useful; work in fairly big quanta of time;\nwhen you restart, begin by rereading what you have so far; when you\nfinish, leave yourself something easy to start with; accumulate\nnotes for topics you plan to cover at the bottom of the file; don't\nfeel obliged to cover any of them; write for a reader who won't\nread the essay as carefully as you do, just as pop songs are\ndesigned to sound ok on crappy car radios; \nif you say anything mistaken, fix it immediately;\nask friends which sentence you'll regret most; go back and tone\ndown harsh remarks; publish stuff online, because\nan audience makes you write more, and thus generate more\nideas; print out drafts instead of just looking at them\non the screen; use simple, germanic words; learn to distinguish\nsurprises from digressions; learn to recognize the approach of an\nending, and when one appears, grab it." }, { "path": "data/PaulGrahamEssays/wtax.txt", "content": "August 2020Some politicians are proposing to introduce wealth taxes in addition\nto income and capital gains taxes. Let's try modeling the effects of various levels\nof wealth tax to see what they would mean in practice for a startup\nfounder.Suppose you start a successful startup in your twenties, and then\nlive for another 60 years. How much of your stock will a wealth tax\nconsume?If the wealth tax applies to all your assets, it's easy to\ncalculate its effect. A wealth tax of 1% means you get to keep\n99% of your stock each year. After 60 years the proportion\nof stock you'll have left will be .99^60, or .547. So a\nstraight 1% wealth tax means the government will over the\ncourse of your life take 45% of your stock.(Losing shares does not, obviously, mean becoming net\npoorer unless the value per share is increasing by less than the \nwealth tax rate.)Here's how much stock the government would take over 60\nyears at various levels of wealth tax:\nwealth taxgovernment takes\n0.1%6%0.5%26%\n1.0%45%\n2.0%70%\n3.0%84%\n4.0%91%5.0%95%\n\n\n\nA wealth tax will usually have a threshold at which it starts.\nHow much difference would a high threshold make? To model that,\nwe need to make some assumptions about the initial value of\nyour stock and the growth rate.Suppose your stock is initially\nworth $2 million, and the company's trajectory is as follows:\nthe value of your stock grows 3x for 2 years, then 2x for 2 years,\nthen 50% for 2 years, after\nwhich you just get a typical public company growth rate,\nwhich we'll call 8%. \n[1]\nSuppose the wealth tax threshold is\n$50 million. How much stock does the government take now?\n\nwealth taxgovernment takes\n0.1%5%0.5%23%\n1.0%41%\n2.0%65%\n3.0%79%\n4.0%88%5.0%93%\n\n\n\nIt may at first seem surprising that such apparently small tax rates\nproduce such dramatic effects. A 2% wealth tax with a $50 million\nthreshold takes about two thirds of a successful founder's stock.The reason wealth taxes have such dramatic effects is that they're\napplied over and over to the same money. Income tax\nhappens every year, but only to that year's income. Whereas if you\nlive for 60 years after acquiring some asset, a wealth tax will tax\nthat same asset 60 times. A wealth tax compounds.Note[1]\nIn practice, eventually some of this 8% would come in the form of \ndividends, which are taxed as income at issue, so this model actually\nrepresents the most optimistic case for the founder." }, { "path": "data/PaulGrahamEssays/yahoo.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nAugust 2010When I went to work for Yahoo after they bought our startup in 1998,\nit felt like the center of the world. It was supposed to be the\nnext big thing. It was supposed to be what Google turned out to\nbe.What went wrong? The problems that hosed Yahoo go back a long time,\npractically to the beginning of the company. They were already\nvery visible when I got there in 1998. Yahoo had two problems\nGoogle didn't: easy money, and ambivalence about being a technology\ncompany.MoneyThe first time I met Jerry Yang, we thought we were meeting for\ndifferent reasons. He thought we were meeting so he could check\nus out in person before buying us. I thought we were meeting so we\ncould show him our new technology, Revenue Loop. It was a way of\nsorting shopping search results. Merchants bid a percentage of\nsales for traffic, but the results were sorted not by the bid but\nby the bid times the average amount a user would buy. It was\nlike the algorithm Google uses now to sort ads, but this was in the\nspring of 1998, before Google was founded.Revenue Loop was the optimal sort for shopping search, in the sense\nthat it sorted in order of how much money Yahoo would make from\neach link. But it wasn't just optimal in that sense. Ranking\nsearch results by user behavior also makes search better. Users\ntrain the search: you can start out finding matches based on mere\ntextual similarity, and as users buy more stuff the search results\nget better and better.Jerry didn't seem to care. I was confused. I was showing him\ntechnology that extracted the maximum value from search traffic,\nand he didn't care? I couldn't tell whether I was explaining it\nbadly, or he was just very poker faced.I didn't realize the answer till later, after I went to work at\nYahoo. It was neither of my guesses. The reason Yahoo didn't care\nabout a technique that extracted the full value of traffic was that\nadvertisers were already overpaying for it. If Yahoo merely extracted\nthe actual value, they'd have made less.Hard as it is to believe now, the big money then was in banner ads.\nAdvertisers were willing to pay ridiculous amounts for banner ads.\nSo Yahoo's sales force had evolved to exploit this source of revenue.\nLed by a large and terrifyingly formidable man called Anil Singh,\nYahoo's sales guys would fly out to Procter & Gamble and come back\nwith million dollar orders for banner ad impressions.The prices seemed cheap compared to print, which was what advertisers,\nfor lack of any other reference, compared them to. But they were\nexpensive compared to what they were worth. So these big, dumb\ncompanies were a dangerous source of revenue to depend on. But\nthere was another source even more dangerous: other Internet startups.By 1998, Yahoo was the beneficiary of a de facto Ponzi scheme.\nInvestors were excited about the Internet. One reason they were\nexcited was Yahoo's revenue growth. So they invested in new Internet\nstartups. The startups then used the money to buy ads on Yahoo to\nget traffic. Which caused yet more revenue growth for Yahoo, and\nfurther convinced investors the Internet was worth investing in.\nWhen I realized this one day, sitting in my cubicle, I jumped up\nlike Archimedes in his bathtub, except instead of \"Eureka!\" I was\nshouting \"Sell!\"Both the Internet startups and the Procter & Gambles were doing\nbrand advertising. They didn't care about targeting. They just\nwanted lots of people to see their ads. So traffic became the thing\nto get at Yahoo. It didn't matter what type.\n[1]It wasn't just Yahoo. All the search engines were doing it. This\nwas why they were trying to get people to start calling them \"portals\"\ninstead of \"search engines.\" Despite the actual meaning of the word\nportal, what they meant by it was a site where users would find\nwhat they wanted on the site itself, instead of just passing through\non their way to other destinations, as they did at a search engine.I remember telling David Filo in late 1998 or early 1999 that Yahoo\nshould buy Google, because I and most of the other programmers in\nthe company were using it instead of Yahoo for search. He told me\nthat it wasn't worth worrying about. Search was only 6% of our\ntraffic, and we were growing at 10% a month. It wasn't worth doing\nbetter.I didn't say \"But search traffic is worth more than other traffic!\"\nI said \"Oh, ok.\" Because I didn't realize either how much search\ntraffic was worth. I'm not sure even Larry and Sergey did then.\nIf they had, Google presumably wouldn't have expended any effort\non enterprise search.If circumstances had been different, the people running Yahoo might\nhave realized sooner how important search was. But they had the\nmost opaque obstacle in the world between them and the truth: money.\nAs long as customers were writing big checks for banner ads, it was\nhard to take search seriously. Google didn't have that to distract\nthem.HackersBut Yahoo also had another problem that made it hard to change\ndirections. They'd been thrown off balance from the start by their\nambivalence about being a technology company.One of the weirdest things about Yahoo when I went to work there\nwas the way they insisted on calling themselves a \"media company.\"\nIf you walked around their offices, it seemed like a software\ncompany. The cubicles were full of programmers writing code, product\nmanagers thinking about feature lists and ship dates, support people\n(yes, there were actually support people) telling users to restart\ntheir browsers, and so on, just like a software company. So why\ndid they call themselves a media company?One reason was the way they made money: by selling ads. In 1995\nit was hard to imagine a technology company making money that way.\nTechnology companies made money by selling their software to users.\nMedia companies sold ads. So they must be a media company.Another big factor was the fear of Microsoft. If anyone at Yahoo\nconsidered the idea that they should be a technology company, the\nnext thought would have been that Microsoft would crush them.It's hard for anyone much younger than me to understand the fear\nMicrosoft still inspired in 1995. Imagine a company with several\ntimes the power Google has now, but way meaner. It was perfectly\nreasonable to be afraid of them. Yahoo watched them crush the first\nhot Internet company, Netscape. It was reasonable to worry that\nif they tried to be the next Netscape, they'd suffer the same fate.\nHow were they to know that Netscape would turn out to be Microsoft's\nlast victim?It would have been a clever move to pretend to be a media company\nto throw Microsoft off their scent. But unfortunately Yahoo actually\ntried to be one, sort of. Project managers at Yahoo were called\n\"producers,\" for example, and the different parts of the company\nwere called \"properties.\" But what Yahoo really needed to be was a\ntechnology company, and by trying to be something else, they ended\nup being something that was neither here nor there. That's why\nYahoo as a company has never had a sharply defined identity.The worst consequence of trying to be a media company was that they\ndidn't take programming seriously enough. Microsoft (back in the\nday), Google, and Facebook have all had hacker-centric cultures.\nBut Yahoo treated programming as a commodity. At Yahoo, user-facing software\nwas controlled by product managers and designers. The job of\nprogrammers was just to take the work of the product managers and\ndesigners the final step, by translating it into code.One obvious result of this practice was that when Yahoo built things,\nthey often weren't very good. But that wasn't the worst problem.\nThe worst problem was that they hired bad programmers.Microsoft (back in the day), Google, and Facebook have all been\nobsessed with hiring the best programmers. Yahoo wasn't. They\npreferred good programmers to bad ones, but they didn't have the\nkind of single-minded, almost obnoxiously elitist focus on hiring\nthe smartest people that the big winners have had. And when you\nconsider how much competition there was for programmers when they\nwere hiring, during the Bubble, it's not surprising that the quality\nof their programmers was uneven.In technology, once you have bad programmers, you're doomed. I\ncan't think of an instance where a company has sunk into technical\nmediocrity and recovered. Good programmers want to work with other\ngood programmers. So once the quality of programmers at your company\nstarts to drop, you enter a death spiral from which there is no\nrecovery.\n[2]At Yahoo this death spiral started early. If there was ever a time when\nYahoo was a Google-style talent magnet, it was over by the time I\ngot there in 1998.The company felt prematurely old. Most technology companies\neventually get taken over by suits and middle managers. At Yahoo\nit felt as if they'd deliberately accelerated this process. They\ndidn't want to be a bunch of hackers. They wanted to be suits. A\nmedia company should be run by suits.The first time I visited Google, they had about 500 people, the\nsame number Yahoo had when I went to work there. But boy did things\nseem different. It was still very much a hacker-centric culture.\nI remember talking to some programmers in the cafeteria about the\nproblem of gaming search results (now known as SEO), and they asked\n\"what should we do?\" Programmers at Yahoo wouldn't have asked that.\nTheirs was not to reason why; theirs was to build what product\nmanagers spec'd. I remember coming away from Google thinking \"Wow,\nit's still a startup.\"There's not much we can learn from Yahoo's first fatal flaw. It's\nprobably too much to hope any company could avoid being damaged by\ndepending on a bogus source of revenue. But startups can learn an\nimportant lesson from the second one. In the software business,\nyou can't afford not to have a hacker-centric culture.Probably the most impressive commitment I've heard to having a\nhacker-centric culture came from Mark Zuckerberg, when he spoke at\nStartup School in 2007. He said that in the early days Facebook\nmade a point of hiring programmers even for jobs that would not\nordinarily consist of programming, like HR and marketing.So which companies need to have a hacker-centric culture? Which\ncompanies are \"in the software business\" in this respect? As Yahoo\ndiscovered, the area covered by this rule is bigger than most people\nrealize. The answer is: any company that needs to have good software.Why would great programmers want to work for a company that didn't\nhave a hacker-centric culture, as long as there were others that\ndid? I can imagine two reasons: if they were paid a huge amount,\nor if the domain was interesting and none of the companies in it\nwere hacker-centric. Otherwise you can't attract good programmers\nto work in a suit-centric culture. And without good programmers\nyou won't get good software, no matter how many people you put on\na task, or how many procedures you establish to ensure \"quality.\"Hacker culture \noften seems kind of irresponsible. That's why people\nproposing to destroy it use phrases like \"adult supervision.\" That\nwas the phrase they used at Yahoo. But there are worse things than\nseeming irresponsible. Losing, for example.\nNotes[1]\nThe closest we got to targeting when I was there was when we\ncreated pets.yahoo.com in order to provoke a bidding war between 3\npet supply startups for the spot as top sponsor.[2]\nIn theory you could beat the death spiral by buying good\nprogrammers instead of hiring them. You can get programmers\nwho would never have come to you as employees by buying their \nstartups. But so far the only companies smart enough\nto do this are companies smart enough not to need to.Thanks to Trevor Blackwell, Jessica Livingston, and\nGeoff Ralston for\nreading drafts of this." }, { "path": "data/PaulGrahamEssays/ycombinator.txt", "content": "March 2008, rev May 2013(This essay grew out of something I wrote for myself to figure\nout what we do. Even though Y Combinator is now 3 years old, we're still\ntrying to understand its implications.)\nI was annoyed recently to read a description of Y Combinator that\nsaid \"Y Combinator does seed funding for startups.\" What was\nespecially annoying about it was that I wrote it. This doesn't\nreally convey what we do. And the reason it's inaccurate is that,\nparadoxically, funding very early stage startups is not mainly about\nfunding.Saying YC does seed funding for startups is a description in terms\nof earlier models. It's like calling a car a horseless carriage.When you scale animals you can't just keep everything in proportion.\nFor example, volume grows as the cube of linear dimension, but\nsurface area only as the square. So as animals get bigger they\nhave trouble radiating heat. That's why mice and rabbits are furry\nand elephants and hippos aren't. You can't make a mouse by scaling\ndown an elephant.YC represents a new, smaller kind of animal—so much smaller\nthat all the rules are different.Before us, most companies in the startup funding business were\nventure capital funds. VCs generally fund later stage companies\nthan we do. And they supply so much money that, even though the\nother things they do may be very valuable, it's not that inaccurate\nto regard VCs as sources of money. Good VCs are \"smart money,\" but\nthey're still money.All good investors supply a combination of money and help. But\nthese scale differently, just as volume and surface area do. Late\nstage investors supply huge amounts of money and\ncomparatively little help: when a company about to go public gets\na mezzanine round of $50 million, the deal tends to be almost\nentirely about money. As you move earlier in the venture\nfunding process, the ratio of help to money increases, because\nearlier stage companies have different needs. Early stage companies\nneed less money because they're smaller and cheaper to run, but\nthey need more help because life is so precarious for them. So\nwhen VCs do a series A round for, say, $2 million, they generally\nexpect to offer a significant amount of help along with the money.Y Combinator occupies the earliest end of the spectrum. We're at\nleast one and generally two steps before VC funding. (Though some\nstartups go straight from YC to VC, the most common trajectory is\nto do an angel round first.) And what happens at Y Combinator is\nas different from what happens in a series A round as a series A\nround is from a mezzanine financing.At our end, money is almost a negligible factor. The startup usually\nconsists of just the founders. Their living expenses are the\ncompany's main expense, and since most founders are under 30, their\nliving expenses are low. But at this early stage companies need a\nlot of help. Practically every question is still unanswered. Some\ncompanies we've funded have been working on their software for a\nyear or more, but others haven't decided what to work on, or even\nwho the founders should be.When PR people and journalists recount the histories of startups\nafter they've become big, they always underestimate how uncertain\nthings were at first. They're not being deliberately misleading.\nWhen you look at a company like Google, it's hard to imagine they\ncould once have been small and helpless. Sure, at one point they\nwere a just a couple guys in a garage—but even then their\ngreatness was assured, and all they had to do was roll forward along\nthe railroad tracks of destiny.Far from it. A lot of startups with just as promising beginnings\nend up failing. Google has such momentum now that it would be hard\nfor anyone to stop them. But all it would have taken in the beginning\nwould have been for two Google employees to focus on the wrong\nthings for six months, and the company could have died.We know, because we've been there, just how vulnerable startups are\nin the earliest phases. Curiously enough, that's why founders tend\nto get so rich from them. Reward is always proportionate to risk,\nand very early stage startups are insanely risky.What we really do at Y Combinator is get startups launched straight.\nOne of many metaphors you could use for YC is a steam catapult on\nan aircraft carrier. We get startups airborne. Barely airborne,\nbut enough that they can accelerate fast.When you're launching planes they have to be set up properly or\nyou're just launching projectiles. They have to be pointed straight\ndown the deck; the wings have to be trimmed properly; the engines\nhave to be at full power; the pilot has to be ready. These are the\nkind of problems we deal with. After we fund startups we work\nclosely with them for three months—so closely in fact that\nwe insist they move to where we are. And what we do in those three\nmonths is make sure everything is set up for launch. If there are\ntensions between cofounders we help sort them out. We get all the\npaperwork set up properly so there are no nasty surprises later.\nIf the founders aren't sure what to focus on first, we try to figure\nthat out. If there is some obstacle right in front of them, we\neither try to remove it, or shift the startup sideways. The goal\nis to get every distraction out of the way so the founders can use\nthat time to build (or finish building) something impressive. And\nthen near the end of the three months we push the button on the\nsteam catapult in the form of Demo Day, where the current group of\nstartups present to pretty much every investor in Silicon Valley.Launching companies isn't identical with launching products. Though\nwe do spend a lot of time on launch strategies for products, there\nare some things that take too long to build for a startup to launch\nthem before raising their next round of funding. Several of the\nmost promising startups we've funded haven't launched their products\nyet, but are definitely launched as companies.In the earliest stage, startups not only have more questions to\nanswer, but they tend to be different kinds of questions. In later\nstage startups the questions are about deals, or hiring, or\norganization. In the earliest phase they tend to be about technology\nand design. What do you make? That's the first problem to solve.\nThat's why our motto is \"Make something people want.\" This is\nalways a good thing for companies to do, but it's even more important\nearly on, because it sets the bounds for every other question. Who\nyou hire, how much money you raise, how you market yourself—they\nall depend on what you're making.Because the early problems are so much about technology and design,\nyou probably need to be hackers to do what we do. While some VCs\nhave technical backgrounds, I don't know any who still write code.\nTheir expertise is mostly in business—as it should be, because\nthat's the kind of expertise you need in the phase between series\nA and (if you're lucky) IPO.We're so different from VCs that we're really a different kind of\nanimal. Can we claim founders are better off as a result of this\nnew type of venture firm? I'm pretty sure the answer is yes, because\nYC is an improved version of what happened to our startup, and our\ncase was not atypical. We started Viaweb with $10,000 in seed money\nfrom our friend Julian. He was a lawyer and arranged all our\npaperwork, so we could just code. We spent three months building\na version 1, which we then presented to investors to raise more\nmoney. Sounds familiar, doesn't it? But YC improves on that\nsignificantly. Julian knew a lot about law and business, but his\nadvice ended there; he was not a startup guy. So we made some basic\nmistakes early on. And when we presented to investors, we presented\nto only 2, because that was all we knew. If we'd had our later\nselves to encourage and advise us, and Demo Day to present at, we\nwould have been in much better shape. We probably could have raised\nmoney at 3 to 5 times the valuation we did.If we take 7% of a company we fund, the founders only have to do\n7.5% better in their next round of funding\nto end up net ahead. We certainly manage that.So who is our 7% coming out of? If the founders end up net ahead\nit's not coming out of them. So is it coming out of later stage\ninvestors? Well, they do end up paying more. But I think they pay\nmore because the company is actually more valuable. And later stage\ninvestors have no problem with that. The returns of a VC fund\ndepend on the quality of the companies they invest in, not how\ncheaply they can buy stock in them.If what we do is useful, why wasn't anyone doing it before? There\nare two answers to that. One is that people were doing it before,\njust haphazardly on a smaller scale. Before us, seed funding came\nprimarily from individual angel investors. Larry and Sergey, for\nexample, got their seed funding from Andy Bechtolsheim, one of the\nfounders of Sun. And because he was a startup guy he probably gave\nthem useful advice. But raising money from angel investors is a\nhit or miss thing. It's a sideline for most of them, so they only\ndo a handful of deals a year and they don't spend a lot of time on\nthe startups they invest in. And they're hard to reach, because\nthey don't want random startups pestering them with business plans.\nThe Google guys were lucky because they knew someone who knew\nBechtolsheim. It generally takes a personal introduction with\nangels.The other reason no one was doing quite what we do is that till\nrecently it was a lot more expensive to start a startup. You'll\nnotice we haven't funded any biotech startups. That's still\nexpensive. But advancing technology has made web startups so cheap\nthat you really can get a company airborne for $15,000. If you\nunderstand how to operate a steam catapult, at least.So in effect what's happened is that a new ecological niche has\nopened up, and Y Combinator is the new kind of animal that has moved\ninto it. We're not a replacement for venture capital funds. We\noccupy a new, adjacent niche. And conditions in our niche are\nreally quite different. It's not just that the problems we face\nare different; the whole structure of the business is different.\nVCs are playing a zero-sum game. They're all competing for a slice\nof a fixed amount of \"deal flow,\" and that explains a lot of their\nbehavior. Whereas our m.o. is to create new deal flow, by encouraging\nhackers who would have gotten jobs to start their own startups\ninstead. We compete more with employers than VCs.It's not surprising something like this would happen. Most fields\nbecome more specialized—more articulated—as they develop,\nand startups are certainly an area in which there has been a lot\nof development over the past couple decades. The venture business\nin its present form is only about forty years old. It stands to\nreason it would evolve.And it's natural that the new niche would at first be described,\neven by its inhabitants, in terms of the old one. But really Y\nCombinator is not in the startup funding business. Really we're\nmore of a small, furry steam catapult.Thanks to Trevor Blackwell, Jessica Livingston, and Robert Morris\nfor reading drafts of this.\nComment on this essay." }, { "path": "data/PaulGrahamEssays/ycstart.txt", "content": "March 2012Y Combinator's 7th birthday was March 11. As usual we were so\nbusy we didn't notice till a few days after. I don't think we've\never managed to remember our birthday on our birthday.\n\nOn March 11 2005, Jessica and I were walking home from dinner in\nHarvard Square. Jessica was working at an investment bank at the\ntime, but she didn't like it much, so she had interviewed for a job\nas director of marketing at a Boston VC fund. The VC fund was doing\nwhat now seems a comically familiar thing for a VC fund to do:\ntaking a long time to make up their mind. Meanwhile I had been\ntelling Jessica all the things they should change about the VC\nbusiness — essentially the ideas now underlying Y Combinator:\ninvestors\nshould be making more, smaller investments, they should be funding\nhackers instead of suits, they should be willing to fund younger\nfounders, etc.\n\nAt the time I had been thinking about doing some angel investing. I\nhad just given a talk to the undergraduate computer club at Harvard\nabout\nhow to start a\nstartup, and it\nhit me afterward that although I had always\nmeant to do angel investing, 7 years had now passed since I got\nenough money to do it, and I still hadn't started. I had also\nbeen thinking about ways to work with Robert Morris and Trevor\nBlackwell again. A few hours before I had\nsent them an email trying to figure out what we could do together.\n\nBetween Harvard Square and my house the idea gelled. We'd start\nour own investment firm and Jessica could work for that instead.\nAs we turned onto Walker Street we decided to do it. I agreed to\nput $100k into the new fund and Jessica agreed to quit her job to\nwork for it. Over the next couple days I recruited Robert\nand Trevor, who put in another $50k each. So YC\nstarted with $200k.\n\nJessica was so happy to be able to quit her job and start her own\ncompany that I took her picture\n when we got home.\n\nThe company wasn't called Y Combinator yet. At first we called it\nCambridge Seed. But that name never saw the light of day, because\nby the time we announced it a few days later, we'd changed the name\nto Y Combinator. We realized early on that what we were doing could\nbe national in scope and we didn't want a name that tied us to one\nplace.\n\nInitially we only had part of the idea. We were going to do\nseed funding with standardized terms. Before YC, seed funding was\nvery haphazard. You'd get that first $10k from your friend's rich\nuncle. The deal terms were often a disaster; often neither the\ninvestor nor the founders nor the lawyer knew what the documents\nshould look like. Facebook's early history as a Florida LLC shows\nhow random things could be in those days. We were going to be\nsomething there had not been before: a standard source of seed\nfunding.\n\nWe modelled YC on the seed funding we ourselves had taken\nwhen we started Viaweb. We started Viaweb with $10k we got from\nour friend Julian Weber,\nthe husband of Idelle Weber, whose\npainting class I took as a grad student at Harvard. Julian knew\nabout business, but you would not describe him as a suit. Among\nother things he'd been president of the National Lampoon. He was\nalso a lawyer, and got all our paperwork set up properly. In return\nfor $10k, getting us set up as a company, teaching us what\nbusiness was about, and remaining calm in times of crisis, Julian\ngot 10% of Viaweb. I remember thinking once what a good deal\nJulian got. And then a second later I realized that without\nJulian, Viaweb would never have made it. So even though it was a\ngood deal for him, it was a good deal for us too. That's why I\nknew there was room for something like Y Combinator.\n\nInitially we didn't have what turned out to be the most important\nidea: funding startups synchronously, instead of asynchronously as\nit had always been done before. Or rather we had the idea, but we\ndidn't realize its significance. We decided very early \nthat the first thing we'd do would\nbe to fund a bunch of startups over the coming summer. But we\ndidn't realize initially that this would be the way we'd do all our\ninvesting. The reason we began by funding a bunch of startups at\nonce was not that we thought it would be a better way to fund\nstartups, but simply because we wanted to learn how to be angel\ninvestors, and a summer program for undergrads seemed the fastest\nway to do it. No one takes summer jobs that seriously. The\nopportunity cost for a bunch of undergrads to spend a summer working\non startups was low enough that we wouldn't feel guilty encouraging\nthem to do it.\n\nWe knew students would already be making plans for the summer, so\nwe did what we're always telling startups to do: we launched fast.\nHere are the\ninitial announcement\nand description of what\nwas at the time called the Summer Founders Program.\n\nWe got lucky in that the length and structure of a summer program\nturns out to be perfect for what we do.\nThe structure of the YC cycle is still almost identical to what\nit was that first summer.\n\nWe also got lucky in who the first batch of founders were. We never\nexpected to make any money from that first batch. We thought of\nthe money we were investing as a combination of an educational expense\nand a charitable donation. But the\nfounders in the first batch turned out to be surprisingly good.\nAnd great people too. We're still friends with a lot of them today.\n\nIt's hard for people to realize now how inconsequential YC seemed at the\ntime. I can't blame people who didn't take us seriously, because\nwe ourselves didn't take that first summer program seriously in the\nvery beginning. But as the summer progressed we were increasingly\nimpressed by how well the startups were doing. Other people started\nto be impressed too. Jessica and I invented a term, \"the Y Combinator\neffect,\" to describe the moment when the realization hit someone\nthat YC was not totally lame. When people came to YC to speak\nat the dinners that first summer, they came in the spirit of someone\ncoming to address a Boy Scout troop. By the time they left the\nbuilding they were all saying some variant of \"Wow, these\ncompanies might actually succeed.\"\n\nNow YC is well enough known that people are no longer surprised\nwhen the companies we fund are legit, but it took a\nwhile for reputation to catch up with reality. That's one of the\nreasons we especially like funding ideas that might be dismissed\nas \"toys\" — because YC itself was dismissed as one initially.\n\nWhen we saw how well it worked to fund companies synchronously,\nwe decided we'd keep doing that. We'd fund two batches of\nstartups a year.\n\nWe funded the second batch in Silicon Valley. That was\na last minute decision. In retrospect I think what pushed me over\nthe edge was going to Foo Camp that fall. The density of startup\npeople in the Bay Area was so much greater than in Boston, and the\nweather was so nice. I remembered that from living there in the\n90s. Plus I didn't want someone else to copy us and describe it\nas the Y Combinator of Silicon Valley. I wanted YC to be the Y Combinator \nof Silicon Valley. So doing the winter batch in California\nseemed like one of those rare cases where the self-indulgent choice\nand the ambitious one were the same.\n\nIf we'd had enough time to do what we wanted, Y Combinator would\nhave been in Berkeley. That was our favorite part of the Bay Area.\nBut we didn't have time to get a building in Berkeley. We didn't\nhave time to get our own building anywhere. The only way to get\nenough space in time was to convince Trevor to let us take over\npart of his (as it then seemed) giant building in Mountain View.\nYet again we lucked out, because Mountain View turned out to be the\nideal place to put something like YC. But even then we barely made\nit. The first dinner in California, we had to warn all the founders\nnot to touch the walls, because the paint was still wet." }, { "path": "data/PaulGrahamEssaysLarge/addiction.txt", "content": "July 2010What hard liquor, cigarettes, heroin, and crack have in common is\nthat they're all more concentrated forms of less addictive predecessors.\nMost if not all the things we describe as addictive are. And the\nscary thing is, the process that created them is accelerating.We wouldn't want to stop it. It's the same process that cures\ndiseases: technological progress. Technological progress means\nmaking things do more of what we want. When the thing we want is\nsomething we want to want, we consider technological progress good.\nIf some new technique makes solar cells x% more efficient, that\nseems strictly better. When progress concentrates something we\ndon't want to want—when it transforms opium into heroin—it seems\nbad. But it's the same process at work.\n[1]No one doubts this process is accelerating, which means increasing\nnumbers of things we like will be transformed into things we like\ntoo much.\n[2]As far as I know there's no word for something we like too much.\nThe closest is the colloquial sense of \"addictive.\" That usage has\nbecome increasingly common during my lifetime. And it's clear why:\nthere are an increasing number of things we need it for. At the\nextreme end of the spectrum are crack and meth. Food has been\ntransformed by a combination of factory farming and innovations in\nfood processing into something with way more immediate bang for the\nbuck, and you can see the results in any town in America. Checkers\nand solitaire have been replaced by World of Warcraft and FarmVille.\nTV has become much more engaging, and even so it can't compete with Facebook.The world is more addictive than it was 40 years ago. And unless\nthe forms of technological progress that produced these things are\nsubject to different laws than technological progress in general,\nthe world will get more addictive in the next 40 years than it did\nin the last 40.The next 40 years will bring us some wonderful things. I don't\nmean to imply they're all to be avoided. Alcohol is a dangerous\ndrug, but I'd rather live in a world with wine than one without.\nMost people can coexist with alcohol; but you have to be careful.\nMore things we like will mean more things we have to be careful\nabout.Most people won't, unfortunately. Which means that as the world\nbecomes more addictive, the two senses in which one can live a\nnormal life will be driven ever further apart. One sense of \"normal\"\nis statistically normal: what everyone else does. The other is the\nsense we mean when we talk about the normal operating range of a\npiece of machinery: what works best.These two senses are already quite far apart. Already someone\ntrying to live well would seem eccentrically abstemious in most of\nthe US. That phenomenon is only going to become more pronounced.\nYou can probably take it as a rule of thumb from now on that if\npeople don't think you're weird, you're living badly.Societies eventually develop antibodies to addictive new things.\nI've seen that happen with cigarettes. When cigarettes first\nappeared, they spread the way an infectious disease spreads through\na previously isolated population. Smoking rapidly became a\n(statistically) normal thing. There were ashtrays everywhere. We\nhad ashtrays in our house when I was a kid, even though neither of\nmy parents smoked. You had to for guests.As knowledge spread about the dangers of smoking, customs changed.\nIn the last 20 years, smoking has been transformed from something\nthat seemed totally normal into a rather seedy habit: from something\nmovie stars did in publicity shots to something small huddles of\naddicts do outside the doors of office buildings. A lot of the\nchange was due to legislation, of course, but the legislation\ncouldn't have happened if customs hadn't already changed.It took a while though—on the order of 100 years. And unless the\nrate at which social antibodies evolve can increase to match the\naccelerating rate at which technological progress throws off new\naddictions, we'll be increasingly unable to rely on customs to\nprotect us.\n[3]\nUnless we want to be canaries in the coal mine\nof each new addiction—the people whose sad example becomes a\nlesson to future generations—we'll have to figure out for ourselves\nwhat to avoid and how. It will actually become a reasonable strategy\n(or a more reasonable strategy) to suspect \neverything new.In fact, even that won't be enough. We'll have to worry not just\nabout new things, but also about existing things becoming more\naddictive. That's what bit me. I've avoided most addictions, but\nthe Internet got me because it became addictive while I was using\nit.\n[4]Most people I know have problems with Internet addiction. We're\nall trying to figure out our own customs for getting free of it.\nThat's why I don't have an iPhone, for example; the last thing I\nwant is for the Internet to follow me out into the world.\n[5]\nMy latest trick is taking long hikes. I used to think running was a\nbetter form of exercise than hiking because it took less time. Now\nthe slowness of hiking seems an advantage, because the longer I\nspend on the trail, the longer I have to think without interruption.Sounds pretty eccentric, doesn't it? It always will when you're\ntrying to solve problems where there are no customs yet to guide\nyou. Maybe I can't plead Occam's razor; maybe I'm simply eccentric.\nBut if I'm right about the acceleration of addictiveness, then this\nkind of lonely squirming to avoid it will increasingly be the fate\nof anyone who wants to get things done. We'll increasingly be\ndefined by what we say no to.\nNotes[1]\nCould you restrict technological progress to areas where you\nwanted it? Only in a limited way, without becoming a police state.\nAnd even then your restrictions would have undesirable side effects.\n\"Good\" and \"bad\" technological progress aren't sharply differentiated,\nso you'd find you couldn't slow the latter without also slowing the\nformer. And in any case, as Prohibition and the \"war on drugs\"\nshow, bans often do more harm than good.[2]\nTechnology has always been accelerating. By Paleolithic\nstandards, technology evolved at a blistering pace in the Neolithic\nperiod.[3]\nUnless we mass produce social customs. I suspect the recent\nresurgence of evangelical Christianity in the US is partly a reaction\nto drugs. In desperation people reach for the sledgehammer; if\ntheir kids won't listen to them, maybe they'll listen to God. But\nthat solution has broader consequences than just getting kids to\nsay no to drugs. You end up saying no to \nscience as well.\nI worry we may be heading for a future in which only a few people\nplot their own itinerary through no-land, while everyone else books\na package tour. Or worse still, has one booked for them by the\ngovernment.[4]\nPeople commonly use the word \"procrastination\" to describe\nwhat they do on the Internet. It seems to me too mild to describe\nwhat's happening as merely not-doing-work. We don't call it\nprocrastination when someone gets drunk instead of working.[5]\nSeveral people have told me they like the iPad because it\nlets them bring the Internet into situations where a laptop would\nbe too conspicuous. In other words, it's a hip flask. (This is\ntrue of the iPhone too, of course, but this advantage isn't as\nobvious because it reads as a phone, and everyone's used to those.)Thanks to Sam Altman, Patrick Collison, Jessica Livingston, and\nRobert Morris for reading drafts of this." }, { "path": "data/PaulGrahamEssaysLarge/aord.txt", "content": "October 2015When I talk to a startup that's been operating for more than 8 or\n9 months, the first thing I want to know is almost always the same.\nAssuming their expenses remain constant and their revenue growth\nis what it has been over the last several months, do they make it to\nprofitability on the money they have left? Or to put it more\ndramatically, by default do they live or die?The startling thing is how often the founders themselves don't know.\nHalf the founders I talk to don't know whether they're default alive\nor default dead.If you're among that number, Trevor Blackwell has made a handy\ncalculator you can use to find out.The reason I want to know first whether a startup is default alive\nor default dead is that the rest of the conversation depends on the\nanswer. If the company is default alive, we can talk about ambitious\nnew things they could do. If it's default dead, we probably need\nto talk about how to save it. We know the current trajectory ends\nbadly. How can they get off that trajectory?Why do so few founders know whether they're default alive or default\ndead? Mainly, I think, because they're not used to asking that.\nIt's not a question that makes sense to ask early on, any more than\nit makes sense to ask a 3 year old how he plans to support\nhimself. But as the company grows older, the question switches from\nmeaningless to critical. That kind of switch often takes people\nby surprise.I propose the following solution: instead of starting to ask too\nlate whether you're default alive or default dead, start asking too\nearly. It's hard to say precisely when the question switches\npolarity. But it's probably not that dangerous to start worrying\ntoo early that you're default dead, whereas it's very dangerous to\nstart worrying too late.The reason is a phenomenon I wrote about earlier: the\nfatal pinch.\nThe fatal pinch is default dead + slow growth + not enough\ntime to fix it. And the way founders end up in it is by not realizing\nthat's where they're headed.There is another reason founders don't ask themselves whether they're\ndefault alive or default dead: they assume it will be easy to raise\nmore money. But that assumption is often false, and worse still, the\nmore you depend on it, the falser it becomes.Maybe it will help to separate facts from hopes. Instead of thinking\nof the future with vague optimism, explicitly separate the components.\nSay \"We're default dead, but we're counting on investors to save\nus.\" Maybe as you say that, it will set off the same alarms in your\nhead that it does in mine. And if you set off the alarms sufficiently\nearly, you may be able to avoid the fatal pinch.It would be safe to be default dead if you could count on investors\nsaving you. As a rule their interest is a function of\ngrowth. If you have steep revenue growth, say over 5x a year, you\ncan start to count on investors being interested even if you're not\nprofitable.\n[1]\nBut investors are so fickle that you can never\ndo more than start to count on them. Sometimes something about your\nbusiness will spook investors even if your growth is great. So no\nmatter how good your growth is, you can never safely treat fundraising\nas more than a plan A. You should always have a plan B as well: you\nshould know (as in write down) precisely what you'll need to do to\nsurvive if you can't raise more money, and precisely when you'll \nhave to switch to plan B if plan A isn't working.In any case, growing fast versus operating cheaply is far from the\nsharp dichotomy many founders assume it to be. In practice there\nis surprisingly little connection between how much a startup spends\nand how fast it grows. When a startup grows fast, it's usually\nbecause the product hits a nerve, in the sense of hitting some big\nneed straight on. When a startup spends a lot, it's usually because\nthe product is expensive to develop or sell, or simply because\nthey're wasteful.If you're paying attention, you'll be asking at this point not just\nhow to avoid the fatal pinch, but how to avoid being default dead.\nThat one is easy: don't hire too fast. Hiring too fast is by far\nthe biggest killer of startups that raise money.\n[2]Founders tell themselves they need to hire in order to grow. But\nmost err on the side of overestimating this need rather than\nunderestimating it. Why? Partly because there's so much work to\ndo. Naive founders think that if they can just hire enough\npeople, it will all get done. Partly because successful startups have\nlots of employees, so it seems like that's what one does in order\nto be successful. In fact the large staffs of successful startups\nare probably more the effect of growth than the cause. And\npartly because when founders have slow growth they don't want to\nface what is usually the real reason: the product is not appealing\nenough.Plus founders who've just raised money are often encouraged to\noverhire by the VCs who funded them. Kill-or-cure strategies are\noptimal for VCs because they're protected by the portfolio effect.\nVCs want to blow you up, in one sense of the phrase or the other.\nBut as a founder your incentives are different. You want above all\nto survive.\n[3]Here's a common way startups die. They make something moderately\nappealing and have decent initial growth. They raise their first\nround fairly easily, because the founders seem smart and the idea\nsounds plausible. But because the product is only moderately\nappealing, growth is ok but not great. The founders convince\nthemselves that hiring a bunch of people is the way to boost growth.\nTheir investors agree. But (because the product is only moderately\nappealing) the growth never comes. Now they're rapidly running out\nof runway. They hope further investment will save them. But because\nthey have high expenses and slow growth, they're now unappealing\nto investors. They're unable to raise more, and the company dies.What the company should have done is address the fundamental problem:\nthat the product is only moderately appealing. Hiring people is\nrarely the way to fix that. More often than not it makes it harder.\nAt this early stage, the product needs to evolve more than to be\n\"built out,\" and that's usually easier with fewer people.\n[4]Asking whether you're default alive or default dead may save you\nfrom this. Maybe the alarm bells it sets off will counteract the\nforces that push you to overhire. Instead you'll be compelled to\nseek growth in other ways. For example, by doing\nthings that don't scale, or by redesigning the product in the\nway only founders can.\nAnd for many if not most startups, these paths to growth will be\nthe ones that actually work.Airbnb waited 4 months after raising money at the end of Y Combinator\nbefore they hired their first employee. In the meantime the founders\nwere terribly overworked. But they were overworked evolving Airbnb\ninto the astonishingly successful organism it is now.Notes[1]\nSteep usage growth will also interest investors. Revenue\nwill ultimately be a constant multiple of usage, so x% usage growth\npredicts x% revenue growth. But in practice investors discount\nmerely predicted revenue, so if you're measuring usage you need a\nhigher growth rate to impress investors.[2]\nStartups that don't raise money are saved from hiring too\nfast because they can't afford to. But that doesn't mean you should\navoid raising money in order to avoid this problem, any more than\nthat total abstinence is the only way to avoid becoming an alcoholic.[3]\nI would not be surprised if VCs' tendency to push founders\nto overhire is not even in their own interest. They don't know how\nmany of the companies that get killed by overspending might have\ndone well if they'd survived. My guess is a significant number.[4]\nAfter reading a draft, Sam Altman wrote:\"I think you should make the hiring point more strongly. I think\nit's roughly correct to say that YC's most successful companies\nhave never been the fastest to hire, and one of the marks of a great\nfounder is being able to resist this urge.\"Paul Buchheit adds:\"A related problem that I see a lot is premature scaling—founders\ntake a small business that isn't really working (bad unit economics,\ntypically) and then scale it up because they want impressive growth\nnumbers. This is similar to over-hiring in that it makes the business\nmuch harder to fix once it's big, plus they are bleeding cash really\nfast.\"\nThanks to Sam Altman, Paul Buchheit, Joe Gebbia, Jessica Livingston,\nand Geoff Ralston for reading drafts of this." }, { "path": "data/PaulGrahamEssaysLarge/apple.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nNovember 2009I don't think Apple realizes how badly the App Store approval process\nis broken. Or rather, I don't think they realize how much it matters\nthat it's broken.The way Apple runs the App Store has harmed their reputation with\nprogrammers more than anything else they've ever done. \nTheir reputation with programmers used to be great.\nIt used to be the most common complaint you heard\nabout Apple was that their fans admired them too uncritically.\nThe App Store has changed that. Now a lot of programmers\nhave started to see Apple as evil.How much of the goodwill Apple once had with programmers have they\nlost over the App Store? A third? Half? And that's just so far.\nThe App Store is an ongoing karma leak.* * *How did Apple get into this mess? Their fundamental problem is\nthat they don't understand software.They treat iPhone apps the way they treat the music they sell through\niTunes. Apple is the channel; they own the user; if you want to\nreach users, you do it on their terms. The record labels agreed,\nreluctantly. But this model doesn't work for software. It doesn't\nwork for an intermediary to own the user. The software business\nlearned that in the early 1980s, when companies like VisiCorp showed\nthat although the words \"software\" and \"publisher\" fit together,\nthe underlying concepts don't. Software isn't like music or books.\nIt's too complicated for a third party to act as an intermediary\nbetween developer and user. And yet that's what Apple is trying\nto be with the App Store: a software publisher. And a particularly\noverreaching one at that, with fussy tastes and a rigidly enforced\nhouse style.If software publishing didn't work in 1980, it works even less now\nthat software development has evolved from a small number of big\nreleases to a constant stream of small ones. But Apple doesn't\nunderstand that either. Their model of product development derives\nfrom hardware. They work on something till they think it's finished,\nthen they release it. You have to do that with hardware, but because\nsoftware is so easy to change, its design can benefit from evolution.\nThe standard way to develop applications now is to launch fast and\niterate. Which means it's a disaster to have long, random delays\neach time you release a new version.Apparently Apple's attitude is that developers should be more careful\nwhen they submit a new version to the App Store. They would say\nthat. But powerful as they are, they're not powerful enough to\nturn back the evolution of technology. Programmers don't use\nlaunch-fast-and-iterate out of laziness. They use it because it\nyields the best results. By obstructing that process, Apple is\nmaking them do bad work, and programmers hate that as much as Apple\nwould.How would Apple like it if when they discovered a serious bug in\nOS X, instead of releasing a software update immediately, they had\nto submit their code to an intermediary who sat on it for a month\nand then rejected it because it contained an icon they didn't like?By breaking software development, Apple gets the opposite of what\nthey intended: the version of an app currently available in the App\nStore tends to be an old and buggy one. One developer told me:\n\n As a result of their process, the App Store is full of half-baked\n applications. I make a new version almost every day that I release\n to beta users. The version on the App Store feels old and crappy.\n I'm sure that a lot of developers feel this way: One emotion is\n \"I'm not really proud about what's in the App Store\", and it's\n combined with the emotion \"Really, it's Apple's fault.\"\n\nAnother wrote:\n\n I believe that they think their approval process helps users by\n ensuring quality. In reality, bugs like ours get through all the\n time and then it can take 4-8 weeks to get that bug fix approved,\n leaving users to think that iPhone apps sometimes just don't work.\n Worse for Apple, these apps work just fine on other platforms\n that have immediate approval processes.\n\nActually I suppose Apple has a third misconception: that all the\ncomplaints about App Store approvals are not a serious problem.\nThey must hear developers complaining. But partners and suppliers\nare always complaining. It would be a bad sign if they weren't;\nit would mean you were being too easy on them. Meanwhile the iPhone\nis selling better than ever. So why do they need to fix anything?They get away with maltreating developers, in the short term, because\nthey make such great hardware. I just bought a new 27\" iMac a\ncouple days ago. It's fabulous. The screen's too shiny, and the\ndisk is surprisingly loud, but it's so beautiful that you can't\nmake yourself care.So I bought it, but I bought it, for the first time, with misgivings.\nI felt the way I'd feel buying something made in a country with a\nbad human rights record. That was new. In the past when I bought\nthings from Apple it was an unalloyed pleasure. Oh boy! They make\nsuch great stuff. This time it felt like a Faustian bargain. They\nmake such great stuff, but they're such assholes. Do I really want\nto support this company?* * *Should Apple care what people like me think? What difference does\nit make if they alienate a small minority of their users?There are a couple reasons they should care. One is that these\nusers are the people they want as employees. If your company seems\nevil, the best programmers won't work for you. That hurt Microsoft\na lot starting in the 90s. Programmers started to feel sheepish\nabout working there. It seemed like selling out. When people from\nMicrosoft were talking to other programmers and they mentioned where\nthey worked, there were a lot of self-deprecating jokes about having\ngone over to the dark side. But the real problem for Microsoft\nwasn't the embarrassment of the people they hired. It was the\npeople they never got. And you know who got them? Google and\nApple. If Microsoft was the Empire, they were the Rebel Alliance.\nAnd it's largely because they got more of the best people that\nGoogle and Apple are doing so much better than Microsoft today.Why are programmers so fussy about their employers' morals? Partly\nbecause they can afford to be. The best programmers can work\nwherever they want. They don't have to work for a company they\nhave qualms about.But the other reason programmers are fussy, I think, is that evil\nbegets stupidity. An organization that wins by exercising power\nstarts to lose the ability to win by doing better work. And it's\nnot fun for a smart person to work in a place where the best ideas\naren't the ones that win. I think the reason Google embraced \"Don't\nbe evil\" so eagerly was not so much to impress the outside world\nas to inoculate themselves against arrogance.\n[1]That has worked for Google so far. They've become more\nbureaucratic, but otherwise they seem to have held true to their\noriginal principles. With Apple that seems less the case. When you\nlook at the famous \n1984 ad \nnow, it's easier to imagine Apple as the\ndictator on the screen than the woman with the hammer.\n[2]\nIn fact, if you read the dictator's speech it sounds uncannily like a\nprophecy of the App Store.\n\n We have triumphed over the unprincipled dissemination of facts.We have created, for the first time in all history, a garden of\n pure ideology, where each worker may bloom secure from the pests\n of contradictory and confusing truths.\n\nThe other reason Apple should care what programmers think of them\nis that when you sell a platform, developers make or break you. If\nanyone should know this, Apple should. VisiCalc made the Apple II.And programmers build applications for the platforms they use. Most\napplications—most startups, probably—grow out of personal projects.\nApple itself did. Apple made microcomputers because that's what\nSteve Wozniak wanted for himself. He couldn't have afforded a\nminicomputer. \n[3]\n Microsoft likewise started out making interpreters\nfor little microcomputers because\nBill Gates and Paul Allen were interested in using them. It's a\nrare startup that doesn't build something the founders use.The main reason there are so many iPhone apps is that so many programmers\nhave iPhones. They may know, because they read it in an article,\nthat Blackberry has such and such market share. But in practice\nit's as if RIM didn't exist. If they're going to build something,\nthey want to be able to use it themselves, and that means building\nan iPhone app.So programmers continue to develop iPhone apps, even though Apple\ncontinues to maltreat them. They're like someone stuck in an abusive\nrelationship. They're so attracted to the iPhone that they can't\nleave. But they're looking for a way out. One wrote:\n\n While I did enjoy developing for the iPhone, the control they\n place on the App Store does not give me the drive to develop\n applications as I would like. In fact I don't intend to make any\n more iPhone applications unless absolutely necessary.\n[4]\n\nCan anything break this cycle? No device I've seen so far could.\nPalm and RIM haven't a hope. The only credible contender is Android.\nBut Android is an orphan; Google doesn't really care about it, not\nthe way Apple cares about the iPhone. Apple cares about the iPhone\nthe way Google cares about search.* * *Is the future of handheld devices one locked down by Apple? It's\na worrying prospect. It would be a bummer to have another grim\nmonoculture like we had in the 1990s. In 1995, writing software\nfor end users was effectively identical with writing Windows\napplications. Our horror at that prospect was the single biggest\nthing that drove us to start building web apps.At least we know now what it would take to break Apple's lock.\nYou'd have to get iPhones out of programmers' hands. If programmers\nused some other device for mobile web access, they'd start to develop\napps for that instead.How could you make a device programmers liked better than the iPhone?\nIt's unlikely you could make something better designed. Apple\nleaves no room there. So this alternative device probably couldn't\nwin on general appeal. It would have to win by virtue of some\nappeal it had to programmers specifically.One way to appeal to programmers is with software. If you\ncould think of an application programmers had to have, but that\nwould be impossible in the circumscribed world of the iPhone, \nyou could presumably get them to switch.That would definitely happen if programmers started to use handhelds\nas development machines—if handhelds displaced laptops the\nway laptops displaced desktops. You need more control of a development\nmachine than Apple will let you have over an iPhone.Could anyone make a device that you'd carry around in your pocket\nlike a phone, and yet would also work as a development machine?\nIt's hard to imagine what it would look like. But I've learned\nnever to say never about technology. A phone-sized device that\nwould work as a development machine is no more miraculous by present\nstandards than the iPhone itself would have seemed by the standards\nof 1995.My current development machine is a MacBook Air, which I use with\nan external monitor and keyboard in my office, and by itself when\ntraveling. If there was a version half the size I'd prefer it.\nThat still wouldn't be small enough to carry around everywhere like\na phone, but we're within a factor of 4 or so. Surely that gap is\nbridgeable. In fact, let's make it an\nRFS. Wanted: \nWoman with hammer.Notes[1]\nWhen Google adopted \"Don't be evil,\" they were still so small\nthat no one would have expected them to be, yet.\n[2]\nThe dictator in the 1984 ad isn't Microsoft, incidentally;\nit's IBM. IBM seemed a lot more frightening in those days, but\nthey were friendlier to developers than Apple is now.[3]\nHe couldn't even afford a monitor. That's why the Apple\nI used a TV as a monitor.[4]\nSeveral people I talked to mentioned how much they liked the\niPhone SDK. The problem is not Apple's products but their policies.\nFortunately policies are software; Apple can change them instantly\nif they want to. Handy that, isn't it?Thanks to Sam Altman, Trevor Blackwell, Ross Boucher, \nJames Bracy, Gabor Cselle,\nPatrick Collison, Jason Freedman, John Gruber, Joe Hewitt, Jessica Livingston,\nRobert Morris, Teng Siong Ong, Nikhil Pandit, Savraj Singh, and Jared Tame for reading drafts of this." }, { "path": "data/PaulGrahamEssaysLarge/avg.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nApril 2001, rev. April 2003(This article is derived from a talk given at the 2001 Franz\nDeveloper Symposium.)\nIn the summer of 1995, my friend Robert Morris and I\nstarted a startup called \nViaweb. \nOur plan was to write\nsoftware that would let end users build online stores.\nWhat was novel about this software, at the time, was\nthat it ran on our server, using ordinary Web pages\nas the interface.A lot of people could have been having this idea at the\nsame time, of course, but as far as I know, Viaweb was\nthe first Web-based application. It seemed such\na novel idea to us that we named the company after it:\nViaweb, because our software worked via the Web,\ninstead of running on your desktop computer.Another unusual thing about this software was that it\nwas written primarily in a programming language called\nLisp. It was one of the first big end-user\napplications to be written in Lisp, which up till then\nhad been used mostly in universities and research labs. [1]The Secret WeaponEric Raymond has written an essay called \"How to Become a Hacker,\"\nand in it, among other things, he tells would-be hackers what\nlanguages they should learn. He suggests starting with Python and\nJava, because they are easy to learn. The serious hacker will also\nwant to learn C, in order to hack Unix, and Perl for system\nadministration and cgi scripts. Finally, the truly serious hacker\nshould consider learning Lisp:\n\n Lisp is worth learning for the profound enlightenment experience\n you will have when you finally get it; that experience will make\n you a better programmer for the rest of your days, even if you\n never actually use Lisp itself a lot.\n\nThis is the same argument you tend to hear for learning Latin. It\nwon't get you a job, except perhaps as a classics professor, but\nit will improve your mind, and make you a better writer in languages\nyou do want to use, like English.But wait a minute. This metaphor doesn't stretch that far. The\nreason Latin won't get you a job is that no one speaks it. If you\nwrite in Latin, no one can understand you. But Lisp is a computer\nlanguage, and computers speak whatever language you, the programmer,\ntell them to.So if Lisp makes you a better programmer, like he says, why wouldn't\nyou want to use it? If a painter were offered a brush that would\nmake him a better painter, it seems to me that he would want to\nuse it in all his paintings, wouldn't he? I'm not trying to make\nfun of Eric Raymond here. On the whole, his advice is good. What\nhe says about Lisp is pretty much the conventional wisdom. But\nthere is a contradiction in the conventional wisdom: Lisp will\nmake you a better programmer, and yet you won't use it.Why not? Programming languages are just tools, after all. If Lisp\nreally does yield better programs, you should use it. And if it\ndoesn't, then who needs it?This is not just a theoretical question. Software is a very\ncompetitive business, prone to natural monopolies. A company that\ngets software written faster and better will, all other things\nbeing equal, put its competitors out of business. And when you're\nstarting a startup, you feel this very keenly. Startups tend to\nbe an all or nothing proposition. You either get rich, or you get\nnothing. In a startup, if you bet on the wrong technology, your\ncompetitors will crush you.Robert and I both knew Lisp well, and we couldn't see any reason\nnot to trust our instincts and go with Lisp. We knew that everyone\nelse was writing their software in C++ or Perl. But we also knew\nthat that didn't mean anything. If you chose technology that way,\nyou'd be running Windows. When you choose technology, you have to\nignore what other people are doing, and consider only what will\nwork the best.This is especially true in a startup. In a big company, you can\ndo what all the other big companies are doing. But a startup can't\ndo what all the other startups do. I don't think a lot of people\nrealize this, even in startups.The average big company grows at about ten percent a year. So if\nyou're running a big company and you do everything the way the\naverage big company does it, you can expect to do as well as the\naverage big company-- that is, to grow about ten percent a year.The same thing will happen if you're running a startup, of course.\nIf you do everything the way the average startup does it, you should\nexpect average performance. The problem here is, average performance\nmeans that you'll go out of business. The survival rate for startups\nis way less than fifty percent. So if you're running a startup,\nyou had better be doing something odd. If not, you're in trouble.Back in 1995, we knew something that I don't think our competitors\nunderstood, and few understand even now: when you're writing\nsoftware that only has to run on your own servers, you can use\nany language you want. When you're writing desktop software,\nthere's a strong bias toward writing applications in the same\nlanguage as the operating system. Ten years ago, writing applications\nmeant writing applications in C. But with Web-based software,\nespecially when you have the source code of both the language and\nthe operating system, you can use whatever language you want.This new freedom is a double-edged sword, however. Now that you\ncan use any language, you have to think about which one to use.\nCompanies that try to pretend nothing has changed risk finding that\ntheir competitors do not.If you can use any language, which do you use? We chose Lisp.\nFor one thing, it was obvious that rapid development would be\nimportant in this market. We were all starting from scratch, so\na company that could get new features done before its competitors\nwould have a big advantage. We knew Lisp was a really good language\nfor writing software quickly, and server-based applications magnify\nthe effect of rapid development, because you can release software\nthe minute it's done.If other companies didn't want to use Lisp, so much the better.\nIt might give us a technological edge, and we needed all the help\nwe could get. When we started Viaweb, we had no experience in\nbusiness. We didn't know anything about marketing, or hiring\npeople, or raising money, or getting customers. Neither of us had\never even had what you would call a real job. The only thing we\nwere good at was writing software. We hoped that would save us.\nAny advantage we could get in the software department, we would\ntake.So you could say that using Lisp was an experiment. Our hypothesis\nwas that if we wrote our software in Lisp, we'd be able to get\nfeatures done faster than our competitors, and also to do things\nin our software that they couldn't do. And because Lisp was so\nhigh-level, we wouldn't need a big development team, so our costs\nwould be lower. If this were so, we could offer a better product\nfor less money, and still make a profit. We would end up getting\nall the users, and our competitors would get none, and eventually\ngo out of business. That was what we hoped would happen, anyway.What were the results of this experiment? Somewhat surprisingly,\nit worked. We eventually had many competitors, on the order of\ntwenty to thirty of them, but none of their software could compete\nwith ours. We had a wysiwyg online store builder that ran on the\nserver and yet felt like a desktop application. Our competitors\nhad cgi scripts. And we were always far ahead of them in features.\nSometimes, in desperation, competitors would try to introduce\nfeatures that we didn't have. But with Lisp our development cycle\nwas so fast that we could sometimes duplicate a new feature within\na day or two of a competitor announcing it in a press release. By\nthe time journalists covering the press release got round to calling\nus, we would have the new feature too.It must have seemed to our competitors that we had some kind of\nsecret weapon-- that we were decoding their Enigma traffic or\nsomething. In fact we did have a secret weapon, but it was simpler\nthan they realized. No one was leaking news of their features to\nus. We were just able to develop software faster than anyone\nthought possible.When I was about nine I happened to get hold of a copy of The Day\nof the Jackal, by Frederick Forsyth. The main character is an\nassassin who is hired to kill the president of France. The assassin\nhas to get past the police to get up to an apartment that overlooks\nthe president's route. He walks right by them, dressed up as an\nold man on crutches, and they never suspect him.Our secret weapon was similar. We wrote our software in a weird\nAI language, with a bizarre syntax full of parentheses. For years\nit had annoyed me to hear Lisp described that way. But now it\nworked to our advantage. In business, there is nothing more valuable\nthan a technical advantage your competitors don't understand. In\nbusiness, as in war, surprise is worth as much as force.And so, I'm a little embarrassed to say, I never said anything\npublicly about Lisp while we were working on Viaweb. We never\nmentioned it to the press, and if you searched for Lisp on our Web\nsite, all you'd find were the titles of two books in my bio. This\nwas no accident. A startup should give its competitors as little\ninformation as possible. If they didn't know what language our\nsoftware was written in, or didn't care, I wanted to keep it that\nway.[2]The people who understood our technology best were the customers.\nThey didn't care what language Viaweb was written in either, but\nthey noticed that it worked really well. It let them build great\nlooking online stores literally in minutes. And so, by word of\nmouth mostly, we got more and more users. By the end of 1996 we\nhad about 70 stores online. At the end of 1997 we had 500. Six\nmonths later, when Yahoo bought us, we had 1070 users. Today, as\nYahoo Store, this software continues to dominate its market. It's\none of the more profitable pieces of Yahoo, and the stores built\nwith it are the foundation of Yahoo Shopping. I left Yahoo in\n1999, so I don't know exactly how many users they have now, but\nthe last I heard there were about 20,000.\nThe Blub ParadoxWhat's so great about Lisp? And if Lisp is so great, why doesn't\neveryone use it? These sound like rhetorical questions, but actually\nthey have straightforward answers. Lisp is so great not because\nof some magic quality visible only to devotees, but because it is\nsimply the most powerful language available. And the reason everyone\ndoesn't use it is that programming languages are not merely\ntechnologies, but habits of mind as well, and nothing changes\nslower. Of course, both these answers need explaining.I'll begin with a shockingly controversial statement: programming\nlanguages vary in power.Few would dispute, at least, that high level languages are more\npowerful than machine language. Most programmers today would agree\nthat you do not, ordinarily, want to program in machine language.\nInstead, you should program in a high-level language, and have a\ncompiler translate it into machine language for you. This idea is\neven built into the hardware now: since the 1980s, instruction sets\nhave been designed for compilers rather than human programmers.Everyone knows it's a mistake to write your whole program by hand\nin machine language. What's less often understood is that there\nis a more general principle here: that if you have a choice of\nseveral languages, it is, all other things being equal, a mistake\nto program in anything but the most powerful one. [3]There are many exceptions to this rule. If you're writing a program\nthat has to work very closely with a program written in a certain\nlanguage, it might be a good idea to write the new program in the\nsame language. If you're writing a program that only has to do\nsomething very simple, like number crunching or bit manipulation,\nyou may as well use a less abstract language, especially since it\nmay be slightly faster. And if you're writing a short, throwaway\nprogram, you may be better off just using whatever language has\nthe best library functions for the task. But in general, for\napplication software, you want to be using the most powerful\n(reasonably efficient) language you can get, and using anything\nelse is a mistake, of exactly the same kind, though possibly in a\nlesser degree, as programming in machine language.You can see that machine language is very low level. But, at least\nas a kind of social convention, high-level languages are often all\ntreated as equivalent. They're not. Technically the term \"high-level\nlanguage\" doesn't mean anything very definite. There's no dividing\nline with machine languages on one side and all the high-level\nlanguages on the other. Languages fall along a continuum [4] of\nabstractness, from the most powerful all the way down to machine\nlanguages, which themselves vary in power.Consider Cobol. Cobol is a high-level language, in the sense that\nit gets compiled into machine language. Would anyone seriously\nargue that Cobol is equivalent in power to, say, Python? It's\nprobably closer to machine language than Python.Or how about Perl 4? Between Perl 4 and Perl 5, lexical closures\ngot added to the language. Most Perl hackers would agree that Perl\n5 is more powerful than Perl 4. But once you've admitted that,\nyou've admitted that one high level language can be more powerful\nthan another. And it follows inexorably that, except in special\ncases, you ought to use the most powerful you can get.This idea is rarely followed to its conclusion, though. After a\ncertain age, programmers rarely switch languages voluntarily.\nWhatever language people happen to be used to, they tend to consider\njust good enough.Programmers get very attached to their favorite languages, and I\ndon't want to hurt anyone's feelings, so to explain this point I'm\ngoing to use a hypothetical language called Blub. Blub falls right\nin the middle of the abstractness continuum. It is not the most\npowerful language, but it is more powerful than Cobol or machine\nlanguage.And in fact, our hypothetical Blub programmer wouldn't use either\nof them. Of course he wouldn't program in machine language. That's\nwhat compilers are for. And as for Cobol, he doesn't know how\nanyone can get anything done with it. It doesn't even have x (Blub\nfeature of your choice).As long as our hypothetical Blub programmer is looking down the\npower continuum, he knows he's looking down. Languages less powerful\nthan Blub are obviously less powerful, because they're missing some\nfeature he's used to. But when our hypothetical Blub programmer\nlooks in the other direction, up the power continuum, he doesn't\nrealize he's looking up. What he sees are merely weird languages.\nHe probably considers them about equivalent in power to Blub, but\nwith all this other hairy stuff thrown in as well. Blub is good\nenough for him, because he thinks in Blub.When we switch to the point of view of a programmer using any of\nthe languages higher up the power continuum, however, we find that\nhe in turn looks down upon Blub. How can you get anything done in\nBlub? It doesn't even have y.By induction, the only programmers in a position to see all the\ndifferences in power between the various languages are those who\nunderstand the most powerful one. (This is probably what Eric\nRaymond meant about Lisp making you a better programmer.) You can't\ntrust the opinions of the others, because of the Blub paradox:\nthey're satisfied with whatever language they happen to use, because\nit dictates the way they think about programs.I know this from my own experience, as a high school kid writing\nprograms in Basic. That language didn't even support recursion.\nIt's hard to imagine writing programs without using recursion, but\nI didn't miss it at the time. I thought in Basic. And I was a\nwhiz at it. Master of all I surveyed.The five languages that Eric Raymond recommends to hackers fall at\nvarious points on the power continuum. Where they fall relative\nto one another is a sensitive topic. What I will say is that I\nthink Lisp is at the top. And to support this claim I'll tell you\nabout one of the things I find missing when I look at the other\nfour languages. How can you get anything done in them, I think,\nwithout macros? [5]Many languages have something called a macro. But Lisp macros are\nunique. And believe it or not, what they do is related to the\nparentheses. The designers of Lisp didn't put all those parentheses\nin the language just to be different. To the Blub programmer, Lisp\ncode looks weird. But those parentheses are there for a reason.\nThey are the outward evidence of a fundamental difference between\nLisp and other languages.Lisp code is made out of Lisp data objects. And not in the trivial\nsense that the source files contain characters, and strings are\none of the data types supported by the language. Lisp code, after\nit's read by the parser, is made of data structures that you can\ntraverse.If you understand how compilers work, what's really going on is\nnot so much that Lisp has a strange syntax as that Lisp has no\nsyntax. You write programs in the parse trees that get generated\nwithin the compiler when other languages are parsed. But these\nparse trees are fully accessible to your programs. You can write\nprograms that manipulate them. In Lisp, these programs are called\nmacros. They are programs that write programs.Programs that write programs? When would you ever want to do that?\nNot very often, if you think in Cobol. All the time, if you think\nin Lisp. It would be convenient here if I could give an example\nof a powerful macro, and say there! how about that? But if I did,\nit would just look like gibberish to someone who didn't know Lisp;\nthere isn't room here to explain everything you'd need to know to\nunderstand what it meant. In \nAnsi Common Lisp I tried to move\nthings along as fast as I could, and even so I didn't get to macros\nuntil page 160.But I think I can give a kind of argument that might be convincing.\nThe source code of the Viaweb editor was probably about 20-25%\nmacros. Macros are harder to write than ordinary Lisp functions,\nand it's considered to be bad style to use them when they're not\nnecessary. So every macro in that code is there because it has to\nbe. What that means is that at least 20-25% of the code in this\nprogram is doing things that you can't easily do in any other\nlanguage. However skeptical the Blub programmer might be about my\nclaims for the mysterious powers of Lisp, this ought to make him\ncurious. We weren't writing this code for our own amusement. We\nwere a tiny startup, programming as hard as we could in order to\nput technical barriers between us and our competitors.A suspicious person might begin to wonder if there was some\ncorrelation here. A big chunk of our code was doing things that\nare very hard to do in other languages. The resulting software\ndid things our competitors' software couldn't do. Maybe there was\nsome kind of connection. I encourage you to follow that thread.\nThere may be more to that old man hobbling along on his crutches\nthan meets the eye.Aikido for StartupsBut I don't expect to convince anyone \n(over 25) \nto go out and learn\nLisp. The purpose of this article is not to change anyone's mind,\nbut to reassure people already interested in using Lisp-- people\nwho know that Lisp is a powerful language, but worry because it\nisn't widely used. In a competitive situation, that's an advantage.\nLisp's power is multiplied by the fact that your competitors don't\nget it.If you think of using Lisp in a startup, you shouldn't worry that\nit isn't widely understood. You should hope that it stays that\nway. And it's likely to. It's the nature of programming languages\nto make most people satisfied with whatever they currently use.\nComputer hardware changes so much faster than personal habits that\nprogramming practice is usually ten to twenty years behind the\nprocessor. At places like MIT they were writing programs in\nhigh-level languages in the early 1960s, but many companies continued\nto write code in machine language well into the 1980s. I bet a\nlot of people continued to write machine language until the processor,\nlike a bartender eager to close up and go home, finally kicked them\nout by switching to a risc instruction set.Ordinarily technology changes fast. But programming languages are\ndifferent: programming languages are not just technology, but what\nprogrammers think in. They're half technology and half religion.[6]\nAnd so the median language, meaning whatever language the median\nprogrammer uses, moves as slow as an iceberg. Garbage collection,\nintroduced by Lisp in about 1960, is now widely considered to be\na good thing. Runtime typing, ditto, is growing in popularity.\nLexical closures, introduced by Lisp in the early 1970s, are now,\njust barely, on the radar screen. Macros, introduced by Lisp in the\nmid 1960s, are still terra incognita.Obviously, the median language has enormous momentum. I'm not\nproposing that you can fight this powerful force. What I'm proposing\nis exactly the opposite: that, like a practitioner of Aikido, you\ncan use it against your opponents.If you work for a big company, this may not be easy. You will have\na hard time convincing the pointy-haired boss to let you build\nthings in Lisp, when he has just read in the paper that some other\nlanguage is poised, like Ada was twenty years ago, to take over\nthe world. But if you work for a startup that doesn't have\npointy-haired bosses yet, you can, like we did, turn the Blub\nparadox to your advantage: you can use technology that your\ncompetitors, glued immovably to the median language, will never be\nable to match.If you ever do find yourself working for a startup, here's a handy\ntip for evaluating competitors. Read their job listings. Everything\nelse on their site may be stock photos or the prose equivalent,\nbut the job listings have to be specific about what they want, or\nthey'll get the wrong candidates.During the years we worked on Viaweb I read a lot of job descriptions.\nA new competitor seemed to emerge out of the woodwork every month\nor so. The first thing I would do, after checking to see if they\nhad a live online demo, was look at their job listings. After a\ncouple years of this I could tell which companies to worry about\nand which not to. The more of an IT flavor the job descriptions\nhad, the less dangerous the company was. The safest kind were the\nones that wanted Oracle experience. You never had to worry about\nthose. You were also safe if they said they wanted C++ or Java\ndevelopers. If they wanted Perl or Python programmers, that would\nbe a bit frightening-- that's starting to sound like a company\nwhere the technical side, at least, is run by real hackers. If I\nhad ever seen a job posting looking for Lisp hackers, I would have\nbeen really worried.\nNotes[1] Viaweb at first had two parts: the editor, written in Lisp,\nwhich people used to build their sites, and the ordering system,\nwritten in C, which handled orders. The first version was mostly\nLisp, because the ordering system was small. Later we added two\nmore modules, an image generator written in C, and a back-office\nmanager written mostly in Perl.In January 2003, Yahoo released a new version of the editor \nwritten in C++ and Perl. It's hard to say whether the program is no\nlonger written in Lisp, though, because to translate this program\ninto C++ they literally had to write a Lisp interpreter: the source\nfiles of all the page-generating templates are still, as far as I\nknow, Lisp code. (See Greenspun's Tenth Rule.)[2] Robert Morris says that I didn't need to be secretive, because\neven if our competitors had known we were using Lisp, they wouldn't\nhave understood why: \"If they were that smart they'd already be\nprogramming in Lisp.\"[3] All languages are equally powerful in the sense of being Turing\nequivalent, but that's not the sense of the word programmers care\nabout. (No one wants to program a Turing machine.) The kind of\npower programmers care about may not be formally definable, but\none way to explain it would be to say that it refers to features\nyou could only get in the less powerful language by writing an\ninterpreter for the more powerful language in it. If language A\nhas an operator for removing spaces from strings and language B\ndoesn't, that probably doesn't make A more powerful, because you\ncan probably write a subroutine to do it in B. But if A supports,\nsay, recursion, and B doesn't, that's not likely to be something\nyou can fix by writing library functions.[4] Note to nerds: or possibly a lattice, narrowing toward the top;\nit's not the shape that matters here but the idea that there is at\nleast a partial order.[5] It is a bit misleading to treat macros as a separate feature.\nIn practice their usefulness is greatly enhanced by other Lisp\nfeatures like lexical closures and rest parameters.[6] As a result, comparisons of programming languages either take\nthe form of religious wars or undergraduate textbooks so determinedly\nneutral that they're really works of anthropology. People who\nvalue their peace, or want tenure, avoid the topic. But the question\nis only half a religious one; there is something there worth\nstudying, especially if you want to design new languages." }, { "path": "data/PaulGrahamEssaysLarge/before.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nOctober 2014(This essay is derived from a guest lecture in Sam Altman's startup class at\nStanford. It's intended for college students, but much of it is\napplicable to potential founders at other ages.)One of the advantages of having kids is that when you have to give\nadvice, you can ask yourself \"what would I tell my own kids?\" My\nkids are little, but I can imagine what I'd tell them about startups\nif they were in college, and that's what I'm going to tell you.Startups are very counterintuitive. I'm not sure why. Maybe it's\njust because knowledge about them hasn't permeated our culture yet.\nBut whatever the reason, starting a startup is a task where you\ncan't always trust your instincts.It's like skiing in that way. When you first try skiing and you\nwant to slow down, your instinct is to lean back. But if you lean\nback on skis you fly down the hill out of control. So part of\nlearning to ski is learning to suppress that impulse. Eventually\nyou get new habits, but at first it takes a conscious effort. At\nfirst there's a list of things you're trying to remember as you\nstart down the hill.Startups are as unnatural as skiing, so there's a similar list for\nstartups. Here I'm going to give you the first part of it — the things\nto remember if you want to prepare yourself to start a startup.\nCounterintuitiveThe first item on it is the fact I already mentioned: that startups\nare so weird that if you trust your instincts, you'll make a lot\nof mistakes. If you know nothing more than this, you may at least\npause before making them.When I was running Y Combinator I used to joke that our function\nwas to tell founders things they would ignore. It's really true.\nBatch after batch, the YC partners warn founders about mistakes\nthey're about to make, and the founders ignore them, and then come\nback a year later and say \"I wish we'd listened.\"Why do the founders ignore the partners' advice? Well, that's the\nthing about counterintuitive ideas: they contradict your intuitions.\nThey seem wrong. So of course your first impulse is to disregard\nthem. And in fact my joking description is not merely the curse\nof Y Combinator but part of its raison d'etre. If founders' instincts\nalready gave them the right answers, they wouldn't need us. You\nonly need other people to give you advice that surprises you. That's\nwhy there are a lot of ski instructors and not many running\ninstructors.\n[1]You can, however, trust your instincts about people. And in fact\none of the most common mistakes young founders make is not to\ndo that enough. They get involved with people who seem impressive,\nbut about whom they feel some misgivings personally. Later when\nthings blow up they say \"I knew there was something off about him,\nbut I ignored it because he seemed so impressive.\"If you're thinking about getting involved with someone — as a\ncofounder, an employee, an investor, or an acquirer — and you\nhave misgivings about them, trust your gut. If someone seems\nslippery, or bogus, or a jerk, don't ignore it.This is one case where it pays to be self-indulgent. Work with\npeople you genuinely like, and you've known long enough to be sure.\nExpertiseThe second counterintuitive point is that it's not that important\nto know a lot about startups. The way to succeed in a startup is\nnot to be an expert on startups, but to be an expert on your users\nand the problem you're solving for them.\nMark Zuckerberg didn't succeed because he was an expert on startups.\nHe succeeded despite being a complete noob at startups, because he\nunderstood his users really well.If you don't know anything about, say, how to raise an angel round,\ndon't feel bad on that account. That sort of thing you can learn\nwhen you need to, and forget after you've done it.In fact, I worry it's not merely unnecessary to learn in great\ndetail about the mechanics of startups, but possibly somewhat\ndangerous. If I met an undergrad who knew all about convertible\nnotes and employee agreements and (God forbid) class FF stock, I\nwouldn't think \"here is someone who is way ahead of their peers.\"\nIt would set off alarms. Because another of the characteristic\nmistakes of young founders is to go through the motions of starting\na startup. They make up some plausible-sounding idea, raise money\nat a good valuation, rent a cool office, hire a bunch of people.\nFrom the outside that seems like what startups do. But the next\nstep after rent a cool office and hire a bunch of people is: gradually\nrealize how completely fucked they are, because while imitating all\nthe outward forms of a startup they have neglected the one thing\nthat's actually essential: making something people want.\nGameWe saw this happen so often that we made up a name for it: playing\nhouse. Eventually I realized why it was happening. The reason\nyoung founders go through the motions of starting a startup is\nbecause that's what they've been trained to do for their whole lives\nup to that point. Think about what you have to do to get into\ncollege, for example. Extracurricular activities, check. Even in\ncollege classes most of the work is as artificial as running laps.I'm not attacking the educational system for being this way. There\nwill always be a certain amount of fakeness in the work you do when\nyou're being taught something, and if you measure their performance\nit's inevitable that people will exploit the difference to the point\nwhere much of what you're measuring is artifacts of the fakeness.I confess I did it myself in college. I found that in a lot of\nclasses there might only be 20 or 30 ideas that were the right shape\nto make good exam questions. The way I studied for exams in these\nclasses was not (except incidentally) to master the material taught\nin the class, but to make a list of potential exam questions and\nwork out the answers in advance. When I walked into the final, the\nmain thing I'd be feeling was curiosity about which of my questions\nwould turn up on the exam. It was like a game.It's not surprising that after being trained for their whole lives\nto play such games, young founders' first impulse on starting a\nstartup is to try to figure out the tricks for winning at this new\ngame. Since fundraising appears to be the measure of success for\nstartups (another classic noob mistake), they always want to know what the\ntricks are for convincing investors. We tell them the best way to\nconvince investors is to make a startup\nthat's actually doing well, meaning growing fast, and then simply\ntell investors so. Then they want to know what the tricks are for\ngrowing fast. And we have to tell them the best way to do that is\nsimply to make something people want.So many of the conversations YC partners have with young founders\nbegin with the founder asking \"How do we...\" and the partner replying\n\"Just...\"Why do the founders always make things so complicated? The reason,\nI realized, is that they're looking for the trick.So this is the third counterintuitive thing to remember about\nstartups: starting a startup is where gaming the system stops\nworking. Gaming the system may continue to work if you go to work\nfor a big company. Depending on how broken the company is, you can\nsucceed by sucking up to the right people, giving the impression\nof productivity, and so on. \n[2]\nBut that doesn't work with startups.\nThere is no boss to trick, only users, and all users care about is\nwhether your product does what they want. Startups are as impersonal\nas physics. You have to make something people want, and you prosper\nonly to the extent you do.The dangerous thing is, faking does work to some degree on investors.\nIf you're super good at sounding like you know what you're talking\nabout, you can fool investors for at least one and perhaps even two\nrounds of funding. But it's not in your interest to. The company\nis ultimately doomed. All you're doing is wasting your own time\nriding it down.So stop looking for the trick. There are tricks in startups, as\nthere are in any domain, but they are an order of magnitude less\nimportant than solving the real problem. A founder who knows nothing\nabout fundraising but has made something users love will have an\neasier time raising money than one who knows every trick in the\nbook but has a flat usage graph. And more importantly, the founder\nwho has made something users love is the one who will go on to\nsucceed after raising the money.Though in a sense it's bad news in that you're deprived of one of\nyour most powerful weapons, I think it's exciting that gaming the\nsystem stops working when you start a startup. It's exciting that\nthere even exist parts of the world where you win by doing good\nwork. Imagine how depressing the world would be if it were all\nlike school and big companies, where you either have to spend a lot\nof time on bullshit things or lose to people who do.\n[3]\nI would\nhave been delighted if I'd realized in college that there were parts\nof the real world where gaming the system mattered less than others,\nand a few where it hardly mattered at all. But there are, and this\nvariation is one of the most important things to consider when\nyou're thinking about your future. How do you win in each type of\nwork, and what would you like to win by doing?\n[4]\nAll-ConsumingThat brings us to our fourth counterintuitive point: startups are\nall-consuming. If you start a startup, it will take over your life\nto a degree you cannot imagine. And if your startup succeeds, it\nwill take over your life for a long time: for several years at the\nvery least, maybe for a decade, maybe for the rest of your working\nlife. So there is a real opportunity cost here.Larry Page may seem to have an enviable life, but there are aspects\nof it that are unenviable. Basically at 25 he started running as\nfast as he could and it must seem to him that he hasn't stopped to\ncatch his breath since. Every day new shit happens in the Google\nempire that only the CEO can deal with, and he, as CEO, has to deal\nwith it. If he goes on vacation for even a week, a whole week's\nbacklog of shit accumulates. And he has to bear this uncomplainingly,\npartly because as the company's daddy he can never show fear or\nweakness, and partly because billionaires get less than zero sympathy\nif they talk about having difficult lives. Which has the strange\nside effect that the difficulty of being a successful startup founder\nis concealed from almost everyone except those who've done it.Y Combinator has now funded several companies that can be called\nbig successes, and in every single case the founders say the same\nthing. It never gets any easier. The nature of the problems change.\nYou're worrying about construction delays at your London office\ninstead of the broken air conditioner in your studio apartment.\nBut the total volume of worry never decreases; if anything it\nincreases.Starting a successful startup is similar to having kids in that\nit's like a button you push that changes your life irrevocably.\nAnd while it's truly wonderful having kids, there are a lot of\nthings that are easier to do before you have them than after. Many\nof which will make you a better parent when you do have kids. And\nsince you can delay pushing the button for a while, most people in\nrich countries do.Yet when it comes to startups, a lot of people seem to think they're\nsupposed to start them while they're still in college. Are you\ncrazy? And what are the universities thinking? They go out of\ntheir way to ensure their students are well supplied with contraceptives,\nand yet they're setting up entrepreneurship programs and startup\nincubators left and right.To be fair, the universities have their hand forced here. A lot\nof incoming students are interested in startups. Universities are,\nat least de facto, expected to prepare them for their careers. So\nstudents who want to start startups hope universities can teach\nthem about startups. And whether universities can do this or not,\nthere's some pressure to claim they can, lest they lose applicants\nto other universities that do.Can universities teach students about startups? Yes and no. They\ncan teach students about startups, but as I explained before, this\nis not what you need to know. What you need to learn about are the\nneeds of your own users, and you can't do that until you actually\nstart the company.\n[5]\nSo starting a startup is intrinsically\nsomething you can only really learn by doing it. And it's impossible\nto do that in college, for the reason I just explained: startups\ntake over your life. You can't start a startup for real as a\nstudent, because if you start a startup for real you're not a student\nanymore. You may be nominally a student for a bit, but you won't even\nbe that for long.\n[6]Given this dichotomy, which of the two paths should you take? Be\na real student and not start a startup, or start a real startup and\nnot be a student? I can answer that one for you. Do not start a\nstartup in college. How to start a startup is just a subset of a\nbigger problem you're trying to solve: how to have a good life.\nAnd though starting a startup can be part of a good life for a lot\nof ambitious people, age 20 is not the optimal time to do it.\nStarting a startup is like a brutally fast depth-first search. Most\npeople should still be searching breadth-first at 20.You can do things in your early 20s that you can't do as well before\nor after, like plunge deeply into projects on a whim and travel\nsuper cheaply with no sense of a deadline. For unambitious people,\nthis sort of thing is the dreaded \"failure to launch,\" but for the\nambitious ones it can be an incomparably valuable sort of exploration.\nIf you start a startup at 20 and you're sufficiently successful,\nyou'll never get to do it.\n[7]Mark Zuckerberg will never get to bum around a foreign country. He\ncan do other things most people can't, like charter jets to fly him\nto foreign countries. But success has taken a lot of the serendipity\nout of his life. Facebook is running him as much as he's running\nFacebook. And while it can be very cool to be in the grip of a\nproject you consider your life's work, there are advantages to\nserendipity too, especially early in life. Among other things it\ngives you more options to choose your life's work from.There's not even a tradeoff here. You're not sacrificing anything\nif you forgo starting a startup at 20, because you're more likely\nto succeed if you wait. In the unlikely case that you're 20 and\none of your side projects takes off like Facebook did, you'll face\na choice of running with it or not, and it may be reasonable to run\nwith it. But the usual way startups take off is for the founders\nto make them take off, and it's gratuitously\nstupid to do that at 20.\nTryShould you do it at any age? I realize I've made startups sound\npretty hard. If I haven't, let me try again: starting a startup\nis really hard. What if it's too hard? How can you tell if you're\nup to this challenge?The answer is the fifth counterintuitive point: you can't tell. Your\nlife so far may have given you some idea what your prospects might\nbe if you tried to become a mathematician, or a professional football\nplayer. But unless you've had a very strange life you haven't done\nmuch that was like being a startup founder.\nStarting a startup will change you a lot. So what you're trying\nto estimate is not just what you are, but what you could grow into,\nand who can do that?For the past 9 years it was my job to predict whether people would\nhave what it took to start successful startups. It was easy to\ntell how smart they were, and most people reading this will be over\nthat threshold. The hard part was predicting how tough and ambitious they would become. There\nmay be no one who has more experience at trying to predict that,\nso I can tell you how much an expert can know about it, and the\nanswer is: not much. I learned to keep a completely open mind about\nwhich of the startups in each batch would turn out to be the stars.The founders sometimes think they know. Some arrive feeling sure\nthey will ace Y Combinator just as they've aced every one of the (few,\nartificial, easy) tests they've faced in life so far. Others arrive\nwondering how they got in, and hoping YC doesn't discover whatever\nmistake caused it to accept them. But there is little correlation\nbetween founders' initial attitudes and how well their companies\ndo.I've read that the same is true in the military — that the\nswaggering recruits are no more likely to turn out to be really\ntough than the quiet ones. And probably for the same reason: that\nthe tests involved are so different from the ones in their previous\nlives.If you're absolutely terrified of starting a startup, you probably\nshouldn't do it. But if you're merely unsure whether you're up to\nit, the only way to find out is to try. Just not now.\nIdeasSo if you want to start a startup one day, what should you do in\ncollege? There are only two things you need initially: an idea and\ncofounders. And the m.o. for getting both is the same. Which leads\nto our sixth and last counterintuitive point: that the way to get\nstartup ideas is not to try to think of startup ideas.I've written a whole essay on this,\nso I won't repeat it all here. But the short version is that if\nyou make a conscious effort to think of startup ideas, the ideas\nyou come up with will not merely be bad, but bad and plausible-sounding,\nmeaning you'll waste a lot of time on them before realizing they're\nbad.The way to come up with good startup ideas is to take a step back.\nInstead of making a conscious effort to think of startup ideas,\nturn your mind into the type that startup ideas form in without any\nconscious effort. In fact, so unconsciously that you don't even\nrealize at first that they're startup ideas.This is not only possible, it's how Apple, Yahoo, Google, and\nFacebook all got started. None of these companies were even meant\nto be companies at first. They were all just side projects. The\nbest startups almost have to start as side projects, because great\nideas tend to be such outliers that your conscious mind would reject\nthem as ideas for companies.Ok, so how do you turn your mind into the type that startup ideas\nform in unconsciously? (1) Learn a lot about things that matter,\nthen (2) work on problems that interest you (3) with people you\nlike and respect. The third part, incidentally, is how you get\ncofounders at the same time as the idea.The first time I wrote that paragraph, instead of \"learn a lot about\nthings that matter,\" I wrote \"become good at some technology.\" But\nthat prescription, though sufficient, is too narrow. What was\nspecial about Brian Chesky and Joe Gebbia was not that they were\nexperts in technology. They were good at design, and perhaps even\nmore importantly, they were good at organizing groups and making\nprojects happen. So you don't have to work on technology per se,\nso long as you work on problems demanding enough to stretch you.What kind of problems are those? That is very hard to answer in\nthe general case. History is full of examples of young people who\nwere working on important problems that no\none else at the time thought were important, and in particular\nthat their parents didn't think were important. On the other hand,\nhistory is even fuller of examples of parents who thought their\nkids were wasting their time and who were right. So how do you\nknow when you're working on real stuff?\n[8]I know how I know. Real problems are interesting, and I am\nself-indulgent in the sense that I always want to work on interesting\nthings, even if no one else cares about them (in fact, especially\nif no one else cares about them), and find it very hard to make\nmyself work on boring things, even if they're supposed to be\nimportant.My life is full of case after case where I worked on something just\nbecause it seemed interesting, and it turned out later to be useful\nin some worldly way. Y\nCombinator itself was something I only did because it seemed\ninteresting. So I seem to have some sort of internal compass that\nhelps me out. But I don't know what other people have in their\nheads. Maybe if I think more about this I can come up with heuristics\nfor recognizing genuinely interesting problems, but for the moment\nthe best I can offer is the hopelessly question-begging advice that\nif you have a taste for genuinely interesting problems, indulging\nit energetically is the best way to prepare yourself for a startup.\nAnd indeed, probably also the best way to live.\n[9]But although I can't explain in the general case what counts as an\ninteresting problem, I can tell you about a large subset of them.\nIf you think of technology as something that's spreading like a\nsort of fractal stain, every moving point on the edge represents\nan interesting problem. So one guaranteed way to turn your mind\ninto the type that has good startup ideas is to get yourself to the\nleading edge of some technology — to cause yourself, as Paul\nBuchheit put it, to \"live in the future.\" When you reach that point,\nideas that will seem to other people uncannily prescient will seem\nobvious to you. You may not realize they're startup ideas, but\nyou'll know they're something that ought to exist.For example, back at Harvard in the mid 90s a fellow grad student\nof my friends Robert and Trevor wrote his own voice over IP software.\nHe didn't mean it to be a startup, and he never tried to turn it\ninto one. He just wanted to talk to his girlfriend in Taiwan without\npaying for long distance calls, and since he was an expert on\nnetworks it seemed obvious to him that the way to do it was turn\nthe sound into packets and ship it over the Internet. He never did\nany more with his software than talk to his girlfriend, but this\nis exactly the way the best startups get started.So strangely enough the optimal thing to do in college if you want\nto be a successful startup founder is not some sort of new, vocational\nversion of college focused on \"entrepreneurship.\" It's the classic\nversion of college as education for its own sake. If you want to\nstart a startup after college, what you should do in college is\nlearn powerful things. And if you have genuine intellectual\ncuriosity, that's what you'll naturally tend to do if you just\nfollow your own inclinations.\n[10]The component of entrepreneurship that really matters is domain\nexpertise. The way to become Larry Page was to become an expert\non search. And the way to become an expert on search was to be\ndriven by genuine curiosity, not some ulterior motive.At its best, starting a startup is merely an ulterior motive for\ncuriosity. And you'll do it best if you introduce the ulterior\nmotive toward the end of the process.So here is the ultimate advice for young would-be startup founders,\nboiled down to two words: just learn.\nNotes[1]\nSome founders listen more than others, and this tends to be a\npredictor of success. One of the things I\nremember about the Airbnbs during YC is how intently they listened.[2]\nIn fact, this is one of the reasons startups are possible. If\nbig companies weren't plagued by internal inefficiencies, they'd\nbe proportionately more effective, leaving less room for startups.[3]\nIn a startup you have to spend a lot of time on schleps, but this sort of work is merely\nunglamorous, not bogus.[4]\nWhat should you do if your true calling is gaming the system?\nManagement consulting.[5]\nThe company may not be incorporated, but if you start to get\nsignificant numbers of users, you've started it, whether you realize\nit yet or not.[6]\nIt shouldn't be that surprising that colleges can't teach\nstudents how to be good startup founders, because they can't teach\nthem how to be good employees either.The way universities \"teach\" students how to be employees is to\nhand off the task to companies via internship programs. But you\ncouldn't do the equivalent thing for startups, because by definition\nif the students did well they would never come back.[7]\nCharles Darwin was 22 when he received an invitation to travel\naboard the HMS Beagle as a naturalist. It was only because he was\notherwise unoccupied, to a degree that alarmed his family, that he\ncould accept it. And yet if he hadn't we probably would not know\nhis name.[8]\nParents can sometimes be especially conservative in this\ndepartment. There are some whose definition of important problems\nincludes only those on the critical path to med school.[9]\nI did manage to think of a heuristic for detecting whether you\nhave a taste for interesting ideas: whether you find known boring\nideas intolerable. Could you endure studying literary theory, or\nworking in middle management at a large company?[10]\nIn fact, if your goal is to start a startup, you can stick\neven more closely to the ideal of a liberal education than past\ngenerations have. Back when students focused mainly on getting a\njob after college, they thought at least a little about how the\ncourses they took might look to an employer. And perhaps even\nworse, they might shy away from taking a difficult class lest they\nget a low grade, which would harm their all-important GPA. Good\nnews: users don't care what your GPA\nwas. And I've never heard of investors caring either. Y Combinator\ncertainly never asks what classes you took in college or what grades\nyou got in them.\nThanks to Sam Altman, Paul Buchheit, John Collison, Patrick\nCollison, Jessica Livingston, Robert Morris, Geoff Ralston, and\nFred Wilson for reading drafts of this." }, { "path": "data/PaulGrahamEssaysLarge/bias.txt", "content": "October 2015This will come as a surprise to a lot of people, but in some cases\nit's possible to detect bias in a selection process without knowing\nanything about the applicant pool. Which is exciting because among\nother things it means third parties can use this technique to detect\nbias whether those doing the selecting want them to or not.You can use this technique whenever (a) you have at least\na random sample of the applicants that were selected, (b) their\nsubsequent performance is measured, and (c) the groups of\napplicants you're comparing have roughly equal distribution of ability.How does it work? Think about what it means to be biased. What\nit means for a selection process to be biased against applicants\nof type x is that it's harder for them to make it through. Which\nmeans applicants of type x have to be better to get selected than\napplicants not of type x.\n[1]\nWhich means applicants of type x\nwho do make it through the selection process will outperform other\nsuccessful applicants. And if the performance of all the successful\napplicants is measured, you'll know if they do.Of course, the test you use to measure performance must be a valid\none. And in particular it must not be invalidated by the bias you're\ntrying to measure.\nBut there are some domains where performance can be measured, and\nin those detecting bias is straightforward. Want to know if the\nselection process was biased against some type of applicant? Check\nwhether they outperform the others. This is not just a heuristic\nfor detecting bias. It's what bias means.For example, many suspect that venture capital firms are biased\nagainst female founders. This would be easy to detect: among their\nportfolio companies, do startups with female founders outperform\nthose without? A couple months ago, one VC firm (almost certainly\nunintentionally) published a study showing bias of this type. First\nRound Capital found that among its portfolio companies, startups\nwith female founders outperformed\nthose without by 63%. \n[2]The reason I began by saying that this technique would come as a\nsurprise to many people is that we so rarely see analyses of this\ntype. I'm sure it will come as a surprise to First Round that they\nperformed one. I doubt anyone there realized that by limiting their\nsample to their own portfolio, they were producing a study not of\nstartup trends but of their own biases when selecting companies.I predict we'll see this technique used more in the future. The\ninformation needed to conduct such studies is increasingly available.\nData about who applies for things is usually closely guarded by the\norganizations selecting them, but nowadays data about who gets\nselected is often publicly available to anyone who takes the trouble\nto aggregate it.\nNotes[1]\nThis technique wouldn't work if the selection process looked\nfor different things from different types of applicants—for\nexample, if an employer hired men based on their ability but women\nbased on their appearance.[2]\nAs Paul Buchheit points out, First Round excluded their most \nsuccessful investment, Uber, from the study. And while it \nmakes sense to exclude outliers from some types of studies, \nstudies of returns from startup investing, which is all about \nhitting outliers, are not one of them.\nThanks to Sam Altman, Jessica Livingston, and Geoff Ralston for reading\ndrafts of this." }, { "path": "data/PaulGrahamEssaysLarge/boss.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nMarch 2008, rev. June 2008Technology tends to separate normal from natural. Our bodies\nweren't designed to eat the foods that people in rich countries eat, or\nto get so little exercise. \nThere may be a similar problem with the way we work: \na normal job may be as bad for us intellectually as white flour\nor sugar is for us physically.I began to suspect this after spending several years working \nwith startup founders. I've now worked with over 200 of them, and I've\nnoticed a definite difference between programmers working on their\nown startups and those working for large organizations.\nI wouldn't say founders seem happier, necessarily;\nstarting a startup can be very stressful. Maybe the best way to put\nit is to say that they're happier in the sense that your body is\nhappier during a long run than sitting on a sofa eating\ndoughnuts.Though they're statistically abnormal, startup founders seem to be\nworking in a way that's more natural for humans.I was in Africa last year and saw a lot of animals in the wild that\nI'd only seen in zoos before. It was remarkable how different they\nseemed. Particularly lions. Lions in the wild seem about ten times\nmore alive. They're like different animals. I suspect that working\nfor oneself feels better to humans in much the same way that living\nin the wild must feel better to a wide-ranging predator like a lion.\nLife in a zoo is easier, but it isn't the life they were designed\nfor.\nTreesWhat's so unnatural about working for a big company? The root of\nthe problem is that humans weren't meant to work in such large\ngroups.Another thing you notice when you see animals in the wild is that\neach species thrives in groups of a certain size. A herd of impalas\nmight have 100 adults; baboons maybe 20; lions rarely 10. Humans\nalso seem designed to work in groups, and what I've read about\nhunter-gatherers accords with research on organizations and my own\nexperience to suggest roughly what the ideal size is: groups of 8\nwork well; by 20 they're getting hard to manage; and a group of 50\nis really unwieldy.\n[1]\nWhatever the upper limit is, we are clearly not meant to work in\ngroups of several hundred. And yet—for reasons having more\nto do with technology than human nature—a great many people\nwork for companies with hundreds or thousands of employees.Companies know groups that large wouldn't work, so they divide\nthemselves into units small enough to work together. But to\ncoordinate these they have to introduce something new: bosses.These smaller groups are always arranged in a tree structure. Your\nboss is the point where your group attaches to the tree. But when\nyou use this trick for dividing a large group into smaller ones,\nsomething strange happens that I've never heard anyone mention\nexplicitly. In the group one level up from yours, your boss\nrepresents your entire group. A group of 10 managers is not merely\na group of 10 people working together in the usual way. It's really\na group of groups. Which means for a group of 10 managers to work\ntogether as if they were simply a group of 10 individuals, the group\nworking for each manager would have to work as if they were a single\nperson—the workers and manager would each share only one\nperson's worth of freedom between them.In practice a group of people are never able to act as if they were\none person. But in a large organization divided into groups in\nthis way, the pressure is always in that direction. Each group\ntries its best to work as if it were the small group of individuals\nthat humans were designed to work in. That was the point of creating\nit. And when you propagate that constraint, the result is that\neach person gets freedom of action in inverse proportion to the\nsize of the entire tree.\n[2]Anyone who's worked for a large organization has felt this. You\ncan feel the difference between working for a company with 100\nemployees and one with 10,000, even if your group has only 10 people.\nCorn SyrupA group of 10 people within a large organization is a kind of fake\ntribe. The number of people you interact with is about right. But\nsomething is missing: individual initiative. Tribes of hunter-gatherers\nhave much more freedom. The leaders have a little more power than other\nmembers of the tribe, but they don't generally tell them what to\ndo and when the way a boss can.It's not your boss's fault. The real problem is that in the group\nabove you in the hierarchy, your entire group is one virtual person.\nYour boss is just the way that constraint is imparted to you.So working in a group of 10 people within a large organization feels\nboth right and wrong at the same time. On the surface it feels\nlike the kind of group you're meant to work in, but something major\nis missing. A job at a big company is like high fructose corn\nsyrup: it has some of the qualities of things you're meant to like,\nbut is disastrously lacking in others.Indeed, food is an excellent metaphor to explain what's wrong with\nthe usual sort of job.For example, working for a big company is the default thing to do,\nat least for programmers. How bad could it be? Well, food shows\nthat pretty clearly. If you were dropped at a random point in\nAmerica today, nearly all the food around you would be bad for you.\nHumans were not designed to eat white flour, refined sugar, high\nfructose corn syrup, and hydrogenated vegetable oil. And yet if\nyou analyzed the contents of the average grocery store you'd probably\nfind these four ingredients accounted for most of the calories.\n\"Normal\" food is terribly bad for you. The only people who eat\nwhat humans were actually designed to eat are a few Birkenstock-wearing\nweirdos in Berkeley.If \"normal\" food is so bad for us, why is it so common? There are\ntwo main reasons. One is that it has more immediate appeal. You\nmay feel lousy an hour after eating that pizza, but eating the first\ncouple bites feels great. The other is economies of scale.\nProducing junk food scales; producing fresh vegetables doesn't.\nWhich means (a) junk food can be very cheap, and (b) it's worth\nspending a lot to market it.If people have to choose between something that's cheap, heavily\nmarketed, and appealing in the short term, and something that's\nexpensive, obscure, and appealing in the long term, which do you\nthink most will choose?It's the same with work. The average MIT graduate wants to work\nat Google or Microsoft, because it's a recognized brand, it's safe,\nand they'll get paid a good salary right away. It's the job\nequivalent of the pizza they had for lunch. The drawbacks will\nonly become apparent later, and then only in a vague sense of\nmalaise.And founders and early employees of startups, meanwhile, are like\nthe Birkenstock-wearing weirdos of Berkeley: though a tiny minority\nof the population, they're the ones living as humans are meant to.\nIn an artificial world, only extremists live naturally.\nProgrammersThe restrictiveness of big company jobs is particularly hard on\nprogrammers, because the essence of programming is to build new\nthings. Sales people make much the same pitches every day; support\npeople answer much the same questions; but once you've written a\npiece of code you don't need to write it again. So a programmer\nworking as programmers are meant to is always making new things.\nAnd when you're part of an organization whose structure gives each\nperson freedom in inverse proportion to the size of the tree, you're\ngoing to face resistance when you do something new.This seems an inevitable consequence of bigness. It's true even\nin the smartest companies. I was talking recently to a founder who\nconsidered starting a startup right out of college, but went to\nwork for Google instead because he thought he'd learn more there.\nHe didn't learn as much as he expected. Programmers learn by doing,\nand most of the things he wanted to do, he couldn't—sometimes\nbecause the company wouldn't let him, but often because the company's\ncode wouldn't let him. Between the drag of legacy code, the overhead\nof doing development in such a large organization, and the restrictions\nimposed by interfaces owned by other groups, he could only try a\nfraction of the things he would have liked to. He said he has\nlearned much more in his own startup, despite the fact that he has\nto do all the company's errands as well as programming, because at\nleast when he's programming he can do whatever he wants.An obstacle downstream propagates upstream. If you're not allowed\nto implement new ideas, you stop having them. And vice versa: when\nyou can do whatever you want, you have more ideas about what to do.\nSo working for yourself makes your brain more powerful in the same\nway a low-restriction exhaust system makes an engine more powerful.Working for yourself doesn't have to mean starting a startup, of\ncourse. But a programmer deciding between a regular job at a big\ncompany and their own startup is probably going to learn more doing\nthe startup.You can adjust the amount of freedom you get by scaling the size\nof company you work for. If you start the company, you'll have the\nmost freedom. If you become one of the first 10 employees you'll\nhave almost as much freedom as the founders. Even a company with\n100 people will feel different from one with 1000.Working for a small company doesn't ensure freedom. The tree\nstructure of large organizations sets an upper bound on freedom,\nnot a lower bound. The head of a small company may still choose\nto be a tyrant. The point is that a large organization is compelled\nby its structure to be one.\nConsequencesThat has real consequences for both organizations and individuals.\nOne is that companies will inevitably slow down as they grow larger,\nno matter how hard they try to keep their startup mojo. It's a\nconsequence of the tree structure that every large organization is\nforced to adopt.Or rather, a large organization could only avoid slowing down if\nthey avoided tree structure. And since human nature limits the\nsize of group that can work together, the only way I can imagine\nfor larger groups to avoid tree structure would be to have no\nstructure: to have each group actually be independent, and to work\ntogether the way components of a market economy do.That might be worth exploring. I suspect there are already some\nhighly partitionable businesses that lean this way. But I don't\nknow any technology companies that have done it.There is one thing companies can do short of structuring themselves\nas sponges: they can stay small. If I'm right, then it really\npays to keep a company as small as it can be at every stage.\nParticularly a technology company. Which means it's doubly important\nto hire the best people. Mediocre hires hurt you twice: they get\nless done, but they also make you big, because you need more of\nthem to solve a given problem.For individuals the upshot is the same: aim small. It will always\nsuck to work for large organizations, and the larger the organization,\nthe more it will suck.In an essay I wrote a couple years ago \nI advised graduating seniors\nto work for a couple years for another company before starting their\nown. I'd modify that now. Work for another company if you want\nto, but only for a small one, and if you want to start your own\nstartup, go ahead.The reason I suggested college graduates not start startups immediately\nwas that I felt most would fail. And they will. But ambitious\nprogrammers are better off doing their own thing and failing than\ngoing to work at a big company. Certainly they'll learn more. They\nmight even be better off financially. A lot of people in their\nearly twenties get into debt, because their expenses grow even\nfaster than the salary that seemed so high when they left school.\nAt least if you start a startup and fail your net worth will be\nzero rather than negative. \n[3]We've now funded so many different types of founders that we have\nenough data to see patterns, and there seems to be no benefit from\nworking for a big company. The people who've worked for a few years\ndo seem better than the ones straight out of college, but only\nbecause they're that much older.The people who come to us from big companies often seem kind of\nconservative. It's hard to say how much is because big companies\nmade them that way, and how much is the natural conservatism that\nmade them work for the big companies in the first place. But\ncertainly a large part of it is learned. I know because I've seen\nit burn off.Having seen that happen so many times is one of the things that\nconvinces me that working for oneself, or at least for a small\ngroup, is the natural way for programmers to live. Founders arriving\nat Y Combinator often have the downtrodden air of refugees. Three\nmonths later they're transformed: they have so much more \nconfidence\nthat they seem as if they've grown several inches taller. \n[4]\nStrange as this sounds, they seem both more worried and happier at the same\ntime. Which is exactly how I'd describe the way lions seem in the\nwild.Watching employees get transformed into founders makes it clear\nthat the difference between the two is due mostly to environment—and\nin particular that the environment in big companies is toxic to\nprogrammers. In the first couple weeks of working on their own\nstartup they seem to come to life, because finally they're working\nthe way people are meant to.Notes[1]\nWhen I talk about humans being meant or designed to live a\ncertain way, I mean by evolution.[2]\nIt's not only the leaves who suffer. The constraint propagates\nup as well as down. So managers are constrained too; instead of\njust doing things, they have to act through subordinates.[3]\nDo not finance your startup with credit cards. Financing a\nstartup with debt is usually a stupid move, and credit card debt\nstupidest of all. Credit card debt is a bad idea, period. It is\na trap set by evil companies for the desperate and the foolish.[4]\nThe founders we fund used to be younger (initially we encouraged\nundergrads to apply), and the first couple times I saw this I used\nto wonder if they were actually getting physically taller.Thanks to Trevor Blackwell, Ross Boucher, Aaron Iba, Abby\nKirigin, Ivan Kirigin, Jessica Livingston, and Robert Morris for\nreading drafts of this." }, { "path": "data/PaulGrahamEssaysLarge/copy.txt", "content": "July 2006\nWhen I was in high school I spent a lot of time imitating bad\nwriters. What we studied in English classes was mostly fiction,\nso I assumed that was the highest form of writing. Mistake number\none. The stories that seemed to be most admired were ones in which\npeople suffered in complicated ways. Anything funny or\ngripping was ipso facto suspect, unless it was old enough to be hard to\nunderstand, like Shakespeare or Chaucer. Mistake number two. The\nideal medium seemed the short story, which I've since learned had\nquite a brief life, roughly coincident with the peak of magazine\npublishing. But since their size made them perfect for use in\nhigh school classes, we read a lot of them, which gave us the\nimpression the short story was flourishing. Mistake number three.\nAnd because they were so short, nothing really had to happen; you\ncould just show a randomly truncated slice of life, and that was\nconsidered advanced. Mistake number four. The result was that I\nwrote a lot of stories in which nothing happened except that someone\nwas unhappy in a way that seemed deep.For most of college I was a philosophy major. I was very impressed\nby the papers published in philosophy journals. They were so\nbeautifully typeset, and their tone was just captivating—alternately\ncasual and buffer-overflowingly technical. A fellow would be walking\nalong a street and suddenly modality qua modality would spring upon\nhim. I didn't ever quite understand these papers, but I figured\nI'd get around to that later, when I had time to reread them more\nclosely. In the meantime I tried my best to imitate them. This\nwas, I can now see, a doomed undertaking, because they weren't\nreally saying anything. No philosopher ever refuted another, for\nexample, because no one said anything definite enough to refute.\nNeedless to say, my imitations didn't say anything either.In grad school I was still wasting time imitating the wrong things.\nThere was then a fashionable type of program called an expert system,\nat the core of which was something called an inference engine. I\nlooked at what these things did and thought \"I could write that in\na thousand lines of code.\" And yet eminent professors were writing\nbooks about them, and startups were selling them for a year's salary\na copy. What an opportunity, I thought; these impressive things\nseem easy to me; I must be pretty sharp. Wrong. It was simply a\nfad. The books the professors wrote about expert systems are now\nignored. They were not even on a path to anything interesting.\nAnd the customers paying so much for them were largely the same\ngovernment agencies that paid thousands for screwdrivers and toilet\nseats.How do you avoid copying the wrong things? Copy only what you\ngenuinely like. That would have saved me in all three cases. I\ndidn't enjoy the short stories we had to read in English classes;\nI didn't learn anything from philosophy papers; I didn't use expert\nsystems myself. I believed these things were good because they\nwere admired.It can be hard to separate the things you like from the things\nyou're impressed with. One trick is to ignore presentation. Whenever\nI see a painting impressively hung in a museum, I ask myself: how\nmuch would I pay for this if I found it at a garage sale, dirty and\nframeless, and with no idea who painted it? If you walk around a\nmuseum trying this experiment, you'll find you get some truly\nstartling results. Don't ignore this data point just because it's\nan outlier.Another way to figure out what you like is to look at what you enjoy\nas guilty pleasures. Many things people like, especially if they're\nyoung and ambitious, they like largely for the feeling of virtue\nin liking them. 99% of people reading Ulysses are thinking\n\"I'm reading Ulysses\" as they do it. A guilty pleasure is\nat least a pure one. What do you read when you don't feel up to being\nvirtuous? What kind of book do you read and feel sad that there's\nonly half of it left, instead of being impressed that you're half\nway through? That's what you really like.Even when you find genuinely good things to copy, there's another\npitfall to be avoided. Be careful to copy what makes them good,\nrather than their flaws. It's easy to be drawn into imitating\nflaws, because they're easier to see, and of course easier to copy\ntoo. For example, most painters in the eighteenth and nineteenth\ncenturies used brownish colors. They were imitating the great\npainters of the Renaissance, whose paintings by that time were brown\nwith dirt. Those paintings have since been cleaned, revealing\nbrilliant colors; their imitators are of course still brown.It was painting, incidentally, that cured me of copying the wrong\nthings. Halfway through grad school I decided I wanted to try being\na painter, and the art world was so manifestly corrupt that it\nsnapped the leash of credulity. These people made philosophy\nprofessors seem as scrupulous as mathematicians. It was so clearly\na choice of doing good work xor being an insider that I was forced\nto see the distinction. It's there to some degree in almost every\nfield, but I had till then managed to avoid facing it.That was one of the most valuable things I learned from painting:\nyou have to figure out for yourself what's \ngood. You can't trust\nauthorities. They'll lie to you on this one.\n\nComment on this essay." }, { "path": "data/PaulGrahamEssaysLarge/corpdev.txt", "content": "January 2015Corporate Development, aka corp dev, is the group within companies\nthat buys other companies. If you're talking to someone from corp\ndev, that's why, whether you realize it yet or not.It's usually a mistake to talk to corp dev unless (a) you want to\nsell your company right now and (b) you're sufficiently likely to\nget an offer at an acceptable price. In practice that means startups\nshould only talk to corp dev when they're either doing really well\nor really badly. If you're doing really badly, meaning the company\nis about to die, you may as well talk to them, because you have\nnothing to lose. And if you're doing really well, you can safely\ntalk to them, because you both know the price will have to be high,\nand if they show the slightest sign of wasting your time, you'll\nbe confident enough to tell them to get lost.The danger is to companies in the middle. Particularly to young\ncompanies that are growing fast, but haven't been doing it for long\nenough to have grown big yet. It's usually a mistake for a promising\ncompany less than a year old even to talk to corp dev.But it's a mistake founders constantly make. When someone from\ncorp dev wants to meet, the founders tell themselves they should\nat least find out what they want. Besides, they don't want to\noffend Big Company by refusing to meet.Well, I'll tell you what they want. They want to talk about buying\nyou. That's what the title \"corp dev\" means. So before agreeing\nto meet with someone from corp dev, ask yourselves, \"Do we want to\nsell the company right now?\" And if the answer is no, tell them\n\"Sorry, but we're focusing on growing the company.\" They won't be\noffended. And certainly the founders of Big Company won't be\noffended. If anything they'll think more highly of you. You'll\nremind them of themselves. They didn't sell either; that's why\nthey're in a position now to buy other companies.\n[1]Most founders who get contacted by corp dev already know what it\nmeans. And yet even when they know what corp dev does and know\nthey don't want to sell, they take the meeting. Why do they do it?\nThe same mix of denial and wishful thinking that underlies most\nmistakes founders make. It's flattering to talk to someone who wants\nto buy you. And who knows, maybe their offer will be surprisingly\nhigh. You should at least see what it is, right?No. If they were going to send you an offer immediately by email,\nsure, you might as well open it. But that is not how conversations\nwith corp dev work. If you get an offer at all, it will be at the\nend of a long and unbelievably distracting process. And if the\noffer is surprising, it will be surprisingly low.Distractions are the thing you can least afford in a startup. And\nconversations with corp dev are the worst sort of distraction,\nbecause as well as consuming your attention they undermine your\nmorale. One of the tricks to surviving a grueling process is not\nto stop and think how tired you are. Instead you get into a sort\nof flow. \n[2]\nImagine what it would do to you if at mile 20 of a\nmarathon, someone ran up beside you and said \"You must feel really\ntired. Would you like to stop and take a rest?\" Conversations\nwith corp dev are like that but worse, because the suggestion of\nstopping gets combined in your mind with the imaginary high price\nyou think they'll offer.And then you're really in trouble. If they can, corp dev people\nlike to turn the tables on you. They like to get you to the point\nwhere you're trying to convince them to buy instead of them trying\nto convince you to sell. And surprisingly often they succeed.This is a very slippery slope, greased with some of the most powerful\nforces that can work on founders' minds, and attended by an experienced\nprofessional whose full time job is to push you down it.Their tactics in pushing you down that slope are usually fairly\nbrutal. Corp dev people's whole job is to buy companies, and they\ndon't even get to choose which. The only way their performance is\nmeasured is by how cheaply they can buy you, and the more ambitious\nones will stop at nothing to achieve that. For example, they'll\nalmost always start with a lowball offer, just to see if you'll\ntake it. Even if you don't, a low initial offer will demoralize you\nand make you easier to manipulate.And that is the most innocent of their tactics. Just wait till\nyou've agreed on a price and think you have a done deal, and then\nthey come back and say their boss has vetoed the deal and won't do\nit for more than half the agreed upon price. Happens all the time.\nIf you think investors can behave badly, it's nothing compared to\nwhat corp dev people can do. Even corp dev people at companies\nthat are otherwise benevolent.I remember once complaining to a\nfriend at Google about some nasty trick their corp dev people had\npulled on a YC startup.\"What happened to Don't be Evil?\" I asked.\"I don't think corp dev got the memo,\" he replied.The tactics you encounter in M&A conversations can be like nothing\nyou've experienced in the otherwise comparatively \nupstanding world\nof Silicon Valley. It's as if a chunk of genetic material from the\nold-fashioned robber baron business world got incorporated into the\nstartup world.\n[3]The simplest way to protect yourself is to use the trick that John\nD. Rockefeller, whose grandfather was an alcoholic, used to protect\nhimself from becoming one. He once told a Sunday school class\n\n Boys, do you know why I never became a drunkard? Because I never\n took the first drink.\n\nDo you want to sell your company right now? Not eventually, right\nnow. If not, just don't take the first meeting. They won't be\noffended. And you in turn will be guaranteed to be spared one of\nthe worst experiences that can happen to a startup.If you do want to sell, there's another set of \ntechniques\n for doing\nthat. But the biggest mistake founders make in dealing with corp\ndev is not doing a bad job of talking to them when they're ready\nto, but talking to them before they are. So if you remember only\nthe title of this essay, you already know most of what you need to\nknow about M&A in the first year.Notes[1]\nI'm not saying you should never sell. I'm saying you should\nbe clear in your own mind about whether you want to sell or not,\nand not be led by manipulation or wishful thinking into trying to\nsell earlier than you otherwise would have.[2]\nIn a startup, as in most competitive sports, the task at hand\nalmost does this for you; you're too busy to feel tired. But when\nyou lose that protection, e.g. at the final whistle, the fatigue\nhits you like a wave. To talk to corp dev is to let yourself feel\nit mid-game.[3]\nTo be fair, the apparent misdeeds of corp dev people are magnified\nby the fact that they function as the face of a large organization\nthat often doesn't know its own mind. Acquirers can be surprisingly\nindecisive about acquisitions, and their flakiness is indistinguishable\nfrom dishonesty by the time it filters down to you.Thanks to Marc Andreessen, Jessica Livingston, Geoff\nRalston, and Qasar Younis for reading drafts of this." }, { "path": "data/PaulGrahamEssaysLarge/desres.txt", "content": "January 2003(This article is derived from a keynote talk at the fall 2002 meeting\nof NEPLS.)Visitors to this country are often surprised to find that\nAmericans like to begin a conversation by asking \"what do you do?\"\nI've never liked this question. I've rarely had a\nneat answer to it. But I think I have finally solved the problem.\nNow, when someone asks me what I do, I look them straight\nin the eye and say \"I'm designing a \nnew dialect of Lisp.\" \nI recommend this answer to anyone who doesn't like being asked what\nthey do. The conversation will turn immediately to other topics.I don't consider myself to be doing research on programming languages.\nI'm just designing one, in the same way that someone might design\na building or a chair or a new typeface.\nI'm not trying to discover anything new. I just want\nto make a language that will be good to program in. In some ways,\nthis assumption makes life a lot easier.The difference between design and research seems to be a question\nof new versus good. Design doesn't have to be new, but it has to \nbe good. Research doesn't have to be good, but it has to be new.\nI think these two paths converge at the top: the best design\nsurpasses its predecessors by using new ideas, and the best research\nsolves problems that are not only new, but actually worth solving.\nSo ultimately we're aiming for the same destination, just approaching\nit from different directions.What I'm going to talk about today is what your target looks like\nfrom the back. What do you do differently when you treat\nprogramming languages as a design problem instead of a research topic?The biggest difference is that you focus more on the user.\nDesign begins by asking, who is this\nfor and what do they need from it? A good architect,\nfor example, does not begin by creating a design that he then\nimposes on the users, but by studying the intended users and figuring\nout what they need.Notice I said \"what they need,\" not \"what they want.\" I don't mean\nto give the impression that working as a designer means working as \na sort of short-order cook, making whatever the client tells you\nto. This varies from field to field in the arts, but\nI don't think there is any field in which the best work is done by\nthe people who just make exactly what the customers tell them to.The customer is always right in\nthe sense that the measure of good design is how well it works\nfor the user. If you make a novel that bores everyone, or a chair\nthat's horribly uncomfortable to sit in, then you've done a bad\njob, period. It's no defense to say that the novel or the chair \nis designed according to the most advanced theoretical principles.And yet, making what works for the user doesn't mean simply making\nwhat the user tells you to. Users don't know what all the choices\nare, and are often mistaken about what they really want.The answer to the paradox, I think, is that you have to design\nfor the user, but you have to design what the user needs, not simply \nwhat he says he wants.\nIt's much like being a doctor. You can't just treat a patient's\nsymptoms. When a patient tells you his symptoms, you have to figure\nout what's actually wrong with him, and treat that.This focus on the user is a kind of axiom from which most of the\npractice of good design can be derived, and around which most design\nissues center.If good design must do what the user needs, who is the user? When\nI say that design must be for users, I don't mean to imply that good \ndesign aims at some kind of \nlowest common denominator. You can pick any group of users you\nwant. If you're designing a tool, for example, you can design it\nfor anyone from beginners to experts, and what's good design\nfor one group might be bad for another. The point\nis, you have to pick some group of users. I don't think you can\neven talk about good or bad design except with\nreference to some intended user.You're most likely to get good design if the intended users include\nthe designer himself. When you design something\nfor a group that doesn't include you, it tends to be for people\nyou consider to be less sophisticated than you, not more sophisticated.That's a problem, because looking down on the user, however benevolently,\nseems inevitably to corrupt the designer.\nI suspect that very few housing\nprojects in the US were designed by architects who expected to live\nin them. You can see the same thing\nin programming languages. C, Lisp, and Smalltalk were created for\ntheir own designers to use. Cobol, Ada, and Java, were created \nfor other people to use.If you think you're designing something for idiots, the odds are\nthat you're not designing something good, even for idiots.\nEven if you're designing something for the most sophisticated\nusers, though, you're still designing for humans. It's different \nin research. In math you\ndon't choose abstractions because they're\neasy for humans to understand; you choose whichever make the\nproof shorter. I think this is true for the sciences generally.\nScientific ideas are not meant to be ergonomic.Over in the arts, things are very different. Design is\nall about people. The human body is a strange\nthing, but when you're designing a chair,\nthat's what you're designing for, and there's no way around it.\nAll the arts have to pander to the interests and limitations\nof humans. In painting, for example, all other things being\nequal a painting with people in it will be more interesting than\none without. It is not merely an accident of history that\nthe great paintings of the Renaissance are all full of people.\nIf they hadn't been, painting as a medium wouldn't have the prestige\nthat it does.Like it or not, programming languages are also for people,\nand I suspect the human brain is just as lumpy and idiosyncratic\nas the human body. Some ideas are easy for people to grasp\nand some aren't. For example, we seem to have a very limited\ncapacity for dealing with detail. It's this fact that makes\nprograming languages a good idea in the first place; if we\ncould handle the detail, we could just program in machine\nlanguage.Remember, too, that languages are not\nprimarily a form for finished programs, but something that\nprograms have to be developed in. Anyone in the arts could\ntell you that you might want different mediums for the\ntwo situations. Marble, for example, is a nice, durable\nmedium for finished ideas, but a hopelessly inflexible one\nfor developing new ideas.A program, like a proof,\nis a pruned version of a tree that in the past has had\nfalse starts branching off all over it. So the test of\na language is not simply how clean the finished program looks\nin it, but how clean the path to the finished program was.\nA design choice that gives you elegant finished programs\nmay not give you an elegant design process. For example, \nI've written a few macro-defining macros full of nested\nbackquotes that look now like little gems, but writing them\ntook hours of the ugliest trial and error, and frankly, I'm still\nnot entirely sure they're correct.We often act as if the test of a language were how good\nfinished programs look in it.\nIt seems so convincing when you see the same program\nwritten in two languages, and one version is much shorter.\nWhen you approach the problem from the direction of the\narts, you're less likely to depend on this sort of\ntest. You don't want to end up with a programming\nlanguage like marble.For example, it is a huge win in developing software to\nhave an interactive toplevel, what in Lisp is called a\nread-eval-print loop. And when you have one this has\nreal effects on the design of the language. It would not\nwork well for a language where you have to declare\nvariables before using them, for example. When you're\njust typing expressions into the toplevel, you want to be \nable to set x to some value and then start doing things\nto x. You don't want to have to declare the type of x\nfirst. You may dispute either of the premises, but if\na language has to have a toplevel to be convenient, and\nmandatory type declarations are incompatible with a\ntoplevel, then no language that makes type declarations \nmandatory could be convenient to program in.In practice, to get good design you have to get close, and stay\nclose, to your users. You have to calibrate your ideas on actual\nusers constantly, especially in the beginning. One of the reasons\nJane Austen's novels are so good is that she read them out loud to\nher family. That's why she never sinks into self-indulgently arty\ndescriptions of landscapes,\nor pretentious philosophizing. (The philosophy's there, but it's\nwoven into the story instead of being pasted onto it like a label.)\nIf you open an average \"literary\" novel and imagine reading it out loud\nto your friends as something you'd written, you'll feel all too\nkeenly what an imposition that kind of thing is upon the reader.In the software world, this idea is known as Worse is Better.\nActually, there are several ideas mixed together in the concept of\nWorse is Better, which is why people are still arguing about\nwhether worse\nis actually better or not. But one of the main ideas in that\nmix is that if you're building something new, you should get a\nprototype in front of users as soon as possible.The alternative approach might be called the Hail Mary strategy.\nInstead of getting a prototype out quickly and gradually refining\nit, you try to create the complete, finished, product in one long\ntouchdown pass. As far as I know, this is a\nrecipe for disaster. Countless startups destroyed themselves this\nway during the Internet bubble. I've never heard of a case\nwhere it worked.What people outside the software world may not realize is that\nWorse is Better is found throughout the arts.\nIn drawing, for example, the idea was discovered during the\nRenaissance. Now almost every drawing teacher will tell you that\nthe right way to get an accurate drawing is not to\nwork your way slowly around the contour of an object, because errors will\naccumulate and you'll find at the end that the lines don't meet.\nInstead you should draw a few quick lines in roughly the right place,\nand then gradually refine this initial sketch.In most fields, prototypes\nhave traditionally been made out of different materials.\nTypefaces to be cut in metal were initially designed \nwith a brush on paper. Statues to be cast in bronze \nwere modelled in wax. Patterns to be embroidered on tapestries\nwere drawn on paper with ink wash. Buildings to be\nconstructed from stone were tested on a smaller scale in wood.What made oil paint so exciting, when it\nfirst became popular in the fifteenth century, was that you\ncould actually make the finished work from the prototype.\nYou could make a preliminary drawing if you wanted to, but you\nweren't held to it; you could work out all the details, and\neven make major changes, as you finished the painting.You can do this in software too. A prototype doesn't have to\nbe just a model; you can refine it into the finished product.\nI think you should always do this when you can. It lets you\ntake advantage of new insights you have along the way. But\nperhaps even more important, it's good for morale.Morale is key in design. I'm surprised people\ndon't talk more about it. One of my first\ndrawing teachers told me: if you're bored when you're\ndrawing something, the drawing will look boring.\nFor example, suppose you have to draw a building, and you\ndecide to draw each brick individually. You can do this\nif you want, but if you get bored halfway through and start\nmaking the bricks mechanically instead of observing each one, \nthe drawing will look worse than if you had merely suggested\nthe bricks.Building something by gradually refining a prototype is good\nfor morale because it keeps you engaged. In software, my \nrule is: always have working code. If you're writing\nsomething that you'll be able to test in an hour, then you\nhave the prospect of an immediate reward to motivate you.\nThe same is true in the arts, and particularly in oil painting.\nMost painters start with a blurry sketch and gradually\nrefine it.\nIf you work this way, then in principle\nyou never have to end the day with something that actually\nlooks unfinished. Indeed, there is even a saying among\npainters: \"A painting is never finished, you just stop\nworking on it.\" This idea will be familiar to anyone who\nhas worked on software.Morale is another reason that it's hard to design something\nfor an unsophisticated user. It's hard to stay interested in\nsomething you don't like yourself. To make something \ngood, you have to be thinking, \"wow, this is really great,\"\nnot \"what a piece of shit; those fools will love it.\"Design means making things for humans. But it's not just the\nuser who's human. The designer is human too.Notice all this time I've been talking about \"the designer.\"\nDesign usually has to be under the control of a single person to\nbe any good. And yet it seems to be possible for several people\nto collaborate on a research project. This seems to\nme one of the most interesting differences between research and\ndesign.There have been famous instances of collaboration in the arts,\nbut most of them seem to have been cases of molecular bonding rather\nthan nuclear fusion. In an opera it's common for one person to\nwrite the libretto and another to write the music. And during the Renaissance, \njourneymen from northern\nEurope were often employed to do the landscapes in the\nbackgrounds of Italian paintings. But these aren't true collaborations.\nThey're more like examples of Robert Frost's\n\"good fences make good neighbors.\" You can stick instances\nof good design together, but within each individual project,\none person has to be in control.I'm not saying that good design requires that one person think\nof everything. There's nothing more valuable than the advice\nof someone whose judgement you trust. But after the talking is\ndone, the decision about what to do has to rest with one person.Why is it that research can be done by collaborators and \ndesign can't? This is an interesting question. I don't \nknow the answer. Perhaps,\nif design and research converge, the best research is also\ngood design, and in fact can't be done by collaborators.\nA lot of the most famous scientists seem to have worked alone.\nBut I don't know enough to say whether there\nis a pattern here. It could be simply that many famous scientists\nworked when collaboration was less common.Whatever the story is in the sciences, true collaboration\nseems to be vanishingly rare in the arts. Design by committee is a\nsynonym for bad design. Why is that so? Is there some way to\nbeat this limitation?I'm inclined to think there isn't-- that good design requires\na dictator. One reason is that good design has to \nbe all of a piece. Design is not just for humans, but\nfor individual humans. If a design represents an idea that \nfits in one person's head, then the idea will fit in the user's\nhead too.Related:" }, { "path": "data/PaulGrahamEssaysLarge/diff.txt", "content": "December 2001 (rev. May 2002)\n\n(This article came about in response to some questions on\nthe LL1 mailing list. It is now\nincorporated in Revenge of the Nerds.)When McCarthy designed Lisp in the late 1950s, it was\na radical departure from existing languages,\nthe most important of which was Fortran.Lisp embodied nine new ideas:\n1. Conditionals. A conditional is an if-then-else\nconstruct. We take these for granted now. They were \ninvented\nby McCarthy in the course of developing Lisp. \n(Fortran at that time only had a conditional\ngoto, closely based on the branch instruction in the \nunderlying hardware.) McCarthy, who was on the Algol committee, got\nconditionals into Algol, whence they spread to most other\nlanguages.2. A function type. In Lisp, functions are first class \nobjects-- they're a data type just like integers, strings,\netc, and have a literal representation, can be stored in variables,\ncan be passed as arguments, and so on.3. Recursion. Recursion existed as a mathematical concept\nbefore Lisp of course, but Lisp was the first programming language to support\nit. (It's arguably implicit in making functions first class\nobjects.)4. A new concept of variables. In Lisp, all variables\nare effectively pointers. Values are what\nhave types, not variables, and assigning or binding\nvariables means copying pointers, not what they point to.5. Garbage-collection.6. Programs composed of expressions. Lisp programs are \ntrees of expressions, each of which returns a value. \n(In some Lisps expressions\ncan return multiple values.) This is in contrast to Fortran\nand most succeeding languages, which distinguish between\nexpressions and statements.It was natural to have this\ndistinction in Fortran because (not surprisingly in a language\nwhere the input format was punched cards) the language was\nline-oriented. You could not nest statements. And\nso while you needed expressions for math to work, there was\nno point in making anything else return a value, because\nthere could not be anything waiting for it.This limitation\nwent away with the arrival of block-structured languages,\nbut by then it was too late. The distinction between\nexpressions and statements was entrenched. It spread from \nFortran into Algol and thence to both their descendants.When a language is made entirely of expressions, you can\ncompose expressions however you want. You can say either\n(using Arc syntax)(if foo (= x 1) (= x 2))or(= x (if foo 1 2))7. A symbol type. Symbols differ from strings in that\nyou can test equality by comparing a pointer.8. A notation for code using trees of symbols.9. The whole language always available. \nThere is\nno real distinction between read-time, compile-time, and runtime.\nYou can compile or run code while reading, read or run code\nwhile compiling, and read or compile code at runtime.Running code at read-time lets users reprogram Lisp's syntax;\nrunning code at compile-time is the basis of macros; compiling\nat runtime is the basis of Lisp's use as an extension\nlanguage in programs like Emacs; and reading at runtime\nenables programs to communicate using s-expressions, an\nidea recently reinvented as XML.\nWhen Lisp was first invented, all these ideas were far\nremoved from ordinary programming practice, which was\ndictated largely by the hardware available in the late 1950s.Over time, the default language, embodied\nin a succession of popular languages, has\ngradually evolved toward Lisp. 1-5 are now widespread.\n6 is starting to appear in the mainstream.\nPython has a form of 7, though there doesn't seem to be\nany syntax for it. \n8, which (with 9) is what makes Lisp macros\npossible, is so far still unique to Lisp,\nperhaps because (a) it requires those parens, or something \njust as bad, and (b) if you add that final increment of power, \nyou can no \nlonger claim to have invented a new language, but only\nto have designed a new dialect of Lisp ; -)Though useful to present-day programmers, it's\nstrange to describe Lisp in terms of its\nvariation from the random expedients other languages\nadopted. That was not, probably, how McCarthy\nthought of it. Lisp wasn't designed to fix the mistakes\nin Fortran; it came about more as the byproduct of an\nattempt to axiomatize computation." }, { "path": "data/PaulGrahamEssaysLarge/ecw.txt", "content": "December 2014If the world were static, we could have monotonically increasing\nconfidence in our beliefs. The more (and more varied) experience\na belief survived, the less likely it would be false. Most people\nimplicitly believe something like this about their opinions. And\nthey're justified in doing so with opinions about things that don't\nchange much, like human nature. But you can't trust your opinions\nin the same way about things that change, which could include\npractically everything else.When experts are wrong, it's often because they're experts on an\nearlier version of the world.Is it possible to avoid that? Can you protect yourself against\nobsolete beliefs? To some extent, yes. I spent almost a decade\ninvesting in early stage startups, and curiously enough protecting\nyourself against obsolete beliefs is exactly what you have to do\nto succeed as a startup investor. Most really good startup ideas\nlook like bad ideas at first, and many of those look bad specifically\nbecause some change in the world just switched them from bad to\ngood. I spent a lot of time learning to recognize such ideas, and\nthe techniques I used may be applicable to ideas in general.The first step is to have an explicit belief in change. People who\nfall victim to a monotonically increasing confidence in their\nopinions are implicitly concluding the world is static. If you\nconsciously remind yourself it isn't, you start to look for change.Where should one look for it? Beyond the moderately useful\ngeneralization that human nature doesn't change much, the unfortunate\nfact is that change is hard to predict. This is largely a tautology\nbut worth remembering all the same: change that matters usually\ncomes from an unforeseen quarter.So I don't even try to predict it. When I get asked in interviews\nto predict the future, I always have to struggle to come up with\nsomething plausible-sounding on the fly, like a student who hasn't\nprepared for an exam.\n[1]\nBut it's not out of laziness that I haven't\nprepared. It seems to me that beliefs about the future are so\nrarely correct that they usually aren't worth the extra rigidity\nthey impose, and that the best strategy is simply to be aggressively\nopen-minded. Instead of trying to point yourself in the right\ndirection, admit you have no idea what the right direction is, and\ntry instead to be super sensitive to the winds of change.It's ok to have working hypotheses, even though they may constrain\nyou a bit, because they also motivate you. It's exciting to chase\nthings and exciting to try to guess answers. But you have to be\ndisciplined about not letting your hypotheses harden into anything\nmore.\n[2]I believe this passive m.o. works not just for evaluating new ideas\nbut also for having them. The way to come up with new ideas is not\nto try explicitly to, but to try to solve problems and simply not\ndiscount weird hunches you have in the process.The winds of change originate in the unconscious minds of domain\nexperts. If you're sufficiently expert in a field, any weird idea\nor apparently irrelevant question that occurs to you is ipso facto\nworth exploring. \n[3]\n Within Y Combinator, when an idea is described\nas crazy, it's a compliment—in fact, on average probably a\nhigher compliment than when an idea is described as good.Startup investors have extraordinary incentives for correcting\nobsolete beliefs. If they can realize before other investors that\nsome apparently unpromising startup isn't, they can make a huge\namount of money. But the incentives are more than just financial.\nInvestors' opinions are explicitly tested: startups come to them\nand they have to say yes or no, and then, fairly quickly, they learn\nwhether they guessed right. The investors who say no to a Google\n(and there were several) will remember it for the rest of their\nlives.Anyone who must in some sense bet on ideas rather than merely\ncommenting on them has similar incentives. Which means anyone who\nwants such incentives can have them, by turning their comments into\nbets: if you write about a topic in some fairly durable and public\nform, you'll find you worry much more about getting things right\nthan most people would in a casual conversation.\n[4]Another trick I've found to protect myself against obsolete beliefs\nis to focus initially on people rather than ideas. Though the nature\nof future discoveries is hard to predict, I've found I can predict\nquite well what sort of people will make them. Good new ideas come\nfrom earnest, energetic, independent-minded people.Betting on people over ideas saved me countless times as an investor.\nWe thought Airbnb was a bad idea, for example. But we could tell\nthe founders were earnest, energetic, and independent-minded.\n(Indeed, almost pathologically so.) So we suspended disbelief and\nfunded them.This too seems a technique that should be generally applicable.\nSurround yourself with the sort of people new ideas come from. If\nyou want to notice quickly when your beliefs become obsolete, you\ncan't do better than to be friends with the people whose discoveries\nwill make them so.It's hard enough already not to become the prisoner of your own\nexpertise, but it will only get harder, because change is accelerating.\nThat's not a recent trend; change has been accelerating since the\npaleolithic era. Ideas beget ideas. I don't expect that to change.\nBut I could be wrong.\nNotes[1]\nMy usual trick is to talk about aspects of the present that\nmost people haven't noticed yet.[2]\nEspecially if they become well enough known that people start\nto identify them with you. You have to be extra skeptical about\nthings you want to believe, and once a hypothesis starts to be\nidentified with you, it will almost certainly start to be in that\ncategory.[3]\nIn practice \"sufficiently expert\" doesn't require one to be\nrecognized as an expert—which is a trailing indicator in any\ncase. In many fields a year of focused work plus caring a lot would\nbe enough.[4]\nThough they are public and persist indefinitely, comments on\ne.g. forums and places like Twitter seem empirically to work like\ncasual conversation. The threshold may be whether what you write\nhas a title.\nThanks to Sam Altman, Patrick Collison, and Robert Morris\nfor reading drafts of this." }, { "path": "data/PaulGrahamEssaysLarge/founders.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nOctober 2010\n\n(I wrote this for Forbes, who asked me to write something\nabout the qualities we look for in founders. In print they had to cut\nthe last item because they didn't have room.)1. DeterminationThis has turned out to be the most important quality in startup\nfounders. We thought when we started Y Combinator that the most\nimportant quality would be intelligence. That's the myth in the\nValley. And certainly you don't want founders to be stupid. But\nas long as you're over a certain threshold of intelligence, what\nmatters most is determination. You're going to hit a lot of\nobstacles. You can't be the sort of person who gets demoralized\neasily.Bill Clerico and Rich Aberman of WePay \nare a good example. They're\ndoing a finance startup, which means endless negotiations with big,\nbureaucratic companies. When you're starting a startup that depends\non deals with big companies to exist, it often feels like they're\ntrying to ignore you out of existence. But when Bill Clerico starts\ncalling you, you may as well do what he asks, because he is not\ngoing away.\n2. FlexibilityYou do not however want the sort of determination implied by phrases\nlike \"don't give up on your dreams.\" The world of startups is so\nunpredictable that you need to be able to modify your dreams on the\nfly. The best metaphor I've found for the combination of determination\nand flexibility you need is a running back. \nHe's determined to get\ndownfield, but at any given moment he may need to go sideways or\neven backwards to get there.The current record holder for flexibility may be Daniel Gross of\nGreplin. He applied to YC with \nsome bad ecommerce idea. We told\nhim we'd fund him if he did something else. He thought for a second,\nand said ok. He then went through two more ideas before settling\non Greplin. He'd only been working on it for a couple days when\nhe presented to investors at Demo Day, but he got a lot of interest.\nHe always seems to land on his feet.\n3. ImaginationIntelligence does matter a lot of course. It seems like the type\nthat matters most is imagination. It's not so important to be able\nto solve predefined problems quickly as to be able to come up with\nsurprising new ideas. In the startup world, most good ideas \nseem\nbad initially. If they were obviously good, someone would already\nbe doing them. So you need the kind of intelligence that produces\nideas with just the right level of craziness.Airbnb is that kind of idea. \nIn fact, when we funded Airbnb, we\nthought it was too crazy. We couldn't believe large numbers of\npeople would want to stay in other people's places. We funded them\nbecause we liked the founders so much. As soon as we heard they'd\nbeen supporting themselves by selling Obama and McCain branded\nbreakfast cereal, they were in. And it turned out the idea was on\nthe right side of crazy after all.\n4. NaughtinessThough the most successful founders are usually good people, they\ntend to have a piratical gleam in their eye. They're not Goody\nTwo-Shoes type good. Morally, they care about getting the big\nquestions right, but not about observing proprieties. That's why\nI'd use the word naughty rather than evil. They delight in \nbreaking\nrules, but not rules that matter. This quality may be redundant\nthough; it may be implied by imagination.Sam Altman of Loopt \nis one of the most successful alumni, so we\nasked him what question we could put on the Y Combinator application\nthat would help us discover more people like him. He said to ask\nabout a time when they'd hacked something to their advantage—hacked in the sense of beating the system, not breaking into\ncomputers. It has become one of the questions we pay most attention\nto when judging applications.\n5. FriendshipEmpirically it seems to be hard to start a startup with just \none\nfounder. Most of the big successes have two or three. And the\nrelationship between the founders has to be strong. They must\ngenuinely like one another, and work well together. Startups do\nto the relationship between the founders what a dog does to a sock:\nif it can be pulled apart, it will be.Emmett Shear and Justin Kan of Justin.tv \nare a good example of close\nfriends who work well together. They've known each other since\nsecond grade. They can practically read one another's minds. I'm\nsure they argue, like all founders, but I have never once sensed\nany unresolved tension between them.Thanks to Jessica Livingston and Chris Steiner for reading drafts of this." }, { "path": "data/PaulGrahamEssaysLarge/foundervisa.txt", "content": "\n\nApril 2009I usually avoid politics, but since we now seem to have an administration that's open to suggestions, I'm going to risk making one. The single biggest thing the government could do to increase the number of startups in this country is a policy that would cost nothing: establish a new class of visa for startup founders.The biggest constraint on the number of new startups that get created in the US is not tax policy or employment law or even Sarbanes-Oxley. It's that we won't let the people who want to start them into the country.Letting just 10,000 startup founders into the country each year could have a visible effect on the economy. If we assume 4 people per startup, which is probably an overestimate, that's 2500 new companies. Each year. They wouldn't all grow as big as Google, but out of 2500 some would come close.By definition these 10,000 founders wouldn't be taking jobs from Americans: it could be part of the terms of the visa that they couldn't work for existing companies, only new ones they'd founded. In fact they'd cause there to be \nmore jobs for Americans, because the companies they started would hire more employees as they grew.The tricky part might seem to be how one defined a startup. But that could be solved quite easily: let the market decide. Startup investors work hard to find the best startups. The government could not do better than to piggyback on their expertise, and use investment by recognized startup investors as the test of whether a company was a real startup.How would the government decide who's a startup investor? The same way they decide what counts as a university for student visas. We'll establish our own accreditation procedure. We know who one another are.10,000 people is a drop in the bucket by immigration standards, but would represent a huge increase in the pool of startup founders. I think this would have such a visible effect on the economy that it would make the legislator who introduced the bill famous. The only way to know for sure would be to try it, and that would cost practically nothing.\nThanks to Trevor Blackwell, Paul Buchheit, Jeff Clavier, David Hornik, Jessica Livingston, Greg Mcadoo, Aydin Senkut, and Fred Wilson for reading drafts of this.Related:" }, { "path": "data/PaulGrahamEssaysLarge/gap.txt", "content": "May 2004When people care enough about something to do it well, those who\ndo it best tend to be far better than everyone else. There's a\nhuge gap between Leonardo and second-rate contemporaries like\nBorgognone. You see the same gap between Raymond Chandler and the\naverage writer of detective novels. A top-ranked professional chess\nplayer could play ten thousand games against an ordinary club player\nwithout losing once.Like chess or painting or writing novels, making money is a very\nspecialized skill. But for some reason we treat this skill\ndifferently. No one complains when a few people surpass all the\nrest at playing chess or writing novels, but when a few people make\nmore money than the rest, we get editorials saying this is wrong.Why? The pattern of variation seems no different than for any other\nskill. What causes people to react so strongly when the skill is\nmaking money?I think there are three reasons we treat making money as different:\nthe misleading model of wealth we learn as children; the disreputable\nway in which, till recently, most fortunes were accumulated; and\nthe worry that great variations in income are somehow bad for\nsociety. As far as I can tell, the first is mistaken, the second\noutdated, and the third empirically false. Could it be that, in a\nmodern democracy, variation in income is actually a sign of health?The Daddy Model of WealthWhen I was five I thought electricity was created by electric\nsockets. I didn't realize there were power plants out there\ngenerating it. Likewise, it doesn't occur to most kids that wealth\nis something that has to be generated. It seems to be something\nthat flows from parents.Because of the circumstances in which they encounter it, children\ntend to misunderstand wealth. They confuse it with money. They\nthink that there is a fixed amount of it. And they think of it as\nsomething that's distributed by authorities (and so should be\ndistributed equally), rather than something that has to be created\n(and might be created unequally).In fact, wealth is not money. Money is just a convenient way of\ntrading one form of wealth for another. Wealth is the underlying\nstuff—the goods and services we buy. When you travel to a\nrich or poor country, you don't have to look at people's bank\naccounts to tell which kind you're in. You can see\nwealth—in buildings and streets, in the clothes and the health\nof the people.Where does wealth come from? People make it. This was easier to\ngrasp when most people lived on farms, and made many of the things\nthey wanted with their own hands. Then you could see in the house,\nthe herds, and the granary the wealth that each family created. It\nwas obvious then too that the wealth of the world was not a fixed\nquantity that had to be shared out, like slices of a pie. If you\nwanted more wealth, you could make it.This is just as true today, though few of us create wealth directly\nfor ourselves (except for a few vestigial domestic tasks). Mostly\nwe create wealth for other people in exchange for money, which we\nthen trade for the forms of wealth we want. \n[1]Because kids are unable to create wealth, whatever they have has\nto be given to them. And when wealth is something you're given,\nthen of course it seems that it should be distributed equally.\n[2]\nAs in most families it is. The kids see to that. \"Unfair,\" they\ncry, when one sibling gets more than another.In the real world, you can't keep living off your parents. If you\nwant something, you either have to make it, or do something of\nequivalent value for someone else, in order to get them to give you\nenough money to buy it. In the real world, wealth is (except for\na few specialists like thieves and speculators) something you have\nto create, not something that's distributed by Daddy. And since\nthe ability and desire to create it vary from person to person,\nit's not made equally.You get paid by doing or making something people want, and those\nwho make more money are often simply better at doing what people\nwant. Top actors make a lot more money than B-list actors. The\nB-list actors might be almost as charismatic, but when people go\nto the theater and look at the list of movies playing, they want\nthat extra oomph that the big stars have.Doing what people want is not the only way to get money, of course.\nYou could also rob banks, or solicit bribes, or establish a monopoly.\nSuch tricks account for some variation in wealth, and indeed for\nsome of the biggest individual fortunes, but they are not the root\ncause of variation in income. The root cause of variation in income,\nas Occam's Razor implies, is the same as the root cause of variation\nin every other human skill.In the United States, the CEO of a large public company makes about\n100 times as much as the average person. \n[3]\nBasketball players\nmake about 128 times as much, and baseball players 72 times as much.\nEditorials quote this kind of statistic with horror. But I have\nno trouble imagining that one person could be 100 times as productive\nas another. In ancient Rome the price of slaves varied by\na factor of 50 depending on their skills. \n[4]\nAnd that's without\nconsidering motivation, or the extra leverage in productivity that\nyou can get from modern technology.Editorials about athletes' or CEOs' salaries remind me of early\nChristian writers, arguing from first principles about whether the\nEarth was round, when they could just walk outside and check.\n[5]\nHow much someone's work is worth is not a policy question. It's\nsomething the market already determines.\"Are they really worth 100 of us?\" editorialists ask. Depends on\nwhat you mean by worth. If you mean worth in the sense of what\npeople will pay for their skills, the answer is yes, apparently.A few CEOs' incomes reflect some kind of wrongdoing. But are there\nnot others whose incomes really do reflect the wealth they generate?\nSteve Jobs saved a company that was in a terminal decline. And not\nmerely in the way a turnaround specialist does, by cutting costs;\nhe had to decide what Apple's next products should be. Few others\ncould have done it. And regardless of the case with CEOs, it's\nhard to see how anyone could argue that the salaries of professional\nbasketball players don't reflect supply and demand.It may seem unlikely in principle that one individual could really\ngenerate so much more wealth than another. The key to this mystery\nis to revisit that question, are they really worth 100 of us?\nWould a basketball team trade one of their players for 100\nrandom people? What would Apple's next product look like if you\nreplaced Steve Jobs with a committee of 100 random people? \n[6]\nThese\nthings don't scale linearly. Perhaps the CEO or the professional\nathlete has only ten times (whatever that means) the skill and\ndetermination of an ordinary person. But it makes all the difference\nthat it's concentrated in one individual.When we say that one kind of work is overpaid and another underpaid,\nwhat are we really saying? In a free market, prices are determined\nby what buyers want. People like baseball more than poetry, so\nbaseball players make more than poets. To say that a certain kind\nof work is underpaid is thus identical with saying that people want\nthe wrong things.Well, of course people want the wrong things. It seems odd to be\nsurprised by that. And it seems even odder to say that it's\nunjust that certain kinds of work are underpaid. \n[7]\nThen\nyou're saying that it's unjust that people want the wrong things.\nIt's lamentable that people prefer reality TV and corndogs to\nShakespeare and steamed vegetables, but unjust? That seems like\nsaying that blue is heavy, or that up is circular.The appearance of the word \"unjust\" here is the unmistakable spectral\nsignature of the Daddy Model. Why else would this idea occur in\nthis odd context? Whereas if the speaker were still operating on\nthe Daddy Model, and saw wealth as something that flowed from a\ncommon source and had to be shared out, rather than something\ngenerated by doing what other people wanted, this is exactly what\nyou'd get on noticing that some people made much more than others.When we talk about \"unequal distribution of income,\" we should\nalso ask, where does that income come from?\n[8]\nWho made the wealth\nit represents? Because to the extent that income varies simply\naccording to how much wealth people create, the distribution may\nbe unequal, but it's hardly unjust.Stealing ItThe second reason we tend to find great disparities of wealth\nalarming is that for most of human history the usual way to accumulate\na fortune was to steal it: in pastoral societies by cattle raiding;\nin agricultural societies by appropriating others' estates in times\nof war, and taxing them in times of peace.In conflicts, those on the winning side would receive the estates\nconfiscated from the losers. In England in the 1060s, when William\nthe Conqueror distributed the estates of the defeated Anglo-Saxon\nnobles to his followers, the conflict was military. By the 1530s,\nwhen Henry VIII distributed the estates of the monasteries to his\nfollowers, it was mostly political. \n[9]\nBut the principle was the\nsame. Indeed, the same principle is at work now in Zimbabwe.In more organized societies, like China, the ruler and his officials\nused taxation instead of confiscation. But here too we see the\nsame principle: the way to get rich was not to create wealth, but\nto serve a ruler powerful enough to appropriate it.This started to change in Europe with the rise of the middle class.\nNow we think of the middle class as people who are neither rich nor\npoor, but originally they were a distinct group. In a feudal\nsociety, there are just two classes: a warrior aristocracy, and the\nserfs who work their estates. The middle class were a new, third\ngroup who lived in towns and supported themselves by manufacturing\nand trade.Starting in the tenth and eleventh centuries, petty nobles and\nformer serfs banded together in towns that gradually became powerful\nenough to ignore the local feudal lords. \n[10]\nLike serfs, the middle\nclass made a living largely by creating wealth. (In port cities\nlike Genoa and Pisa, they also engaged in piracy.) But unlike serfs\nthey had an incentive to create a lot of it. Any wealth a serf\ncreated belonged to his master. There was not much point in making\nmore than you could hide. Whereas the independence of the townsmen\nallowed them to keep whatever wealth they created.Once it became possible to get rich by creating wealth, society as\na whole started to get richer very rapidly. Nearly everything we\nhave was created by the middle class. Indeed, the other two classes\nhave effectively disappeared in industrial societies, and their\nnames been given to either end of the middle class. (In the original\nsense of the word, Bill Gates is middle class.)But it was not till the Industrial Revolution that wealth creation\ndefinitively replaced corruption as the best way to get rich. In\nEngland, at least, corruption only became unfashionable (and in\nfact only started to be called \"corruption\") when there started to\nbe other, faster ways to get rich.Seventeenth-century England was much like the third world today,\nin that government office was a recognized route to wealth. The\ngreat fortunes of that time still derived more from what we would\nnow call corruption than from commerce. \n[11]\nBy the nineteenth\ncentury that had changed. There continued to be bribes, as there\nstill are everywhere, but politics had by then been left to men who\nwere driven more by vanity than greed. Technology had made it\npossible to create wealth faster than you could steal it. The\nprototypical rich man of the nineteenth century was not a courtier\nbut an industrialist.With the rise of the middle class, wealth stopped being a zero-sum\ngame. Jobs and Wozniak didn't have to make us poor to make themselves\nrich. Quite the opposite: they created things that made our lives\nmaterially richer. They had to, or we wouldn't have paid for them.But since for most of the world's history the main route to wealth\nwas to steal it, we tend to be suspicious of rich people. Idealistic\nundergraduates find their unconsciously preserved child's model of\nwealth confirmed by eminent writers of the past. It is a case of\nthe mistaken meeting the outdated.\"Behind every great fortune, there is a crime,\" Balzac wrote. Except\nhe didn't. What he actually said was that a great fortune with no\napparent cause was probably due to a crime well enough executed\nthat it had been forgotten. If we were talking about Europe in\n1000, or most of the third world today, the standard misquotation\nwould be spot on. But Balzac lived in nineteenth-century France,\nwhere the Industrial Revolution was well advanced. He knew you\ncould make a fortune without stealing it. After all, he did himself,\nas a popular novelist.\n[12]Only a few countries (by no coincidence, the richest ones) have\nreached this stage. In most, corruption still has the upper hand.\nIn most, the fastest way to get wealth is by stealing it. And so\nwhen we see increasing differences in income in a rich country,\nthere is a tendency to worry that it's sliding back toward becoming\nanother Venezuela. I think the opposite is happening. I think\nyou're seeing a country a full step ahead of Venezuela.The Lever of TechnologyWill technology increase the gap between rich and poor? It will\ncertainly increase the gap between the productive and the unproductive.\nThat's the whole point of technology. With a tractor an energetic\nfarmer could plow six times as much land in a day as he could with\na team of horses. But only if he mastered a new kind of farming.I've seen the lever of technology grow visibly in my own time. In\nhigh school I made money by mowing lawns and scooping ice cream at\nBaskin-Robbins. This was the only kind of work available at the\ntime. Now high school kids could write software or design web\nsites. But only some of them will; the rest will still be scooping\nice cream.I remember very vividly when in 1985 improved technology made it\npossible for me to buy a computer of my own. Within months I was\nusing it to make money as a freelance programmer. A few years\nbefore, I couldn't have done this. A few years before, there was\nno such thing as a freelance programmer. But Apple created\nwealth, in the form of powerful, inexpensive computers, and programmers\nimmediately set to work using it to create more.As this example suggests, the rate at which technology increases\nour productive capacity is probably exponential, rather than linear.\nSo we should expect to see ever-increasing variation in individual\nproductivity as time goes on. Will that increase the gap between\nrich and the poor? Depends which gap you mean.Technology should increase the gap in income, but it seems to\ndecrease other gaps. A hundred years ago, the rich led a different\nkind of life from ordinary people. They lived in houses\nfull of servants, wore elaborately uncomfortable clothes, and\ntravelled about in carriages drawn by teams of horses which themselves\nrequired their own houses and servants. Now, thanks to technology,\nthe rich live more like the average person.Cars are a good example of why. It's possible to buy expensive,\nhandmade cars that cost hundreds of thousands of dollars. But there\nis not much point. Companies make more money by building a large\nnumber of ordinary cars than a small number of expensive ones. So\na company making a mass-produced car can afford to spend a lot more\non its design. If you buy a custom-made car, something will always\nbe breaking. The only point of buying one now is to advertise that\nyou can.Or consider watches. Fifty years ago, by spending a lot of money\non a watch you could get better performance. When watches had\nmechanical movements, expensive watches kept better time. Not any\nmore. Since the invention of the quartz movement, an ordinary Timex\nis more accurate than a Patek Philippe costing hundreds of thousands\nof dollars.\n[13]\nIndeed, as with expensive cars, if you're determined\nto spend a lot of money on a watch, you have to put up with some\ninconvenience to do it: as well as keeping worse time, mechanical\nwatches have to be wound.The only thing technology can't cheapen is brand. Which is precisely\nwhy we hear ever more about it. Brand is the residue left as the\nsubstantive differences between rich and poor evaporate. But what\nlabel you have on your stuff is a much smaller matter than having\nit versus not having it. In 1900, if you kept a carriage, no one\nasked what year or brand it was. If you had one, you were rich.\nAnd if you weren't rich, you took the omnibus or walked. Now even\nthe poorest Americans drive cars, and it is only because we're so\nwell trained by advertising that we can even recognize the especially\nexpensive ones.\n[14]The same pattern has played out in industry after industry. If\nthere is enough demand for something, technology will make it cheap\nenough to sell in large volumes, and the mass-produced versions\nwill be, if not better, at least more convenient.\n[15]\nAnd there\nis nothing the rich like more than convenience. The rich people I\nknow drive the same cars, wear the same clothes, have the same kind\nof furniture, and eat the same foods as my other friends. Their\nhouses are in different neighborhoods, or if in the same neighborhood\nare different sizes, but within them life is similar. The houses\nare made using the same construction techniques and contain much\nthe same objects. It's inconvenient to do something expensive and\ncustom.The rich spend their time more like everyone else too. Bertie\nWooster seems long gone. Now, most people who are rich enough not\nto work do anyway. It's not just social pressure that makes them;\nidleness is lonely and demoralizing.Nor do we have the social distinctions there were a hundred years\nago. The novels and etiquette manuals of that period read now\nlike descriptions of some strange tribal society. \"With respect\nto the continuance of friendships...\" hints Mrs. Beeton's Book\nof Household Management (1880), \"it may be found necessary, in\nsome cases, for a mistress to relinquish, on assuming the responsibility\nof a household, many of those commenced in the earlier part of her\nlife.\" A woman who married a rich man was expected to drop friends\nwho didn't. You'd seem a barbarian if you behaved that way today.\nYou'd also have a very boring life. People still tend to segregate\nthemselves somewhat, but much more on the basis of education than\nwealth.\n[16]Materially and socially, technology seems to be decreasing the gap\nbetween the rich and the poor, not increasing it. If Lenin walked\naround the offices of a company like Yahoo or Intel or Cisco, he'd\nthink communism had won. Everyone would be wearing the same clothes,\nhave the same kind of office (or rather, cubicle) with the same\nfurnishings, and address one another by their first names instead\nof by honorifics. Everything would seem exactly as he'd predicted,\nuntil he looked at their bank accounts. Oops.Is it a problem if technology increases that gap? It doesn't seem\nto be so far. As it increases the gap in income, it seems to\ndecrease most other gaps.Alternative to an AxiomOne often hears a policy criticized on the grounds that it would\nincrease the income gap between rich and poor. As if it were an\naxiom that this would be bad. It might be true that increased\nvariation in income would be bad, but I don't see how we can say\nit's axiomatic.Indeed, it may even be false, in industrial democracies. In a\nsociety of serfs and warlords, certainly, variation in income is a\nsign of an underlying problem. But serfdom is not the only cause\nof variation in income. A 747 pilot doesn't make 40 times as much\nas a checkout clerk because he is a warlord who somehow holds her\nin thrall. His skills are simply much more valuable.I'd like to propose an alternative idea: that in a modern society,\nincreasing variation in income is a sign of health. Technology\nseems to increase the variation in productivity at faster than\nlinear rates. If we don't see corresponding variation in income,\nthere are three possible explanations: (a) that technical innovation\nhas stopped, (b) that the people who would create the most wealth\naren't doing it, or (c) that they aren't getting paid for it.I think we can safely say that (a) and (b) would be bad. If you\ndisagree, try living for a year using only the resources available\nto the average Frankish nobleman in 800, and report back to us.\n(I'll be generous and not send you back to the stone age.)The only option, if you're going to have an increasingly prosperous\nsociety without increasing variation in income, seems to be (c),\nthat people will create a lot of wealth without being paid for it.\nThat Jobs and Wozniak, for example, will cheerfully work 20-hour\ndays to produce the Apple computer for a society that allows them,\nafter taxes, to keep just enough of their income to match what they\nwould have made working 9 to 5 at a big company.Will people create wealth if they can't get paid for it? Only if\nit's fun. People will write operating systems for free. But they\nwon't install them, or take support calls, or train customers to\nuse them. And at least 90% of the work that even the highest tech\ncompanies do is of this second, unedifying kind.All the unfun kinds of wealth creation slow dramatically in a society\nthat confiscates private fortunes. We can confirm this empirically.\nSuppose you hear a strange noise that you think may be due to a\nnearby fan. You turn the fan off, and the noise stops. You turn\nthe fan back on, and the noise starts again. Off, quiet. On,\nnoise. In the absence of other information, it would seem the noise\nis caused by the fan.At various times and places in history, whether you could accumulate\na fortune by creating wealth has been turned on and off. Northern\nItaly in 800, off (warlords would steal it). Northern Italy in\n1100, on. Central France in 1100, off (still feudal). England in\n1800, on. England in 1974, off (98% tax on investment income).\nUnited States in 1974, on. We've even had a twin study: West\nGermany, on; East Germany, off. In every case, the creation of\nwealth seems to appear and disappear like the noise of a fan as you\nswitch on and off the prospect of keeping it.There is some momentum involved. It probably takes at least a\ngeneration to turn people into East Germans (luckily for England).\nBut if it were merely a fan we were studying, without all the extra\nbaggage that comes from the controversial topic of wealth, no one\nwould have any doubt that the fan was causing the noise.If you suppress variations in income, whether by stealing private\nfortunes, as feudal rulers used to do, or by taxing them away, as\nsome modern governments have done, the result always seems to be\nthe same. Society as a whole ends up poorer.If I had a choice of living in a society where I was materially\nmuch better off than I am now, but was among the poorest, or in one\nwhere I was the richest, but much worse off than I am now, I'd take\nthe first option. If I had children, it would arguably be immoral\nnot to. It's absolute poverty you want to avoid, not relative\npoverty. If, as the evidence so far implies, you have to have one\nor the other in your society, take relative poverty.You need rich people in your society not so much because in spending\ntheir money they create jobs, but because of what they have to do\nto get rich. I'm not talking about the trickle-down effect\nhere. I'm not saying that if you let Henry Ford get rich, he'll\nhire you as a waiter at his next party. I'm saying that he'll make\nyou a tractor to replace your horse.Notes[1]\nPart of the reason this subject is so contentious is that some\nof those most vocal on the subject of wealth—university\nstudents, heirs, professors, politicians, and journalists—have\nthe least experience creating it. (This phenomenon will be familiar\nto anyone who has overheard conversations about sports in a bar.)Students are mostly still on the parental dole, and have not stopped\nto think about where that money comes from. Heirs will be on the\nparental dole for life. Professors and politicians live within\nsocialist eddies of the economy, at one remove from the creation\nof wealth, and are paid a flat rate regardless of how hard they\nwork. And journalists as part of their professional code segregate\nthemselves from the revenue-collecting half of the businesses they\nwork for (the ad sales department). Many of these people never\ncome face to face with the fact that the money they receive represents\nwealth—wealth that, except in the case of journalists, someone\nelse created earlier. They live in a world in which income is\ndoled out by a central authority according to some abstract notion\nof fairness (or randomly, in the case of heirs), rather than given\nby other people in return for something they wanted, so it may seem\nto them unfair that things don't work the same in the rest of the\neconomy.(Some professors do create a great deal of wealth for\nsociety. But the money they're paid isn't a quid pro quo.\nIt's more in the nature of an investment.)[2]\nWhen one reads about the origins of the Fabian Society, it\nsounds like something cooked up by the high-minded Edwardian\nchild-heroes of Edith Nesbit's The Wouldbegoods.[3]\nAccording to a study by the Corporate Library, the median total\ncompensation, including salary, bonus, stock grants, and the exercise\nof stock options, of S&P 500 CEOs in 2002 was $3.65 million.\nAccording to Sports Illustrated, the average NBA player's\nsalary during the 2002-03 season was $4.54 million, and the average\nmajor league baseball player's salary at the start of the 2003\nseason was $2.56 million. According to the Bureau of Labor\nStatistics, the mean annual wage in the US in 2002 was $35,560.[4]\nIn the early empire the price of an ordinary adult slave seems\nto have been about 2,000 sestertii (e.g. Horace, Sat. ii.7.43).\nA servant girl cost 600 (Martial vi.66), while Columella (iii.3.8)\nsays that a skilled vine-dresser was worth 8,000. A doctor, P.\nDecimus Eros Merula, paid 50,000 sestertii for his freedom (Dessau,\nInscriptiones 7812). Seneca (Ep. xxvii.7) reports\nthat one Calvisius Sabinus paid 100,000 sestertii apiece for slaves\nlearned in the Greek classics. Pliny (Hist. Nat. vii.39)\nsays that the highest price paid for a slave up to his time was\n700,000 sestertii, for the linguist (and presumably teacher) Daphnis,\nbut that this had since been exceeded by actors buying their own\nfreedom.Classical Athens saw a similar variation in prices. An ordinary\nlaborer was worth about 125 to 150 drachmae. Xenophon (Mem.\nii.5) mentions prices ranging from 50 to 6,000 drachmae (for the\nmanager of a silver mine).For more on the economics of ancient slavery see:Jones, A. H. M., \"Slavery in the Ancient World,\" Economic History\nReview, 2:9 (1956), 185-199, reprinted in Finley, M. I. (ed.),\nSlavery in Classical Antiquity, Heffer, 1964.[5]\nEratosthenes (276—195 BC) used shadow lengths in different\ncities to estimate the Earth's circumference. He was off by only\nabout 2%.[6]\nNo, and Windows, respectively.[7]\nOne of the biggest divergences between the Daddy Model and\nreality is the valuation of hard work. In the Daddy Model, hard\nwork is in itself deserving. In reality, wealth is measured by\nwhat one delivers, not how much effort it costs. If I paint someone's\nhouse, the owner shouldn't pay me extra for doing it with a toothbrush.It will seem to someone still implicitly operating on the Daddy\nModel that it is unfair when someone works hard and doesn't get\npaid much. To help clarify the matter, get rid of everyone else\nand put our worker on a desert island, hunting and gathering fruit.\nIf he's bad at it he'll work very hard and not end up with much\nfood. Is this unfair? Who is being unfair to him?[8]\nPart of the reason for the tenacity of the Daddy Model may be\nthe dual meaning of \"distribution.\" When economists talk about\n\"distribution of income,\" they mean statistical distribution. But\nwhen you use the phrase frequently, you can't help associating it\nwith the other sense of the word (as in e.g. \"distribution of alms\"),\nand thereby subconsciously seeing wealth as something that flows\nfrom some central tap. The word \"regressive\" as applied to tax\nrates has a similar effect, at least on me; how can anything\nregressive be good?[9]\n\"From the beginning of the reign Thomas Lord Roos was an assiduous\ncourtier of the young Henry VIII and was soon to reap the rewards.\nIn 1525 he was made a Knight of the Garter and given the Earldom\nof Rutland. In the thirties his support of the breach with Rome,\nhis zeal in crushing the Pilgrimage of Grace, and his readiness to\nvote the death-penalty in the succession of spectacular treason\ntrials that punctuated Henry's erratic matrimonial progress made\nhim an obvious candidate for grants of monastic property.\"Stone, Lawrence, Family and Fortune: Studies in Aristocratic\nFinance in the Sixteenth and Seventeenth Centuries, Oxford\nUniversity Press, 1973, p. 166.[10]\nThere is archaeological evidence for large settlements earlier,\nbut it's hard to say what was happening in them.Hodges, Richard and David Whitehouse, Mohammed, Charlemagne and\nthe Origins of Europe, Cornell University Press, 1983.[11]\nWilliam Cecil and his son Robert were each in turn the most\npowerful minister of the crown, and both used their position to\namass fortunes among the largest of their times. Robert in particular\ntook bribery to the point of treason. \"As Secretary of State and\nthe leading advisor to King James on foreign policy, [he] was a\nspecial recipient of favour, being offered large bribes by the Dutch\nnot to make peace with Spain, and large bribes by Spain to make\npeace.\" (Stone, op. cit., p. 17.)[12]\nThough Balzac made a lot of money from writing, he was notoriously\nimprovident and was troubled by debts all his life.[13]\nA Timex will gain or lose about .5 seconds per day. The most\naccurate mechanical watch, the Patek Philippe 10 Day Tourbillon,\nis rated at -1.5 to +2 seconds. Its retail price is about $220,000.[14]\nIf asked to choose which was more expensive, a well-preserved\n1989 Lincoln Town Car ten-passenger limousine ($5,000) or a 2004\nMercedes S600 sedan ($122,000), the average Edwardian might well\nguess wrong.[15]\nTo say anything meaningful about income trends, you have to\ntalk about real income, or income as measured in what it can buy.\nBut the usual way of calculating real income ignores much of the\ngrowth in wealth over time, because it depends on a consumer price\nindex created by bolting end to end a series of numbers that are\nonly locally accurate, and that don't include the prices of new\ninventions until they become so common that their prices stabilize.So while we might think it was very much better to live in a world\nwith antibiotics or air travel or an electric power grid than\nwithout, real income statistics calculated in the usual way will\nprove to us that we are only slightly richer for having these things.Another approach would be to ask, if you were going back to the\nyear x in a time machine, how much would you have to spend on trade\ngoods to make your fortune? For example, if you were going back\nto 1970 it would certainly be less than $500, because the processing\npower you can get for $500 today would have been worth at least\n$150 million in 1970. The function goes asymptotic fairly quickly,\nbecause for times over a hundred years or so you could get all you\nneeded in present-day trash. In 1800 an empty plastic drink bottle\nwith a screw top would have seemed a miracle of workmanship.[16]\nSome will say this amounts to the same thing, because the rich\nhave better opportunities for education. That's a valid point. It\nis still possible, to a degree, to buy your kids' way into top\ncolleges by sending them to private schools that in effect hack the\ncollege admissions process.According to a 2002 report by the National Center for Education\nStatistics, about 1.7% of American kids attend private, non-sectarian\nschools. At Princeton, 36% of the class of 2007 came from such\nschools. (Interestingly, the number at Harvard is significantly\nlower, about 28%.) Obviously this is a huge loophole. It does at\nleast seem to be closing, not widening.Perhaps the designers of admissions processes should take a lesson\nfrom the example of computer security, and instead of just assuming\nthat their system can't be hacked, measure the degree to which it\nis." }, { "path": "data/PaulGrahamEssaysLarge/gba.txt", "content": "April 2004To the popular press, \"hacker\" means someone who breaks\ninto computers. Among programmers it means a good programmer.\nBut the two meanings are connected. To programmers,\n\"hacker\" connotes mastery in the most literal sense: someone\nwho can make a computer do what he wants—whether the computer\nwants to or not.To add to the confusion, the noun \"hack\" also has two senses. It can\nbe either a compliment or an insult. It's called a hack when\nyou do something in an ugly way. But when you do something\nso clever that you somehow beat the system, that's also\ncalled a hack. The word is used more often in the former than\nthe latter sense, probably because ugly solutions are more\ncommon than brilliant ones.Believe it or not, the two senses of \"hack\" are also\nconnected. Ugly and imaginative solutions have something in\ncommon: they both break the rules. And there is a gradual\ncontinuum between rule breaking that's merely ugly (using\nduct tape to attach something to your bike) and rule breaking\nthat is brilliantly imaginative (discarding Euclidean space).Hacking predates computers. When he\nwas working on the Manhattan Project, Richard Feynman used to\namuse himself by breaking into safes containing secret documents.\nThis tradition continues today.\nWhen we were in grad school, a hacker friend of mine who spent too much\ntime around MIT had\nhis own lock picking kit.\n(He now runs a hedge fund, a not unrelated enterprise.)It is sometimes hard to explain to authorities why one would\nwant to do such things.\nAnother friend of mine once got in trouble with the government for\nbreaking into computers. This had only recently been declared\na crime, and the FBI found that their usual investigative\ntechnique didn't work. Police investigation apparently begins with\na motive. The usual motives are few: drugs, money, sex,\nrevenge. Intellectual curiosity was not one of the motives on\nthe FBI's list. Indeed, the whole concept seemed foreign to\nthem.Those in authority tend to be annoyed by hackers'\ngeneral attitude of disobedience. But that disobedience is\na byproduct of the qualities that make them good programmers.\nThey may laugh at the CEO when he talks in generic corporate\nnewspeech, but they also laugh at someone who tells them\na certain problem can't be solved.\nSuppress one, and you suppress the other.This attitude is sometimes affected. Sometimes young programmers\nnotice the eccentricities of eminent hackers and decide to\nadopt some of their own in order to seem smarter.\nThe fake version is not merely\nannoying; the prickly attitude of these posers\ncan actually slow the process of innovation.But even factoring in their annoying eccentricities,\nthe disobedient attitude of hackers is a net win. I wish its\nadvantages were better understood.For example, I suspect people in Hollywood are\nsimply mystified by\nhackers' attitudes toward copyrights. They are a perennial\ntopic of heated discussion on Slashdot.\nBut why should people who program computers\nbe so concerned about copyrights, of all things?Partly because some companies use mechanisms to prevent\ncopying. Show any hacker a lock and his first thought is\nhow to pick it. But there is a deeper reason that\nhackers are alarmed by measures like copyrights and patents.\nThey see increasingly aggressive measures to protect\n\"intellectual property\"\nas a threat to the intellectual\nfreedom they need to do their job.\nAnd they are right.It is by poking about inside current technology that\nhackers get ideas for the next generation. No thanks,\nintellectual homeowners may say, we don't need any\noutside help. But they're wrong.\nThe next generation of computer technology has\noften—perhaps more often than not—been developed by outsiders.In 1977 there was no doubt some group within IBM developing\nwhat they expected to be\nthe next generation of business computer. They were mistaken.\nThe next generation of business computer was\nbeing developed on entirely different lines by two long-haired\nguys called Steve in a garage in Los Altos. At about the\nsame time, the powers that be\nwere cooperating to develop the\nofficial next generation operating system, Multics.\nBut two guys who thought Multics excessively complex went off\nand wrote their own. They gave it a name that\nwas a joking reference to Multics: Unix.The latest intellectual property laws impose\nunprecedented restrictions on the sort of poking around that\nleads to new ideas. In the past, a competitor might use patents\nto prevent you from selling a copy of something they\nmade, but they couldn't prevent you from\ntaking one apart to see how it worked. The latest\nlaws make this a crime. How are we\nto develop new technology if we can't study current\ntechnology to figure out how to improve it?Ironically, hackers have brought this on themselves.\nComputers are responsible for the problem. The control systems\ninside machines used to be physical: gears and levers and cams.\nIncreasingly, the brains (and thus the value) of products is\nin software. And by this I mean software in the general sense:\ni.e. data. A song on an LP is physically stamped into the\nplastic. A song on an iPod's disk is merely stored on it.Data is by definition easy to copy. And the Internet\nmakes copies easy to distribute. So it is no wonder\ncompanies are afraid. But, as so often happens, fear has\nclouded their judgement. The government has responded\nwith draconian laws to protect intellectual property.\nThey probably mean well. But\nthey may not realize that such laws will do more harm\nthan good.Why are programmers so violently opposed to these laws?\nIf I were a legislator, I'd be interested in this\nmystery—for the same reason that, if I were a farmer and suddenly\nheard a lot of squawking coming from my hen house one night,\nI'd want to go out and investigate. Hackers are not stupid,\nand unanimity is very rare in this world.\nSo if they're all squawking, \nperhaps there is something amiss.Could it be that such laws, though intended to protect America,\nwill actually harm it? Think about it. There is something\nvery American about Feynman breaking into safes during\nthe Manhattan Project. It's hard to imagine the authorities\nhaving a sense of humor about such things over\nin Germany at that time. Maybe it's not a coincidence.Hackers are unruly. That is the essence of hacking. And it\nis also the essence of Americanness. It is no accident\nthat Silicon Valley\nis in America, and not France, or Germany,\nor England, or Japan. In those countries, people color inside\nthe lines.I lived for a while in Florence. But after I'd been there\na few months I realized that what I'd been unconsciously hoping\nto find there was back in the place I'd just left.\nThe reason Florence is famous is that in 1450, it was New York.\nIn 1450 it was filled with the kind of turbulent and ambitious\npeople you find now in America. (So I went back to America.)It is greatly to America's advantage that it is\na congenial atmosphere for the right sort of unruliness—that\nit is a home not just for the smart, but for smart-alecks.\nAnd hackers are invariably smart-alecks. If we had a national\nholiday, it would be April 1st. It says a great deal about\nour work that we use the same word for a brilliant or a\nhorribly cheesy solution. When we cook one up we're not\nalways 100% sure which kind it is. But as long as it has\nthe right sort of wrongness, that's a promising sign.\nIt's odd that people\nthink of programming as precise and methodical. Computers\nare precise and methodical. Hacking is something you do\nwith a gleeful laugh.In our world some of the most characteristic solutions\nare not far removed from practical\njokes. IBM was no doubt rather surprised by the consequences\nof the licensing deal for DOS, just as the hypothetical\n\"adversary\" must be when Michael Rabin solves a problem by\nredefining it as one that's easier to solve.Smart-alecks have to develop a keen sense of how much they\ncan get away with. And lately hackers \nhave sensed a change\nin the atmosphere.\nLately hackerliness seems rather frowned upon.To hackers the recent contraction in civil liberties seems\nespecially ominous. That must also mystify outsiders. \nWhy should we care especially about civil\nliberties? Why programmers, more than\ndentists or salesmen or landscapers?Let me put the case in terms a government official would appreciate.\nCivil liberties are not just an ornament, or a quaint\nAmerican tradition. Civil liberties make countries rich.\nIf you made a graph of\nGNP per capita vs. civil liberties, you'd notice a definite\ntrend. Could civil liberties really be a cause, rather\nthan just an effect? I think so. I think a society in which\npeople can do and say what they want will also tend to\nbe one in which the most efficient solutions win, rather than\nthose sponsored by the most influential people.\nAuthoritarian countries become corrupt;\ncorrupt countries become poor; and poor countries are weak. \nIt seems to me there is\na Laffer curve for government power, just as for\ntax revenues. At least, it seems likely enough that it\nwould be stupid to try the experiment and find out. Unlike\nhigh tax rates, you can't repeal totalitarianism if it\nturns out to be a mistake.This is why hackers worry. The government spying on people doesn't\nliterally make programmers write worse code. It just leads\neventually to a world in which bad ideas win. And because\nthis is so important to hackers, they're especially sensitive\nto it. They can sense totalitarianism approaching from a\ndistance, as animals can sense an approaching \nthunderstorm.It would be ironic if, as hackers fear, recent measures\nintended to protect national security and intellectual property\nturned out to be a missile aimed right at what makes \nAmerica successful. But it would not be the first time that\nmeasures taken in an atmosphere of panic had\nthe opposite of the intended effect.There is such a thing as Americanness.\nThere's nothing like living abroad to teach you that. \nAnd if you want to know whether something will nurture or squash\nthis quality, it would be hard to find a better focus\ngroup than hackers, because they come closest of any group\nI know to embodying it. Closer, probably, than\nthe men running our government,\nwho for all their talk of patriotism\nremind me more of Richelieu or Mazarin\nthan Thomas Jefferson or George Washington.When you read what the founding fathers had to say for\nthemselves, they sound more like hackers.\n\"The spirit of resistance to government,\"\nJefferson wrote, \"is so valuable on certain occasions, that I wish\nit always to be kept alive.\"Imagine an American president saying that today.\nLike the remarks of an outspoken old grandmother, the sayings of\nthe founding fathers have embarrassed generations of\ntheir less confident successors. They remind us where we come from.\nThey remind us that it is the people who break rules that are\nthe source of America's wealth and power.Those in a position to impose rules naturally want them to be\nobeyed. But be careful what you ask for. You might get it.Thanks to Ken Anderson, Trevor Blackwell, Daniel Giffin, \nSarah Harlin, Shiro Kawai, Jessica Livingston, Matz, \nJackie McDonough, Robert Morris, Eric Raymond, Guido van Rossum,\nDavid Weinberger, and\nSteven Wolfram for reading drafts of this essay.\n(The image shows Steves Jobs and Wozniak \nwith a \"blue box.\"\nPhoto by Margret Wozniak. Reproduced by permission of Steve\nWozniak.)" }, { "path": "data/PaulGrahamEssaysLarge/gh.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nJuly 2004(This essay is derived from a talk at Oscon 2004.)\nA few months ago I finished a new \nbook, \nand in reviews I keep\nnoticing words like \"provocative'' and \"controversial.'' To say\nnothing of \"idiotic.''I didn't mean to make the book controversial. I was trying to make\nit efficient. I didn't want to waste people's time telling them\nthings they already knew. It's more efficient just to give them\nthe diffs. But I suppose that's bound to yield an alarming book.EdisonsThere's no controversy about which idea is most controversial:\nthe suggestion that variation in wealth might not be as big a\nproblem as we think.I didn't say in the book that variation in wealth was in itself a\ngood thing. I said in some situations it might be a sign of good\nthings. A throbbing headache is not a good thing, but it can be\na sign of a good thing-- for example, that you're recovering\nconsciousness after being hit on the head.Variation in wealth can be a sign of variation in productivity.\n(In a society of one, they're identical.) And that\nis almost certainly a good thing: if your society has no variation\nin productivity, it's probably not because everyone is Thomas\nEdison. It's probably because you have no Thomas Edisons.In a low-tech society you don't see much variation in productivity.\nIf you have a tribe of nomads collecting sticks for a fire, how\nmuch more productive is the best stick gatherer going to be than\nthe worst? A factor of two? Whereas when you hand people a complex tool\nlike a computer, the variation in what they can do with\nit is enormous.That's not a new idea. Fred Brooks wrote about it in 1974, and\nthe study he quoted was published in 1968. But I think he\nunderestimated the variation between programmers. He wrote about productivity in lines\nof code: the best programmers can solve a given problem in a tenth\nthe time. But what if the problem isn't given? In programming, as\nin many fields, the hard part isn't solving problems, but deciding\nwhat problems to solve. Imagination is hard to measure, but\nin practice it dominates the kind of productivity that's measured\nin lines of code.Productivity varies in any field, but there are few in which it\nvaries so much. The variation between programmers\nis so great that it becomes a difference in kind. I don't\nthink this is something intrinsic to programming, though. In every field,\ntechnology magnifies differences in productivity. I think what's\nhappening in programming is just that we have a lot of technological\nleverage. But in every field the lever is getting longer, so the\nvariation we see is something that more and more fields will see\nas time goes on. And the success of companies, and countries, will\ndepend increasingly on how they deal with it.If variation in productivity increases with technology, then the\ncontribution of the most productive individuals will not only be\ndisproportionately large, but will actually grow with time. When\nyou reach the point where 90% of a group's output is created by 1%\nof its members, you lose big if something (whether Viking raids,\nor central planning) drags their productivity down to the average.If we want to get the most out of them, we need to understand these\nespecially productive people. What motivates them? What do they\nneed to do their jobs? How do you recognize them? How do you\nget them to come and work for you? And then of course there's the\nquestion, how do you become one?More than MoneyI know a handful of super-hackers, so I sat down and thought about\nwhat they have in common. Their defining quality is probably that\nthey really love to program. Ordinary programmers write code to pay\nthe bills. Great hackers think of it as something they do for fun,\nand which they're delighted to find people will pay them for.Great programmers are sometimes said to be indifferent to money.\nThis isn't quite true. It is true that all they really care about\nis doing interesting work. But if you make enough money, you get\nto work on whatever you want, and for that reason hackers are\nattracted by the idea of making really large amounts of money.\nBut as long as they still have to show up for work every day, they\ncare more about what they do there than how much they get paid for\nit.Economically, this is a fact of the greatest importance, because\nit means you don't have to pay great hackers anything like what\nthey're worth. A great programmer might be ten or a hundred times\nas productive as an ordinary one, but he'll consider himself lucky\nto get paid three times as much. As I'll explain later, this is\npartly because great hackers don't know how good they are. But\nit's also because money is not the main thing they want.What do hackers want? Like all craftsmen, hackers like good tools.\nIn fact, that's an understatement. Good hackers find it unbearable\nto use bad tools. They'll simply refuse to work on projects with\nthe wrong infrastructure.At a startup I once worked for, one of the things pinned up on our\nbulletin board was an ad from IBM. It was a picture of an AS400,\nand the headline read, I think, \"hackers despise\nit.'' [1]When you decide what infrastructure to use for a project, you're\nnot just making a technical decision. You're also making a social\ndecision, and this may be the more important of the two. For\nexample, if your company wants to write some software, it might\nseem a prudent choice to write it in Java. But when you choose a\nlanguage, you're also choosing a community. The programmers you'll\nbe able to hire to work on a Java project won't be as\nsmart as the\nones you could get to work on a project written in Python.\nAnd the quality of your hackers probably matters more than the\nlanguage you choose. Though, frankly, the fact that good hackers\nprefer Python to Java should tell you something about the relative\nmerits of those languages.Business types prefer the most popular languages because they view\nlanguages as standards. They don't want to bet the company on\nBetamax. The thing about languages, though, is that they're not\njust standards. If you have to move bits over a network, by all\nmeans use TCP/IP. But a programming language isn't just a format.\nA programming language is a medium of expression.I've read that Java has just overtaken Cobol as the most popular\nlanguage. As a standard, you couldn't wish for more. But as a\nmedium of expression, you could do a lot better. Of all the great\nprogrammers I can think of, I know of only one who would voluntarily\nprogram in Java. And of all the great programmers I can think of\nwho don't work for Sun, on Java, I know of zero.Great hackers also generally insist on using open source software.\nNot just because it's better, but because it gives them more control.\nGood hackers insist on control. This is part of what makes them\ngood hackers: when something's broken, they need to fix it. You\nwant them to feel this way about the software they're writing for\nyou. You shouldn't be surprised when they feel the same way about\nthe operating system.A couple years ago a venture capitalist friend told me about a new\nstartup he was involved with. It sounded promising. But the next\ntime I talked to him, he said they'd decided to build their software\non Windows NT, and had just hired a very experienced NT developer\nto be their chief technical officer. When I heard this, I thought,\nthese guys are doomed. One, the CTO couldn't be a first rate\nhacker, because to become an eminent NT developer he would have\nhad to use NT voluntarily, multiple times, and I couldn't imagine\na great hacker doing that; and two, even if he was good, he'd have\na hard time hiring anyone good to work for him if the project had\nto be built on NT. [2]The Final FrontierAfter software, the most important tool to a hacker is probably\nhis office. Big companies think the function of office space is to express\nrank. But hackers use their offices for more than that: they\nuse their office as a place to think in. And if you're a technology\ncompany, their thoughts are your product. So making hackers work\nin a noisy, distracting environment is like having a paint factory\nwhere the air is full of soot.The cartoon strip Dilbert has a lot to say about cubicles, and with\ngood reason. All the hackers I know despise them. The mere prospect\nof being interrupted is enough to prevent hackers from working on\nhard problems. If you want to get real work done in an office with\ncubicles, you have two options: work at home, or come in early or\nlate or on a weekend, when no one else is there. Don't companies\nrealize this is a sign that something is broken? An office\nenvironment is supposed to be something that helps\nyou work, not something you work despite.Companies like Cisco are proud that everyone there has a cubicle,\neven the CEO. But they're not so advanced as they think; obviously\nthey still view office space as a badge of rank. Note too that\nCisco is famous for doing very little product development in house.\nThey get new technology by buying the startups that created it-- where\npresumably the hackers did have somewhere quiet to work.One big company that understands what hackers need is Microsoft.\nI once saw a recruiting ad for Microsoft with a big picture of a\ndoor. Work for us, the premise was, and we'll give you a place to\nwork where you can actually get work done. And you know, Microsoft\nis remarkable among big companies in that they are able to develop\nsoftware in house. Not well, perhaps, but well enough.If companies want hackers to be productive, they should look at\nwhat they do at home. At home, hackers can arrange things themselves\nso they can get the most done. And when they work at home, hackers\ndon't work in noisy, open spaces; they work in rooms with doors. They\nwork in cosy, neighborhoody places with people around and somewhere\nto walk when they need to mull something over, instead of in glass\nboxes set in acres of parking lots. They have a sofa they can take\na nap on when they feel tired, instead of sitting in a coma at\ntheir desk, pretending to work. There's no crew of people with\nvacuum cleaners that roars through every evening during the prime\nhacking hours. There are no meetings or, God forbid, corporate\nretreats or team-building exercises. And when you look at what\nthey're doing on that computer, you'll find it reinforces what I\nsaid earlier about tools. They may have to use Java and Windows\nat work, but at home, where they can choose for themselves, you're\nmore likely to find them using Perl and Linux.Indeed, these statistics about Cobol or Java being the most popular\nlanguage can be misleading. What we ought to look at, if we want\nto know what tools are best, is what hackers choose when they can\nchoose freely-- that is, in projects of their own. When you ask\nthat question, you find that open source operating systems already\nhave a dominant market share, and the number one language is probably\nPerl.InterestingAlong with good tools, hackers want interesting projects. What\nmakes a project interesting? Well, obviously overtly sexy\napplications like stealth planes or special effects software would\nbe interesting to work on. But any application can be interesting\nif it poses novel technical challenges. So it's hard to predict\nwhich problems hackers will like, because some become\ninteresting only when the people working on them discover a new\nkind of solution. Before ITA\n(who wrote the software inside Orbitz),\nthe people working on airline fare searches probably thought it\nwas one of the most boring applications imaginable. But ITA made\nit interesting by \nredefining the problem in a more ambitious way.I think the same thing happened at Google. When Google was founded,\nthe conventional wisdom among the so-called portals was that search\nwas boring and unimportant. But the guys at Google didn't think\nsearch was boring, and that's why they do it so well.This is an area where managers can make a difference. Like a parent\nsaying to a child, I bet you can't clean up your whole room in\nten minutes, a good manager can sometimes redefine a problem as a\nmore interesting one. Steve Jobs seems to be particularly good at\nthis, in part simply by having high standards. There were a lot\nof small, inexpensive computers before the Mac. He redefined the\nproblem as: make one that's beautiful. And that probably drove\nthe developers harder than any carrot or stick could.They certainly delivered. When the Mac first appeared, you didn't\neven have to turn it on to know it would be good; you could tell\nfrom the case. A few weeks ago I was walking along the street in\nCambridge, and in someone's trash I saw what appeared to be a Mac\ncarrying case. I looked inside, and there was a Mac SE. I carried\nit home and plugged it in, and it booted. The happy Macintosh\nface, and then the finder. My God, it was so simple. It was just\nlike ... Google.Hackers like to work for people with high standards. But it's not\nenough just to be exacting. You have to insist on the right things.\nWhich usually means that you have to be a hacker yourself. I've\nseen occasional articles about how to manage programmers. Really\nthere should be two articles: one about what to do if\nyou are yourself a programmer, and one about what to do if you're not. And the \nsecond could probably be condensed into two words: give up.The problem is not so much the day to day management. Really good\nhackers are practically self-managing. The problem is, if you're\nnot a hacker, you can't tell who the good hackers are. A similar\nproblem explains why American cars are so ugly. I call it the\ndesign paradox. You might think that you could make your products\nbeautiful just by hiring a great designer to design them. But if\nyou yourself don't have good taste, \nhow are you going to recognize\na good designer? By definition you can't tell from his portfolio.\nAnd you can't go by the awards he's won or the jobs he's had,\nbecause in design, as in most fields, those tend to be driven by\nfashion and schmoozing, with actual ability a distant third.\nThere's no way around it: you can't manage a process intended to\nproduce beautiful things without knowing what beautiful is. American\ncars are ugly because American car companies are run by people with\nbad taste.Many people in this country think of taste as something elusive,\nor even frivolous. It is neither. To drive design, a manager must\nbe the most demanding user of a company's products. And if you\nhave really good taste, you can, as Steve Jobs does, make satisfying\nyou the kind of problem that good people like to work on.Nasty Little ProblemsIt's pretty easy to say what kinds of problems are not interesting:\nthose where instead of solving a few big, clear, problems, you have\nto solve a lot of nasty little ones. One of the worst kinds of\nprojects is writing an interface to a piece of software that's\nfull of bugs. Another is when you have to customize\nsomething for an individual client's complex and ill-defined needs.\nTo hackers these kinds of projects are the death of a thousand\ncuts.The distinguishing feature of nasty little problems is that you\ndon't learn anything from them. Writing a compiler is interesting\nbecause it teaches you what a compiler is. But writing an interface\nto a buggy piece of software doesn't teach you anything, because the\nbugs are random. [3] So it's not just fastidiousness that makes good\nhackers avoid nasty little problems. It's more a question of\nself-preservation. Working on nasty little problems makes you\nstupid. Good hackers avoid it for the same reason models avoid\ncheeseburgers.Of course some problems inherently have this character. And because\nof supply and demand, they pay especially well. So a company that\nfound a way to get great hackers to work on tedious problems would\nbe very successful. How would you do it?One place this happens is in startups. At our startup we had \nRobert Morris working as a system administrator. That's like having the\nRolling Stones play at a bar mitzvah. You can't hire that kind of\ntalent. But people will do any amount of drudgery for companies\nof which they're the founders. [4]Bigger companies solve the problem by partitioning the company.\nThey get smart people to work for them by establishing a separate\nR&D department where employees don't have to work directly on\ncustomers' nasty little problems. [5] In this model, the research\ndepartment functions like a mine. They produce new ideas; maybe\nthe rest of the company will be able to use them.You may not have to go to this extreme. \nBottom-up programming\nsuggests another way to partition the company: have the smart people\nwork as toolmakers. If your company makes software to do x, have\none group that builds tools for writing software of that type, and\nanother that uses these tools to write the applications. This way\nyou might be able to get smart people to write 99% of your code,\nbut still keep them almost as insulated from users as they would\nbe in a traditional research department. The toolmakers would have\nusers, but they'd only be the company's own developers. [6]If Microsoft used this approach, their software wouldn't be so full\nof security holes, because the less smart people writing the actual\napplications wouldn't be doing low-level stuff like allocating\nmemory. Instead of writing Word directly in C, they'd be plugging\ntogether big Lego blocks of Word-language. (Duplo, I believe, is\nthe technical term.)ClumpingAlong with interesting problems, what good hackers like is other\ngood hackers. Great hackers tend to clump together-- sometimes\nspectacularly so, as at Xerox Parc. So you won't attract good\nhackers in linear proportion to how good an environment you create\nfor them. The tendency to clump means it's more like the square\nof the environment. So it's winner take all. At any given time,\nthere are only about ten or twenty places where hackers most want to\nwork, and if you aren't one of them, you won't just have fewer\ngreat hackers, you'll have zero.Having great hackers is not, by itself, enough to make a company\nsuccessful. It works well for Google and ITA, which are two of\nthe hot spots right now, but it didn't help Thinking Machines or\nXerox. Sun had a good run for a while, but their business model\nis a down elevator. In that situation, even the best hackers can't\nsave you.I think, though, that all other things being equal, a company that\ncan attract great hackers will have a huge advantage. There are\npeople who would disagree with this. When we were making the rounds\nof venture capital firms in the 1990s, several told us that software\ncompanies didn't win by writing great software, but through brand,\nand dominating channels, and doing the right deals.They really seemed to believe this, and I think I know why. I\nthink what a lot of VCs are looking for, at least unconsciously,\nis the next Microsoft. And of course if Microsoft is your model,\nyou shouldn't be looking for companies that hope to win by writing\ngreat software. But VCs are mistaken to look for the next Microsoft,\nbecause no startup can be the next Microsoft unless some other\ncompany is prepared to bend over at just the right moment and be\nthe next IBM.It's a mistake to use Microsoft as a model, because their whole\nculture derives from that one lucky break. Microsoft is a bad data\npoint. If you throw them out, you find that good products do tend\nto win in the market. What VCs should be looking for is the next\nApple, or the next Google.I think Bill Gates knows this. What worries him about Google is\nnot the power of their brand, but the fact that they have\nbetter hackers. [7]\nRecognitionSo who are the great hackers? How do you know when you meet one?\nThat turns out to be very hard. Even hackers can't tell. I'm\npretty sure now that my friend Trevor Blackwell is a great hacker.\nYou may have read on Slashdot how he made his \nown Segway. The\nremarkable thing about this project was that he wrote all the\nsoftware in one day (in Python, incidentally).For Trevor, that's\npar for the course. But when I first met him, I thought he was a\ncomplete idiot. He was standing in Robert Morris's office babbling\nat him about something or other, and I remember standing behind\nhim making frantic gestures at Robert to shoo this nut out of his\noffice so we could go to lunch. Robert says he misjudged Trevor\nat first too. Apparently when Robert first met him, Trevor had\njust begun a new scheme that involved writing down everything about\nevery aspect of his life on a stack of index cards, which he carried\nwith him everywhere. He'd also just arrived from Canada, and had\na strong Canadian accent and a mullet.The problem is compounded by the fact that hackers, despite their\nreputation for social obliviousness, sometimes put a good deal of\neffort into seeming smart. When I was in grad school I used to\nhang around the MIT AI Lab occasionally. It was kind of intimidating\nat first. Everyone there spoke so fast. But after a while I\nlearned the trick of speaking fast. You don't have to think any\nfaster; just use twice as many words to say everything. With this amount of noise in the signal, it's hard to tell good\nhackers when you meet them. I can't tell, even now. You also\ncan't tell from their resumes. It seems like the only way to judge\na hacker is to work with him on something.And this is the reason that high-tech areas \nonly happen around universities. The active ingredient\nhere is not so much the professors as the students. Startups grow up\naround universities because universities bring together promising young\npeople and make them work on the same projects. The\nsmart ones learn who the other smart ones are, and together\nthey cook up new projects of their own.Because you can't tell a great hacker except by working with him,\nhackers themselves can't tell how good they are. This is true to\na degree in most fields. I've found that people who\nare great at something are not so much convinced of their own\ngreatness as mystified at why everyone else seems so incompetent.\nBut it's particularly hard for hackers to know how good they are,\nbecause it's hard to compare their work. This is easier in most\nother fields. In the hundred meters, you know in 10 seconds who's\nfastest. Even in math there seems to be a general consensus about\nwhich problems are hard to solve, and what constitutes a good\nsolution. But hacking is like writing. Who can say which of two\nnovels is better? Certainly not the authors.With hackers, at least, other hackers can tell. That's because,\nunlike novelists, hackers collaborate on projects. When you get\nto hit a few difficult problems over the net at someone, you learn\npretty quickly how hard they hit them back. But hackers can't\nwatch themselves at work. So if you ask a great hacker how good\nhe is, he's almost certain to reply, I don't know. He's not just\nbeing modest. He really doesn't know.And none of us know, except about people we've actually worked\nwith. Which puts us in a weird situation: we don't know who our\nheroes should be. The hackers who become famous tend to become\nfamous by random accidents of PR. Occasionally I need to give an\nexample of a great hacker, and I never know who to use. The first\nnames that come to mind always tend to be people I know personally,\nbut it seems lame to use them. So, I think, maybe I should say\nRichard Stallman, or Linus Torvalds, or Alan Kay, or someone famous\nlike that. But I have no idea if these guys are great hackers.\nI've never worked with them on anything.If there is a Michael Jordan of hacking, no one knows, including\nhim.CultivationFinally, the question the hackers have all been wondering about:\nhow do you become a great hacker? I don't know if it's possible\nto make yourself into one. But it's certainly possible to do things\nthat make you stupid, and if you can make yourself stupid, you\ncan probably make yourself smart too.The key to being a good hacker may be to work on what you like.\nWhen I think about the great hackers I know, one thing they have\nin common is the extreme \ndifficulty of making them work \non anything they\ndon't want to. I don't know if this is cause or effect; it may be\nboth.To do something well you have to love it. \nSo to the extent you\ncan preserve hacking as something you love, you're likely to do it\nwell. Try to keep the sense of wonder you had about programming at\nage 14. If you're worried that your current job is rotting your\nbrain, it probably is.The best hackers tend to be smart, of course, but that's true in\na lot of fields. Is there some quality that's unique to hackers?\nI asked some friends, and the number one thing they mentioned was\ncuriosity. \nI'd always supposed that all smart people were curious--\nthat curiosity was simply the first derivative of knowledge. But\napparently hackers are particularly curious, especially about how\nthings work. That makes sense, because programs are in effect\ngiant descriptions of how things work.Several friends mentioned hackers' ability to concentrate-- their\nability, as one put it, to \"tune out everything outside their own\nheads.'' I've certainly noticed this. And I've heard several \nhackers say that after drinking even half a beer they can't program at\nall. So maybe hacking does require some special ability to focus.\nPerhaps great hackers can load a large amount of context into their\nhead, so that when they look at a line of code, they see not just\nthat line but the whole program around it. John McPhee\nwrote that Bill Bradley's success as a basketball player was due\npartly to his extraordinary peripheral vision. \"Perfect'' eyesight\nmeans about 47 degrees of vertical peripheral vision. Bill Bradley\nhad 70; he could see the basket when he was looking at the floor.\nMaybe great hackers have some similar inborn ability. (I cheat by\nusing a very dense language, \nwhich shrinks the court.)This could explain the disconnect over cubicles. Maybe the people\nin charge of facilities, not having any concentration to shatter,\nhave no idea that working in a cubicle feels to a hacker like having\none's brain in a blender. (Whereas Bill, if the rumors of autism\nare true, knows all too well.)One difference I've noticed between great hackers and smart people\nin general is that hackers are more \npolitically incorrect. To the\nextent there is a secret handshake among good hackers, it's when they\nknow one another well enough to express opinions that would get\nthem stoned to death by the general public. And I can see why\npolitical incorrectness would be a useful quality in programming.\nPrograms are very complex and, at least in the hands of good\nprogrammers, very fluid. In such situations it's helpful to have\na habit of questioning assumptions.Can you cultivate these qualities? I don't know. But you can at\nleast not repress them. So here is my best shot at a recipe. If\nit is possible to make yourself into a great hacker, the way to do\nit may be to make the following deal with yourself: you never have\nto work on boring projects (unless your family will starve otherwise),\nand in return, you'll never allow yourself to do a half-assed job.\nAll the great hackers I know seem to have made that deal, though\nperhaps none of them had any choice in the matter.Notes\n[1] In fairness, I have to say that IBM makes decent hardware. I\nwrote this on an IBM laptop.[2] They did turn out to be doomed. They shut down a few months\nlater.[3] I think this is what people mean when they talk\nabout the \"meaning of life.\" On the face of it, this seems an \nodd idea. Life isn't an expression; how could it have meaning?\nBut it can have a quality that feels a lot like meaning. In a project\nlike a compiler, you have to solve a lot of problems, but the problems\nall fall into a pattern, as in a signal. Whereas when the problems\nyou have to solve are random, they seem like noise.\n[4] Einstein at one point worked designing refrigerators. (He had equity.)[5] It's hard to say exactly what constitutes research in the\ncomputer world, but as a first approximation, it's software that\ndoesn't have users.I don't think it's publication that makes the best hackers want to work\nin research departments. I think it's mainly not having to have a\nthree hour meeting with a product manager about problems integrating\nthe Korean version of Word 13.27 with the talking paperclip.[6] Something similar has been happening for a long time in the\nconstruction industry. When you had a house built a couple hundred\nyears ago, the local builders built everything in it. But increasingly\nwhat builders do is assemble components designed and manufactured\nby someone else. This has, like the arrival of desktop publishing,\ngiven people the freedom to experiment in disastrous ways, but it\nis certainly more efficient.[7] Google is much more dangerous to Microsoft than Netscape was.\nProbably more dangerous than any other company has ever been. Not\nleast because they're determined to fight. On their job listing\npage, they say that one of their \"core values'' is \"Don't be evil.''\nFrom a company selling soybean oil or mining equipment, such a\nstatement would merely be eccentric. But I think all of us in the\ncomputer world recognize who that is a declaration of war on.Thanks to Jessica Livingston, Robert Morris, and Sarah Harlin\nfor reading earlier versions of this talk." }, { "path": "data/PaulGrahamEssaysLarge/goodtaste.txt", "content": "November 2021(This essay is derived from a talk at the Cambridge Union.)When I was a kid, I'd have said there wasn't. My father told me so.\nSome people like some things, and other people like other things,\nand who's to say who's right?It seemed so obvious that there was no such thing as good taste\nthat it was only through indirect evidence that I realized my father\nwas wrong. And that's what I'm going to give you here: a proof by\nreductio ad absurdum. If we start from the premise that there's no\nsuch thing as good taste, we end up with conclusions that are\nobviously false, and therefore the premise must be wrong.We'd better start by saying what good taste is. There's a narrow\nsense in which it refers to aesthetic judgements and a broader one\nin which it refers to preferences of any kind. The strongest proof\nwould be to show that taste exists in the narrowest sense, so I'm\ngoing to talk about taste in art. You have better taste than me if\nthe art you like is better than the art I like.If there's no such thing as good taste, then there's no such thing\nas good art. Because if there is such a\nthing as good art, it's\neasy to tell which of two people has better taste. Show them a lot\nof works by artists they've never seen before and ask them to\nchoose the best, and whoever chooses the better art has better\ntaste.So if you want to discard the concept of good taste, you also have\nto discard the concept of good art. And that means you have to\ndiscard the possibility of people being good at making it. Which\nmeans there's no way for artists to be good at their jobs. And not\njust visual artists, but anyone who is in any sense an artist. You\ncan't have good actors, or novelists, or composers, or dancers\neither. You can have popular novelists, but not good ones.We don't realize how far we'd have to go if we discarded the concept\nof good taste, because we don't even debate the most obvious cases.\nBut it doesn't just mean we can't say which of two famous painters\nis better. It means we can't say that any painter is better than a\nrandomly chosen eight year old.That was how I realized my father was wrong. I started studying\npainting. And it was just like other kinds of work I'd done: you\ncould do it well, or badly, and if you tried hard, you could get\nbetter at it. And it was obvious that Leonardo and Bellini were\nmuch better at it than me. That gap between us was not imaginary.\nThey were so good. And if they could be good, then art could be\ngood, and there was such a thing as good taste after all.Now that I've explained how to show there is such a thing as good\ntaste, I should also explain why people think there isn't. There\nare two reasons. One is that there's always so much disagreement\nabout taste. Most people's response to art is a tangle of unexamined\nimpulses. Is the artist famous? Is the subject attractive? Is this\nthe sort of art they're supposed to like? Is it hanging in a famous\nmuseum, or reproduced in a big, expensive book? In practice most\npeople's response to art is dominated by such extraneous factors.And the people who do claim to have good taste are so often mistaken.\nThe paintings admired by the so-called experts in one generation\nare often so different from those admired a few generations later.\nIt's easy to conclude there's nothing real there at all. It's only\nwhen you isolate this force, for example by trying to paint and\ncomparing your work to Bellini's, that you can see that it does in\nfact exist.The other reason people doubt that art can be good is that there\ndoesn't seem to be any room in the art for this goodness. The\nargument goes like this. Imagine several people looking at a work\nof art and judging how good it is. If being good art really is a\nproperty of objects, it should be in the object somehow. But it\ndoesn't seem to be; it seems to be something happening in the heads\nof each of the observers. And if they disagree, how do you choose\nbetween them?The solution to this puzzle is to realize that the purpose of art\nis to work on its human audience, and humans have a lot in common.\nAnd to the extent the things an object acts upon respond in the\nsame way, that's arguably what it means for the object to have the\ncorresponding property. If everything a particle interacts with\nbehaves as if the particle had a mass of m, then it has a mass of\nm. So the distinction between \"objective\" and \"subjective\" is not\nbinary, but a matter of degree, depending on how much the subjects\nhave in common. Particles interacting with one another are at one\npole, but people interacting with art are not all the way at the\nother; their reactions aren't random.Because people's responses to art aren't random, art can be designed\nto operate on people, and be good or bad depending on how effectively\nit does so. Much as a vaccine can be. If someone were talking about\nthe ability of a vaccine to confer immunity, it would seem very\nfrivolous to object that conferring immunity wasn't really a property\nof vaccines, because acquiring immunity is something that happens\nin the immune system of each individual person. Sure, people's\nimmune systems vary, and a vaccine that worked on one might not\nwork on another, but that doesn't make it meaningless to talk about\nthe effectiveness of a vaccine.The situation with art is messier, of course. You can't measure\neffectiveness by simply taking a vote, as you do with vaccines.\nYou have to imagine the responses of subjects with a deep knowledge\nof art, and enough clarity of mind to be able to ignore extraneous\ninfluences like the fame of the artist. And even then you'd still\nsee some disagreement. People do vary, and judging art is hard,\nespecially recent art. There is definitely not a total order either\nof works or of people's ability to judge them. But there is equally\ndefinitely a partial order of both. So while it's not possible to\nhave perfect taste, it is possible to have good taste.\nThanks to the Cambridge Union for inviting me, and to Trevor\nBlackwell, Jessica Livingston, and Robert Morris for reading drafts\nof this.\n" }, { "path": "data/PaulGrahamEssaysLarge/hubs.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nOctober 2011If you look at a list of US cities sorted by population, the number\nof successful startups per capita varies by orders of magnitude.\nSomehow it's as if most places were sprayed with startupicide.I wondered about this for years. I could see the average town was\nlike a roach motel for startup ambitions: smart, ambitious people\nwent in, but no startups came out. But I was never able to figure\nout exactly what happened inside the motel—exactly what was\nkilling all the potential startups.\n[1]A couple weeks ago I finally figured it out. I was framing the\nquestion wrong. The problem is not that most towns kill startups.\nIt's that death is the default for startups,\nand most towns don't save them. Instead of thinking of most places\nas being sprayed with startupicide, it's more accurate to think of\nstartups as all being poisoned, and a few places being sprayed with\nthe antidote.Startups in other places are just doing what startups naturally do:\nfail. The real question is, what's saving startups in places\nlike Silicon Valley?\n[2]EnvironmentI think there are two components to the antidote: being in a place\nwhere startups are the cool thing to do, and chance meetings with\npeople who can help you. And what drives them both is the number\nof startup people around you.The first component is particularly helpful in the first stage of\na startup's life, when you go from merely having an interest in\nstarting a company to actually doing it. It's quite a leap to start\na startup. It's an unusual thing to do. But in Silicon Valley it\nseems normal.\n[3]In most places, if you start a startup, people treat you as if\nyou're unemployed. People in the Valley aren't automatically\nimpressed with you just because you're starting a company, but they\npay attention. Anyone who's been here any amount of time knows not\nto default to skepticism, no matter how inexperienced you seem or\nhow unpromising your idea sounds at first, because they've all seen\ninexperienced founders with unpromising sounding ideas who a few\nyears later were billionaires.Having people around you care about what you're doing is an\nextraordinarily powerful force. Even the\nmost willful people are susceptible to it. About a year after we\nstarted Y Combinator I said something to a partner at a well known\nVC firm that gave him the (mistaken) impression I was considering\nstarting another startup. He responded so eagerly that for about\nhalf a second I found myself considering doing it.In most other cities, the prospect of starting a startup just doesn't\nseem real. In the Valley it's not only real but fashionable. That\nno doubt causes a lot of people to start startups who shouldn't.\nBut I think that's ok. Few people are suited to running a startup,\nand it's very hard to predict beforehand which are (as I know all\ntoo well from being in the business of trying to predict beforehand),\nso lots of people starting startups who shouldn't is probably the\noptimal state of affairs. As long as you're at a point in your\nlife when you can bear the risk of failure, the best way to find\nout if you're suited to running a startup is to try\nit.ChanceThe second component of the antidote is chance meetings with people\nwho can help you. This force works in both phases: both in the\ntransition from the desire to start a startup to starting one, and\nthe transition from starting a company to succeeding. The power\nof chance meetings is more variable than people around you caring\nabout startups, which is like a sort of background radiation that\naffects everyone equally, but at its strongest it is far stronger.Chance meetings produce miracles to compensate for the disasters\nthat characteristically befall startups. In the Valley, terrible\nthings happen to startups all the time, just like they do to startups\neverywhere. The reason startups are more likely to make it here\nis that great things happen to them too. In the Valley, lightning\nhas a sign bit.For example, you start a site for college students and you decide\nto move to the Valley for the summer to work on it. And then on a\nrandom suburban street in Palo Alto you happen to run into Sean\nParker, who understands the domain really well because he started\na similar startup himself, and also knows all the investors. And\nmoreover has advanced views, for 2004, on founders retaining control of their companies.You can't say precisely what the miracle will be, or even for sure\nthat one will happen. The best one can say is: if you're in a\nstartup hub, unexpected good things will probably happen to you,\nespecially if you deserve them.I bet this is true even for startups we fund. Even with us working\nto make things happen for them on purpose rather than by accident,\nthe frequency of helpful chance meetings in the Valley is so high\nthat it's still a significant increment on what we can deliver.Chance meetings play a role like the role relaxation plays in having\nideas. Most people have had the experience of working hard on some\nproblem, not being able to solve it, giving up and going to bed,\nand then thinking of the answer in the shower in the morning. What\nmakes the answer appear is letting your thoughts drift a bit—and thus drift off the wrong\npath you'd been pursuing last night and onto the right one adjacent\nto it.Chance meetings let your acquaintance drift in the same way taking\na shower lets your thoughts drift. The critical thing in both cases\nis that they drift just the right amount. The meeting between Larry\nPage and Sergey Brin was a good example. They let their acquaintance\ndrift, but only a little; they were both meeting someone they had\na lot in common with.For Larry Page the most important component of the antidote was\nSergey Brin, and vice versa. The antidote is \npeople. It's not the\nphysical infrastructure of Silicon Valley that makes it work, or\nthe weather, or anything like that. Those helped get it started,\nbut now that the reaction is self-sustaining what drives it is the\npeople.Many observers have noticed that one of the most distinctive things\nabout startup hubs is the degree to which people help one another\nout, with no expectation of getting anything in return. I'm not\nsure why this is so. Perhaps it's because startups are less of a\nzero sum game than most types of business; they are rarely killed\nby competitors. Or perhaps it's because so many startup founders\nhave backgrounds in the sciences, where collaboration is encouraged.A large part of YC's function is to accelerate that process. We're\na sort of Valley within the Valley, where the density of people\nworking on startups and their willingness to help one another are\nboth artificially amplified.NumbersBoth components of the antidote—an environment that encourages\nstartups, and chance meetings with people who help you—are\ndriven by the same underlying cause: the number of startup people\naround you. To make a startup hub, you need a lot of people\ninterested in startups.There are three reasons. The first, obviously, is that if you don't\nhave enough density, the chance meetings don't happen.\n[4]\nThe second is that different startups need such different things, so\nyou need a lot of people to supply each startup with what they need\nmost. Sean Parker was exactly what Facebook needed in 2004. Another\nstartup might have needed a database guy, or someone with connections\nin the movie business.This is one of the reasons we fund such a large number of companies,\nincidentally. The bigger the community, the greater the chance it\nwill contain the person who has that one thing you need most.The third reason you need a lot of people to make a startup hub is\nthat once you have enough people interested in the same problem,\nthey start to set the social norms. And it is a particularly\nvaluable thing when the atmosphere around you encourages you to do\nsomething that would otherwise seem too ambitious. In most places\nthe atmosphere pulls you back toward the mean.I flew into the Bay Area a few days ago. I notice this every time\nI fly over the Valley: somehow you can sense something is going on. \nObviously you can sense prosperity in how well kept a\nplace looks. But there are different kinds of prosperity. Silicon\nValley doesn't look like Boston, or New York, or LA, or DC. I tried\nasking myself what word I'd use to describe the feeling the Valley\nradiated, and the word that came to mind was optimism.Notes[1]\nI'm not saying it's impossible to succeed in a city with few\nother startups, just harder. If you're sufficiently good at\ngenerating your own morale, you can survive without external\nencouragement. Wufoo was based in Tampa and they succeeded. But\nthe Wufoos are exceptionally disciplined.[2]\nIncidentally, this phenomenon is not limited to startups. Most\nunusual ambitions fail, unless the person who has them manages to\nfind the right sort of community.[3]\nStarting a company is common, but starting a startup is rare.\nI've talked about the distinction between the two elsewhere, but\nessentially a startup is a new business designed for scale. Most\nnew businesses are service businesses and except in rare cases those\ndon't scale.[4]\nAs I was writing this, I had a demonstration of the density of\nstartup people in the Valley. Jessica and I bicycled to University\nAve in Palo Alto to have lunch at the fabulous Oren's Hummus. As\nwe walked in, we met Charlie Cheever sitting near the door. Selina\nTobaccowala stopped to say hello on her way out. Then Josh Wilson\ncame in to pick up a take out order. After lunch we went to get\nfrozen yogurt. On the way we met Rajat Suri. When we got to the\nyogurt place, we found Dave Shen there, and as we walked out we ran\ninto Yuri Sagalov. We walked with him for a block or so and we ran\ninto Muzzammil Zaveri, and then a block later we met Aydin Senkut.\nThis is everyday life in Palo Alto. I wasn't trying to meet people;\nI was just having lunch. And I'm sure for every startup founder\nor investor I saw that I knew, there were 5 more I didn't. If Ron\nConway had been with us he would have met 30 people he knew.Thanks to Sam Altman, Paul Buchheit, Jessica Livingston, and\nHarj Taggar for reading drafts of this." }, { "path": "data/PaulGrahamEssaysLarge/iflisp.txt", "content": "May 2003If Lisp is so great, why don't more people use it? I was \nasked this question by a student in the audience at a \ntalk I gave recently. Not for the first time, either.In languages, as in so many things, there's not much \ncorrelation between popularity and quality. Why does \nJohn Grisham (King of Torts sales rank, 44) outsell\nJane Austen (Pride and Prejudice sales rank, 6191)?\nWould even Grisham claim that it's because he's a better\nwriter?Here's the first sentence of Pride and Prejudice:\n\nIt is a truth universally acknowledged, that a single man \nin possession of a good fortune must be in want of a\nwife.\n\n\"It is a truth universally acknowledged?\" Long words for\nthe first sentence of a love story.Like Jane Austen, Lisp looks hard. Its syntax, or lack\nof syntax, makes it look completely unlike \nthe languages\nmost people are used to. Before I learned Lisp, I was afraid\nof it too. I recently came across a notebook from 1983\nin which I'd written:\n\nI suppose I should learn Lisp, but it seems so foreign.\n\nFortunately, I was 19 at the time and not too resistant to learning\nnew things. I was so ignorant that learning\nalmost anything meant learning new things.People frightened by Lisp make up other reasons for not\nusing it. The standard\nexcuse, back when C was the default language, was that Lisp\nwas too slow. Now that Lisp dialects are among\nthe faster\nlanguages available, that excuse has gone away.\nNow the standard excuse is openly circular: that other languages\nare more popular.(Beware of such reasoning. It gets you Windows.)Popularity is always self-perpetuating, but it's especially\nso in programming languages. More libraries\nget written for popular languages, which makes them still\nmore popular. Programs often have to work with existing programs,\nand this is easier if they're written in the same language,\nso languages spread from program to program like a virus.\nAnd managers prefer popular languages, because they give them \nmore leverage over developers, who can more easily be replaced.Indeed, if programming languages were all more or less equivalent,\nthere would be little justification for using any but the most\npopular. But they aren't all equivalent, not by a long\nshot. And that's why less popular languages, like Jane Austen's \nnovels, continue to survive at all. When everyone else is reading \nthe latest John Grisham novel, there will always be a few people \nreading Jane Austen instead." }, { "path": "data/PaulGrahamEssaysLarge/island.txt", "content": "July 2006I've discovered a handy test for figuring out what you're addicted\nto. Imagine you were going to spend the weekend at a friend's house\non a little island off the coast of Maine. There are no shops on\nthe island and you won't be able to leave while you're there. Also,\nyou've never been to this house before, so you can't assume it will\nhave more than any house might.What, besides clothes and toiletries, do you make a point of packing?\nThat's what you're addicted to. For example, if you find yourself\npacking a bottle of vodka (just in case), you may want to stop and\nthink about that.For me the list is four things: books, earplugs, a notebook, and a\npen.There are other things I might bring if I thought of it, like music,\nor tea, but I can live without them. I'm not so addicted to caffeine\nthat I wouldn't risk the house not having any tea, just for a\nweekend.Quiet is another matter. I realize it seems a bit eccentric to\ntake earplugs on a trip to an island off the coast of Maine. If\nanywhere should be quiet, that should. But what if the person in\nthe next room snored? What if there was a kid playing basketball?\n(Thump, thump, thump... thump.) Why risk it? Earplugs are small.Sometimes I can think with noise. If I already have momentum on\nsome project, I can work in noisy places. I can edit an essay or\ndebug code in an airport. But airports are not so bad: most of the\nnoise is whitish. I couldn't work with the sound of a sitcom coming\nthrough the wall, or a car in the street playing thump-thump music.And of course there's another kind of thinking, when you're starting\nsomething new, that requires complete quiet. You never\nknow when this will strike. It's just as well to carry plugs.The notebook and pen are professional equipment, as it were. Though\nactually there is something druglike about them, in the sense that\ntheir main purpose is to make me feel better. I hardly ever go\nback and read stuff I write down in notebooks. It's just that if\nI can't write things down, worrying about remembering one idea gets\nin the way of having the next. Pen and paper wick ideas.The best notebooks I've found are made by a company called Miquelrius.\nI use their smallest size, which is about 2.5 x 4 in.\nThe secret to writing on such\nnarrow pages is to break words only when you run out of space, like\na Latin inscription. I use the cheapest plastic Bic ballpoints,\npartly because their gluey ink doesn't seep through pages, and\npartly so I don't worry about losing them.I only started carrying a notebook about three years ago. Before\nthat I used whatever scraps of paper I could find. But the problem\nwith scraps of paper is that they're not ordered. In a notebook\nyou can guess what a scribble means by looking at the pages\naround it. In the scrap era I was constantly finding notes I'd\nwritten years before that might say something I needed to remember,\nif I could only figure out what.As for books, I know the house would probably have something to\nread. On the average trip I bring four books and only read one of\nthem, because I find new books to read en route. Really bringing\nbooks is insurance.I realize this dependence on books is not entirely good—that what\nI need them for is distraction. The books I bring on trips are\noften quite virtuous, the sort of stuff that might be assigned\nreading in a college class. But I know my motives aren't virtuous.\nI bring books because if the world gets boring I need to be able\nto slip into another distilled by some writer. It's like eating\njam when you know you should be eating fruit.There is a point where I'll do without books. I was walking in\nsome steep mountains once, and decided I'd rather just think, if I\nwas bored, rather than carry a single unnecessary ounce. It wasn't\nso bad. I found I could entertain myself by having ideas instead\nof reading other people's. If you stop eating jam, fruit starts\nto taste better.So maybe I'll try not bringing books on some future trip. They're\ngoing to have to pry the plugs out of my cold, dead ears, however." }, { "path": "data/PaulGrahamEssaysLarge/know.txt", "content": "December 2014I've read Villehardouin's chronicle of the Fourth Crusade at least\ntwo times, maybe three. And yet if I had to write down everything\nI remember from it, I doubt it would amount to much more than a\npage. Multiply this times several hundred, and I get an uneasy\nfeeling when I look at my bookshelves. What use is it to read all\nthese books if I remember so little from them?A few months ago, as I was reading Constance Reid's excellent\nbiography of Hilbert, I figured out if not the answer to this\nquestion, at least something that made me feel better about it.\nShe writes:\n\n Hilbert had no patience with mathematical lectures which filled\n the students with facts but did not teach them how to frame a\n problem and solve it. He often used to tell them that \"a perfect\n formulation of a problem is already half its solution.\"\n\nThat has always seemed to me an important point, and I was even\nmore convinced of it after hearing it confirmed by Hilbert.But how had I come to believe in this idea in the first place? A\ncombination of my own experience and other things I'd read. None\nof which I could at that moment remember! And eventually I'd forget\nthat Hilbert had confirmed it too. But my increased belief in the\nimportance of this idea would remain something I'd learned from\nthis book, even after I'd forgotten I'd learned it.Reading and experience train your model of the world. And even if\nyou forget the experience or what you read, its effect on your model\nof the world persists. Your mind is like a compiled program you've\nlost the source of. It works, but you don't know why.The place to look for what I learned from Villehardouin's chronicle\nis not what I remember from it, but my mental models of the crusades,\nVenice, medieval culture, siege warfare, and so on. Which doesn't\nmean I couldn't have read more attentively, but at least the harvest\nof reading is not so miserably small as it might seem.This is one of those things that seem obvious in retrospect. But\nit was a surprise to me and presumably would be to anyone else who\nfelt uneasy about (apparently) forgetting so much they'd read.Realizing it does more than make you feel a little better about\nforgetting, though. There are specific implications.For example, reading and experience are usually \"compiled\" at the\ntime they happen, using the state of your brain at that time. The\nsame book would get compiled differently at different points in\nyour life. Which means it is very much worth reading important\nbooks multiple times. I always used to feel some misgivings about\nrereading books. I unconsciously lumped reading together with work\nlike carpentry, where having to do something again is a sign you\ndid it wrong the first time. Whereas now the phrase \"already read\"\nseems almost ill-formed.Intriguingly, this implication isn't limited to books. Technology\nwill increasingly make it possible to relive our experiences. When\npeople do that today it's usually to enjoy them again (e.g. when\nlooking at pictures of a trip) or to find the origin of some bug in\ntheir compiled code (e.g. when Stephen Fry succeeded in remembering\nthe childhood trauma that prevented him from singing). But as\ntechnologies for recording and playing back your life improve, it\nmay become common for people to relive experiences without any goal\nin mind, simply to learn from them again as one might when rereading\na book.Eventually we may be able not just to play back experiences but\nalso to index and even edit them. So although not knowing how you\nknow things may seem part of being human, it may not be.\nThanks to Sam Altman, Jessica Livingston, and Robert Morris for reading \ndrafts of this." }, { "path": "data/PaulGrahamEssaysLarge/langdes.txt", "content": "May 2001\n\n(These are some notes I made\nfor a panel discussion on programming language design\nat MIT on May 10, 2001.)1. Programming Languages Are for People.Programming languages\nare how people talk to computers. The computer would be just as\nhappy speaking any language that was unambiguous. The reason we\nhave high level languages is because people can't deal with\nmachine language. The point of programming\nlanguages is to prevent our poor frail human brains from being \noverwhelmed by a mass of detail.Architects know that some kinds of design problems are more personal\nthan others. One of the cleanest, most abstract design problems\nis designing bridges. There your job is largely a matter of spanning\na given distance with the least material. The other end of the\nspectrum is designing chairs. Chair designers have to spend their\ntime thinking about human butts.Software varies in the same way. Designing algorithms for routing\ndata through a network is a nice, abstract problem, like designing\nbridges. Whereas designing programming languages is like designing\nchairs: it's all about dealing with human weaknesses.Most of us hate to acknowledge this. Designing systems of great\nmathematical elegance sounds a lot more appealing to most of us\nthan pandering to human weaknesses. And there is a role for mathematical\nelegance: some kinds of elegance make programs easier to understand.\nBut elegance is not an end in itself.And when I say languages have to be designed to suit human weaknesses,\nI don't mean that languages have to be designed for bad programmers.\nIn fact I think you ought to design for the \nbest programmers, but\neven the best programmers have limitations. I don't think anyone\nwould like programming in a language where all the variables were\nthe letter x with integer subscripts.2. Design for Yourself and Your Friends.If you look at the history of programming languages, a lot of the best\nones were languages designed for their own authors to use, and a\nlot of the worst ones were designed for other people to use.When languages are designed for other people, it's always a specific\ngroup of other people: people not as smart as the language designer.\nSo you get a language that talks down to you. Cobol is the most\nextreme case, but a lot of languages are pervaded by this spirit.It has nothing to do with how abstract the language is. C is pretty\nlow-level, but it was designed for its authors to use, and that's\nwhy hackers like it.The argument for designing languages for bad programmers is that\nthere are more bad programmers than good programmers. That may be\nso. But those few good programmers write a disproportionately\nlarge percentage of the software.I'm interested in the question, how do you design a language that\nthe very best hackers will like? I happen to think this is\nidentical to the question, how do you design a good programming\nlanguage?, but even if it isn't, it is at least an interesting\nquestion.3. Give the Programmer as Much Control as Possible.Many languages\n(especially the ones designed for other people) have the attitude\nof a governess: they try to prevent you from\ndoing things that they think aren't good for you. I like the \nopposite approach: give the programmer as much\ncontrol as you can.When I first learned Lisp, what I liked most about it was\nthat it considered me an equal partner. In the other languages\nI had learned up till then, there was the language and there was my \nprogram, written in the language, and the two were very separate.\nBut in Lisp the functions and macros I wrote were just like those\nthat made up the language itself. I could rewrite the language\nif I wanted. It had the same appeal as open-source software.4. Aim for Brevity.Brevity is underestimated and even scorned.\nBut if you look into the hearts of hackers, you'll see that they\nreally love it. How many times have you heard hackers speak fondly\nof how in, say, APL, they could do amazing things with just a couple\nlines of code? I think anything that really smart people really\nlove is worth paying attention to.I think almost anything\nyou can do to make programs shorter is good. There should be lots\nof library functions; anything that can be implicit should be;\nthe syntax should be terse to a fault; even the names of things\nshould be short.And it's not only programs that should be short. The manual should\nbe thin as well. A good part of manuals is taken up with clarifications\nand reservations and warnings and special cases. If you force \nyourself to shorten the manual, in the best case you do it by fixing\nthe things in the language that required so much explanation.5. Admit What Hacking Is.A lot of people wish that hacking was\nmathematics, or at least something like a natural science. I think\nhacking is more like architecture. Architecture is\nrelated to physics, in the sense that architects have to design\nbuildings that don't fall down, but the actual goal of architects\nis to make great buildings, not to make discoveries about statics.What hackers like to do is make great programs.\nAnd I think, at least in our own minds, we have to remember that it's\nan admirable thing to write great programs, even when this work \ndoesn't translate easily into the conventional intellectual\ncurrency of research papers. Intellectually, it is just as\nworthwhile to design a language programmers will love as it is to design a\nhorrible one that embodies some idea you can publish a paper\nabout.1. How to Organize Big Libraries?Libraries are becoming an\nincreasingly important component of programming languages. They're\nalso getting bigger, and this can be dangerous. If it takes longer\nto find the library function that will do what you want than it\nwould take to write it yourself, then all that code is doing nothing\nbut make your manual thick. (The Symbolics manuals were a case in \npoint.) So I think we will have to work on ways to organize\nlibraries. The ideal would be to design them so that the programmer\ncould guess what library call would do the right thing.2. Are People Really Scared of Prefix Syntax?This is an open\nproblem in the sense that I have wondered about it for years and\nstill don't know the answer. Prefix syntax seems perfectly natural\nto me, except possibly for math. But it could be that a lot of \nLisp's unpopularity is simply due to having an unfamiliar syntax. \nWhether to do anything about it, if it is true, is another question. \n\n3. What Do You Need for Server-Based Software?\n\nI think a lot of the most exciting new applications that get written\nin the next twenty years will be Web-based applications, meaning\nprograms that sit on the server and talk to you through a Web\nbrowser. And to write these kinds of programs we may need some\nnew things.One thing we'll need is support for the new way that server-based \napps get released. Instead of having one or two big releases a\nyear, like desktop software, server-based apps get released as a\nseries of small changes. You may have as many as five or ten\nreleases a day. And as a rule everyone will always use the latest\nversion.You know how you can design programs to be debuggable?\nWell, server-based software likewise has to be designed to be\nchangeable. You have to be able to change it easily, or at least\nto know what is a small change and what is a momentous one.Another thing that might turn out to be useful for server based\nsoftware, surprisingly, is continuations. In Web-based software\nyou can use something like continuation-passing style to get the\neffect of subroutines in the inherently \nstateless world of a Web\nsession. Maybe it would be worthwhile having actual continuations,\nif it was not too expensive.4. What New Abstractions Are Left to Discover?I'm not sure how\nreasonable a hope this is, but one thing I would really love to \ndo, personally, is discover a new abstraction-- something that would\nmake as much of a difference as having first class functions or\nrecursion or even keyword parameters. This may be an impossible\ndream. These things don't get discovered that often. But I am always\nlooking.1. You Can Use Whatever Language You Want.Writing application\nprograms used to mean writing desktop software. And in desktop\nsoftware there is a big bias toward writing the application in the\nsame language as the operating system. And so ten years ago,\nwriting software pretty much meant writing software in C.\nEventually a tradition evolved:\napplication programs must not be written in unusual languages. \nAnd this tradition had so long to develop that nontechnical people\nlike managers and venture capitalists also learned it.Server-based software blows away this whole model. With server-based\nsoftware you can use any language you want. Almost nobody understands\nthis yet (especially not managers and venture capitalists).\nA few hackers understand it, and that's why we even hear\nabout new, indy languages like Perl and Python. We're not hearing\nabout Perl and Python because people are using them to write Windows\napps.What this means for us, as people interested in designing programming\nlanguages, is that there is now potentially an actual audience for\nour work.2. Speed Comes from Profilers.Language designers, or at least\nlanguage implementors, like to write compilers that generate fast\ncode. But I don't think this is what makes languages fast for users.\nKnuth pointed out long ago that speed only matters in a few critical\nbottlenecks. And anyone who's tried it knows that you can't guess\nwhere these bottlenecks are. Profilers are the answer.Language designers are solving the wrong problem. Users don't need\nbenchmarks to run fast. What they need is a language that can show\nthem what parts of their own programs need to be rewritten. That's\nwhere speed comes from in practice. So maybe it would be a net \nwin if language implementors took half the time they would\nhave spent doing compiler optimizations and spent it writing a\ngood profiler instead.3. You Need an Application to Drive the Design of a Language.This may not be an absolute rule, but it seems like the best languages\nall evolved together with some application they were being used to\nwrite. C was written by people who needed it for systems programming.\nLisp was developed partly to do symbolic differentiation, and\nMcCarthy was so eager to get started that he was writing differentiation\nprograms even in the first paper on Lisp, in 1960.It's especially good if your application solves some new problem.\nThat will tend to drive your language to have new features that \nprogrammers need. I personally am interested in writing\na language that will be good for writing server-based applications.[During the panel, Guy Steele also made this point, with the\nadditional suggestion that the application should not consist of\nwriting the compiler for your language, unless your language\nhappens to be intended for writing compilers.]4. A Language Has to Be Good for Writing Throwaway Programs.You know what a throwaway program is: something you write quickly for\nsome limited task. I think if you looked around you'd find that \na lot of big, serious programs started as throwaway programs. I\nwould not be surprised if most programs started as throwaway\nprograms. And so if you want to make a language that's good for\nwriting software in general, it has to be good for writing throwaway\nprograms, because that is the larval stage of most software.5. Syntax Is Connected to Semantics.It's traditional to think of\nsyntax and semantics as being completely separate. This will\nsound shocking, but it may be that they aren't.\nI think that what you want in your language may be related\nto how you express it.I was talking recently to Robert Morris, and he pointed out that\noperator overloading is a bigger win in languages with infix\nsyntax. In a language with prefix syntax, any function you define\nis effectively an operator. If you want to define a plus for a\nnew type of number you've made up, you can just define a new function\nto add them. If you do that in a language with infix syntax,\nthere's a big difference in appearance between the use of an\noverloaded operator and a function call.1. New Programming Languages.Back in the 1970s\nit was fashionable to design new programming languages. Recently\nit hasn't been. But I think server-based software will make new \nlanguages fashionable again. With server-based software, you can\nuse any language you want, so if someone does design a language that\nactually seems better than others that are available, there will be\npeople who take a risk and use it.2. Time-Sharing.Richard Kelsey gave this as an idea whose time\nhas come again in the last panel, and I completely agree with him.\nMy guess (and Microsoft's guess, it seems) is that much computing\nwill move from the desktop onto remote servers. In other words, \ntime-sharing is back. And I think there will need to be support\nfor it at the language level. For example, I know that Richard\nand Jonathan Rees have done a lot of work implementing process \nscheduling within Scheme 48.3. Efficiency.Recently it was starting to seem that computers\nwere finally fast enough. More and more we were starting to hear\nabout byte code, which implies to me at least that we feel we have\ncycles to spare. But I don't think we will, with server-based\nsoftware. Someone is going to have to pay for the servers that\nthe software runs on, and the number of users they can support per\nmachine will be the divisor of their capital cost.So I think efficiency will matter, at least in computational\nbottlenecks. It will be especially important to do i/o fast,\nbecause server-based applications do a lot of i/o.It may turn out that byte code is not a win, in the end. Sun and\nMicrosoft seem to be facing off in a kind of a battle of the byte\ncodes at the moment. But they're doing it because byte code is a\nconvenient place to insert themselves into the process, not because\nbyte code is in itself a good idea. It may turn out that this\nwhole battleground gets bypassed. That would be kind of amusing.1. Clients.This is just a guess, but my guess is that\nthe winning model for most applications will be purely server-based.\nDesigning software that works on the assumption that everyone will \nhave your client is like designing a society on the assumption that\neveryone will just be honest. It would certainly be convenient, but\nyou have to assume it will never happen.I think there will be a proliferation of devices that have some\nkind of Web access, and all you'll be able to assume about them is\nthat they can support simple html and forms. Will you have a\nbrowser on your cell phone? Will there be a phone in your palm \npilot? Will your blackberry get a bigger screen? Will you be able\nto browse the Web on your gameboy? Your watch? I don't know. \nAnd I don't have to know if I bet on\neverything just being on the server. It's\njust so much more robust to have all the \nbrains on the server.2. Object-Oriented Programming.I realize this is a\ncontroversial one, but I don't think object-oriented programming\nis such a big deal. I think it is a fine model for certain kinds\nof applications that need that specific kind of data structure, \nlike window systems, simulations, and cad programs. But I don't\nsee why it ought to be the model for all programming.I think part of the reason people in big companies like object-oriented\nprogramming is because it yields a lot of what looks like work.\nSomething that might naturally be represented as, say, a list of\nintegers, can now be represented as a class with all kinds of\nscaffolding and hustle and bustle.Another attraction of\nobject-oriented programming is that methods give you some of the\neffect of first class functions. But this is old news to Lisp\nprogrammers. When you have actual first class functions, you can\njust use them in whatever way is appropriate to the task at hand,\ninstead of forcing everything into a mold of classes and methods.What this means for language design, I think, is that you shouldn't\nbuild object-oriented programming in too deeply. Maybe the\nanswer is to offer more general, underlying stuff, and let people design\nwhatever object systems they want as libraries.3. Design by Committee.Having your language designed by a committee is a big pitfall, \nand not just for the reasons everyone knows about. Everyone\nknows that committees tend to yield lumpy, inconsistent designs. \nBut I think a greater danger is that they won't take risks.\nWhen one person is in charge he can take risks\nthat a committee would never agree on.Is it necessary to take risks to design a good language though?\nMany people might suspect\nthat language design is something where you should stick fairly\nclose to the conventional wisdom. I bet this isn't true.\nIn everything else people do, reward is proportionate to risk.\nWhy should language design be any different?" }, { "path": "data/PaulGrahamEssaysLarge/laundry.txt", "content": "October 2004\nAs E. B. White said, \"good writing is rewriting.\" I didn't\nrealize this when I was in school. In writing, as in math and \nscience, they only show you the finished product.\nYou don't see all the false starts. This gives students a\nmisleading view of how things get made.Part of the reason it happens is that writers don't want \npeople to see their mistakes. But I'm willing to let people\nsee an early draft if it will show how much you have\nto rewrite to beat an essay into shape.Below is the oldest version I can find of\nThe Age of the Essay \n(probably the second or third day), with\ntext that ultimately survived in \nred and text that later\ngot deleted in gray.\nThere seem to be several categories of cuts: things I got wrong,\nthings that seem like bragging, flames,\ndigressions, stretches of awkward prose, and unnecessary words.I discarded more from the beginning. That's\nnot surprising; it takes a while to hit your stride. There\nare more digressions at the start, because I'm not sure where\nI'm heading.The amount of cutting is about average. I probably write\nthree to four words for every one that appears in the final\nversion of an essay.(Before anyone gets mad at me for opinions expressed here, remember\nthat anything you see here that's not in the final version is obviously\nsomething I chose not to publish, often because I disagree\nwith it.)\nRecently a friend said that what he liked about\nmy essays was that they weren't written the way\nwe'd been taught to write essays in school. You\nremember: topic sentence, introductory paragraph,\nsupporting paragraphs, conclusion. It hadn't\noccurred to me till then that those horrible things\nwe had to write in school were even connected to\nwhat I was doing now. But sure enough, I thought,\nthey did call them \"essays,\" didn't they?Well, they're not. Those things you have to write\nin school are not only not essays, they're one of the\nmost pointless of all the pointless hoops you have\nto jump through in school. And I worry that they\nnot only teach students the wrong things about writing,\nbut put them off writing entirely.So I'm going to give the other side of the story: what\nan essay really is, and how you write one. Or at least,\nhow I write one. Students be forewarned: if you actually write\nthe kind of essay I describe, you'll probably get bad\ngrades. But knowing how it's really done should\nat least help you to understand the feeling of futility\nyou have when you're writing the things they tell you to.\nThe most obvious difference between real essays and\nthe things one has to write in school is that real\nessays are not exclusively about English literature.\nIt's a fine thing for schools to\n\nteach students how to\nwrite. But for some bizarre reason (actually, a very specific bizarre\nreason that I'll explain in a moment),\n\nthe teaching of\nwriting has gotten mixed together with the study\nof literature. And so all over the country, students are\nwriting not about how a baseball team with a small budget \nmight compete with the Yankees, or the role of color in\nfashion, or what constitutes a good dessert, but about\nsymbolism in Dickens.With obvious \nresults. Only a few people really\n\ncare about\nsymbolism in Dickens. The teacher doesn't.\nThe students don't. Most of the people who've had to write PhD\ndisserations about Dickens don't. And certainly\n\nDickens himself would be more interested in an essay\nabout color or baseball.How did things get this way? To answer that we have to go back\nalmost a thousand years. Between about 500 and 1000, life was\nnot very good in Europe. The term \"dark ages\" is presently\nout of fashion as too judgemental (the period wasn't dark; \nit was just different), but if this label didn't already\nexist, it would seem an inspired metaphor. What little\noriginal thought there was took place in lulls between\nconstant wars and had something of the character of\nthe thoughts of parents with a new baby.\nThe most amusing thing written during this\nperiod, Liudprand of Cremona's Embassy to Constantinople, is,\nI suspect, mostly inadvertantly so.Around 1000 Europe began to catch its breath.\nAnd once they\nhad the luxury of curiosity, one of the first things they discovered\nwas what we call \"the classics.\"\nImagine if we were visited \nby aliens. If they could even get here they'd presumably know a\nfew things we don't. Immediately Alien Studies would become\nthe most dynamic field of scholarship: instead of painstakingly\ndiscovering things for ourselves, we could simply suck up\neverything they'd discovered. So it was in Europe in 1200.\nWhen classical texts began to circulate in Europe, they contained\nnot just new answers, but new questions. (If anyone proved\na theorem in christian Europe before 1200, for example, there\nis no record of it.)For a couple centuries, some of the most important work\nbeing done was intellectual archaelogy. Those were also\nthe centuries during which schools were first established.\nAnd since reading ancient texts was the essence of what\nscholars did then, it became the basis of the curriculum.By 1700, someone who wanted to learn about\nphysics didn't need to start by mastering Greek in order to read Aristotle. But schools\nchange slower than scholarship: the study of\nancient texts\nhad such prestige that it remained the backbone of \neducation\nuntil the late 19th century. By then it was merely a tradition.\nIt did serve some purposes: reading a foreign language was difficult,\nand thus taught discipline, or at least, kept students busy;\nit introduced students to\ncultures quite different from their own; and its very uselessness\nmade it function (like white gloves) as a social bulwark.\nBut it certainly wasn't\ntrue, and hadn't been true for centuries, that students were\nserving apprenticeships in the hottest area of scholarship.Classical scholarship had also changed. In the early era, philology\nactually mattered. The texts that filtered into Europe were\nall corrupted to some degree by the errors of translators and\ncopyists. Scholars had to figure out what Aristotle said\nbefore they could figure out what he meant. But by the modern\nera such questions were answered as well as they were ever\ngoing to be. And so the study of ancient texts became less\nabout ancientness and more about texts.The time was then ripe for the question: if the study of\nancient texts is a valid field for scholarship, why not modern\ntexts? The answer, of course, is that the raison d'etre\nof classical scholarship was a kind of intellectual archaelogy that\ndoes not need to be done in the case of contemporary authors.\nBut for obvious reasons no one wanted to give that answer.\nThe archaeological work being mostly done, it implied that\nthe people studying the classics were, if not wasting their\ntime, at least working on problems of minor importance.And so began the study of modern literature. There was some\ninitial resistance, but it didn't last long.\nThe limiting\nreagent in the growth of university departments is what\nparents will let undergraduates study. If parents will let\ntheir children major in x, the rest follows straightforwardly.\nThere will be jobs teaching x, and professors to fill them.\nThe professors will establish scholarly journals and publish\none another's papers. Universities with x departments will\nsubscribe to the journals. Graduate students who want jobs\nas professors of x will write dissertations about it. It may\ntake a good long while for the more prestigious universities\nto cave in and establish departments in cheesier xes, but\nat the other end of the scale there are so many universities\ncompeting to attract students that the mere establishment of\na discipline requires little more than the desire to do it.High schools imitate universities.\nAnd so once university\nEnglish departments were established in the late nineteenth century,\nthe 'riting component of the 3 Rs \nwas morphed into English.\nWith the bizarre consequence that high school students now\nhad to write about English literature-- to write, without\neven realizing it, imitations of whatever\nEnglish professors had been publishing in their journals a\nfew decades before. It's no wonder if this seems to the\nstudent a pointless exercise, because we're now three steps\nremoved from real work: the students are imitating English\nprofessors, who are imitating classical scholars, who are\nmerely the inheritors of a tradition growing out of what\nwas, 700 years ago, fascinating and urgently needed work.Perhaps high schools should drop English and just teach writing.\nThe valuable part of English classes is learning to write, and\nthat could be taught better by itself. Students learn better\nwhen they're interested in what they're doing, and it's hard\nto imagine a topic less interesting than symbolism in Dickens.\nMost of the people who write about that sort of thing professionally\nare not really interested in it. (Though indeed, it's been a\nwhile since they were writing about symbolism; now they're\nwriting about gender.)I have no illusions about how eagerly this suggestion will \nbe adopted. Public schools probably couldn't stop teaching\nEnglish even if they wanted to; they're probably required to by\nlaw. But here's a related suggestion that goes with the grain\ninstead of against it: that universities establish a\nwriting major. Many of the students who now major in English\nwould major in writing if they could, and most would\nbe better off.It will be argued that it is a good thing for students to be\nexposed to their literary heritage. Certainly. But is that\nmore important than that they learn to write well? And are\nEnglish classes even the place to do it? After all,\nthe average public high school student gets zero exposure to \nhis artistic heritage. No disaster results.\nThe people who are interested in art learn about it for\nthemselves, and those who aren't don't. I find that American\nadults are no better or worse informed about literature than\nart, despite the fact that they spent years studying literature\nin high school and no time at all studying art. Which presumably\nmeans that what they're taught in school is rounding error \ncompared to what they pick up on their own.Indeed, English classes may even be harmful. In my case they\nwere effectively aversion therapy. Want to make someone dislike\na book? Force him to read it and write an essay about it.\nAnd make the topic so intellectually bogus that you\ncould not, if asked, explain why one ought to write about it.\nI love to read more than anything, but by the end of high school\nI never read the books we were assigned. I was so disgusted with\nwhat we were doing that it became a point of honor\nwith me to write nonsense at least as good at the other students'\nwithout having more than glanced over the book to learn the names\nof the characters and a few random events in it.I hoped this might be fixed in college, but I found the same\nproblem there. It was not the teachers. It was English. \nWe were supposed to read novels and write essays about them.\nAbout what, and why? That no one seemed to be able to explain.\nEventually by trial and error I found that what the teacher \nwanted us to do was pretend that the story had really taken\nplace, and to analyze based on what the characters said and did (the\nsubtler clues, the better) what their motives must have been.\nOne got extra credit for motives having to do with class,\nas I suspect one must now for those involving gender and \nsexuality. I learned how to churn out such stuff well enough\nto get an A, but I never took another English class.And the books we did these disgusting things to, like those\nwe mishandled in high school, I find still have black marks\nagainst them in my mind. The one saving grace was that \nEnglish courses tend to favor pompous, dull writers like\nHenry James, who deserve black marks against their names anyway.\nOne of the principles the IRS uses in deciding whether to\nallow deductions is that, if something is fun, it isn't work.\nFields that are intellectually unsure of themselves rely on\na similar principle. Reading P.G. Wodehouse or Evelyn Waugh or\nRaymond Chandler is too obviously pleasing to seem like\nserious work, as reading Shakespeare would have been before \nEnglish evolved enough to make it an effort to understand him. [sh]\nAnd so good writers (just you wait and see who's still in\nprint in 300 years) are less likely to have readers turned \nagainst them by clumsy, self-appointed tour guides.\nThe other big difference between a real essay and the \nthings\nthey make you write in school is that a real essay doesn't \ntake a position and then defend it. That principle,\nlike the idea that we ought to be writing about literature, \nturns out to be another intellectual hangover of long\nforgotten origins. It's often mistakenly believed that\nmedieval universities were mostly seminaries. In fact they\nwere more law schools. And at least in our tradition\nlawyers are advocates: they are\ntrained to be able to\ntake\neither side of an argument and make as good a case for it \nas they can. Whether or not this is a good idea (in the case of prosecutors,\nit probably isn't), it tended to pervade\nthe atmosphere of\nearly universities. After the lecture the most common form\nof discussion was the disputation. This idea\nis at least\nnominally preserved in our present-day thesis defense-- indeed,\nin the very word thesis. Most people treat the words \nthesis\nand dissertation as interchangeable, but originally, at least,\na thesis was a position one took and the dissertation was\nthe argument by which one defended it.I'm not complaining that we blur these two words together.\nAs far as I'm concerned, the sooner we lose the original\nsense of the word thesis, the better. For many, perhaps most, \ngraduate students, it is stuffing a square peg into a round\nhole to try to recast one's work as a single thesis. And\nas for the disputation, that seems clearly a net lose.\nArguing two sides of a case may be a necessary evil in a\nlegal dispute, but it's not the best way to get at the truth,\nas I think lawyers would be the first to admit.\nAnd yet this principle is built into the very structure of \nthe essays\nthey teach you to write in high school. The topic\nsentence is your thesis, chosen in advance, the supporting \nparagraphs the blows you strike in the conflict, and the\nconclusion--- uh, what it the conclusion? I was never sure \nabout that in high school. If your thesis was well expressed,\nwhat need was there to restate it? In theory it seemed that\nthe conclusion of a really good essay ought not to need to \nsay any more than QED.\nBut when you understand the origins\nof this sort of \"essay\", you can see where the\nconclusion comes from. It's the concluding remarks to the \njury.\nWhat other alternative is there? To answer that\nwe have to\nreach back into history again, though this time not so far.\nTo Michel de Montaigne, inventor of the essay.\nHe was\ndoing something quite different from what a\nlawyer does,\nand\nthe difference is embodied in the name. Essayer is the French\nverb meaning \"to try\" (the cousin of our word assay),\n\nand an \"essai\" is an effort.\nAn essay is something you\nwrite in order\nto figure something out.Figure out what? You don't know yet. And so you can't begin with a\nthesis, because you don't have one, and may never have \none. An essay doesn't begin with a statement, but with a \nquestion. In a real essay, you don't take a position and\ndefend it. You see a door that's ajar, and you open it and\nwalk in to see what's inside.If all you want to do is figure things out, why do you need\nto write anything, though? Why not just sit and think? Well,\nthere precisely is Montaigne's great discovery. Expressing\nideas helps to form them. Indeed, helps is far too weak a\nword. 90%\nof what ends up in my essays was stuff\nI only\nthought of when I sat down to write them. That's why I\nwrite them.So there's another difference between essays and\nthe things\nyou have to write in school. In school\n\nyou are, in theory,\nexplaining yourself to someone else. In the best case---if\nyou're really organized---you're just writing it down.\nIn a real essay you're writing for yourself. You're\nthinking out loud.But not quite. Just as inviting people over forces you to\nclean up your apartment, writing something that you know\n\nother people will read forces you to think well. So it\ndoes matter to have an audience. The things I've written\njust for myself are no good. Indeed, they're bad in\na particular way:\nthey tend to peter out. When I run into\ndifficulties, I notice that I\ntend to conclude with a few vague\nquestions and then drift off to get a cup of tea.This seems a common problem.\nIt's practically the standard\nending in blog entries--- with the addition of a \"heh\" or an \nemoticon, prompted by the all too accurate sense that\nsomething is missing.And indeed, a lot of\npublished essays peter out in this\nsame way.\nParticularly the sort written by the staff writers of newsmagazines. Outside writers tend to supply\neditorials of the defend-a-position variety, which\nmake a beeline toward a rousing (and\nforeordained) conclusion. But the staff writers feel\nobliged to write something more\nbalanced, which in\npractice ends up meaning blurry.\nSince they're\nwriting for a popular magazine, they start with the\nmost radioactively controversial questions, from which\n(because they're writing for a popular magazine)\nthey then proceed to recoil from\nin terror.\nGay marriage, for or\nagainst? This group says one thing. That group says\nanother. One thing is certain: the question is a\ncomplex one. (But don't get mad at us. We didn't\ndraw any conclusions.)Questions aren't enough. An essay has to come up with answers.\nThey don't always, of course. Sometimes you start with a \npromising question and get nowhere. But those you don't\npublish. Those are like experiments that get inconclusive\nresults. Something you publish ought to tell the reader \nsomething he didn't already know.\nBut what you tell him doesn't matter, so long as \nit's interesting. I'm sometimes accused of meandering.\nIn defend-a-position writing that would be a flaw.\nThere you're not concerned with truth. You already\nknow where you're going, and you want to go straight there,\nblustering through obstacles, and hand-waving\nyour way across swampy ground. But that's not what\nyou're trying to do in an essay. An essay is supposed to\nbe a search for truth. It would be suspicious if it didn't\nmeander.The Meander is a river in Asia Minor (aka\nTurkey).\nAs you might expect, it winds all over the place.\nBut does it\ndo this out of frivolity? Quite the opposite.\nLike all rivers, it's rigorously following the laws of physics.\nThe path it has discovered,\nwinding as it is, represents\nthe most economical route to the sea.The river's algorithm is simple. At each step, flow down.\nFor the essayist this translates to: flow interesting.\nOf all the places to go next, choose\nwhichever seems\nmost interesting.I'm pushing this metaphor a bit. An essayist\ncan't have\nquite as little foresight as a river. In fact what you do\n(or what I do) is somewhere between a river and a roman\nroad-builder. I have a general idea of the direction\nI want to go in, and\nI choose the next topic with that in mind. This essay is\nabout writing, so I do occasionally yank it back in that\ndirection, but it is not all the sort of essay I\nthought I was going to write about writing.Note too that hill-climbing (which is what this algorithm is\ncalled) can get you in trouble.\nSometimes, just\nlike a river,\nyou\nrun up against a blank wall. What\nI do then is just \nwhat the river does: backtrack.\nAt one point in this essay\nI found that after following a certain thread I ran out\nof ideas. I had to go back n\nparagraphs and start over\nin another direction. For illustrative purposes I've left\nthe abandoned branch as a footnote.\nErr on the side of the river. An essay is not a reference\nwork. It's not something you read looking for a specific\nanswer, and feel cheated if you don't find it. I'd much\nrather read an essay that went off in an unexpected but\ninteresting direction than one that plodded dutifully along\na prescribed course.So what's interesting? For me, interesting means surprise.\nDesign, as Matz\nhas said, should follow the principle of\nleast surprise.\nA button that looks like it will make a\nmachine stop should make it stop, not speed up. Essays\nshould do the opposite. Essays should aim for maximum\nsurprise.I was afraid of flying for a long time and could only travel\nvicariously. When friends came back from faraway places,\nit wasn't just out of politeness that I asked them about\ntheir trip.\nI really wanted to know. And I found that\nthe best way to get information out of them was to ask\nwhat surprised them. How was the place different from what\nthey expected? This is an extremely useful question.\nYou can ask it of even\nthe most unobservant people, and it will\nextract information they didn't even know they were\nrecording. Indeed, you can ask it in real time. Now when I go somewhere\nnew, I make a note of what surprises me about it. Sometimes I\neven make a conscious effort to visualize the place beforehand,\nso I'll have a detailed image to diff with reality.\nSurprises are facts\nyou didn't already \nknow.\nBut they're\nmore than that. They're facts\nthat contradict things you\nthought you knew. And so they're the most valuable sort of\nfact you can get. They're like a food that's not merely\nhealthy, but counteracts the unhealthy effects of things\nyou've already eaten.\nHow do you find surprises? Well, therein lies half\nthe work of essay writing. (The other half is expressing\nyourself well.) You can at least\nuse yourself as a\nproxy for the reader. You should only write about things\nyou've thought about a lot. And anything you come across\nthat surprises you, who've thought about the topic a lot,\nwill probably surprise most readers.For example, in a recent essay I pointed out that because\nyou can only judge computer programmers by working with\nthem, no one knows in programming who the heroes should\nbe.\nI\ncertainly\ndidn't realize this when I started writing\nthe \nessay, and even now I find it kind of weird. That's\nwhat you're looking for.So if you want to write essays, you need two ingredients:\nyou need\na few topics that you think about a lot, and you\nneed some ability to ferret out the unexpected.What should you think about? My guess is that it\ndoesn't matter. Almost everything is\ninteresting if you get deeply\nenough into it. The one possible exception\nare\nthings\nlike working in fast food, which\nhave deliberately had all\nthe variation sucked out of them.\nIn retrospect, was there\nanything interesting about working in Baskin-Robbins?\nWell, it was interesting to notice\nhow important color was\nto the customers. Kids a certain age would point into\nthe case and say that they wanted yellow. Did they want\nFrench Vanilla or Lemon? They would just look at you\nblankly. They wanted yellow. And then there was the\nmystery of why the perennial favorite Pralines n' Cream\nwas so appealing. I'm inclined now to\nthink it was the salt.\nAnd the mystery of why Passion Fruit tasted so disgusting.\nPeople would order it because of the name, and were always\ndisappointed. It should have been called In-sink-erator\nFruit.\nAnd there was\nthe difference in the way fathers and\nmothers bought ice cream for their kids.\nFathers tended to\nadopt the attitude of\nbenevolent kings bestowing largesse,\nand mothers that of\nharried bureaucrats,\ngiving in to\npressure against their better judgement.\nSo, yes, there does seem to be material, even in\nfast food.What about the other half, ferreting out the unexpected?\nThat may require some natural ability. I've noticed for\na long time that I'm pathologically observant. ....[That was as far as I'd gotten at the time.]Notes[sh] In Shakespeare's own time, serious writing meant theological\ndiscourses, not the bawdy plays acted over on the other \nside of the river among the bear gardens and whorehouses.The other extreme, the work that seems formidable from the moment\nit's created (indeed, is deliberately intended to be)\nis represented by Milton. Like the Aeneid, Paradise Lost is a\nrock imitating a butterfly that happened to get fossilized.\nEven Samuel Johnson seems to have balked at this, on the one \nhand paying Milton the compliment of an extensive biography,\nand on the other writing of Paradise Lost that \"none who read it\never wished it longer.\"" }, { "path": "data/PaulGrahamEssaysLarge/love.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nJanuary 2006To do something well you have to like it. That idea is not exactly\nnovel. We've got it down to four words: \"Do what you love.\" But\nit's not enough just to tell people that. Doing what you love is\ncomplicated.The very idea is foreign to what most of us learn as kids. When I\nwas a kid, it seemed as if work and fun were opposites by definition.\nLife had two states: some of the time adults were making you do\nthings, and that was called work; the rest of the time you could\ndo what you wanted, and that was called playing. Occasionally the\nthings adults made you do were fun, just as, occasionally, playing\nwasn't—for example, if you fell and hurt yourself. But except\nfor these few anomalous cases, work was pretty much defined as\nnot-fun.And it did not seem to be an accident. School, it was implied, was\ntedious because it was preparation for grownup work.The world then was divided into two groups, grownups and kids.\nGrownups, like some kind of cursed race, had to work. Kids didn't,\nbut they did have to go to school, which was a dilute version of\nwork meant to prepare us for the real thing. Much as we disliked\nschool, the grownups all agreed that grownup work was worse, and\nthat we had it easy.Teachers in particular all seemed to believe implicitly that work\nwas not fun. Which is not surprising: work wasn't fun for most of\nthem. Why did we have to memorize state capitals instead of playing\ndodgeball? For the same reason they had to watch over a bunch of\nkids instead of lying on a beach. You couldn't just do what you\nwanted.I'm not saying we should let little kids do whatever they want.\nThey may have to be made to work on certain things. But if we make\nkids work on dull stuff, it might be wise to tell them that tediousness\nis not the defining quality of work, and indeed that the reason\nthey have to work on dull stuff now is so they can work on more\ninteresting stuff later.\n[1]Once, when I was about 9 or 10, my father told me I could be whatever\nI wanted when I grew up, so long as I enjoyed it. I remember that\nprecisely because it seemed so anomalous. It was like being told\nto use dry water. Whatever I thought he meant, I didn't think he\nmeant work could literally be fun—fun like playing. It\ntook me years to grasp that.JobsBy high school, the prospect of an actual job was on the horizon.\nAdults would sometimes come to speak to us about their work, or we\nwould go to see them at work. It was always understood that they\nenjoyed what they did. In retrospect I think one may have: the\nprivate jet pilot. But I don't think the bank manager really did.The main reason they all acted as if they enjoyed their work was\npresumably the upper-middle class convention that you're supposed\nto. It would not merely be bad for your career to say that you\ndespised your job, but a social faux-pas.Why is it conventional to pretend to like what you do? The first\nsentence of this essay explains that. If you have to like something\nto do it well, then the most successful people will all like what\nthey do. That's where the upper-middle class tradition comes from.\nJust as houses all over America are full of \nchairs\nthat are, without\nthe owners even knowing it, nth-degree imitations of chairs designed\n250 years ago for French kings, conventional attitudes about work\nare, without the owners even knowing it, nth-degree imitations of\nthe attitudes of people who've done great things.What a recipe for alienation. By the time they reach an age to\nthink about what they'd like to do, most kids have been thoroughly\nmisled about the idea of loving one's work. School has trained\nthem to regard work as an unpleasant duty. Having a job is said\nto be even more onerous than schoolwork. And yet all the adults\nclaim to like what they do. You can't blame kids for thinking \"I\nam not like these people; I am not suited to this world.\"Actually they've been told three lies: the stuff they've been taught\nto regard as work in school is not real work; grownup work is not\n(necessarily) worse than schoolwork; and many of the adults around\nthem are lying when they say they like what they do.The most dangerous liars can be the kids' own parents. If you take\na boring job to give your family a high standard of living, as so\nmany people do, you risk infecting your kids with the idea that\nwork is boring. \n[2]\nMaybe it would be better for kids in this one\ncase if parents were not so unselfish. A parent who set an example\nof loving their work might help their kids more than an expensive\nhouse.\n[3]It was not till I was in college that the idea of work finally broke\nfree from the idea of making a living. Then the important question\nbecame not how to make money, but what to work on. Ideally these\ncoincided, but some spectacular boundary cases (like Einstein in\nthe patent office) proved they weren't identical.The definition of work was now to make some original contribution\nto the world, and in the process not to starve. But after the habit\nof so many years my idea of work still included a large component\nof pain. Work still seemed to require discipline, because only\nhard problems yielded grand results, and hard problems couldn't\nliterally be fun. Surely one had to force oneself to work on them.If you think something's supposed to hurt, you're less likely to\nnotice if you're doing it wrong. That about sums up my experience\nof graduate school.BoundsHow much are you supposed to like what you do? Unless you\nknow that, you don't know when to stop searching. And if, like most\npeople, you underestimate it, you'll tend to stop searching too\nearly. You'll end up doing something chosen for you by your parents,\nor the desire to make money, or prestige—or sheer inertia.Here's an upper bound: Do what you love doesn't mean, do what you\nwould like to do most this second. Even Einstein probably\nhad moments when he wanted to have a cup of coffee, but told himself\nhe ought to finish what he was working on first.It used to perplex me when I read about people who liked what they\ndid so much that there was nothing they'd rather do. There didn't\nseem to be any sort of work I liked that much. If I had a\nchoice of (a) spending the next hour working on something or (b)\nbe teleported to Rome and spend the next hour wandering about, was\nthere any sort of work I'd prefer? Honestly, no.But the fact is, almost anyone would rather, at any given moment,\nfloat about in the Carribbean, or have sex, or eat some delicious\nfood, than work on hard problems. The rule about doing what you\nlove assumes a certain length of time. It doesn't mean, do what\nwill make you happiest this second, but what will make you happiest\nover some longer period, like a week or a month.Unproductive pleasures pall eventually. After a while you get tired\nof lying on the beach. If you want to stay happy, you have to do\nsomething.As a lower bound, you have to like your work more than any unproductive\npleasure. You have to like what you do enough that the concept of\n\"spare time\" seems mistaken. Which is not to say you have to spend\nall your time working. You can only work so much before you get\ntired and start to screw up. Then you want to do something else—even something mindless. But you don't regard this time as the\nprize and the time you spend working as the pain you endure to earn\nit.I put the lower bound there for practical reasons. If your work\nis not your favorite thing to do, you'll have terrible problems\nwith procrastination. You'll have to force yourself to work, and\nwhen you resort to that the results are distinctly inferior.To be happy I think you have to be doing something you not only\nenjoy, but admire. You have to be able to say, at the end, wow,\nthat's pretty cool. This doesn't mean you have to make something.\nIf you learn how to hang glide, or to speak a foreign language\nfluently, that will be enough to make you say, for a while at least,\nwow, that's pretty cool. What there has to be is a test.So one thing that falls just short of the standard, I think, is\nreading books. Except for some books in math and the hard sciences,\nthere's no test of how well you've read a book, and that's why\nmerely reading books doesn't quite feel like work. You have to do\nsomething with what you've read to feel productive.I think the best test is one Gino Lee taught me: to try to do things\nthat would make your friends say wow. But it probably wouldn't\nstart to work properly till about age 22, because most people haven't\nhad a big enough sample to pick friends from before then.SirensWhat you should not do, I think, is worry about the opinion of\nanyone beyond your friends. You shouldn't worry about prestige.\nPrestige is the opinion of the rest of the world. When you can ask\nthe opinions of people whose judgement you respect, what does it\nadd to consider the opinions of people you don't even know? \n[4]This is easy advice to give. It's hard to follow, especially when\nyou're young. \n[5]\nPrestige is like a powerful magnet that warps\neven your beliefs about what you enjoy. It causes you to work not\non what you like, but what you'd like to like.That's what leads people to try to write novels, for example. They\nlike reading novels. They notice that people who write them win\nNobel prizes. What could be more wonderful, they think, than to\nbe a novelist? But liking the idea of being a novelist is not\nenough; you have to like the actual work of novel-writing if you're\ngoing to be good at it; you have to like making up elaborate lies.Prestige is just fossilized inspiration. If you do anything well\nenough, you'll make it prestigious. Plenty of things we now\nconsider prestigious were anything but at first. Jazz comes to\nmind—though almost any established art form would do. So just\ndo what you like, and let prestige take care of itself.Prestige is especially dangerous to the ambitious. If you want to\nmake ambitious people waste their time on errands, the way to do\nit is to bait the hook with prestige. That's the recipe for getting\npeople to give talks, write forewords, serve on committees, be\ndepartment heads, and so on. It might be a good rule simply to\navoid any prestigious task. If it didn't suck, they wouldn't have\nhad to make it prestigious.Similarly, if you admire two kinds of work equally, but one is more\nprestigious, you should probably choose the other. Your opinions\nabout what's admirable are always going to be slightly influenced\nby prestige, so if the two seem equal to you, you probably have\nmore genuine admiration for the less prestigious one.The other big force leading people astray is money. Money by itself\nis not that dangerous. When something pays well but is regarded\nwith contempt, like telemarketing, or prostitution, or personal\ninjury litigation, ambitious people aren't tempted by it. That\nkind of work ends up being done by people who are \"just trying to\nmake a living.\" (Tip: avoid any field whose practitioners say\nthis.) The danger is when money is combined with prestige, as in,\nsay, corporate law, or medicine. A comparatively safe and prosperous\ncareer with some automatic baseline prestige is dangerously tempting\nto someone young, who hasn't thought much about what they really\nlike.The test of whether people love what they do is whether they'd do\nit even if they weren't paid for it—even if they had to work at\nanother job to make a living. How many corporate lawyers would do\ntheir current work if they had to do it for free, in their spare\ntime, and take day jobs as waiters to support themselves?This test is especially helpful in deciding between different kinds\nof academic work, because fields vary greatly in this respect. Most\ngood mathematicians would work on math even if there were no jobs\nas math professors, whereas in the departments at the other end of\nthe spectrum, the availability of teaching jobs is the driver:\npeople would rather be English professors than work in ad agencies,\nand publishing papers is the way you compete for such jobs. Math\nwould happen without math departments, but it is the existence of\nEnglish majors, and therefore jobs teaching them, that calls into\nbeing all those thousands of dreary papers about gender and identity\nin the novels of Conrad. No one does \nthat \nkind of thing for fun.The advice of parents will tend to err on the side of money. It\nseems safe to say there are more undergrads who want to be novelists\nand whose parents want them to be doctors than who want to be doctors\nand whose parents want them to be novelists. The kids think their\nparents are \"materialistic.\" Not necessarily. All parents tend to\nbe more conservative for their kids than they would for themselves,\nsimply because, as parents, they share risks more than rewards. If\nyour eight year old son decides to climb a tall tree, or your teenage\ndaughter decides to date the local bad boy, you won't get a share\nin the excitement, but if your son falls, or your daughter gets\npregnant, you'll have to deal with the consequences.DisciplineWith such powerful forces leading us astray, it's not surprising\nwe find it so hard to discover what we like to work on. Most people\nare doomed in childhood by accepting the axiom that work = pain.\nThose who escape this are nearly all lured onto the rocks by prestige\nor money. How many even discover something they love to work on?\nA few hundred thousand, perhaps, out of billions.It's hard to find work you love; it must be, if so few do. So don't\nunderestimate this task. And don't feel bad if you haven't succeeded\nyet. In fact, if you admit to yourself that you're discontented,\nyou're a step ahead of most people, who are still in denial. If\nyou're surrounded by colleagues who claim to enjoy work that you\nfind contemptible, odds are they're lying to themselves. Not\nnecessarily, but probably.Although doing great work takes less discipline than people think—because the way to do great work is to find something you like so\nmuch that you don't have to force yourself to do it—finding\nwork you love does usually require discipline. Some people are\nlucky enough to know what they want to do when they're 12, and just\nglide along as if they were on railroad tracks. But this seems the\nexception. More often people who do great things have careers with\nthe trajectory of a ping-pong ball. They go to school to study A,\ndrop out and get a job doing B, and then become famous for C after\ntaking it up on the side.Sometimes jumping from one sort of work to another is a sign of\nenergy, and sometimes it's a sign of laziness. Are you dropping\nout, or boldly carving a new path? You often can't tell yourself.\nPlenty of people who will later do great things seem to be disappointments\nearly on, when they're trying to find their niche.Is there some test you can use to keep yourself honest? One is to\ntry to do a good job at whatever you're doing, even if you don't\nlike it. Then at least you'll know you're not using dissatisfaction\nas an excuse for being lazy. Perhaps more importantly, you'll get\ninto the habit of doing things well.Another test you can use is: always produce. For example, if you\nhave a day job you don't take seriously because you plan to be a\nnovelist, are you producing? Are you writing pages of fiction,\nhowever bad? As long as you're producing, you'll know you're not\nmerely using the hazy vision of the grand novel you plan to write\none day as an opiate. The view of it will be obstructed by the all\ntoo palpably flawed one you're actually writing.\"Always produce\" is also a heuristic for finding the work you love.\nIf you subject yourself to that constraint, it will automatically\npush you away from things you think you're supposed to work on,\ntoward things you actually like. \"Always produce\" will discover\nyour life's work the way water, with the aid of gravity, finds the\nhole in your roof.Of course, figuring out what you like to work on doesn't mean you\nget to work on it. That's a separate question. And if you're\nambitious you have to keep them separate: you have to make a conscious\neffort to keep your ideas about what you want from being contaminated\nby what seems possible. \n[6]It's painful to keep them apart, because it's painful to observe\nthe gap between them. So most people pre-emptively lower their\nexpectations. For example, if you asked random people on the street\nif they'd like to be able to draw like Leonardo, you'd find most\nwould say something like \"Oh, I can't draw.\" This is more a statement\nof intention than fact; it means, I'm not going to try. Because\nthe fact is, if you took a random person off the street and somehow\ngot them to work as hard as they possibly could at drawing for the\nnext twenty years, they'd get surprisingly far. But it would require\na great moral effort; it would mean staring failure in the eye every\nday for years. And so to protect themselves people say \"I can't.\"Another related line you often hear is that not everyone can do\nwork they love—that someone has to do the unpleasant jobs. Really?\nHow do you make them? In the US the only mechanism for forcing\npeople to do unpleasant jobs is the draft, and that hasn't been\ninvoked for over 30 years. All we can do is encourage people to\ndo unpleasant work, with money and prestige.If there's something people still won't do, it seems as if society\njust has to make do without. That's what happened with domestic\nservants. For millennia that was the canonical example of a job\n\"someone had to do.\" And yet in the mid twentieth century servants\npractically disappeared in rich countries, and the rich have just\nhad to do without.So while there may be some things someone has to do, there's a good\nchance anyone saying that about any particular job is mistaken.\nMost unpleasant jobs would either get automated or go undone if no\none were willing to do them.Two RoutesThere's another sense of \"not everyone can do work they love\"\nthat's all too true, however. One has to make a living, and it's\nhard to get paid for doing work you love. There are two routes to\nthat destination:\n\n The organic route: as you become more eminent, gradually to\n increase the parts of your job that you like at the expense of\n those you don't.The two-job route: to work at things you don't like to get money\n to work on things you do.\n\nThe organic route is more common. It happens naturally to anyone\nwho does good work. A young architect has to take whatever work\nhe can get, but if he does well he'll gradually be in a position\nto pick and choose among projects. The disadvantage of this route\nis that it's slow and uncertain. Even tenure is not real freedom.The two-job route has several variants depending on how long you\nwork for money at a time. At one extreme is the \"day job,\" where\nyou work regular hours at one job to make money, and work on what\nyou love in your spare time. At the other extreme you work at\nsomething till you make enough not to \nhave to work for money again.The two-job route is less common than the organic route, because\nit requires a deliberate choice. It's also more dangerous. Life\ntends to get more expensive as you get older, so it's easy to get\nsucked into working longer than you expected at the money job.\nWorse still, anything you work on changes you. If you work too\nlong on tedious stuff, it will rot your brain. And the best paying\njobs are most dangerous, because they require your full attention.The advantage of the two-job route is that it lets you jump over\nobstacles. The landscape of possible jobs isn't flat; there are\nwalls of varying heights between different kinds of work. \n[7]\nThe trick of maximizing the parts of your job that you like can get you\nfrom architecture to product design, but not, probably, to music.\nIf you make money doing one thing and then work on another, you\nhave more freedom of choice.Which route should you take? That depends on how sure you are of\nwhat you want to do, how good you are at taking orders, how much\nrisk you can stand, and the odds that anyone will pay (in your\nlifetime) for what you want to do. If you're sure of the general\narea you want to work in and it's something people are likely to\npay you for, then you should probably take the organic route. But\nif you don't know what you want to work on, or don't like to take\norders, you may want to take the two-job route, if you can stand\nthe risk.Don't decide too soon. Kids who know early what they want to do\nseem impressive, as if they got the answer to some math question\nbefore the other kids. They have an answer, certainly, but odds\nare it's wrong.A friend of mine who is a quite successful doctor complains constantly\nabout her job. When people applying to medical school ask her for\nadvice, she wants to shake them and yell \"Don't do it!\" (But she\nnever does.) How did she get into this fix? In high school she\nalready wanted to be a doctor. And she is so ambitious and determined\nthat she overcame every obstacle along the way—including,\nunfortunately, not liking it.Now she has a life chosen for her by a high-school kid.When you're young, you're given the impression that you'll get\nenough information to make each choice before you need to make it.\nBut this is certainly not so with work. When you're deciding what\nto do, you have to operate on ridiculously incomplete information.\nEven in college you get little idea what various types of work are\nlike. At best you may have a couple internships, but not all jobs\noffer internships, and those that do don't teach you much more about\nthe work than being a batboy teaches you about playing baseball.In the design of lives, as in the design of most other things, you\nget better results if you use flexible media. So unless you're\nfairly sure what you want to do, your best bet may be to choose a\ntype of work that could turn into either an organic or two-job\ncareer. That was probably part of the reason I chose computers.\nYou can be a professor, or make a lot of money, or morph it into\nany number of other kinds of work.It's also wise, early on, to seek jobs that let you do many different\nthings, so you can learn faster what various kinds of work are like.\nConversely, the extreme version of the two-job route is dangerous\nbecause it teaches you so little about what you like. If you work\nhard at being a bond trader for ten years, thinking that you'll\nquit and write novels when you have enough money, what happens when\nyou quit and then discover that you don't actually like writing\nnovels?Most people would say, I'd take that problem. Give me a million\ndollars and I'll figure out what to do. But it's harder than it\nlooks. Constraints give your life shape. Remove them and most\npeople have no idea what to do: look at what happens to those who\nwin lotteries or inherit money. Much as everyone thinks they want\nfinancial security, the happiest people are not those who have it,\nbut those who like what they do. So a plan that promises freedom\nat the expense of knowing what to do with it may not be as good as\nit seems.Whichever route you take, expect a struggle. Finding work you love\nis very difficult. Most people fail. Even if you succeed, it's\nrare to be free to work on what you want till your thirties or\nforties. But if you have the destination in sight you'll be more\nlikely to arrive at it. If you know you can love work, you're in\nthe home stretch, and if you know what work you love, you're\npractically there.Notes[1]\nCurrently we do the opposite: when we make kids do boring work,\nlike arithmetic drills, instead of admitting frankly that it's\nboring, we try to disguise it with superficial decorations.[2]\nOne father told me about a related phenomenon: he found himself\nconcealing from his family how much he liked his work. When he\nwanted to go to work on a saturday, he found it easier to say that\nit was because he \"had to\" for some reason, rather than admitting\nhe preferred to work than stay home with them.[3]\nSomething similar happens with suburbs. Parents move to suburbs\nto raise their kids in a safe environment, but suburbs are so dull\nand artificial that by the time they're fifteen the kids are convinced\nthe whole world is boring.[4]\nI'm not saying friends should be the only audience for your\nwork. The more people you can help, the better. But friends should\nbe your compass.[5]\nDonald Hall said young would-be poets were mistaken to be so\nobsessed with being published. But you can imagine what it would\ndo for a 24 year old to get a poem published in The New Yorker.\nNow to people he meets at parties he's a real poet. Actually he's\nno better or worse than he was before, but to a clueless audience\nlike that, the approval of an official authority makes all the\ndifference. So it's a harder problem than Hall realizes. The\nreason the young care so much about prestige is that the people\nthey want to impress are not very discerning.[6]\nThis is isomorphic to the principle that you should prevent\nyour beliefs about how things are from being contaminated by how\nyou wish they were. Most people let them mix pretty promiscuously.\nThe continuing popularity of religion is the most visible index of\nthat.[7]\nA more accurate metaphor would be to say that the graph of jobs\nis not very well connected.Thanks to Trevor Blackwell, Dan Friedman, Sarah Harlin,\nJessica Livingston, Jackie McDonough, Robert Morris, Peter Norvig, \nDavid Sloo, and Aaron Swartz\nfor reading drafts of this." }, { "path": "data/PaulGrahamEssaysLarge/mod.txt", "content": "December 2019There are two distinct ways to be politically moderate: on purpose\nand by accident. Intentional moderates are trimmers, deliberately\nchoosing a position mid-way between the extremes of right and left.\nAccidental moderates end up in the middle, on average, because they\nmake up their own minds about each question, and the far right and\nfar left are roughly equally wrong.You can distinguish intentional from accidental moderates by the\ndistribution of their opinions. If the far left opinion on some\nmatter is 0 and the far right opinion 100, an intentional moderate's\nopinion on every question will be near 50. Whereas an accidental\nmoderate's opinions will be scattered over a broad range, but will,\nlike those of the intentional moderate, average to about 50.Intentional moderates are similar to those on the far left and the\nfar right in that their opinions are, in a sense, not their own.\nThe defining quality of an ideologue, whether on the left or the\nright, is to acquire one's opinions in bulk. You don't get to pick\nand choose. Your opinions about taxation can be predicted from your\nopinions about sex. And although intentional moderates\nmight seem to be the opposite of ideologues, their beliefs (though\nin their case the word \"positions\" might be more accurate) are also\nacquired in bulk. If the median opinion shifts to the right or left,\nthe intentional moderate must shift with it. Otherwise they stop\nbeing moderate.Accidental moderates, on the other hand, not only choose their own\nanswers, but choose their own questions. They may not care at all\nabout questions that the left and right both think are terribly\nimportant. So you can only even measure the politics of an accidental\nmoderate from the intersection of the questions they care about and\nthose the left and right care about, and this can\nsometimes be vanishingly small.It is not merely a manipulative rhetorical trick to say \"if you're\nnot with us, you're against us,\" but often simply false.Moderates are sometimes derided as cowards, particularly by \nthe extreme left. But while it may be accurate to call intentional\nmoderates cowards, openly being an accidental moderate requires the\nmost courage of all, because you get attacked from both right and\nleft, and you don't have the comfort of being an orthodox member\nof a large group to sustain you.Nearly all the most impressive people I know are accidental moderates.\nIf I knew a lot of professional athletes, or people in the entertainment\nbusiness, that might be different. Being on the far left or far\nright doesn't affect how fast you run or how well you sing. But\nsomeone who works with ideas has to be independent-minded to do it\nwell.Or more precisely, you have to be independent-minded about the ideas\nyou work with. You could be mindlessly doctrinaire in your politics\nand still be a good mathematician. In the 20th century, a lot of\nvery smart people were Marxists — just no one who was smart about\nthe subjects Marxism involves. But if the ideas you use in your\nwork intersect with the politics of your time, you have two choices:\nbe an accidental moderate, or be mediocre.Notes[1] It's possible in theory for one side to be entirely right and\nthe other to be entirely wrong. Indeed, ideologues must always\nbelieve this is the case. But historically it rarely has been.[2] For some reason the far right tend to ignore moderates rather\nthan despise them as backsliders. I'm not sure why. Perhaps it\nmeans that the far right is less ideological than the far left. Or\nperhaps that they are more confident, or more resigned, or simply\nmore disorganized. I just don't know.[3] Having heretical opinions doesn't mean you have to express\nthem openly. It may be\neasier to have them if you don't.\nThanks to Austen Allred, Trevor Blackwell, Patrick Collison, Jessica Livingston,\nAmjad Masad, Ryan Petersen, and Harj Taggar for reading drafts of this." }, { "path": "data/PaulGrahamEssaysLarge/newideas.txt", "content": "May 2021There's one kind of opinion I'd be very afraid to express publicly.\nIf someone I knew to be both a domain expert and a reasonable person\nproposed an idea that sounded preposterous, I'd be very reluctant\nto say \"That will never work.\"Anyone who has studied the history of ideas, and especially the\nhistory of science, knows that's how big things start. Someone\nproposes an idea that sounds crazy, most people dismiss it, then\nit gradually takes over the world.Most implausible-sounding ideas are in fact bad and could be safely\ndismissed. But not when they're proposed by reasonable domain\nexperts. If the person proposing the idea is reasonable, then they\nknow how implausible it sounds. And yet they're proposing it anyway.\nThat suggests they know something you don't. And if they have deep\ndomain expertise, that's probably the source of it.\n[1]Such ideas are not merely unsafe to dismiss, but disproportionately\nlikely to be interesting. When the average person proposes an\nimplausible-sounding idea, its implausibility is evidence of their\nincompetence. But when a reasonable domain expert does it, the\nsituation is reversed. There's something like an efficient market\nhere: on average the ideas that seem craziest will, if correct,\nhave the biggest effect. So if you can eliminate the theory that\nthe person proposing an implausible-sounding idea is incompetent,\nits implausibility switches from evidence that it's boring to\nevidence that it's exciting.\n[2]Such ideas are not guaranteed to work. But they don't have to be.\nThey just have to be sufficiently good bets — to have sufficiently\nhigh expected value. And I think on average they do. I think if you\nbet on the entire set of implausible-sounding ideas proposed by\nreasonable domain experts, you'd end up net ahead.The reason is that everyone is too conservative. The word \"paradigm\"\nis overused, but this is a case where it's warranted. Everyone is\ntoo much in the grip of the current paradigm. Even the people who\nhave the new ideas undervalue them initially. Which means that\nbefore they reach the stage of proposing them publicly, they've\nalready subjected them to an excessively strict filter.\n[3]The wise response to such an idea is not to make statements, but\nto ask questions, because there's a real mystery here. Why has this\nsmart and reasonable person proposed an idea that seems so wrong?\nAre they mistaken, or are you? One of you has to be. If you're the\none who's mistaken, that would be good to know, because it means\nthere's a hole in your model of the world. But even if they're\nmistaken, it should be interesting to learn why. A trap that an\nexpert falls into is one you have to worry about too.This all seems pretty obvious. And yet there are clearly a lot of\npeople who don't share my fear of dismissing new ideas. Why do they\ndo it? Why risk looking like a jerk now and a fool later, instead\nof just reserving judgement?One reason they do it is envy. If you propose a radical new idea\nand it succeeds, your reputation (and perhaps also your wealth)\nwill increase proportionally. Some people would be envious if that\nhappened, and this potential envy propagates back into a conviction\nthat you must be wrong.Another reason people dismiss new ideas is that it's an easy way\nto seem sophisticated. When a new idea first emerges, it usually\nseems pretty feeble. It's a mere hatchling. Received wisdom is a\nfull-grown eagle by comparison. So it's easy to launch a devastating\nattack on a new idea, and anyone who does will seem clever to those\nwho don't understand this asymmetry.This phenomenon is exacerbated by the difference between how those\nworking on new ideas and those attacking them are rewarded. The\nrewards for working on new ideas are weighted by the value of the\noutcome. So it's worth working on something that only has a 10%\nchance of succeeding if it would make things more than 10x better.\nWhereas the rewards for attacking new ideas are roughly constant;\nsuch attacks seem roughly equally clever regardless of the target.People will also attack new ideas when they have a vested interest\nin the old ones. It's not surprising, for example, that some of\nDarwin's harshest critics were churchmen. People build whole careers\non some ideas. When someone claims they're false or obsolete, they\nfeel threatened.The lowest form of dismissal is mere factionalism: to automatically\ndismiss any idea associated with the opposing faction. The lowest\nform of all is to dismiss an idea because of who proposed it.But the main thing that leads reasonable people to dismiss new ideas\nis the same thing that holds people back from proposing them: the\nsheer pervasiveness of the current paradigm. It doesn't just affect\nthe way we think; it is the Lego blocks we build thoughts out of.\nPopping out of the current paradigm is something only a few people\ncan do. And even they usually have to suppress their intuitions at\nfirst, like a pilot flying through cloud who has to trust his\ninstruments over his sense of balance.\n[4]Paradigms don't just define our present thinking. They also vacuum\nup the trail of crumbs that led to them, making our standards for\nnew ideas impossibly high. The current paradigm seems so perfect\nto us, its offspring, that we imagine it must have been accepted\ncompletely as soon as it was discovered — that whatever the church thought\nof the heliocentric model, astronomers must have been convinced as\nsoon as Copernicus proposed it. Far, in fact, from it. Copernicus\npublished the heliocentric model in 1532, but it wasn't till the\nmid seventeenth century that the balance of scientific opinion\nshifted in its favor.\n[5]Few understand how feeble new ideas look when they first appear.\nSo if you want to have new ideas yourself, one of the most valuable\nthings you can do is to learn what they look like when they're born.\nRead about how new ideas happened, and try to get yourself into the\nheads of people at the time. How did things look to them, when the\nnew idea was only half-finished, and even the person who had it was\nonly half-convinced it was right?But you don't have to stop at history. You can observe big new ideas\nbeing born all around you right now. Just look for a reasonable\ndomain expert proposing something that sounds wrong.If you're nice, as well as wise, you won't merely resist attacking\nsuch people, but encourage them. Having new ideas is a lonely\nbusiness. Only those who've tried it know how lonely. These people\nneed your help. And if you help them, you'll probably learn something\nin the process.Notes[1]\nThis domain expertise could be in another field. Indeed,\nsuch crossovers tend to be particularly promising.[2]\nI'm not claiming this principle extends much beyond math,\nengineering, and the hard sciences. In politics, for example,\ncrazy-sounding ideas generally are as bad as they sound. Though\narguably this is not an exception, because the people who propose\nthem are not in fact domain experts; politicians are domain experts\nin political tactics, like how to get elected and how to get\nlegislation passed, but not in the world that policy acts upon.\nPerhaps no one could be.[3]\nThis sense of \"paradigm\" was defined by Thomas Kuhn in his\nStructure of Scientific Revolutions, but I also recommend his\nCopernican Revolution, where you can see him at work developing the\nidea.[4]\nThis is one reason people with a touch of Asperger's may have\nan advantage in discovering new ideas. They're always flying on\ninstruments.[5]\nHall, Rupert. From Galileo to Newton. Collins, 1963. This\nbook is particularly good at getting into contemporaries' heads.Thanks to Trevor Blackwell, Patrick Collison, Suhail Doshi, Daniel\nGackle, Jessica Livingston, and Robert Morris for reading drafts of this." }, { "path": "data/PaulGrahamEssaysLarge/nft.txt", "content": "May 2021Noora Health, a nonprofit I've \nsupported for years, just launched\na new NFT. It has a dramatic name, Save Thousands of Lives,\nbecause that's what the proceeds will do.Noora has been saving lives for 7 years. They run programs in\nhospitals in South Asia to teach new mothers how to take care of\ntheir babies once they get home. They're in 165 hospitals now. And\nbecause they know the numbers before and after they start at a new\nhospital, they can measure the impact they have. It is massive.\nFor every 1000 live births, they save 9 babies.This number comes from a study\nof 133,733 families at 28 different\nhospitals that Noora conducted in collaboration with the Better\nBirth team at Ariadne Labs, a joint center for health systems\ninnovation at Brigham and Women’s Hospital and Harvard T.H. Chan\nSchool of Public Health.Noora is so effective that even if you measure their costs in the\nmost conservative way, by dividing their entire budget by the number\nof lives saved, the cost of saving a life is the lowest I've seen.\n$1,235.For this NFT, they're going to issue a public report tracking how\nthis specific tranche of money is spent, and estimating the number\nof lives saved as a result.NFTs are a new territory, and this way of using them is especially\nnew, but I'm excited about its potential. And I'm excited to see\nwhat happens with this particular auction, because unlike an NFT\nrepresenting something that has already happened,\nthis NFT gets better as the price gets higher.The reserve price was about $2.5 million, because that's what it\ntakes for the name to be accurate: that's what it costs to save\n2000 lives. But the higher the price of this NFT goes, the more\nlives will be saved. What a sentence to be able to write." }, { "path": "data/PaulGrahamEssaysLarge/philosophy.txt", "content": "September 2007In high school I decided I was going to study philosophy in college.\nI had several motives, some more honorable than others. One of the\nless honorable was to shock people. College was regarded as job\ntraining where I grew up, so studying philosophy seemed an impressively\nimpractical thing to do. Sort of like slashing holes in your clothes\nor putting a safety pin through your ear, which were other forms\nof impressive impracticality then just coming into fashion.But I had some more honest motives as well. I thought studying\nphilosophy would be a shortcut straight to wisdom. All the people\nmajoring in other things would just end up with a bunch of domain\nknowledge. I would be learning what was really what.I'd tried to read a few philosophy books. Not recent ones; you\nwouldn't find those in our high school library. But I tried to\nread Plato and Aristotle. I doubt I believed I understood them,\nbut they sounded like they were talking about something important.\nI assumed I'd learn what in college.The summer before senior year I took some college classes. I learned\na lot in the calculus class, but I didn't learn much in Philosophy\n101. And yet my plan to study philosophy remained intact. It was\nmy fault I hadn't learned anything. I hadn't read the books we\nwere assigned carefully enough. I'd give Berkeley's Principles\nof Human Knowledge another shot in college. Anything so admired\nand so difficult to read must have something in it, if one could\nonly figure out what.Twenty-six years later, I still don't understand Berkeley. I have\na nice edition of his collected works. Will I ever read it? Seems\nunlikely.The difference between then and now is that now I understand why\nBerkeley is probably not worth trying to understand. I think I see\nnow what went wrong with philosophy, and how we might fix it.WordsI did end up being a philosophy major for most of college. It\ndidn't work out as I'd hoped. I didn't learn any magical truths\ncompared to which everything else was mere domain knowledge. But\nI do at least know now why I didn't. Philosophy doesn't really\nhave a subject matter in the way math or history or most other\nuniversity subjects do. There is no core of knowledge one must\nmaster. The closest you come to that is a knowledge of what various\nindividual philosophers have said about different topics over the\nyears. Few were sufficiently correct that people have forgotten\nwho discovered what they discovered.Formal logic has some subject matter. I took several classes in\nlogic. I don't know if I learned anything from them.\n[1]\nIt does seem to me very important to be able to flip ideas around in\none's head: to see when two ideas don't fully cover the space of\npossibilities, or when one idea is the same as another but with a\ncouple things changed. But did studying logic teach me the importance\nof thinking this way, or make me any better at it? I don't know.There are things I know I learned from studying philosophy. The\nmost dramatic I learned immediately, in the first semester of\nfreshman year, in a class taught by Sydney Shoemaker. I learned\nthat I don't exist. I am (and you are) a collection of cells that\nlurches around driven by various forces, and calls itself I. But\nthere's no central, indivisible thing that your identity goes with.\nYou could conceivably lose half your brain and live. Which means\nyour brain could conceivably be split into two halves and each\ntransplanted into different bodies. Imagine waking up after such\nan operation. You have to imagine being two people.The real lesson here is that the concepts we use in everyday life\nare fuzzy, and break down if pushed too hard. Even a concept as\ndear to us as I. It took me a while to grasp this, but when I\ndid it was fairly sudden, like someone in the nineteenth century\ngrasping evolution and realizing the story of creation they'd been\ntold as a child was all wrong. \n[2]\nOutside of math there's a limit\nto how far you can push words; in fact, it would not be a bad\ndefinition of math to call it the study of terms that have precise\nmeanings. Everyday words are inherently imprecise. They work well\nenough in everyday life that you don't notice. Words seem to work,\njust as Newtonian physics seems to. But you can always make them\nbreak if you push them far enough.I would say that this has been, unfortunately for philosophy, the\ncentral fact of philosophy. Most philosophical debates are not\nmerely afflicted by but driven by confusions over words. Do we\nhave free will? Depends what you mean by \"free.\" Do abstract ideas\nexist? Depends what you mean by \"exist.\"Wittgenstein is popularly credited with the idea that most philosophical\ncontroversies are due to confusions over language. I'm not sure\nhow much credit to give him. I suspect a lot of people realized\nthis, but reacted simply by not studying philosophy, rather than\nbecoming philosophy professors.How did things get this way? Can something people have spent\nthousands of years studying really be a waste of time? Those are\ninteresting questions. In fact, some of the most interesting\nquestions you can ask about philosophy. The most valuable way to\napproach the current philosophical tradition may be neither to get\nlost in pointless speculations like Berkeley, nor to shut them down\nlike Wittgenstein, but to study it as an example of reason gone\nwrong.HistoryWestern philosophy really begins with Socrates, Plato, and Aristotle.\nWhat we know of their predecessors comes from fragments and references\nin later works; their doctrines could be described as speculative\ncosmology that occasionally strays into analysis. Presumably they\nwere driven by whatever makes people in every other society invent\ncosmologies.\n[3]With Socrates, Plato, and particularly Aristotle, this tradition\nturned a corner. There started to be a lot more analysis. I suspect\nPlato and Aristotle were encouraged in this by progress in math.\nMathematicians had by then shown that you could figure things out\nin a much more conclusive way than by making up fine sounding stories\nabout them. \n[4]People talk so much about abstractions now that we don't realize\nwhat a leap it must have been when they first started to. It was\npresumably many thousands of years between when people first started\ndescribing things as hot or cold and when someone asked \"what is\nheat?\" No doubt it was a very gradual process. We don't know if\nPlato or Aristotle were the first to ask any of the questions they\ndid. But their works are the oldest we have that do this on a large\nscale, and there is a freshness (not to say naivete) about them\nthat suggests some of the questions they asked were new to them,\nat least.Aristotle in particular reminds me of the phenomenon that happens\nwhen people discover something new, and are so excited by it that\nthey race through a huge percentage of the newly discovered territory\nin one lifetime. If so, that's evidence of how new this kind of\nthinking was. \n[5]This is all to explain how Plato and Aristotle can be very impressive\nand yet naive and mistaken. It was impressive even to ask the\nquestions they did. That doesn't mean they always came up with\ngood answers. It's not considered insulting to say that ancient\nGreek mathematicians were naive in some respects, or at least lacked\nsome concepts that would have made their lives easier. So I hope\npeople will not be too offended if I propose that ancient philosophers\nwere similarly naive. In particular, they don't seem to have fully\ngrasped what I earlier called the central fact of philosophy: that\nwords break if you push them too far.\"Much to the surprise of the builders of the first digital computers,\"\nRod Brooks wrote, \"programs written for them usually did not work.\"\n[6]\nSomething similar happened when people first started trying\nto talk about abstractions. Much to their surprise, they didn't\narrive at answers they agreed upon. In fact, they rarely seemed\nto arrive at answers at all.They were in effect arguing about artifacts induced by sampling at\ntoo low a resolution.The proof of how useless some of their answers turned out to be is\nhow little effect they have. No one after reading Aristotle's\nMetaphysics does anything differently as a result.\n[7]Surely I'm not claiming that ideas have to have practical applications\nto be interesting? No, they may not have to. Hardy's boast that\nnumber theory had no use whatsoever wouldn't disqualify it. But\nhe turned out to be mistaken. In fact, it's suspiciously hard to\nfind a field of math that truly has no practical use. And Aristotle's\nexplanation of the ultimate goal of philosophy in Book A of the\nMetaphysics implies that philosophy should be useful too.Theoretical KnowledgeAristotle's goal was to find the most general of general principles.\nThe examples he gives are convincing: an ordinary worker builds\nthings a certain way out of habit; a master craftsman can do more\nbecause he grasps the underlying principles. The trend is clear:\nthe more general the knowledge, the more admirable it is. But then\nhe makes a mistake—possibly the most important mistake in the\nhistory of philosophy. He has noticed that theoretical knowledge\nis often acquired for its own sake, out of curiosity, rather than\nfor any practical need. So he proposes there are two kinds of\ntheoretical knowledge: some that's useful in practical matters and\nsome that isn't. Since people interested in the latter are interested\nin it for its own sake, it must be more noble. So he sets as his\ngoal in the Metaphysics the exploration of knowledge that has no\npractical use. Which means no alarms go off when he takes on grand\nbut vaguely understood questions and ends up getting lost in a sea\nof words.His mistake was to confuse motive and result. Certainly, people\nwho want a deep understanding of something are often driven by\ncuriosity rather than any practical need. But that doesn't mean\nwhat they end up learning is useless. It's very valuable in practice\nto have a deep understanding of what you're doing; even if you're\nnever called on to solve advanced problems, you can see shortcuts\nin the solution of simple ones, and your knowledge won't break down\nin edge cases, as it would if you were relying on formulas you\ndidn't understand. Knowledge is power. That's what makes theoretical\nknowledge prestigious. It's also what causes smart people to be\ncurious about certain things and not others; our DNA is not so\ndisinterested as we might think.So while ideas don't have to have immediate practical applications\nto be interesting, the kinds of things we find interesting will\nsurprisingly often turn out to have practical applications.The reason Aristotle didn't get anywhere in the Metaphysics was\npartly that he set off with contradictory aims: to explore the most\nabstract ideas, guided by the assumption that they were useless.\nHe was like an explorer looking for a territory to the north of\nhim, starting with the assumption that it was located to the south.And since his work became the map used by generations of future\nexplorers, he sent them off in the wrong direction as well. \n[8]\nPerhaps worst of all, he protected them from both the criticism of\noutsiders and the promptings of their own inner compass by establishing\nthe principle that the most noble sort of theoretical knowledge had\nto be useless.The Metaphysics is mostly a failed experiment. A few ideas from\nit turned out to be worth keeping; the bulk of it has had no effect\nat all. The Metaphysics is among the least read of all famous\nbooks. It's not hard to understand the way Newton's Principia\nis, but the way a garbled message is.Arguably it's an interesting failed experiment. But unfortunately\nthat was not the conclusion Aristotle's successors derived from\nworks like the Metaphysics. \n[9]\nSoon after, the western world\nfell on intellectual hard times. Instead of version 1s to be\nsuperseded, the works of Plato and Aristotle became revered texts\nto be mastered and discussed. And so things remained for a shockingly\nlong time. It was not till around 1600 (in Europe, where the center\nof gravity had shifted by then) that one found people confident\nenough to treat Aristotle's work as a catalog of mistakes. And\neven then they rarely said so outright.If it seems surprising that the gap was so long, consider how little\nprogress there was in math between Hellenistic times and the\nRenaissance.In the intervening years an unfortunate idea took hold: that it\nwas not only acceptable to produce works like the Metaphysics,\nbut that it was a particularly prestigious line of work, done by a\nclass of people called philosophers. No one thought to go back and\ndebug Aristotle's motivating argument. And so instead of correcting\nthe problem Aristotle discovered by falling into it—that you can\neasily get lost if you talk too loosely about very abstract ideas—they \ncontinued to fall into it.The SingularityCuriously, however, the works they produced continued to attract\nnew readers. Traditional philosophy occupies a kind of singularity\nin this respect. If you write in an unclear way about big ideas,\nyou produce something that seems tantalizingly attractive to\ninexperienced but intellectually ambitious students. Till one knows\nbetter, it's hard to distinguish something that's hard to understand\nbecause the writer was unclear in his own mind from something like\na mathematical proof that's hard to understand because the ideas\nit represents are hard to understand. To someone who hasn't learned\nthe difference, traditional philosophy seems extremely attractive:\nas hard (and therefore impressive) as math, yet broader in scope.\nThat was what lured me in as a high school student.This singularity is even more singular in having its own defense\nbuilt in. When things are hard to understand, people who suspect\nthey're nonsense generally keep quiet. There's no way to prove a\ntext is meaningless. The closest you can get is to show that the\nofficial judges of some class of texts can't distinguish them from\nplacebos. \n[10]And so instead of denouncing philosophy, most people who suspected\nit was a waste of time just studied other things. That alone is\nfairly damning evidence, considering philosophy's claims. It's\nsupposed to be about the ultimate truths. Surely all smart people\nwould be interested in it, if it delivered on that promise.Because philosophy's flaws turned away the sort of people who might\nhave corrected them, they tended to be self-perpetuating. Bertrand\nRussell wrote in a letter in 1912:\n\n Hitherto the people attracted to philosophy have been mostly those\n who loved the big generalizations, which were all wrong, so that\n few people with exact minds have taken up the subject.\n[11]\n\nHis response was to launch Wittgenstein at it, with dramatic results.I think Wittgenstein deserves to be famous not for the discovery\nthat most previous philosophy was a waste of time, which judging\nfrom the circumstantial evidence must have been made by every smart\nperson who studied a little philosophy and declined to pursue it\nfurther, but for how he acted in response.\n[12]\nInstead of quietly\nswitching to another field, he made a fuss, from inside. He was\nGorbachev.The field of philosophy is still shaken from the fright Wittgenstein\ngave it. \n[13]\nLater in life he spent a lot of time talking about\nhow words worked. Since that seems to be allowed, that's what a\nlot of philosophers do now. Meanwhile, sensing a vacuum in the\nmetaphysical speculation department, the people who used to do\nliterary criticism have been edging Kantward, under new names like\n\"literary theory,\" \"critical theory,\" and when they're feeling\nambitious, plain \"theory.\" The writing is the familiar word salad:\n\n Gender is not like some of the other grammatical modes which\n express precisely a mode of conception without any reality that\n corresponds to the conceptual mode, and consequently do not express\n precisely something in reality by which the intellect could be\n moved to conceive a thing the way it does, even where that motive\n is not something in the thing as such.\n [14]\n\nThe singularity I've described is not going away. There's a market\nfor writing that sounds impressive and can't be disproven. There\nwill always be both supply and demand. So if one group abandons\nthis territory, there will always be others ready to occupy it.A ProposalWe may be able to do better. Here's an intriguing possibility.\nPerhaps we should do what Aristotle meant to do, instead of what\nhe did. The goal he announces in the Metaphysics seems one worth\npursuing: to discover the most general truths. That sounds good.\nBut instead of trying to discover them because they're useless,\nlet's try to discover them because they're useful.I propose we try again, but that we use that heretofore despised\ncriterion, applicability, as a guide to keep us from wondering\noff into a swamp of abstractions. Instead of trying to answer the\nquestion:\n\n What are the most general truths?\n\nlet's try to answer the question\n\n Of all the useful things we can say, which are the most general?\n\nThe test of utility I propose is whether we cause people who read\nwhat we've written to do anything differently afterward. Knowing\nwe have to give definite (if implicit) advice will keep us from\nstraying beyond the resolution of the words we're using.The goal is the same as Aristotle's; we just approach it from a\ndifferent direction.As an example of a useful, general idea, consider that of the\ncontrolled experiment. There's an idea that has turned out to be\nwidely applicable. Some might say it's part of science, but it's\nnot part of any specific science; it's literally meta-physics (in\nour sense of \"meta\"). The idea of evolution is another. It turns\nout to have quite broad applications—for example, in genetic\nalgorithms and even product design. Frankfurt's distinction between\nlying and bullshitting seems a promising recent example.\n[15]These seem to me what philosophy should look like: quite general\nobservations that would cause someone who understood them to do\nsomething differently.Such observations will necessarily be about things that are imprecisely\ndefined. Once you start using words with precise meanings, you're\ndoing math. So starting from utility won't entirely solve the\nproblem I described above—it won't flush out the metaphysical\nsingularity. But it should help. It gives people with good\nintentions a new roadmap into abstraction. And they may thereby\nproduce things that make the writing of the people with bad intentions\nlook bad by comparison.One drawback of this approach is that it won't produce the sort of\nwriting that gets you tenure. And not just because it's not currently\nthe fashion. In order to get tenure in any field you must not\narrive at conclusions that members of tenure committees can disagree\nwith. In practice there are two kinds of solutions to this problem.\nIn math and the sciences, you can prove what you're saying, or at\nany rate adjust your conclusions so you're not claiming anything\nfalse (\"6 of 8 subjects had lower blood pressure after the treatment\").\nIn the humanities you can either avoid drawing any definite conclusions\n(e.g. conclude that an issue is a complex one), or draw conclusions\nso narrow that no one cares enough to disagree with you.The kind of philosophy I'm advocating won't be able to take either\nof these routes. At best you'll be able to achieve the essayist's\nstandard of proof, not the mathematician's or the experimentalist's.\nAnd yet you won't be able to meet the usefulness test without\nimplying definite and fairly broadly applicable conclusions. Worse\nstill, the usefulness test will tend to produce results that annoy\npeople: there's no use in telling people things they already believe,\nand people are often upset to be told things they don't.Here's the exciting thing, though. Anyone can do this. Getting\nto general plus useful by starting with useful and cranking up the\ngenerality may be unsuitable for junior professors trying to get\ntenure, but it's better for everyone else, including professors who\nalready have it. This side of the mountain is a nice gradual slope.\nYou can start by writing things that are useful but very specific,\nand then gradually make them more general. Joe's has good burritos.\nWhat makes a good burrito? What makes good food? What makes\nanything good? You can take as long as you want. You don't have\nto get all the way to the top of the mountain. You don't have to\ntell anyone you're doing philosophy.If it seems like a daunting task to do philosophy, here's an\nencouraging thought. The field is a lot younger than it seems.\nThough the first philosophers in the western tradition lived about\n2500 years ago, it would be misleading to say the field is 2500\nyears old, because for most of that time the leading practitioners\nweren't doing much more than writing commentaries on Plato or\nAristotle while watching over their shoulders for the next invading\narmy. In the times when they weren't, philosophy was hopelessly\nintermingled with religion. It didn't shake itself free till a\ncouple hundred years ago, and even then was afflicted by the\nstructural problems I've described above. If I say this, some will\nsay it's a ridiculously overbroad and uncharitable generalization,\nand others will say it's old news, but here goes: judging from their\nworks, most philosophers up to the present have been wasting their\ntime. So in a sense the field is still at the first step. \n[16]That sounds a preposterous claim to make. It won't seem so\npreposterous in 10,000 years. Civilization always seems old, because\nit's always the oldest it's ever been. The only way to say whether\nsomething is really old or not is by looking at structural evidence,\nand structurally philosophy is young; it's still reeling from the\nunexpected breakdown of words.Philosophy is as young now as math was in 1500. There is a lot\nmore to discover.Notes\n[1]\nIn practice formal logic is not much use, because despite\nsome progress in the last 150 years we're still only able to formalize\na small percentage of statements. We may never do that much better,\nfor the same reason 1980s-style \"knowledge representation\" could\nnever have worked; many statements may have no representation more\nconcise than a huge, analog brain state.[2]\nIt was harder for Darwin's contemporaries to grasp this than\nwe can easily imagine. The story of creation in the Bible is not\njust a Judeo-Christian concept; it's roughly what everyone must\nhave believed since before people were people. The hard part of\ngrasping evolution was to realize that species weren't, as they\nseem to be, unchanging, but had instead evolved from different,\nsimpler organisms over unimaginably long periods of time.Now we don't have to make that leap. No one in an industrialized\ncountry encounters the idea of evolution for the first time as an\nadult. Everyone's taught about it as a child, either as truth or\nheresy.[3]\nGreek philosophers before Plato wrote in verse. This must\nhave affected what they said. If you try to write about the nature\nof the world in verse, it inevitably turns into incantation. Prose\nlets you be more precise, and more tentative.[4]\nPhilosophy is like math's\nne'er-do-well brother. It was born when Plato and Aristotle looked\nat the works of their predecessors and said in effect \"why can't\nyou be more like your brother?\" Russell was still saying the same\nthing 2300 years later.Math is the precise half of the most abstract ideas, and philosophy\nthe imprecise half. It's probably inevitable that philosophy will\nsuffer by comparison, because there's no lower bound to its precision.\nBad math is merely boring, whereas bad philosophy is nonsense. And\nyet there are some good ideas in the imprecise half.[5]\nAristotle's best work was in logic and zoology, both of which\nhe can be said to have invented. But the most dramatic departure\nfrom his predecessors was a new, much more analytical style of\nthinking. He was arguably the first scientist.[6]\nBrooks, Rodney, Programming in Common Lisp, Wiley, 1985, p.\n94.[7]\nSome would say we depend on Aristotle more than we realize,\nbecause his ideas were one of the ingredients in our common culture.\nCertainly a lot of the words we use have a connection with Aristotle,\nbut it seems a bit much to suggest that we wouldn't have the concept\nof the essence of something or the distinction between matter and\nform if Aristotle hadn't written about them.One way to see how much we really depend on Aristotle would be to\ndiff European culture with Chinese: what ideas did European culture\nhave in 1800 that Chinese culture didn't, in virtue of Aristotle's\ncontribution?[8]\nThe meaning of the word \"philosophy\" has changed over time.\nIn ancient times it covered a broad range of topics, comparable in\nscope to our \"scholarship\" (though without the methodological\nimplications). Even as late as Newton's time it included what we\nnow call \"science.\" But core of the subject today is still what\nseemed to Aristotle the core: the attempt to discover the most\ngeneral truths.Aristotle didn't call this \"metaphysics.\" That name got assigned\nto it because the books we now call the Metaphysics came after\n(meta = after) the Physics in the standard edition of Aristotle's\nworks compiled by Andronicus of Rhodes three centuries later. What\nwe call \"metaphysics\" Aristotle called \"first philosophy.\"[9]\nSome of Aristotle's immediate successors may have realized\nthis, but it's hard to say because most of their works are lost.[10]\nSokal, Alan, \"Transgressing the Boundaries: Toward a Transformative\nHermeneutics of Quantum Gravity,\" Social Text 46/47, pp. 217-252.Abstract-sounding nonsense seems to be most attractive when it's\naligned with some axe the audience already has to grind. If this\nis so we should find it's most popular with groups that are (or\nfeel) weak. The powerful don't need its reassurance.[11]\nLetter to Ottoline Morrell, December 1912. Quoted in:Monk, Ray, Ludwig Wittgenstein: The Duty of Genius, Penguin, 1991,\np. 75.[12]\nA preliminary result, that all metaphysics between Aristotle\nand 1783 had been a waste of time, is due to I. Kant.[13]\nWittgenstein asserted a sort of mastery to which the inhabitants\nof early 20th century Cambridge seem to have been peculiarly\nvulnerable—perhaps partly because so many had been raised religious\nand then stopped believing, so had a vacant space in their heads\nfor someone to tell them what to do (others chose Marx or Cardinal\nNewman), and partly because a quiet, earnest place like Cambridge\nin that era had no natural immunity to messianic figures, just as\nEuropean politics then had no natural immunity to dictators.[14]\nThis is actually from the Ordinatio of Duns Scotus (ca.\n1300), with \"number\" replaced by \"gender.\" Plus ca change.Wolter, Allan (trans), Duns Scotus: Philosophical Writings, Nelson,\n1963, p. 92.[15]\nFrankfurt, Harry, On Bullshit, Princeton University Press,\n2005.[16]\nSome introductions to philosophy now take the line that\nphilosophy is worth studying as a process rather than for any\nparticular truths you'll learn. The philosophers whose works they\ncover would be rolling in their graves at that. They hoped they\nwere doing more than serving as examples of how to argue: they hoped\nthey were getting results. Most were wrong, but it doesn't seem\nan impossible hope.This argument seems to me like someone in 1500 looking at the lack\nof results achieved by alchemy and saying its value was as a process.\nNo, they were going about it wrong. It turns out it is possible\nto transmute lead into gold (though not economically at current\nenergy prices), but the route to that knowledge was to\nbacktrack and try another approach.Thanks to Trevor Blackwell, Paul Buchheit, Jessica Livingston, \nRobert Morris, Mark Nitzberg, and Peter Norvig for reading drafts of this." }, { "path": "data/PaulGrahamEssaysLarge/popular.txt", "content": "May 2001(This article was written as a kind of business plan for a\nnew language.\nSo it is missing (because it takes for granted) the most important\nfeature of a good programming language: very powerful abstractions.)A friend of mine once told an eminent operating systems\nexpert that he wanted to design a really good\nprogramming language. The expert told him that it would be a\nwaste of time, that programming languages don't become popular\nor unpopular based on their merits, and so no matter how\ngood his language was, no one would use it. At least, that\nwas what had happened to the language he had designed.What does make a language popular? Do popular\nlanguages deserve their popularity? Is it worth trying to\ndefine a good programming language? How would you do it?I think the answers to these questions can be found by looking \nat hackers, and learning what they want. Programming\nlanguages are for hackers, and a programming language\nis good as a programming language (rather than, say, an\nexercise in denotational semantics or compiler design)\nif and only if hackers like it.1 The Mechanics of PopularityIt's true, certainly, that most people don't choose programming\nlanguages simply based on their merits. Most programmers are told\nwhat language to use by someone else. And yet I think the effect\nof such external factors on the popularity of programming languages\nis not as great as it's sometimes thought to be. I think a bigger\nproblem is that a hacker's idea of a good programming language is\nnot the same as most language designers'.Between the two, the hacker's opinion is the one that matters.\nProgramming languages are not theorems. They're tools, designed\nfor people, and they have to be designed to suit human strengths\nand weaknesses as much as shoes have to be designed for human feet.\nIf a shoe pinches when you put it on, it's a bad shoe, however\nelegant it may be as a piece of sculpture.It may be that the majority of programmers can't tell a good language\nfrom a bad one. But that's no different with any other tool. It\ndoesn't mean that it's a waste of time to try designing a good\nlanguage. Expert hackers \ncan tell a good language when they see\none, and they'll use it. Expert hackers are a tiny minority,\nadmittedly, but that tiny minority write all the good software,\nand their influence is such that the rest of the programmers will\ntend to use whatever language they use. Often, indeed, it is not\nmerely influence but command: often the expert hackers are the very\npeople who, as their bosses or faculty advisors, tell the other\nprogrammers what language to use.The opinion of expert hackers is not the only force that determines\nthe relative popularity of programming languages — legacy software\n(Cobol) and hype (Ada, Java) also play a role — but I think it is\nthe most powerful force over the long term. Given an initial critical\nmass and enough time, a programming language probably becomes about\nas popular as it deserves to be. And popularity further separates\ngood languages from bad ones, because feedback from real live users\nalways leads to improvements. Look at how much any popular language\nhas changed during its life. Perl and Fortran are extreme cases,\nbut even Lisp has changed a lot. Lisp 1.5 didn't have macros, for\nexample; these evolved later, after hackers at MIT had spent a\ncouple years using Lisp to write real programs. [1]So whether or not a language has to be good to be popular, I think\na language has to be popular to be good. And it has to stay popular\nto stay good. The state of the art in programming languages doesn't\nstand still. And yet the Lisps we have today are still pretty much\nwhat they had at MIT in the mid-1980s, because that's the last time\nLisp had a sufficiently large and demanding user base.Of course, hackers have to know about a language before they can\nuse it. How are they to hear? From other hackers. But there has to\nbe some initial group of hackers using the language for others even\nto hear about it. I wonder how large this group has to be; how many\nusers make a critical mass? Off the top of my head, I'd say twenty.\nIf a language had twenty separate users, meaning twenty users who\ndecided on their own to use it, I'd consider it to be real.Getting there can't be easy. I would not be surprised if it is\nharder to get from zero to twenty than from twenty to a thousand.\nThe best way to get those initial twenty users is probably to use\na trojan horse: to give people an application they want, which\nhappens to be written in the new language.2 External FactorsLet's start by acknowledging one external factor that does affect\nthe popularity of a programming language. To become popular, a\nprogramming language has to be the scripting language of a popular\nsystem. Fortran and Cobol were the scripting languages of early\nIBM mainframes. C was the scripting language of Unix, and so, later,\nwas Perl. Tcl is the scripting language of Tk. Java and Javascript\nare intended to be the scripting languages of web browsers.Lisp is not a massively popular language because it is not the\nscripting language of a massively popular system. What popularity\nit retains dates back to the 1960s and 1970s, when it was the\nscripting language of MIT. A lot of the great programmers of the\nday were associated with MIT at some point. And in the early 1970s,\nbefore C, MIT's dialect of Lisp, called MacLisp, was one of the\nonly programming languages a serious hacker would want to use.Today Lisp is the scripting language of two moderately popular\nsystems, Emacs and Autocad, and for that reason I suspect that most\nof the Lisp programming done today is done in Emacs Lisp or AutoLisp.Programming languages don't exist in isolation. To hack is a\ntransitive verb — hackers are usually hacking something — and in\npractice languages are judged relative to whatever they're used to\nhack. So if you want to design a popular language, you either have\nto supply more than a language, or you have to design your language\nto replace the scripting language of some existing system.Common Lisp is unpopular partly because it's an orphan. It did\noriginally come with a system to hack: the Lisp Machine. But Lisp\nMachines (along with parallel computers) were steamrollered by the\nincreasing power of general purpose processors in the 1980s. Common\nLisp might have remained popular if it had been a good scripting\nlanguage for Unix. It is, alas, an atrociously bad one.One way to describe this situation is to say that a language isn't\njudged on its own merits. Another view is that a programming language\nreally isn't a programming language unless it's also the scripting\nlanguage of something. This only seems unfair if it comes as a\nsurprise. I think it's no more unfair than expecting a programming\nlanguage to have, say, an implementation. It's just part of what\na programming language is.A programming language does need a good implementation, of course,\nand this must be free. Companies will pay for software, but individual\nhackers won't, and it's the hackers you need to attract.A language also needs to have a book about it. The book should be\nthin, well-written, and full of good examples. K&R is the ideal\nhere. At the moment I'd almost say that a language has to have a\nbook published by O'Reilly. That's becoming the test of mattering\nto hackers.There should be online documentation as well. In fact, the book\ncan start as online documentation. But I don't think that physical\nbooks are outmoded yet. Their format is convenient, and the de\nfacto censorship imposed by publishers is a useful if imperfect\nfilter. Bookstores are one of the most important places for learning\nabout new languages.3 BrevityGiven that you can supply the three things any language needs — a\nfree implementation, a book, and something to hack — how do you\nmake a language that hackers will like?One thing hackers like is brevity. Hackers are lazy, in the same\nway that mathematicians and modernist architects are lazy: they\nhate anything extraneous. It would not be far from the truth to\nsay that a hacker about to write a program decides what language\nto use, at least subconsciously, based on the total number of\ncharacters he'll have to type. If this isn't precisely how hackers\nthink, a language designer would do well to act as if it were.It is a mistake to try to baby the user with long-winded expressions\nthat are meant to resemble English. Cobol is notorious for this\nflaw. A hacker would consider being asked to writeadd x to y giving zinstead ofz = x+yas something between an insult to his intelligence and a sin against\nGod.It has sometimes been said that Lisp should use first and rest\ninstead of car and cdr, because it would make programs easier to\nread. Maybe for the first couple hours. But a hacker can learn\nquickly enough that car means the first element of a list and cdr\nmeans the rest. Using first and rest means 50% more typing. And\nthey are also different lengths, meaning that the arguments won't\nline up when they're called, as car and cdr often are, in successive\nlines. I've found that it matters a lot how code lines up on the\npage. I can barely read Lisp code when it is set in a variable-width\nfont, and friends say this is true for other languages too.Brevity is one place where strongly typed languages lose. All other\nthings being equal, no one wants to begin a program with a bunch\nof declarations. Anything that can be implicit, should be.The individual tokens should be short as well. Perl and Common Lisp\noccupy opposite poles on this question. Perl programs can be almost\ncryptically dense, while the names of built-in Common Lisp operators\nare comically long. The designers of Common Lisp probably expected\nusers to have text editors that would type these long names for\nthem. But the cost of a long name is not just the cost of typing\nit. There is also the cost of reading it, and the cost of the space\nit takes up on your screen.4 HackabilityThere is one thing more important than brevity to a hacker: being\nable to do what you want. In the history of programming languages\na surprising amount of effort has gone into preventing programmers\nfrom doing things considered to be improper. This is a dangerously\npresumptuous plan. How can the language designer know what the\nprogrammer is going to need to do? I think language designers would\ndo better to consider their target user to be a genius who will\nneed to do things they never anticipated, rather than a bumbler\nwho needs to be protected from himself. The bumbler will shoot\nhimself in the foot anyway. You may save him from referring to\nvariables in another package, but you can't save him from writing\na badly designed program to solve the wrong problem, and taking\nforever to do it.Good programmers often want to do dangerous and unsavory things.\nBy unsavory I mean things that go behind whatever semantic facade\nthe language is trying to present: getting hold of the internal\nrepresentation of some high-level abstraction, for example. Hackers\nlike to hack, and hacking means getting inside things and second\nguessing the original designer.Let yourself be second guessed. When you make any tool, people use\nit in ways you didn't intend, and this is especially true of a\nhighly articulated tool like a programming language. Many a hacker\nwill want to tweak your semantic model in a way that you never\nimagined. I say, let them; give the programmer access to as much\ninternal stuff as you can without endangering runtime systems like\nthe garbage collector.In Common Lisp I have often wanted to iterate through the fields\nof a struct — to comb out references to a deleted object, for example,\nor find fields that are uninitialized. I know the structs are just\nvectors underneath. And yet I can't write a general purpose function\nthat I can call on any struct. I can only access the fields by\nname, because that's what a struct is supposed to mean.A hacker may only want to subvert the intended model of things once\nor twice in a big program. But what a difference it makes to be\nable to. And it may be more than a question of just solving a\nproblem. There is a kind of pleasure here too. Hackers share the\nsurgeon's secret pleasure in poking about in gross innards, the\nteenager's secret pleasure in popping zits. [2] For boys, at least,\ncertain kinds of horrors are fascinating. Maxim magazine publishes\nan annual volume of photographs, containing a mix of pin-ups and\ngrisly accidents. They know their audience.Historically, Lisp has been good at letting hackers have their way.\nThe political correctness of Common Lisp is an aberration. Early\nLisps let you get your hands on everything. A good deal of that\nspirit is, fortunately, preserved in macros. What a wonderful thing,\nto be able to make arbitrary transformations on the source code.Classic macros are a real hacker's tool — simple, powerful, and\ndangerous. It's so easy to understand what they do: you call a\nfunction on the macro's arguments, and whatever it returns gets\ninserted in place of the macro call. Hygienic macros embody the\nopposite principle. They try to protect you from understanding what\nthey're doing. I have never heard hygienic macros explained in one\nsentence. And they are a classic example of the dangers of deciding\nwhat programmers are allowed to want. Hygienic macros are intended\nto protect me from variable capture, among other things, but variable\ncapture is exactly what I want in some macros.A really good language should be both clean and dirty: cleanly\ndesigned, with a small core of well understood and highly orthogonal\noperators, but dirty in the sense that it lets hackers have their\nway with it. C is like this. So were the early Lisps. A real hacker's\nlanguage will always have a slightly raffish character.A good programming language should have features that make the kind\nof people who use the phrase \"software engineering\" shake their\nheads disapprovingly. At the other end of the continuum are languages\nlike Ada and Pascal, models of propriety that are good for teaching\nand not much else.5 Throwaway ProgramsTo be attractive to hackers, a language must be good for writing\nthe kinds of programs they want to write. And that means, perhaps\nsurprisingly, that it has to be good for writing throwaway programs.A throwaway program is a program you write quickly for some limited\ntask: a program to automate some system administration task, or\ngenerate test data for a simulation, or convert data from one format\nto another. The surprising thing about throwaway programs is that,\nlike the \"temporary\" buildings built at so many American universities\nduring World War II, they often don't get thrown away. Many evolve\ninto real programs, with real features and real users.I have a hunch that the best big programs begin life this way,\nrather than being designed big from the start, like the Hoover Dam.\nIt's terrifying to build something big from scratch. When people\ntake on a project that's too big, they become overwhelmed. The\nproject either gets bogged down, or the result is sterile and\nwooden: a shopping mall rather than a real downtown, Brasilia rather\nthan Rome, Ada rather than C.Another way to get a big program is to start with a throwaway\nprogram and keep improving it. This approach is less daunting, and\nthe design of the program benefits from evolution. I think, if one\nlooked, that this would turn out to be the way most big programs\nwere developed. And those that did evolve this way are probably\nstill written in whatever language they were first written in,\nbecause it's rare for a program to be ported, except for political\nreasons. And so, paradoxically, if you want to make a language that\nis used for big systems, you have to make it good for writing\nthrowaway programs, because that's where big systems come from.Perl is a striking example of this idea. It was not only designed\nfor writing throwaway programs, but was pretty much a throwaway\nprogram itself. Perl began life as a collection of utilities for\ngenerating reports, and only evolved into a programming language\nas the throwaway programs people wrote in it grew larger. It was\nnot until Perl 5 (if then) that the language was suitable for\nwriting serious programs, and yet it was already massively popular.What makes a language good for throwaway programs? To start with,\nit must be readily available. A throwaway program is something that\nyou expect to write in an hour. So the language probably must\nalready be installed on the computer you're using. It can't be\nsomething you have to install before you use it. It has to be there.\nC was there because it came with the operating system. Perl was\nthere because it was originally a tool for system administrators,\nand yours had already installed it.Being available means more than being installed, though. An\ninteractive language, with a command-line interface, is more\navailable than one that you have to compile and run separately. A\npopular programming language should be interactive, and start up\nfast.Another thing you want in a throwaway program is brevity. Brevity\nis always attractive to hackers, and never more so than in a program\nthey expect to turn out in an hour.6 LibrariesOf course the ultimate in brevity is to have the program already\nwritten for you, and merely to call it. And this brings us to what\nI think will be an increasingly important feature of programming\nlanguages: library functions. Perl wins because it has large\nlibraries for manipulating strings. This class of library functions\nare especially important for throwaway programs, which are often\noriginally written for converting or extracting data. Many Perl\nprograms probably begin as just a couple library calls stuck\ntogether.I think a lot of the advances that happen in programming languages\nin the next fifty years will have to do with library functions. I\nthink future programming languages will have libraries that are as\ncarefully designed as the core language. Programming language design\nwill not be about whether to make your language strongly or weakly\ntyped, or object oriented, or functional, or whatever, but about\nhow to design great libraries. The kind of language designers who\nlike to think about how to design type systems may shudder at this.\nIt's almost like writing applications! Too bad. Languages are for\nprogrammers, and libraries are what programmers need.It's hard to design good libraries. It's not simply a matter of\nwriting a lot of code. Once the libraries get too big, it can\nsometimes take longer to find the function you need than to write\nthe code yourself. Libraries need to be designed using a small set\nof orthogonal operators, just like the core language. It ought to\nbe possible for the programmer to guess what library call will do\nwhat he needs.Libraries are one place Common Lisp falls short. There are only\nrudimentary libraries for manipulating strings, and almost none\nfor talking to the operating system. For historical reasons, Common\nLisp tries to pretend that the OS doesn't exist. And because you\ncan't talk to the OS, you're unlikely to be able to write a serious\nprogram using only the built-in operators in Common Lisp. You have\nto use some implementation-specific hacks as well, and in practice\nthese tend not to give you everything you want. Hackers would think\na lot more highly of Lisp if Common Lisp had powerful string\nlibraries and good OS support.7 SyntaxCould a language with Lisp's syntax, or more precisely, lack of\nsyntax, ever become popular? I don't know the answer to this\nquestion. I do think that syntax is not the main reason Lisp isn't\ncurrently popular. Common Lisp has worse problems than unfamiliar\nsyntax. I know several programmers who are comfortable with prefix\nsyntax and yet use Perl by default, because it has powerful string\nlibraries and can talk to the os.There are two possible problems with prefix notation: that it is\nunfamiliar to programmers, and that it is not dense enough. The\nconventional wisdom in the Lisp world is that the first problem is\nthe real one. I'm not so sure. Yes, prefix notation makes ordinary\nprogrammers panic. But I don't think ordinary programmers' opinions\nmatter. Languages become popular or unpopular based on what expert\nhackers think of them, and I think expert hackers might be able to\ndeal with prefix notation. Perl syntax can be pretty incomprehensible,\nbut that has not stood in the way of Perl's popularity. If anything\nit may have helped foster a Perl cult.A more serious problem is the diffuseness of prefix notation. For\nexpert hackers, that really is a problem. No one wants to write\n(aref a x y) when they could write a[x,y].In this particular case there is a way to finesse our way out of\nthe problem. If we treat data structures as if they were functions\non indexes, we could write (a x y) instead, which is even shorter\nthan the Perl form. Similar tricks may shorten other types of\nexpressions.We can get rid of (or make optional) a lot of parentheses by making\nindentation significant. That's how programmers read code anyway:\nwhen indentation says one thing and delimiters say another, we go\nby the indentation. Treating indentation as significant would\neliminate this common source of bugs as well as making programs\nshorter.Sometimes infix syntax is easier to read. This is especially true\nfor math expressions. I've used Lisp my whole programming life and\nI still don't find prefix math expressions natural. And yet it is\nconvenient, especially when you're generating code, to have operators\nthat take any number of arguments. So if we do have infix syntax,\nit should probably be implemented as some kind of read-macro.I don't think we should be religiously opposed to introducing syntax\ninto Lisp, as long as it translates in a well-understood way into\nunderlying s-expressions. There is already a good deal of syntax\nin Lisp. It's not necessarily bad to introduce more, as long as no\none is forced to use it. In Common Lisp, some delimiters are reserved\nfor the language, suggesting that at least some of the designers\nintended to have more syntax in the future.One of the most egregiously unlispy pieces of syntax in Common Lisp\noccurs in format strings; format is a language in its own right,\nand that language is not Lisp. If there were a plan for introducing\nmore syntax into Lisp, format specifiers might be able to be included\nin it. It would be a good thing if macros could generate format\nspecifiers the way they generate any other kind of code.An eminent Lisp hacker told me that his copy of CLTL falls open to\nthe section format. Mine too. This probably indicates room for\nimprovement. It may also mean that programs do a lot of I/O.8 EfficiencyA good language, as everyone knows, should generate fast code. But\nin practice I don't think fast code comes primarily from things\nyou do in the design of the language. As Knuth pointed out long\nago, speed only matters in certain critical bottlenecks. And as\nmany programmers have observed since, one is very often mistaken\nabout where these bottlenecks are.So, in practice, the way to get fast code is to have a very good\nprofiler, rather than by, say, making the language strongly typed.\nYou don't need to know the type of every argument in every call in\nthe program. You do need to be able to declare the types of arguments\nin the bottlenecks. And even more, you need to be able to find out\nwhere the bottlenecks are.One complaint people have had with Lisp is that it's hard to tell\nwhat's expensive. This might be true. It might also be inevitable,\nif you want to have a very abstract language. And in any case I\nthink good profiling would go a long way toward fixing the problem:\nyou'd soon learn what was expensive.Part of the problem here is social. Language designers like to\nwrite fast compilers. That's how they measure their skill. They\nthink of the profiler as an add-on, at best. But in practice a good\nprofiler may do more to improve the speed of actual programs written\nin the language than a compiler that generates fast code. Here,\nagain, language designers are somewhat out of touch with their\nusers. They do a really good job of solving slightly the wrong\nproblem.It might be a good idea to have an active profiler — to push\nperformance data to the programmer instead of waiting for him to\ncome asking for it. For example, the editor could display bottlenecks\nin red when the programmer edits the source code. Another approach\nwould be to somehow represent what's happening in running programs.\nThis would be an especially big win in server-based applications,\nwhere you have lots of running programs to look at. An active\nprofiler could show graphically what's happening in memory as a\nprogram's running, or even make sounds that tell what's happening.Sound is a good cue to problems. In one place I worked, we had a\nbig board of dials showing what was happening to our web servers.\nThe hands were moved by little servomotors that made a slight noise\nwhen they turned. I couldn't see the board from my desk, but I\nfound that I could tell immediately, by the sound, when there was\na problem with a server.It might even be possible to write a profiler that would automatically\ndetect inefficient algorithms. I would not be surprised if certain\npatterns of memory access turned out to be sure signs of bad\nalgorithms. If there were a little guy running around inside the\ncomputer executing our programs, he would probably have as long\nand plaintive a tale to tell about his job as a federal government\nemployee. I often have a feeling that I'm sending the processor on\na lot of wild goose chases, but I've never had a good way to look\nat what it's doing.A number of Lisps now compile into byte code, which is then executed\nby an interpreter. This is usually done to make the implementation\neasier to port, but it could be a useful language feature. It might\nbe a good idea to make the byte code an official part of the\nlanguage, and to allow programmers to use inline byte code in\nbottlenecks. Then such optimizations would be portable too.The nature of speed, as perceived by the end-user, may be changing.\nWith the rise of server-based applications, more and more programs\nmay turn out to be i/o-bound. It will be worth making i/o fast.\nThe language can help with straightforward measures like simple,\nfast, formatted output functions, and also with deep structural\nchanges like caching and persistent objects.Users are interested in response time. But another kind of efficiency\nwill be increasingly important: the number of simultaneous users\nyou can support per processor. Many of the interesting applications\nwritten in the near future will be server-based, and the number of\nusers per server is the critical question for anyone hosting such\napplications. In the capital cost of a business offering a server-based\napplication, this is the divisor.For years, efficiency hasn't mattered much in most end-user\napplications. Developers have been able to assume that each user\nwould have an increasingly powerful processor sitting on their\ndesk. And by Parkinson's Law, software has expanded to use the\nresources available. That will change with server-based applications.\nIn that world, the hardware and software will be supplied together.\nFor companies that offer server-based applications, it will make\na very big difference to the bottom line how many users they can\nsupport per server.In some applications, the processor will be the limiting factor,\nand execution speed will be the most important thing to optimize.\nBut often memory will be the limit; the number of simultaneous\nusers will be determined by the amount of memory you need for each\nuser's data. The language can help here too. Good support for\nthreads will enable all the users to share a single heap. It may\nalso help to have persistent objects and/or language level support\nfor lazy loading.9 TimeThe last ingredient a popular language needs is time. No one wants\nto write programs in a language that might go away, as so many\nprogramming languages do. So most hackers will tend to wait until\na language has been around for a couple years before even considering\nusing it.Inventors of wonderful new things are often surprised to discover\nthis, but you need time to get any message through to people. A\nfriend of mine rarely does anything the first time someone asks\nhim. He knows that people sometimes ask for things that they turn\nout not to want. To avoid wasting his time, he waits till the third\nor fourth time he's asked to do something; by then, whoever's asking\nhim may be fairly annoyed, but at least they probably really do\nwant whatever they're asking for.Most people have learned to do a similar sort of filtering on new\nthings they hear about. They don't even start paying attention\nuntil they've heard about something ten times. They're perfectly\njustified: the majority of hot new whatevers do turn out to be a\nwaste of time, and eventually go away. By delaying learning VRML,\nI avoided having to learn it at all.So anyone who invents something new has to expect to keep repeating\ntheir message for years before people will start to get it. We\nwrote what was, as far as I know, the first web-server based\napplication, and it took us years to get it through to people that\nit didn't have to be downloaded. It wasn't that they were stupid.\nThey just had us tuned out.The good news is, simple repetition solves the problem. All you\nhave to do is keep telling your story, and eventually people will\nstart to hear. It's not when people notice you're there that they\npay attention; it's when they notice you're still there.It's just as well that it usually takes a while to gain momentum.\nMost technologies evolve a good deal even after they're first\nlaunched — programming languages especially. Nothing could be better,\nfor a new techology, than a few years of being used only by a small\nnumber of early adopters. Early adopters are sophisticated and\ndemanding, and quickly flush out whatever flaws remain in your\ntechnology. When you only have a few users you can be in close\ncontact with all of them. And early adopters are forgiving when\nyou improve your system, even if this causes some breakage.There are two ways new technology gets introduced: the organic\ngrowth method, and the big bang method. The organic growth method\nis exemplified by the classic seat-of-the-pants underfunded garage\nstartup. A couple guys, working in obscurity, develop some new\ntechnology. They launch it with no marketing and initially have\nonly a few (fanatically devoted) users. They continue to improve\nthe technology, and meanwhile their user base grows by word of\nmouth. Before they know it, they're big.The other approach, the big bang method, is exemplified by the\nVC-backed, heavily marketed startup. They rush to develop a product,\nlaunch it with great publicity, and immediately (they hope) have\na large user base.Generally, the garage guys envy the big bang guys. The big bang\nguys are smooth and confident and respected by the VCs. They can\nafford the best of everything, and the PR campaign surrounding the\nlaunch has the side effect of making them celebrities. The organic\ngrowth guys, sitting in their garage, feel poor and unloved. And\nyet I think they are often mistaken to feel sorry for themselves.\nOrganic growth seems to yield better technology and richer founders\nthan the big bang method. If you look at the dominant technologies\ntoday, you'll find that most of them grew organically.This pattern doesn't only apply to companies. You see it in sponsored\nresearch too. Multics and Common Lisp were big-bang projects, and\nUnix and MacLisp were organic growth projects.10 Redesign\"The best writing is rewriting,\" wrote E. B. White. Every good\nwriter knows this, and it's true for software too. The most important\npart of design is redesign. Programming languages, especially,\ndon't get redesigned enough.To write good software you must simultaneously keep two opposing\nideas in your head. You need the young hacker's naive faith in\nhis abilities, and at the same time the veteran's skepticism. You\nhave to be able to think \nhow hard can it be? with one half of\nyour brain while thinking \nit will never work with the other.The trick is to realize that there's no real contradiction here.\nYou want to be optimistic and skeptical about two different things.\nYou have to be optimistic about the possibility of solving the\nproblem, but skeptical about the value of whatever solution you've\ngot so far.People who do good work often think that whatever they're working\non is no good. Others see what they've done and are full of wonder,\nbut the creator is full of worry. This pattern is no coincidence:\nit is the worry that made the work good.If you can keep hope and worry balanced, they will drive a project\nforward the same way your two legs drive a bicycle forward. In the\nfirst phase of the two-cycle innovation engine, you work furiously\non some problem, inspired by your confidence that you'll be able\nto solve it. In the second phase, you look at what you've done in\nthe cold light of morning, and see all its flaws very clearly. But\nas long as your critical spirit doesn't outweigh your hope, you'll\nbe able to look at your admittedly incomplete system, and think,\nhow hard can it be to get the rest of the way?, thereby continuing\nthe cycle.It's tricky to keep the two forces balanced. In young hackers,\noptimism predominates. They produce something, are convinced it's\ngreat, and never improve it. In old hackers, skepticism predominates,\nand they won't even dare to take on ambitious projects.Anything you can do to keep the redesign cycle going is good. Prose\ncan be rewritten over and over until you're happy with it. But\nsoftware, as a rule, doesn't get redesigned enough. Prose has\nreaders, but software has users. If a writer rewrites an essay,\npeople who read the old version are unlikely to complain that their\nthoughts have been broken by some newly introduced incompatibility.Users are a double-edged sword. They can help you improve your\nlanguage, but they can also deter you from improving it. So choose\nyour users carefully, and be slow to grow their number. Having\nusers is like optimization: the wise course is to delay it. Also,\nas a general rule, you can at any given time get away with changing\nmore than you think. Introducing change is like pulling off a\nbandage: the pain is a memory almost as soon as you feel it.Everyone knows that it's not a good idea to have a language designed\nby a committee. Committees yield bad design. But I think the worst\ndanger of committees is that they interfere with redesign. It is\nso much work to introduce changes that no one wants to bother.\nWhatever a committee decides tends to stay that way, even if most\nof the members don't like it.Even a committee of two gets in the way of redesign. This happens\nparticularly in the interfaces between pieces of software written\nby two different people. To change the interface both have to agree\nto change it at once. And so interfaces tend not to change at all,\nwhich is a problem because they tend to be one of the most ad hoc\nparts of any system.One solution here might be to design systems so that interfaces\nare horizontal instead of vertical — so that modules are always\nvertically stacked strata of abstraction. Then the interface will\ntend to be owned by one of them. The lower of two levels will either\nbe a language in which the upper is written, in which case the\nlower level will own the interface, or it will be a slave, in which\ncase the interface can be dictated by the upper level.11 LispWhat all this implies is that there is hope for a new Lisp. There\nis hope for any language that gives hackers what they want, including\nLisp. I think we may have made a mistake in thinking that hackers\nare turned off by Lisp's strangeness. This comforting illusion may\nhave prevented us from seeing the real problem with Lisp, or at\nleast Common Lisp, which is that it sucks for doing what hackers\nwant to do. A hacker's language needs powerful libraries and\nsomething to hack. Common Lisp has neither. A hacker's language is\nterse and hackable. Common Lisp is not.The good news is, it's not Lisp that sucks, but Common Lisp. If we\ncan develop a new Lisp that is a real hacker's language, I think\nhackers will use it. They will use whatever language does the job.\nAll we have to do is make sure this new Lisp does some important\njob better than other languages.History offers some encouragement. Over time, successive new\nprogramming languages have taken more and more features from Lisp.\nThere is no longer much left to copy before the language you've\nmade is Lisp. The latest hot language, Python, is a watered-down\nLisp with infix syntax and no macros. A new Lisp would be a natural\nstep in this progression.I sometimes think that it would be a good marketing trick to call\nit an improved version of Python. That sounds hipper than Lisp. To\nmany people, Lisp is a slow AI language with a lot of parentheses.\nFritz Kunze's official biography carefully avoids mentioning the\nL-word. But my guess is that we shouldn't be afraid to call the\nnew Lisp Lisp. Lisp still has a lot of latent respect among the\nvery best hackers — the ones who took 6.001 and understood it, for\nexample. And those are the users you need to win.In \"How to Become a Hacker,\" Eric Raymond describes Lisp as something\nlike Latin or Greek — a language you should learn as an intellectual\nexercise, even though you won't actually use it:\n\n Lisp is worth learning for the profound enlightenment experience\n you will have when you finally get it; that experience will make\n you a better programmer for the rest of your days, even if you\n never actually use Lisp itself a lot.\n\nIf I didn't know Lisp, reading this would set me asking questions.\nA language that would make me a better programmer, if it means\nanything at all, means a language that would be better for programming.\nAnd that is in fact the implication of what Eric is saying.As long as that idea is still floating around, I think hackers will\nbe receptive enough to a new Lisp, even if it is called Lisp. But\nthis Lisp must be a hacker's language, like the classic Lisps of\nthe 1970s. It must be terse, simple, and hackable. And it must have\npowerful libraries for doing what hackers want to do now.In the matter of libraries I think there is room to beat languages\nlike Perl and Python at their own game. A lot of the new applications\nthat will need to be written in the coming years will be \nserver-based\napplications. There's no reason a new Lisp shouldn't have string\nlibraries as good as Perl, and if this new Lisp also had powerful\nlibraries for server-based applications, it could be very popular.\nReal hackers won't turn up their noses at a new tool that will let\nthem solve hard problems with a few library calls. Remember, hackers\nare lazy.It could be an even bigger win to have core language support for\nserver-based applications. For example, explicit support for programs\nwith multiple users, or data ownership at the level of type tags.Server-based applications also give us the answer to the question\nof what this new Lisp will be used to hack. It would not hurt to\nmake Lisp better as a scripting language for Unix. (It would be\nhard to make it worse.) But I think there are areas where existing\nlanguages would be easier to beat. I think it might be better to\nfollow the model of Tcl, and supply the Lisp together with a complete\nsystem for supporting server-based applications. Lisp is a natural\nfit for server-based applications. Lexical closures provide a way\nto get the effect of subroutines when the ui is just a series of\nweb pages. S-expressions map nicely onto html, and macros are good\nat generating it. There need to be better tools for writing\nserver-based applications, and there needs to be a new Lisp, and\nthe two would work very well together.12 The Dream LanguageBy way of summary, let's try describing the hacker's dream language.\nThe dream language is \nbeautiful, clean, and terse. It has an\ninteractive toplevel that starts up fast. You can write programs\nto solve common problems with very little code. Nearly all the\ncode in any program you write is code that's specific to your\napplication. Everything else has been done for you.The syntax of the language is brief to a fault. You never have to\ntype an unnecessary character, or even to use the shift key much.Using big abstractions you can write the first version of a program\nvery quickly. Later, when you want to optimize, there's a really\ngood profiler that tells you where to focus your attention. You\ncan make inner loops blindingly fast, even writing inline byte code\nif you need to.There are lots of good examples to learn from, and the language is\nintuitive enough that you can learn how to use it from examples in\na couple minutes. You don't need to look in the manual much. The\nmanual is thin, and has few warnings and qualifications.The language has a small core, and powerful, highly orthogonal\nlibraries that are as carefully designed as the core language. The\nlibraries all work well together; everything in the language fits\ntogether like the parts in a fine camera. Nothing is deprecated,\nor retained for compatibility. The source code of all the libraries\nis readily available. It's easy to talk to the operating system\nand to applications written in other languages.The language is built in layers. The higher-level abstractions are\nbuilt in a very transparent way out of lower-level abstractions,\nwhich you can get hold of if you want.Nothing is hidden from you that doesn't absolutely have to be. The\nlanguage offers abstractions only as a way of saving you work,\nrather than as a way of telling you what to do. In fact, the language\nencourages you to be an equal participant in its design. You can\nchange everything about it, including even its syntax, and anything\nyou write has, as much as possible, the same status as what comes\npredefined.Notes[1] Macros very close to the modern idea were proposed by Timothy\nHart in 1964, two years after Lisp 1.5 was released. What was\nmissing, initially, were ways to avoid variable capture and multiple\nevaluation; Hart's examples are subject to both.[2] In When the Air Hits Your Brain, neurosurgeon Frank Vertosick\nrecounts a conversation in which his chief resident, Gary, talks\nabout the difference between surgeons and internists (\"fleas\"):\n\n Gary and I ordered a large pizza and found an open booth. The\n chief lit a cigarette. \"Look at those goddamn fleas, jabbering\n about some disease they'll see once in their lifetimes. That's\n the trouble with fleas, they only like the bizarre stuff. They\n hate their bread and butter cases. That's the difference between\n us and the fucking fleas. See, we love big juicy lumbar disc\n herniations, but they hate hypertension....\"\n\nIt's hard to think of a lumbar disc herniation as juicy (except\nliterally). And yet I think I know what they mean. I've often had\na juicy bug to track down. Someone who's not a programmer would\nfind it hard to imagine that there could be pleasure in a bug.\nSurely it's better if everything just works. In one way, it is.\nAnd yet there is undeniably a grim satisfaction in hunting down\ncertain sorts of bugs." }, { "path": "data/PaulGrahamEssaysLarge/pow.txt", "content": "January 2017People who are powerful but uncharismatic will tend to be disliked.\nTheir power makes them a target for criticism that they don't have\nthe charisma to disarm. That was Hillary Clinton's problem. It also\ntends to be a problem for any CEO who is more of a builder than a\nschmoozer. And yet the builder-type CEO is (like Hillary) probably\nthe best person for the job.I don't think there is any solution to this problem. It's human\nnature. The best we can do is to recognize that it's happening, and\nto understand that being a magnet for criticism is sometimes a sign\nnot that someone is the wrong person for a job, but that they're\nthe right one." }, { "path": "data/PaulGrahamEssaysLarge/rootsoflisp.txt", "content": "May 2001\n\n(I wrote this article to help myself understand exactly\nwhat McCarthy discovered. You don't need to know this stuff\nto program in Lisp, but it should be helpful to \nanyone who wants to\nunderstand the essence of Lisp — both in the sense of its\norigins and its semantic core. The fact that it has such a core\nis one of Lisp's distinguishing features, and the reason why,\nunlike other languages, Lisp has dialects.)In 1960, John \nMcCarthy published a remarkable paper in\nwhich he did for programming something like what Euclid did for\ngeometry. He showed how, given a handful of simple\noperators and a notation for functions, you can\nbuild a whole programming language.\nHe called this language Lisp, for \"List Processing,\"\nbecause one of his key ideas was to use a simple\ndata structure called a list for both\ncode and data.It's worth understanding what McCarthy discovered, not\njust as a landmark in the history of computers, but as\na model for what programming is tending to become in\nour own time. It seems to me that there have been\ntwo really clean, consistent models of programming so\nfar: the C model and the Lisp model.\nThese two seem points of high ground, with swampy lowlands\nbetween them. As computers have grown more powerful,\nthe new languages being developed have been moving\nsteadily toward the Lisp model. A popular recipe\nfor new programming languages in the past 20 years \nhas been to take the C model of computing and add to\nit, piecemeal, parts taken from the Lisp model,\nlike runtime typing and garbage collection.In this article I'm going to try to explain in the\nsimplest possible terms what McCarthy discovered.\nThe point is not just to learn about an interesting\ntheoretical result someone figured out forty years ago,\nbut to show where languages are heading.\nThe unusual thing about Lisp — in fact, the defining\nquality of Lisp — is that it can be written in\nitself. To understand what McCarthy meant by this,\nwe're going to retrace his steps, with his mathematical\nnotation translated into running Common Lisp code." }, { "path": "data/PaulGrahamEssaysLarge/rss.txt", "content": "Aaron Swartz created a scraped\nfeed\nof the essays page." }, { "path": "data/PaulGrahamEssaysLarge/siliconvalley.txt", "content": "May 2006(This essay is derived from a keynote at Xtech.)Could you reproduce Silicon Valley elsewhere, or is there something\nunique about it?It wouldn't be surprising if it were hard to reproduce in other\ncountries, because you couldn't reproduce it in most of the US\neither. What does it take to make a silicon valley even here?What it takes is the right people. If you could get the right ten\nthousand people to move from Silicon Valley to Buffalo, Buffalo\nwould become Silicon Valley. \n[1]That's a striking departure from the past. Up till a couple decades\nago, geography was destiny for cities. All great cities were located\non waterways, because cities made money by trade, and water was the\nonly economical way to ship.Now you could make a great city anywhere, if you could get the right\npeople to move there. So the question of how to make a silicon\nvalley becomes: who are the right people, and how do you get them\nto move?Two TypesI think you only need two kinds of people to create a technology\nhub: rich people and nerds. They're the limiting reagents in the\nreaction that produces startups, because they're the only ones\npresent when startups get started. Everyone else will move.Observation bears this out: within the US, towns have become startup\nhubs if and only if they have both rich people and nerds. Few\nstartups happen in Miami, for example, because although it's full\nof rich people, it has few nerds. It's not the kind of place nerds\nlike.Whereas Pittsburgh has the opposite problem: plenty of nerds, but\nno rich people. The top US Computer Science departments are said\nto be MIT, Stanford, Berkeley, and Carnegie-Mellon. MIT yielded\nRoute 128. Stanford and Berkeley yielded Silicon Valley. But\nCarnegie-Mellon? The record skips at that point. Lower down the\nlist, the University of Washington yielded a high-tech community\nin Seattle, and the University of Texas at Austin yielded one in\nAustin. But what happened in Pittsburgh? And in Ithaca, home of\nCornell, which is also high on the list?I grew up in Pittsburgh and went to college at Cornell, so I can\nanswer for both. The weather is terrible, particularly in winter,\nand there's no interesting old city to make up for it, as there is\nin Boston. Rich people don't want to live in Pittsburgh or Ithaca.\nSo while there are plenty of hackers who could start startups,\nthere's no one to invest in them.Not BureaucratsDo you really need the rich people? Wouldn't it work to have the\ngovernment invest in the nerds? No, it would not. Startup investors\nare a distinct type of rich people. They tend to have a lot of\nexperience themselves in the technology business. This (a) helps\nthem pick the right startups, and (b) means they can supply advice\nand connections as well as money. And the fact that they have a\npersonal stake in the outcome makes them really pay attention.Bureaucrats by their nature are the exact opposite sort of people\nfrom startup investors. The idea of them making startup investments\nis comic. It would be like mathematicians running Vogue-- or\nperhaps more accurately, Vogue editors running a math journal.\n[2]Though indeed, most things bureaucrats do, they do badly. We just\ndon't notice usually, because they only have to compete against\nother bureaucrats. But as startup investors they'd have to compete\nagainst pros with a great deal more experience and motivation.Even corporations that have in-house VC groups generally forbid\nthem to make their own investment decisions. Most are only allowed\nto invest in deals where some reputable private VC firm is willing\nto act as lead investor.Not BuildingsIf you go to see Silicon Valley, what you'll see are buildings.\nBut it's the people that make it Silicon Valley, not the buildings.\nI read occasionally about attempts to set up \"technology\nparks\" in other places, as if the active ingredient of Silicon\nValley were the office space. An article about Sophia Antipolis\nbragged that companies there included Cisco, Compaq, IBM, NCR, and\nNortel. Don't the French realize these aren't startups?Building office buildings for technology companies won't get you a\nsilicon valley, because the key stage in the life of a startup\nhappens before they want that kind of space. The key stage is when\nthey're three guys operating out of an apartment. Wherever the\nstartup is when it gets funded, it will stay. The defining quality\nof Silicon Valley is not that Intel or Apple or Google have offices\nthere, but that they were started there.So if you want to reproduce Silicon Valley, what you need to reproduce\nis those two or three founders sitting around a kitchen table\ndeciding to start a company. And to reproduce that you need those\npeople.UniversitiesThe exciting thing is, all you need are the people. If you could\nattract a critical mass of nerds and investors to live somewhere,\nyou could reproduce Silicon Valley. And both groups are highly\nmobile. They'll go where life is good. So what makes a place good\nto them?What nerds like is other nerds. Smart people will go wherever other\nsmart people are. And in particular, to great universities. In\ntheory there could be other ways to attract them, but so far\nuniversities seem to be indispensable. Within the US, there are\nno technology hubs without first-rate universities-- or at least,\nfirst-rate computer science departments.So if you want to make a silicon valley, you not only need a\nuniversity, but one of the top handful in the world. It has to be\ngood enough to act as a magnet, drawing the best people from thousands\nof miles away. And that means it has to stand up to existing magnets\nlike MIT and Stanford.This sounds hard. Actually it might be easy. My professor friends,\nwhen they're deciding where they'd like to work, consider one thing\nabove all: the quality of the other faculty. What attracts professors\nis good colleagues. So if you managed to recruit, en masse, a\nsignificant number of the best young researchers, you could create\na first-rate university from nothing overnight. And you could do\nthat for surprisingly little. If you paid 200 people hiring bonuses\nof $3 million apiece, you could put together a faculty that would\nbear comparison with any in the world. And from that point the\nchain reaction would be self-sustaining. So whatever it costs to\nestablish a mediocre university, for an additional half billion or\nso you could have a great one. \n[3]PersonalityHowever, merely creating a new university would not be enough to\nstart a silicon valley. The university is just the seed. It has\nto be planted in the right soil, or it won't germinate. Plant it\nin the wrong place, and you just create Carnegie-Mellon.To spawn startups, your university has to be in a town that has\nattractions other than the university. It has to be a place where\ninvestors want to live, and students want to stay after they graduate.The two like much the same things, because most startup investors\nare nerds themselves. So what do nerds look for in a town? Their\ntastes aren't completely different from other people's, because a\nlot of the towns they like most in the US are also big tourist\ndestinations: San Francisco, Boston, Seattle. But their tastes\ncan't be quite mainstream either, because they dislike other big\ntourist destinations, like New York, Los Angeles, and Las Vegas.There has been a lot written lately about the \"creative class.\" The\nthesis seems to be that as wealth derives increasingly from ideas,\ncities will prosper only if they attract those who have them. That\nis certainly true; in fact it was the basis of Amsterdam's prosperity\n400 years ago.A lot of nerd tastes they share with the creative class in general.\nFor example, they like well-preserved old neighborhoods instead of\ncookie-cutter suburbs, and locally-owned shops and restaurants\ninstead of national chains. Like the rest of the creative class,\nthey want to live somewhere with personality.What exactly is personality? I think it's the feeling that each\nbuilding is the work of a distinct group of people. A town with\npersonality is one that doesn't feel mass-produced. So if you want\nto make a startup hub-- or any town to attract the \"creative class\"--\nyou probably have to ban large development projects.\nWhen a large tract has been developed by a single organization, you\ncan always tell. \n[4]Most towns with personality are old, but they don't have to be.\nOld towns have two advantages: they're denser, because they were\nlaid out before cars, and they're more varied, because they were\nbuilt one building at a time. You could have both now. Just have\nbuilding codes that ensure density, and ban large scale developments.A corollary is that you have to keep out the biggest developer of\nall: the government. A government that asks \"How can we build a\nsilicon valley?\" has probably ensured failure by the way they framed\nthe question. You don't build a silicon valley; you let one grow.NerdsIf you want to attract nerds, you need more than a town with\npersonality. You need a town with the right personality. Nerds\nare a distinct subset of the creative class, with different tastes\nfrom the rest. You can see this most clearly in New York, which\nattracts a lot of creative people, but few nerds. \n[5]What nerds like is the kind of town where people walk around smiling.\nThis excludes LA, where no one walks at all, and also New York,\nwhere people walk, but not smiling. When I was in grad school in\nBoston, a friend came to visit from New York. On the subway back\nfrom the airport she asked \"Why is everyone smiling?\" I looked and\nthey weren't smiling. They just looked like they were compared to\nthe facial expressions she was used to.If you've lived in New York, you know where these facial expressions\ncome from. It's the kind of place where your mind may be excited,\nbut your body knows it's having a bad time. People don't so much\nenjoy living there as endure it for the sake of the excitement.\nAnd if you like certain kinds of excitement, New York is incomparable.\nIt's a hub of glamour, a magnet for all the shorter half-life\nisotopes of style and fame.Nerds don't care about glamour, so to them the appeal of New York\nis a mystery. People who like New York will pay a fortune for a\nsmall, dark, noisy apartment in order to live in a town where the\ncool people are really cool. A nerd looks at that deal and sees\nonly: pay a fortune for a small, dark, noisy apartment.Nerds will pay a premium to live in a town where the smart people\nare really smart, but you don't have to pay as much for that. It's\nsupply and demand: glamour is popular, so you have to pay a lot for\nit.Most nerds like quieter pleasures. They like cafes instead of\nclubs; used bookshops instead of fashionable clothing shops; hiking\ninstead of dancing; sunlight instead of tall buildings. A nerd's\nidea of paradise is Berkeley or Boulder.YouthIt's the young nerds who start startups, so it's those specifically\nthe city has to appeal to. The startup hubs in the US are all\nyoung-feeling towns. This doesn't mean they have to be new.\nCambridge has the oldest town plan in America, but it feels young\nbecause it's full of students.What you can't have, if you want to create a silicon valley, is a\nlarge, existing population of stodgy people. It would be a waste\nof time to try to reverse the fortunes of a declining industrial town\nlike Detroit or Philadelphia by trying to encourage startups. Those\nplaces have too much momentum in the wrong direction. You're better\noff starting with a blank slate in the form of a small town. Or\nbetter still, if there's a town young people already flock to, that\none.The Bay Area was a magnet for the young and optimistic for decades\nbefore it was associated with technology. It was a place people\nwent in search of something new. And so it became synonymous with\nCalifornia nuttiness. There's still a lot of that there. If you\nwanted to start a new fad-- a new way to focus one's \"energy,\" for\nexample, or a new category of things not to eat-- the Bay Area would\nbe the place to do it. But a place that tolerates oddness in the\nsearch for the new is exactly what you want in a startup hub, because\neconomically that's what startups are. Most good startup ideas\nseem a little crazy; if they were obviously good ideas, someone\nwould have done them already.(How many people are going to want computers in their houses?\nWhat, another search engine?)That's the connection between technology and liberalism. Without\nexception the high-tech cities in the US are also the most liberal.\nBut it's not because liberals are smarter that this is so. It's\nbecause liberal cities tolerate odd ideas, and smart people by\ndefinition have odd ideas.Conversely, a town that gets praised for being \"solid\" or representing\n\"traditional values\" may be a fine place to live, but it's never\ngoing to succeed as a startup hub. The 2004 presidential election,\nthough a disaster in other respects, conveniently supplied us with\na county-by-county \nmap of such places. \n[6]To attract the young, a town must have an intact center. In most\nAmerican cities the center has been abandoned, and the growth, if\nany, is in the suburbs. Most American cities have been turned\ninside out. But none of the startup hubs has: not San Francisco,\nor Boston, or Seattle. They all have intact centers.\n[7]\nMy guess is that no city with a dead center could be turned into a\nstartup hub. Young people don't want to live in the suburbs.Within the US, the two cities I think could most easily be turned\ninto new silicon valleys are Boulder and Portland. Both have the\nkind of effervescent feel that attracts the young. They're each\nonly a great university short of becoming a silicon valley, if they\nwanted to.TimeA great university near an attractive town. Is that all it takes?\nThat was all it took to make the original Silicon Valley. Silicon\nValley traces its origins to William Shockley, one of the inventors\nof the transistor. He did the research that won him the Nobel Prize\nat Bell Labs, but when he started his own company in 1956 he moved\nto Palo Alto to do it. At the time that was an odd thing to do.\nWhy did he? Because he had grown up there and remembered how nice\nit was. Now Palo Alto is suburbia, but then it was a charming\ncollege town-- a charming college town with perfect weather and San\nFrancisco only an hour away.The companies that rule Silicon Valley now are all descended in\nvarious ways from Shockley Semiconductor. Shockley was a difficult\nman, and in 1957 his top people-- \"the traitorous eight\"-- left to\nstart a new company, Fairchild Semiconductor. Among them were\nGordon Moore and Robert Noyce, who went on to found Intel, and\nEugene Kleiner, who founded the VC firm Kleiner Perkins. Forty-two\nyears later, Kleiner Perkins funded Google, and the partner responsible\nfor the deal was John Doerr, who came to Silicon Valley in 1974 to\nwork for Intel.So although a lot of the newest companies in Silicon Valley don't\nmake anything out of silicon, there always seem to be multiple links\nback to Shockley. There's a lesson here: startups beget startups.\nPeople who work for startups start their own. People who get rich\nfrom startups fund new ones. I suspect this kind of organic growth\nis the only way to produce a startup hub, because it's the only way\nto grow the expertise you need.That has two important implications. The first is that you need\ntime to grow a silicon valley. The university you could create in\na couple years, but the startup community around it has to grow\norganically. The cycle time is limited by the time it takes a\ncompany to succeed, which probably averages about five years.The other implication of the organic growth hypothesis is that you\ncan't be somewhat of a startup hub. You either have a self-sustaining\nchain reaction, or not. Observation confirms this too: cities\neither have a startup scene, or they don't. There is no middle\nground. Chicago has the third largest metropolitan area in America.\nAs source of startups it's negligible compared to Seattle, number 15.The good news is that the initial seed can be quite small. Shockley\nSemiconductor, though itself not very successful, was big enough.\nIt brought a critical mass of experts in an important new technology\ntogether in a place they liked enough to stay.CompetingOf course, a would-be silicon valley faces an obstacle the original\none didn't: it has to compete with Silicon Valley. Can that be\ndone? Probably.One of Silicon Valley's biggest advantages is its venture capital\nfirms. This was not a factor in Shockley's day, because VC funds\ndidn't exist. In fact, Shockley Semiconductor and Fairchild\nSemiconductor were not startups at all in our sense. They were\nsubsidiaries-- of Beckman Instruments and Fairchild Camera and\nInstrument respectively. Those companies were apparently willing\nto establish subsidiaries wherever the experts wanted to live.Venture investors, however, prefer to fund startups within an hour's\ndrive. For one, they're more likely to notice startups nearby.\nBut when they do notice startups in other towns they prefer them\nto move. They don't want to have to travel to attend board meetings,\nand in any case the odds of succeeding are higher in a startup hub.The centralizing effect of venture firms is a double one: they cause\nstartups to form around them, and those draw in more startups through\nacquisitions. And although the first may be weakening because it's\nnow so cheap to start some startups, the second seems as strong as ever.\nThree of the most admired\n\"Web 2.0\" companies were started outside the usual startup hubs,\nbut two of them have already been reeled in through acquisitions.Such centralizing forces make it harder for new silicon valleys to\nget started. But by no means impossible. Ultimately power rests\nwith the founders. A startup with the best people will beat one\nwith funding from famous VCs, and a startup that was sufficiently\nsuccessful would never have to move. So a town that\ncould exert enough pull over the right people could resist and\nperhaps even surpass Silicon Valley.For all its power, Silicon Valley has a great weakness: the paradise\nShockley found in 1956 is now one giant parking lot. San Francisco\nand Berkeley are great, but they're forty miles away. Silicon\nValley proper is soul-crushing suburban sprawl. It\nhas fabulous weather, which makes it significantly better than the\nsoul-crushing sprawl of most other American cities. But a competitor\nthat managed to avoid sprawl would have real leverage. All a city\nneeds is to be the kind of place the next traitorous eight look at\nand say \"I want to stay here,\" and that would be enough to get the\nchain reaction started.Notes[1]\nIt's interesting to consider how low this number could be\nmade. I suspect five hundred would be enough, even if they could\nbring no assets with them. Probably just thirty, if I could pick them, \nwould be enough to turn Buffalo into a significant startup hub.[2]\nBureaucrats manage to allocate research funding moderately\nwell, but only because (like an in-house VC fund) they outsource\nmost of the work of selection. A professor at a famous university\nwho is highly regarded by his peers will get funding, pretty much\nregardless of the proposal. That wouldn't work for startups, whose\nfounders aren't sponsored by organizations, and are often unknowns.[3]\nYou'd have to do it all at once, or at least a whole department\nat a time, because people would be more likely to come if they\nknew their friends were. And you should probably start from scratch,\nrather than trying to upgrade an existing university, or much energy\nwould be lost in friction.[4]\nHypothesis: Any plan in which multiple independent buildings\nare gutted or demolished to be \"redeveloped\" as a single project\nis a net loss of personality for the city, with the exception of\nthe conversion of buildings not previously public, like warehouses.[5]\nA few startups get started in New York, but less\nthan a tenth as many per capita as in Boston, and mostly\nin less nerdy fields like finance and media.[6]\nSome blue counties are false positives (reflecting the\nremaining power of Democractic party machines), but there are no\nfalse negatives. You can safely write off all the red counties.[7]\nSome \"urban renewal\" experts took a shot at destroying Boston's\nin the 1960s, leaving the area around city hall a bleak wasteland,\nbut most neighborhoods successfully resisted them.Thanks to Chris Anderson, Trevor Blackwell, Marc Hedlund,\nJessica Livingston, Robert Morris, Greg Mcadoo, Fred Wilson,\nand Stephen Wolfram for\nreading drafts of this, and to Ed Dumbill for inviting me to speak.(The second part of this talk became Why Startups\nCondense in America.)" }, { "path": "data/PaulGrahamEssaysLarge/startuplessons.txt", "content": "April 2006(This essay is derived from a talk at the 2006 \nStartup School.)The startups we've funded so far are pretty quick, but they seem\nquicker to learn some lessons than others. I think it's because\nsome things about startups are kind of counterintuitive.We've now \ninvested \nin enough companies that I've learned a trick\nfor determining which points are the counterintuitive ones:\nthey're the ones I have to keep repeating.So I'm going to number these points, and maybe with future startups\nI'll be able to pull off a form of Huffman coding. I'll make them\nall read this, and then instead of nagging them in detail, I'll\njust be able to say: number four!\n1. Release Early.The thing I probably repeat most is this recipe for a startup: get\na version 1 out fast, then improve it based on users' reactions.By \"release early\" I don't mean you should release something full\nof bugs, but that you should release something minimal. Users hate\nbugs, but they don't seem to mind a minimal version 1, if there's\nmore coming soon.There are several reasons it pays to get version 1 done fast. One\nis that this is simply the right way to write software, whether for\na startup or not. I've been repeating that since 1993, and I haven't seen much since to\ncontradict it. I've seen a lot of startups die because they were\ntoo slow to release stuff, and none because they were too quick.\n[1]One of the things that will surprise you if you build something\npopular is that you won't know your users. Reddit now has almost half a million\nunique visitors a month. Who are all those people? They have no\nidea. No web startup does. And since you don't know your users,\nit's dangerous to guess what they'll like. Better to release\nsomething and let them tell you.Wufoo took this to heart and released\ntheir form-builder before the underlying database. You can't even\ndrive the thing yet, but 83,000 people came to sit in the driver's\nseat and hold the steering wheel. And Wufoo got valuable feedback\nfrom it: Linux users complained they used too much Flash, so they\nrewrote their software not to. If they'd waited to release everything\nat once, they wouldn't have discovered this problem till it was\nmore deeply wired in.Even if you had no users, it would still be important to release\nquickly, because for a startup the initial release acts as a shakedown\ncruise. If anything major is broken-- if the idea's no good,\nfor example, or the founders hate one another-- the stress of getting\nthat first version out will expose it. And if you have such problems\nyou want to find them early.Perhaps the most important reason to release early, though, is that\nit makes you work harder. When you're working on something that\nisn't released, problems are intriguing. In something that's out\nthere, problems are alarming. There is a lot more urgency once you\nrelease. And I think that's precisely why people put it off. They\nknow they'll have to work a lot harder once they do. \n[2]\n2. Keep Pumping Out Features.Of course, \"release early\" has a second component, without which\nit would be bad advice. If you're going to start with something\nthat doesn't do much, you better improve it fast.What I find myself repeating is \"pump out features.\" And this rule\nisn't just for the initial stages. This is something all startups\nshould do for as long as they want to be considered startups.I don't mean, of course, that you should make your application ever\nmore complex. By \"feature\" I mean one unit of hacking-- one quantum\nof making users' lives better.As with exercise, improvements beget improvements. If you run every\nday, you'll probably feel like running tomorrow. But if you skip\nrunning for a couple weeks, it will be an effort to drag yourself\nout. So it is with hacking: the more ideas you implement, the more\nideas you'll have. You should make your system better at least in\nsome small way every day or two.This is not just a good way to get development done; it is also a\nform of marketing. Users love a site that's constantly improving.\nIn fact, users expect a site to improve. Imagine if you visited a\nsite that seemed very good, and then returned two months later and\nnot one thing had changed. Wouldn't it start to seem lame? \n[3]They'll like you even better when you improve in response to their\ncomments, because customers are used to companies ignoring them.\nIf you're the rare exception-- a company that actually listens--\nyou'll generate fanatical loyalty. You won't need to advertise,\nbecause your users will do it for you.This seems obvious too, so why do I have to keep repeating it? I\nthink the problem here is that people get used to how things are.\nOnce a product gets past the stage where it has glaring flaws, you\nstart to get used to it, and gradually whatever features it happens\nto have become its identity. For example, I doubt many people at\nYahoo (or Google for that matter) realized how much better web mail\ncould be till Paul Buchheit showed them.I think the solution is to assume that anything you've made is far\nshort of what it could be. Force yourself, as a sort of intellectual\nexercise, to keep thinking of improvements. Ok, sure, what you\nhave is perfect. But if you had to change something, what would\nit be?If your product seems finished, there are two possible explanations:\n(a) it is finished, or (b) you lack imagination. Experience suggests\n(b) is a thousand times more likely.\n3. Make Users Happy.Improving constantly is an instance of a more general rule: make\nusers happy. One thing all startups have in common is that they\ncan't force anyone to do anything. They can't force anyone to use\ntheir software, and they can't force anyone to do deals with them.\nA startup has to sing for its supper. That's why the successful\nones make great things. They have to, or die.When you're running a startup you feel like a little bit of debris\nblown about by powerful winds. The most powerful wind is users.\nThey can either catch you and loft you up into the sky, as they did\nwith Google, or leave you flat on the pavement, as they do with\nmost startups. Users are a fickle wind, but more powerful than any\nother. If they take you up, no competitor can keep you down.As a little piece of debris, the rational thing for you to do is\nnot to lie flat, but to curl yourself into a shape the wind will\ncatch.I like the wind metaphor because it reminds you how impersonal the\nstream of traffic is. The vast majority of people who visit your\nsite will be casual visitors. It's them you have to design your\nsite for. The people who really care will find what they want by\nthemselves.The median visitor will arrive with their finger poised on the Back\nbutton. Think about your own experience: most links you\nfollow lead to something lame. Anyone who has used the web for\nmore than a couple weeks has been trained to click on Back after\nfollowing a link. So your site has to say \"Wait! Don't click on\nBack. This site isn't lame. Look at this, for example.\"There are two things you have to do to make people pause. The most\nimportant is to explain, as concisely as possible, what the hell\nyour site is about. How often have you visited a site that seemed\nto assume you already knew what they did? For example, the corporate\nsite that says the\ncompany makes\n\n enterprise content management solutions for business that enable\n organizations to unify people, content and processes to minimize\n business risk, accelerate time-to-value and sustain lower total\n cost of ownership.\n\nAn established company may get away with such an opaque description,\nbut no startup can. A startup\nshould be able to explain in one or two sentences exactly what it\ndoes. \n[4]\nAnd not just to users. You need this for everyone:\ninvestors, acquirers, partners, reporters, potential employees, and\neven current employees. You probably shouldn't even start a company\nto do something that can't be described compellingly in one or two\nsentences.The other thing I repeat is to give people everything you've got,\nright away. If you have something impressive, try to put it on the\nfront page, because that's the only one most visitors will see.\nThough indeed there's a paradox here: the more you push the good\nstuff toward the front, the more likely visitors are to explore\nfurther. \n[5]In the best case these two suggestions get combined: you tell\nvisitors what your site is about by showing them. One of the\nstandard pieces of advice in fiction writing is \"show, don't tell.\"\nDon't say that a character's angry; have him grind his teeth, or\nbreak his pencil in half. Nothing will explain what your site does\nso well as using it.The industry term here is \"conversion.\" The job of your site is\nto convert casual visitors into users-- whatever your definition\nof a user is. You can measure this in your growth rate. Either\nyour site is catching on, or it isn't, and you must know which. If\nyou have decent growth, you'll win in the end, no matter how obscure\nyou are now. And if you don't, you need to fix something.\n4. Fear the Right Things.Another thing I find myself saying a lot is \"don't worry.\" Actually,\nit's more often \"don't worry about this; worry about that instead.\"\nStartups are right to be paranoid, but they sometimes fear the wrong\nthings.Most visible disasters are not so alarming as they seem. Disasters\nare normal in a startup: a founder quits, you discover a patent\nthat covers what you're doing, your servers keep crashing, you run\ninto an insoluble technical problem, you have to change your name,\na deal falls through-- these are all par for the course. They won't\nkill you unless you let them.Nor will most competitors. A lot of startups worry \"what if Google\nbuilds something like us?\" Actually big companies are not the ones\nyou have to worry about-- not even Google. The people at Google\nare smart, but no smarter than you; they're not as motivated, because\nGoogle is not going to go out of business if this one product fails;\nand even at Google they have a lot of bureaucracy to slow them down.What you should fear, as a startup, is not the established players,\nbut other startups you don't know exist yet. They're way more\ndangerous than Google because, like you, they're cornered animals.Looking just at existing competitors can give you a false sense of\nsecurity. You should compete against what someone else could be\ndoing, not just what you can see people doing. A corollary is that\nyou shouldn't relax just because you have no visible competitors\nyet. No matter what your idea, there's someone else out there\nworking on the same thing.That's the downside of it being easier to start a startup: more people\nare doing it. But I disagree with Caterina Fake when she says that\nmakes this a bad time to start a startup. More people are starting\nstartups, but not as many more as could. Most college graduates\nstill think they have to get a job. The average person can't ignore\nsomething that's been beaten into their head since they were three\njust because serving web pages recently got a lot cheaper.And in any case, competitors are not the biggest threat. Way more\nstartups hose themselves than get crushed by competitors. There\nare a lot of ways to do it, but the three main ones are internal\ndisputes, inertia, and ignoring users. Each is, by itself, enough\nto kill you. But if I had to pick the worst, it would be ignoring\nusers. If you want a recipe for a startup that's going to die,\nhere it is: a couple of founders who have some great idea they know\neveryone is going to love, and that's what they're going to build,\nno matter what.Almost everyone's initial plan is broken. If companies stuck to\ntheir initial plans, Microsoft would be selling programming languages,\nand Apple would be selling printed circuit boards. In both cases\ntheir customers told them what their business should be-- and they\nwere smart enough to listen.As Richard Feynman said, the imagination of nature is greater than\nthe imagination of man. You'll find more interesting things by\nlooking at the world than you could ever produce just by thinking.\nThis principle is very powerful. It's why the best abstract painting\nstill falls short of Leonardo, for example. And it applies to\nstartups too. No idea for a product could ever be so clever as the\nones you can discover by smashing a beam of prototypes into a beam\nof users.\n5. Commitment Is a Self-Fulfilling Prophecy.I now have enough experience with startups to be able to say what\nthe most important quality is in a startup founder, and it's not\nwhat you might think. The most important quality in a startup\nfounder is determination. Not intelligence-- determination.This is a little depressing. I'd like to believe Viaweb succeeded\nbecause we were smart, not merely determined. A lot of people in\nthe startup world want to believe that. Not just founders, but\ninvestors too. They like the idea of inhabiting a world ruled by\nintelligence. And you can tell they really believe this, because\nit affects their investment decisions.Time after time VCs invest in startups founded by eminent professors.\nThis may work in biotech, where a lot of startups simply commercialize\nexisting research, but in software you want to invest in students,\nnot professors. Microsoft, Yahoo, and Google were all founded by\npeople who dropped out of school to do it. What students lack in\nexperience they more than make up in dedication.Of course, if you want to get rich, it's not enough merely to be\ndetermined. You have to be smart too, right? I'd like to think\nso, but I've had an experience that convinced me otherwise: I spent\nseveral years living in New York.You can lose quite a lot in the brains department and it won't kill\nyou. But lose even a little bit in the commitment department, and\nthat will kill you very rapidly.Running a startup is like walking on your hands: it's possible, but\nit requires extraordinary effort. If an ordinary employee were\nasked to do the things a startup founder has to, he'd be very\nindignant. Imagine if you were hired at some big company, and in\naddition to writing software ten times faster than you'd ever had\nto before, they expected you to answer support calls, administer\nthe servers, design the web site, cold-call customers, find the\ncompany office space, and go out and get everyone lunch.And to do all this not in the calm, womb-like atmosphere of a big\ncompany, but against a backdrop of constant disasters. That's the\npart that really demands determination. In a startup, there's\nalways some disaster happening. So if you're the least bit inclined\nto find an excuse to quit, there's always one right there.But if you lack commitment, chances are it will have been hurting\nyou long before you actually quit. Everyone who deals with startups\nknows how important commitment is, so if they sense you're ambivalent,\nthey won't give you much attention. If you lack commitment, you'll\njust find that for some mysterious reason good things happen to\nyour competitors but not to you. If you lack commitment, it will\nseem to you that you're unlucky.Whereas if you're determined to stick around, people will pay\nattention to you, because odds are they'll have to deal with you\nlater. You're a local, not just a tourist, so everyone has to come\nto terms with you.At Y Combinator we sometimes mistakenly fund teams who have the\nattitude that they're going to give this startup thing a shot for\nthree months, and if something great happens, they'll stick with\nit-- \"something great\" meaning either that someone wants to buy\nthem or invest millions of dollars in them. But if this is your\nattitude, \"something great\" is very unlikely to happen to you,\nbecause both acquirers and investors judge you by your level of\ncommitment.If an acquirer thinks you're going to stick around no matter what,\nthey'll be more likely to buy you, because if they don't and you\nstick around, you'll probably grow, your price will go up, and\nthey'll be left wishing they'd bought you earlier. Ditto for\ninvestors. What really motivates investors, even big VCs, is not\nthe hope of good returns, but the fear of missing out. \n[6]\nSo if\nyou make it clear you're going to succeed no matter what, and the only\nreason you need them is to make it happen a little faster, you're\nmuch more likely to get money.You can't fake this. The only way to convince everyone that you're\nready to fight to the death is actually to be ready to.You have to be the right kind of determined, though. I carefully\nchose the word determined rather than stubborn, because stubbornness\nis a disastrous quality in a startup. You have to be determined,\nbut flexible, like a running back. A successful running back doesn't\njust put his head down and try to run through people. He improvises:\nif someone appears in front of him, he runs around them; if someone\ntries to grab him, he spins out of their grip; he'll even run in\nthe wrong direction briefly if that will help. The one thing he'll\nnever do is stand still. \n[7]\n6. There Is Always Room.I was talking recently to a startup founder about whether it might\nbe good to add a social component to their software. He said he\ndidn't think so, because the whole social thing was tapped out.\nReally? So in a hundred years the only social networking sites\nwill be the Facebook, MySpace, Flickr, and Del.icio.us? Not likely.There is always room for new stuff. At every point in history,\neven the darkest bits of the dark ages, people were discovering\nthings that made everyone say \"why didn't anyone think of that\nbefore?\" We know this continued to be true up till 2004, when the\nFacebook was founded-- though strictly speaking someone else did\nthink of that.The reason we don't see the opportunities all around us is that we\nadjust to however things are, and assume that's how things have to\nbe. For example, it would seem crazy to most people to try to make\na better search engine than Google. Surely that field, at least,\nis tapped out. Really? In a hundred years-- or even twenty-- are\npeople still going to search for information using something like\nthe current Google? Even Google probably doesn't think that.In particular, I don't think there's any limit to the number of\nstartups. Sometimes you hear people saying \"All these guys starting\nstartups now are going to be disappointed. How many little startups\nare Google and Yahoo going to buy, after all?\" That sounds cleverly\nskeptical, but I can prove it's mistaken. No one proposes that\nthere's some limit to the number of people who can be employed in\nan economy consisting of big, slow-moving companies with a couple\nthousand people each. Why should there be any limit to the number\nwho could be employed by small, fast-moving companies with ten each?\nIt seems to me the only limit would be the number of people who\nwant to work that hard.The limit on the number of startups is not the number that can get\nacquired by Google and Yahoo-- though it seems even that should\nbe unlimited, if the startups were actually worth buying-- but the\namount of wealth that can be created. And I don't think there's\nany limit on that, except cosmological ones.So for all practical purposes, there is no limit to the number of\nstartups. Startups make wealth, which means they make things people\nwant, and if there's a limit on the number of things people want,\nwe are nowhere near it. I still don't even have a flying car.\n7. Don't Get Your Hopes Up.This is another one I've been repeating since long before Y Combinator.\nIt was practically the corporate motto at Viaweb.Startup founders are naturally optimistic. They wouldn't do it\notherwise. But you should treat your optimism the way you'd treat\nthe core of a nuclear reactor: as a source of power that's also\nvery dangerous. You have to build a shield around it, or it will\nfry you.The shielding of a reactor is not uniform; the reactor would be\nuseless if it were. It's pierced in a few places to let pipes in.\nAn optimism shield has to be pierced too. I think the place to\ndraw the line is between what you expect of yourself, and what you\nexpect of other people. It's ok to be optimistic about what you\ncan do, but assume the worst about machines and other people.This is particularly necessary in a startup, because you tend to\nbe pushing the limits of whatever you're doing. So things don't\nhappen in the smooth, predictable way they do in the rest of the\nworld. Things change suddenly, and usually for the worse.Shielding your optimism is nowhere more important than with deals.\nIf your startup is doing a deal, just assume it's not going to\nhappen. The VCs who say they're going to invest in you aren't.\nThe company that says they're going to buy you isn't. The big\ncustomer who wants to use your system in their whole company won't.\nThen if things work out you can be pleasantly surprised.The reason I warn startups not to get their hopes up is not to save\nthem from being disappointed when things fall through. It's\nfor a more practical reason: to prevent them from leaning their\ncompany against something that's going to fall over, taking them\nwith it.For example, if someone says they want to invest in you, there's a\nnatural tendency to stop looking for other investors. That's why\npeople proposing deals seem so positive: they want you to\nstop looking. And you want to stop too, because doing deals is a\npain. Raising money, in particular, is a huge time sink. So you\nhave to consciously force yourself to keep looking.Even if you ultimately do the first deal, it will be to your advantage\nto have kept looking, because you'll get better terms. Deals are\ndynamic; unless you're negotiating with someone unusually honest,\nthere's not a single point where you shake hands and the deal's\ndone. There are usually a lot of subsidiary questions to be cleared\nup after the handshake, and if the other side senses weakness-- if\nthey sense you need this deal-- they will be very tempted to screw\nyou in the details.VCs and corp dev guys are professional negotiators. They're trained\nto take advantage of weakness. \n[8]\nSo while they're often nice\nguys, they just can't help it. And as pros they do this more than\nyou. So don't even try to bluff them. The only way a startup can\nhave any leverage in a deal is genuinely not to need it. And if\nyou don't believe in a deal, you'll be less likely to depend on it.So I want to plant a hypnotic suggestion in your heads: when you\nhear someone say the words \"we want to invest in you\" or \"we want\nto acquire you,\" I want the following phrase to appear automatically\nin your head: don't get your hopes up. Just continue running\nyour company as if this deal didn't exist. Nothing is more likely\nto make it close.The way to succeed in a startup is to focus on the goal of getting\nlots of users, and keep walking swiftly toward it while investors\nand acquirers scurry alongside trying to wave money in your face.\nSpeed, not MoneyThe way I've described it, starting a startup sounds pretty stressful.\nIt is. When I talk to the founders of the companies we've funded,\nthey all say the same thing: I knew it would be hard, but I didn't\nrealize it would be this hard.So why do it? It would be worth enduring a lot of pain and stress\nto do something grand or heroic, but just to make money? Is making\nmoney really that important?No, not really. It seems ridiculous to me when people take business\ntoo seriously. I regard making money as a boring errand to be got\nout of the way as soon as possible. There is nothing grand or\nheroic about starting a startup per se.So why do I spend so much time thinking about startups? I'll tell\nyou why. Economically, a startup is best seen not as a way to get\nrich, but as a way to work faster. You have to make a living, and\na startup is a way to get that done quickly, instead of letting it\ndrag on through your whole life.\n[9]We take it for granted most of the time, but human life is fairly\nmiraculous. It is also palpably short. You're given this marvellous\nthing, and then poof, it's taken away. You can see why people\ninvent gods to explain it. But even to people who don't believe\nin gods, life commands respect. There are times in most of our\nlives when the days go by in a blur, and almost everyone has a\nsense, when this happens, of wasting something precious. As Ben\nFranklin said, if you love life, don't waste time, because time is\nwhat life is made of.So no, there's nothing particularly grand about making money. That's\nnot what makes startups worth the trouble. What's important about\nstartups is the speed. By compressing the dull but necessary task\nof making a living into the smallest possible time, you show respect\nfor life, and there is something grand about that.Notes[1]\nStartups can die from releasing something full of bugs, and not\nfixing them fast enough, but I don't know of any that died from\nreleasing something stable but minimal very early, then promptly\nimproving it.[2]\nI know this is why I haven't released Arc. The moment I do,\nI'll have people nagging me for features.[3]\nA web site is different from a book or movie or desktop application\nin this respect. Users judge a site not as a single snapshot, but\nas an animation with multiple frames. Of the two, I'd say the rate of\nimprovement is more important to users than where you currently\nare.[4]\nIt should not always tell this to users, however. For example,\nMySpace is basically a replacement mall for mallrats. But it was\nwiser for them, initially, to pretend that the site was about bands.[5]\nSimilarly, don't make users register to try your site. Maybe\nwhat you have is so valuable that visitors should gladly register\nto get at it. But they've been trained to expect the opposite.\nMost of the things they've tried on the web have sucked-- and\nprobably especially those that made them register.[6]\nVCs have rational reasons for behaving this way. They don't\nmake their money (if they make money) off their median investments.\nIn a typical fund, half the companies fail, most of the rest generate\nmediocre returns, and one or two \"make the fund\" by succeeding\nspectacularly. So if they miss just a few of the most promising\nopportunities, it could hose the whole fund.[7]\nThe attitude of a running back doesn't translate to soccer.\nThough it looks great when a forward dribbles past multiple defenders,\na player who persists in trying such things will do worse in the\nlong term than one who passes.[8]\nThe reason Y Combinator never negotiates valuations\nis that we're not professional negotiators, and don't want to turn\ninto them.[9]\nThere are two ways to do \nwork you love: (a) to make money, then work\non what you love, or (b) to get a job where you get paid to work on\nstuff you love. In practice the first phases of both\nconsist mostly of unedifying schleps, and in (b) the second phase is less\nsecure.Thanks to Sam Altman, Trevor Blackwell, Beau Hartshorne, Jessica \nLivingston, and Robert Morris for reading drafts of this." }, { "path": "data/PaulGrahamEssaysLarge/submarine.txt", "content": "April 2005\"Suits make a corporate comeback,\" says the New\nYork Times. Why does this sound familiar? Maybe because\nthe suit was also back in February,\n\nSeptember\n2004, June\n2004, March\n2004, September\n2003, \n\nNovember\n2002, \nApril 2002,\nand February\n2002.\n\nWhy do the media keep running stories saying suits are back? Because\nPR firms tell \nthem to. One of the most surprising things I discovered\nduring my brief business career was the existence of the PR industry,\nlurking like a huge, quiet submarine beneath the news. Of the\nstories you read in traditional media that aren't about politics,\ncrimes, or disasters, more than half probably come from PR firms.I know because I spent years hunting such \"press hits.\" Our startup spent\nits entire marketing budget on PR: at a time when we were assembling\nour own computers to save money, we were paying a PR firm $16,000\na month. And they were worth it. PR is the news equivalent of\nsearch engine optimization; instead of buying ads, which readers\nignore, you get yourself inserted directly into the stories. [1]Our PR firm\nwas one of the best in the business. In 18 months, they got press\nhits in over 60 different publications. \nAnd we weren't the only ones they did great things for. \nIn 1997 I got a call from another\nstartup founder considering hiring them to promote his company. I\ntold him they were PR gods, worth every penny of their outrageous \nfees. But I remember thinking his company's name was odd.\nWhy call an auction site \"eBay\"?\nSymbiosisPR is not dishonest. Not quite. In fact, the reason the best PR\nfirms are so effective is precisely that they aren't dishonest.\nThey give reporters genuinely valuable information. A good PR firm\nwon't bug reporters just because the client tells them to; they've\nworked hard to build their credibility with reporters, and they\ndon't want to destroy it by feeding them mere propaganda.If anyone is dishonest, it's the reporters. The main reason PR \nfirms exist is that reporters are lazy. Or, to put it more nicely,\noverworked. Really they ought to be out there digging up stories\nfor themselves. But it's so tempting to sit in their offices and\nlet PR firms bring the stories to them. After all, they know good\nPR firms won't lie to them.A good flatterer doesn't lie, but tells his victim selective truths\n(what a nice color your eyes are). Good PR firms use the same\nstrategy: they give reporters stories that are true, but whose truth\nfavors their clients.For example, our PR firm often pitched stories about how the Web \nlet small merchants compete with big ones. This was perfectly true.\nBut the reason reporters ended up writing stories about this\nparticular truth, rather than some other one, was that small merchants\nwere our target market, and we were paying the piper.Different publications vary greatly in their reliance on PR firms.\nAt the bottom of the heap are the trade press, who make most of\ntheir money from advertising and would give the magazines away for\nfree if advertisers would let them. [2] The average\ntrade publication is a bunch of ads, glued together by just enough\narticles to make it look like a magazine. They're so desperate for\n\"content\" that some will print your press releases almost verbatim,\nif you take the trouble to write them to read like articles.At the other extreme are publications like the New York Times\nand the Wall Street Journal. Their reporters do go out and\nfind their own stories, at least some of the time. They'll listen \nto PR firms, but briefly and skeptically. We managed to get press \nhits in almost every publication we wanted, but we never managed \nto crack the print edition of the Times. [3]The weak point of the top reporters is not laziness, but vanity.\nYou don't pitch stories to them. You have to approach them as if\nyou were a specimen under their all-seeing microscope, and make it\nseem as if the story you want them to run is something they thought \nof themselves.Our greatest PR coup was a two-part one. We estimated, based on\nsome fairly informal math, that there were about 5000 stores on the\nWeb. We got one paper to print this number, which seemed neutral \nenough. But once this \"fact\" was out there in print, we could quote\nit to other publications, and claim that with 1000 users we had 20%\nof the online store market.This was roughly true. We really did have the biggest share of the\nonline store market, and 5000 was our best guess at its size. But\nthe way the story appeared in the press sounded a lot more definite.Reporters like definitive statements. For example, many of the\nstories about Jeremy Jaynes's conviction say that he was one of the\n10 worst spammers. This \"fact\" originated in Spamhaus's ROKSO list,\nwhich I think even Spamhaus would admit is a rough guess at the top\nspammers. The first stories about Jaynes cited this source, but\nnow it's simply repeated as if it were part of the indictment. \n[4]All you can say with certainty about Jaynes is that he was a fairly\nbig spammer. But reporters don't want to print vague stuff like\n\"fairly big.\" They want statements with punch, like \"top ten.\" And\nPR firms give them what they want.\nWearing suits, we're told, will make us \n3.6\npercent more productive.BuzzWhere the work of PR firms really does get deliberately misleading is in\nthe generation of \"buzz.\" They usually feed the same story to \nseveral different publications at once. And when readers see similar\nstories in multiple places, they think there is some important trend\nafoot. Which is exactly what they're supposed to think.When Windows 95 was launched, people waited outside stores\nat midnight to buy the first copies. None of them would have been\nthere without PR firms, who generated such a buzz in\nthe news media that it became self-reinforcing, like a nuclear chain\nreaction.I doubt PR firms realize it yet, but the Web makes it possible to \ntrack them at work. If you search for the obvious phrases, you\nturn up several efforts over the years to place stories about the \nreturn of the suit. For example, the Reuters article \n\nthat got picked up by USA\nToday in September 2004. \"The suit is back,\" it begins.Trend articles like this are almost always the work of\nPR firms. Once you know how to read them, it's straightforward to\nfigure out who the client is. With trend stories, PR firms usually\nline up one or more \"experts\" to talk about the industry generally. \nIn this case we get three: the NPD Group, the creative director of\nGQ, and a research director at Smith Barney. [5] When\nyou get to the end of the experts, look for the client. And bingo, \nthere it is: The Men's Wearhouse.Not surprising, considering The Men's Wearhouse was at that moment \nrunning ads saying \"The Suit is Back.\" Talk about a successful\npress hit-- a wire service article whose first sentence is your own\nad copy.The secret to finding other press hits from a given pitch\nis to realize that they all started from the same document back at\nthe PR firm. Search for a few key phrases and the names of the\nclients and the experts, and you'll turn up other variants of this \nstory.Casual\nfridays are out and dress codes are in writes Diane E. Lewis\nin The Boston Globe. In a remarkable coincidence, Ms. Lewis's\nindustry contacts also include the creative director of GQ.Ripped jeans and T-shirts are out, writes Mary Kathleen Flynn in\nUS News & World Report. And she too knows the \ncreative director of GQ.Men's suits\nare back writes Nicole Ford in Sexbuzz.Com (\"the ultimate men's\nentertainment magazine\").Dressing\ndown loses appeal as men suit up at the office writes Tenisha\nMercer of The Detroit News.\nNow that so many news articles are online, I suspect you could find\na similar pattern for most trend stories placed by PR firms. I\npropose we call this new sport \"PR diving,\" and I'm sure there are\nfar more striking examples out there than this clump of five stories.OnlineAfter spending years chasing them, it's now second nature\nto me to recognize press hits for what they are. But before we\nhired a PR firm I had no idea where articles in the mainstream media\ncame from. I could tell a lot of them were crap, but I didn't\nrealize why.Remember the exercises in critical reading you did in school, where\nyou had to look at a piece of writing and step back and ask whether\nthe author was telling the whole truth? If you really want to be\na critical reader, it turns out you have to step back one step\nfurther, and ask not just whether the author is telling the truth,\nbut why he's writing about this subject at all.Online, the answer tends to be a lot simpler. Most people who\npublish online write what they write for the simple reason that\nthey want to. You\ncan't see the fingerprints of PR firms all over the articles, as\nyou can in so many print publications-- which is one of the reasons,\nthough they may not consciously realize it, that readers trust\nbloggers more than Business Week.I was talking recently to a friend who works for a\nbig newspaper. He thought the print media were in serious trouble,\nand that they were still mostly in denial about it. \"They think\nthe decline is cyclic,\" he said. \"Actually it's structural.\"In other words, the readers are leaving, and they're not coming\nback.\nWhy? I think the main reason is that the writing online is more honest.\nImagine how incongruous the New York Times article about\nsuits would sound if you read it in a blog:\n The urge to look corporate-- sleek, commanding,\n prudent, yet with just a touch of hubris on your well-cut sleeve--\n is an unexpected development in a time of business disgrace.\n \nThe problem\nwith this article is not just that it originated in a PR firm.\nThe whole tone is bogus. This is the tone of someone writing down\nto their audience.Whatever its flaws, the writing you find online\nis authentic. It's not mystery meat cooked up\nout of scraps of pitch letters and press releases, and pressed into \nmolds of zippy\njournalese. It's people writing what they think.I didn't realize, till there was an alternative, just how artificial\nmost of the writing in the mainstream media was. I'm not saying\nI used to believe what I read in Time and Newsweek. Since high\nschool, at least, I've thought of magazines like that more as\nguides to what ordinary people were being\ntold to think than as \nsources of information. But I didn't realize till the last \nfew years that writing for publication didn't have to mean writing\nthat way. I didn't realize you could write as candidly and\ninformally as you would if you were writing to a friend.Readers aren't the only ones who've noticed the\nchange. The PR industry has too.\nA hilarious article\non the site of the PR Society of America gets to the heart of the \nmatter:\n Bloggers are sensitive about becoming mouthpieces\n for other organizations and companies, which is the reason they\n began blogging in the first place. \nPR people fear bloggers for the same reason readers\nlike them. And that means there may be a struggle ahead. As\nthis new kind of writing draws readers away from traditional media, we\nshould be prepared for whatever PR mutates into to compensate. \nWhen I think \nhow hard PR firms work to score press hits in the traditional \nmedia, I can't imagine they'll work any less hard to feed stories\nto bloggers, if they can figure out how.\nNotes[1] PR has at least \none beneficial feature: it favors small companies. If PR didn't \nwork, the only alternative would be to advertise, and only big\ncompanies can afford that.[2] Advertisers pay \nless for ads in free publications, because they assume readers \nignore something they get for free. This is why so many trade\npublications nominally have a cover price and yet give away free\nsubscriptions with such abandon.[3] Different sections\nof the Times vary so much in their standards that they're\npractically different papers. Whoever fed the style section reporter\nthis story about suits coming back would have been sent packing by\nthe regular news reporters.[4] The most striking\nexample I know of this type is the \"fact\" that the Internet worm \nof 1988 infected 6000 computers. I was there when it was cooked up,\nand this was the recipe: someone guessed that there were about\n60,000 computers attached to the Internet, and that the worm might\nhave infected ten percent of them.Actually no one knows how many computers the worm infected, because\nthe remedy was to reboot them, and this destroyed all traces. But\npeople like numbers. And so this one is now replicated\nall over the Internet, like a little worm of its own.[5] Not all were\nnecessarily supplied by the PR firm. Reporters sometimes call a few\nadditional sources on their own, like someone adding a few fresh \nvegetables to a can of soup.\nThanks to Ingrid Basset, Trevor Blackwell, Sarah Harlin, Jessica \nLivingston, Jackie McDonough, Robert Morris, and Aaron Swartz (who\nalso found the PRSA article) for reading drafts of this.Correction: Earlier versions used a recent\nBusiness Week article mentioning del.icio.us as an example\nof a press hit, but Joshua Schachter tells me \nit was spontaneous." }, { "path": "data/PaulGrahamEssaysLarge/sun.txt", "content": "September 2017The most valuable insights are both general and surprising. \nF = ma for example. But general and surprising is a hard\ncombination to achieve. That territory tends to be picked\nclean, precisely because those insights are so valuable.Ordinarily, the best that people can do is one without the\nother: either surprising without being general (e.g.\ngossip), or general without being surprising (e.g.\nplatitudes).Where things get interesting is the moderately valuable\ninsights. You get those from small additions of whichever\nquality was missing. The more common case is a small\naddition of generality: a piece of gossip that's more than\njust gossip, because it teaches something interesting about\nthe world. But another less common approach is to focus on\nthe most general ideas and see if you can find something new\nto say about them. Because these start out so general, you\nonly need a small delta of novelty to produce a useful\ninsight.A small delta of novelty is all you'll be able to get most\nof the time. Which means if you take this route, your ideas\nwill seem a lot like ones that already exist. Sometimes\nyou'll find you've merely rediscovered an idea that did\nalready exist. But don't be discouraged. Remember the huge\nmultiplier that kicks in when you do manage to think of\nsomething even a little new.Corollary: the more general the ideas you're talking about,\nthe less you should worry about repeating yourself. If you\nwrite enough, it's inevitable you will. Your brain is much\nthe same from year to year and so are the stimuli that hit\nit. I feel slightly bad when I find I've said something\nclose to what I've said before, as if I were plagiarizing\nmyself. But rationally one shouldn't. You won't say\nsomething exactly the same way the second time, and that\nvariation increases the chance you'll get that tiny but\ncritical delta of novelty.And of course, ideas beget ideas. (That sounds \nfamiliar.)\nAn idea with a small amount of novelty could lead to one\nwith more. But only if you keep going. So it's doubly\nimportant not to let yourself be discouraged by people who\nsay there's not much new about something you've discovered.\n\"Not much new\" is a real achievement when you're talking\nabout the most general ideas. It's not true that there's nothing new under the sun. There\nare some domains where there's almost nothing new. But\nthere's a big difference between nothing and almost nothing,\nwhen it's multiplied by the area under the sun.\nThanks to Sam Altman, Patrick Collison, and Jessica\nLivingston for reading drafts of this." }, { "path": "data/PaulGrahamEssaysLarge/superangels.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nOctober 2010After barely changing at all for decades, the startup funding\nbusiness is now in what could, at least by comparison, be called\nturmoil. At Y Combinator we've seen dramatic changes in the funding\nenvironment for startups. Fortunately one of them is much higher\nvaluations.The trends we've been seeing are probably not YC-specific. I wish\nI could say they were, but the main cause is probably just that we\nsee trends first—partly because the startups we fund are very\nplugged into the Valley and are quick to take advantage of anything\nnew, and partly because we fund so many that we have enough data\npoints to see patterns clearly.What we're seeing now, everyone's probably going to be seeing in\nthe next couple years. So I'm going to explain what we're seeing,\nand what that will mean for you if you try to raise money.Super-AngelsLet me start by describing what the world of startup funding used\nto look like. There used to be two sharply differentiated types\nof investors: angels and venture capitalists. Angels are individual\nrich people who invest small amounts of their own money, while VCs\nare employees of funds that invest large amounts of other people's.For decades there were just those two types of investors, but now\na third type has appeared halfway between them: the so-called\nsuper-angels. \n[1]\n And VCs have been provoked by their arrival\ninto making a lot of angel-style investments themselves. So the\npreviously sharp line between angels and VCs has become hopelessly\nblurred.There used to be a no man's land between angels and VCs. Angels\nwould invest $20k to $50k apiece, and VCs usually a million or more.\nSo an angel round meant a collection of angel investments that\ncombined to maybe $200k, and a VC round meant a series A round in\nwhich a single VC fund (or occasionally two) invested $1-5 million.The no man's land between angels and VCs was a very inconvenient\none for startups, because it coincided with the amount many wanted\nto raise. Most startups coming out of Demo Day wanted to raise\naround $400k. But it was a pain to stitch together that much out\nof angel investments, and most VCs weren't interested in investments\nso small. That's the fundamental reason the super-angels have\nappeared. They're responding to the market.The arrival of a new type of investor is big news for startups,\nbecause there used to be only two and they rarely competed with one\nanother. Super-angels compete with both angels and VCs. That's\ngoing to change the rules about how to raise money. I don't know\nyet what the new rules will be, but it looks like most of the changes\nwill be for the better.A super-angel has some of the qualities of an angel, and some of\nthe qualities of a VC. They're usually individuals, like angels.\nIn fact many of the current super-angels were initially angels of\nthe classic type. But like VCs, they invest other people's money.\nThis allows them to invest larger amounts than angels: a typical\nsuper-angel investment is currently about $100k. They make investment\ndecisions quickly, like angels. And they make a lot more investments\nper partner than VCs—up to 10 times as many.The fact that super-angels invest other people's money makes them\ndoubly alarming to VCs. They don't just compete for startups; they\nalso compete for investors. What super-angels really are is a new\nform of fast-moving, lightweight VC fund. And those of us in the\ntechnology world know what usually happens when something comes\nalong that can be described in terms like that. Usually it's the\nreplacement.Will it be? As of now, few of the startups that take money from\nsuper-angels are ruling out taking VC money. They're just postponing\nit. But that's still a problem for VCs. Some of the startups that\npostpone raising VC money may do so well on the angel money they\nraise that they never bother to raise more. And those who do raise\nVC rounds will be able to get higher valuations when they do. If\nthe best startups get 10x higher valuations when they raise series\nA rounds, that would cut VCs' returns from winners at least tenfold.\n[2]So I think VC funds are seriously threatened by the super-angels.\nBut one thing that may save them to some extent is the uneven\ndistribution of startup outcomes: practically all the returns are\nconcentrated in a few big successes. The expected value of a startup\nis the percentage chance it's Google. So to the extent that winning\nis a matter of absolute returns, the super-angels could win practically\nall the battles for individual startups and yet lose the war, if\nthey merely failed to get those few big winners. And there's a\nchance that could happen, because the top VC funds have better\nbrands, and can also do more for their portfolio companies. \n[3]Because super-angels make more investments per partner, they have\nless partner per investment. They can't pay as much attention to\nyou as a VC on your board could. How much is that extra attention\nworth? It will vary enormously from one partner to another. There's\nno consensus yet in the general case. So for now this is something\nstartups are deciding individually.Till now, VCs' claims about how much value they added were sort of\nlike the government's. Maybe they made you feel better, but you\nhad no choice in the matter, if you needed money on the scale only\nVCs could supply. Now that VCs have competitors, that's going to\nput a market price on the help they offer. The interesting thing\nis, no one knows yet what it will be.Do startups that want to get really big need the sort of advice and\nconnections only the top VCs can supply? Or would super-angel money\ndo just as well? The VCs will say you need them, and the super-angels\nwill say you don't. But the truth is, no one knows yet, not even\nthe VCs and super-angels themselves. All the super-angels know\nis that their new model seems promising enough to be worth trying,\nand all the VCs know is that it seems promising enough to worry\nabout.RoundsWhatever the outcome, the conflict between VCs and super-angels is\ngood news for founders. And not just for the obvious reason that\nmore competition for deals means better terms. The whole shape of\ndeals is changing.One of the biggest differences between angels and VCs is the amount\nof your company they want. VCs want a lot. In a series A round\nthey want a third of your company, if they can get it. They don't\ncare much how much they pay for it, but they want a lot because the\nnumber of series A investments they can do is so small. In a\ntraditional series A investment, at least one partner from the VC\nfund takes a seat on your board. \n[4]\n Since board seats last about\n5 years and each partner can't handle more than about 10 at once,\nthat means a VC fund can only do about 2 series A deals per partner\nper year. And that means they need to get as much of the company\nas they can in each one. You'd have to be a very promising startup\nindeed to get a VC to use up one of his 10 board seats for only a\nfew percent of you.Since angels generally don't take board seats, they don't have this\nconstraint. They're happy to buy only a few percent of you. And\nalthough the super-angels are in most respects mini VC funds, they've\nretained this critical property of angels. They don't take board\nseats, so they don't need a big percentage of your company.Though that means you'll get correspondingly less attention from\nthem, it's good news in other respects. Founders never really liked\ngiving up as much equity as VCs wanted. It was a lot of the company\nto give up in one shot. Most founders doing series A deals would\nprefer to take half as much money for half as much stock, and then\nsee what valuation they could get for the second half of the stock\nafter using the first half of the money to increase its value. But\nVCs never offered that option.Now startups have another alternative. Now it's easy to raise angel\nrounds about half the size of series A rounds. Many of the startups\nwe fund are taking this route, and I predict that will be true of\nstartups in general.A typical big angel round might be $600k on a convertible note with\na valuation cap of $4 million premoney. Meaning that when the note\nconverts into stock (in a later round, or upon acquisition), the\ninvestors in that round will get .6 / 4.6, or 13% of the company.\nThat's a lot less than the 30 to 40% of the company you usually\ngive up in a series A round if you do it so early. \n[5]But the advantage of these medium-sized rounds is not just that\nthey cause less dilution. You also lose less control. After an\nangel round, the founders almost always still have control of the\ncompany, whereas after a series A round they often don't. The\ntraditional board structure after a series A round is two founders,\ntwo VCs, and a (supposedly) neutral fifth person. Plus series A\nterms usually give the investors a veto over various kinds of\nimportant decisions, including selling the company. Founders usually\nhave a lot of de facto control after a series A, as long as things\nare going well. But that's not the same as just being able to do\nwhat you want, like you could before.A third and quite significant advantage of angel rounds is that\nthey're less stressful to raise. Raising a traditional series A\nround has in the past taken weeks, if not months. When a VC firm\ncan only do 2 deals per partner per year, they're careful about\nwhich they do. To get a traditional series A round you have to go\nthrough a series of meetings, culminating in a full partner meeting\nwhere the firm as a whole says yes or no. That's the really scary\npart for founders: not just that series A rounds take so long, but\nat the end of this long process the VCs might still say no. The\nchance of getting rejected after the full partner meeting averages\nabout 25%. At some firms it's over 50%.Fortunately for founders, VCs have been getting a lot faster.\nNowadays Valley VCs are more likely to take 2 weeks than 2 months.\nBut they're still not as fast as angels and super-angels, the most\ndecisive of whom sometimes decide in hours.Raising an angel round is not only quicker, but you get feedback\nas it progresses. An angel round is not an all or nothing thing\nlike a series A. It's composed of multiple investors with varying\ndegrees of seriousness, ranging from the upstanding ones who commit\nunequivocally to the jerks who give you lines like \"come back to\nme to fill out the round.\" You usually start collecting money from\nthe most committed investors and work your way out toward the\nambivalent ones, whose interest increases as the round fills up.But at each point you know how you're doing. If investors turn\ncold you may have to raise less, but when investors in an angel\nround turn cold the process at least degrades gracefully, instead\nof blowing up in your face and leaving you with nothing, as happens\nif you get rejected by a VC fund after a full partner meeting.\nWhereas if investors seem hot, you can not only close the round\nfaster, but now that convertible notes are becoming the norm,\nactually raise the price to reflect demand.ValuationHowever, the VCs have a weapon they can use against the super-angels,\nand they have started to use it. VCs have started making angel-sized\ninvestments too. The term \"angel round\" doesn't mean that all the\ninvestors in it are angels; it just describes the structure of the\nround. Increasingly the participants include VCs making investments\nof a hundred thousand or two. And when VCs invest in angel rounds\nthey can do things that super-angels don't like. VCs are quite\nvaluation-insensitive in angel rounds—partly because they are\nin general, and partly because they don't care that much about the\nreturns on angel rounds, which they still view mostly as a way to\nrecruit startups for series A rounds later. So VCs who invest in\nangel rounds can blow up the valuations for angels and super-angels\nwho invest in them. \n[6]Some super-angels seem to care about valuations. Several turned\ndown YC-funded startups after Demo Day because their valuations\nwere too high. This was not a problem for the startups; by definition\na high valuation means enough investors were willing to accept it.\nBut it was mysterious to me that the super-angels would quibble\nabout valuations. Did they not understand that the big returns\ncome from a few big successes, and that it therefore mattered far\nmore which startups you picked than how much you paid for them?After thinking about it for a while and observing certain other\nsigns, I have a theory that explains why the super-angels may be\nsmarter than they seem. It would make sense for super-angels to\nwant low valuations if they're hoping to invest in startups that\nget bought early. If you're hoping to hit the next Google, you\nshouldn't care if the valuation is 20 million. But if you're looking\nfor companies that are going to get bought for 30 million, you care.\nIf you invest at 20 and the company gets bought for 30, you only\nget 1.5x. You might as well buy Apple.So if some of the super-angels were looking for companies that could\nget acquired quickly, that would explain why they'd care about\nvaluations. But why would they be looking for those? Because\ndepending on the meaning of \"quickly,\" it could actually be very\nprofitable. A company that gets acquired for 30 million is a failure\nto a VC, but it could be a 10x return for an angel, and moreover,\na quick 10x return. Rate of return is what matters in\ninvesting—not the multiple you get, but the multiple per year.\nIf a super-angel gets 10x in one year, that's a higher rate of\nreturn than a VC could ever hope to get from a company that took 6\nyears to go public. To get the same rate of return, the VC would\nhave to get a multiple of 10^6—one million x. Even Google\ndidn't come close to that.So I think at least some super-angels are looking for companies\nthat will get bought. That's the only rational explanation for\nfocusing on getting the right valuations, instead of the right\ncompanies. And if so they'll be different to deal with than VCs.\nThey'll be tougher on valuations, but more accommodating if you want\nto sell early.PrognosisWho will win, the super-angels or the VCs? I think the answer to\nthat is, some of each. They'll each become more like one another.\nThe super-angels will start to invest larger amounts, and the VCs\nwill gradually figure out ways to make more, smaller investments\nfaster. A decade from now the players will be hard to tell apart,\nand there will probably be survivors from each group.What does that mean for founders? One thing it means is that the\nhigh valuations startups are presently getting may not last forever.\nTo the extent that valuations are being driven up by price-insensitive\nVCs, they'll fall again if VCs become more like super-angels and\nstart to become more miserly about valuations. Fortunately if this\ndoes happen it will take years.The short term forecast is more competition between investors, which\nis good news for you. The super-angels will try to undermine the\nVCs by acting faster, and the VCs will try to undermine the\nsuper-angels by driving up valuations. Which for founders will\nresult in the perfect combination: funding rounds that close fast,\nwith high valuations.But remember that to get that combination, your startup will have\nto appeal to both super-angels and VCs. If you don't seem like you\nhave the potential to go public, you won't be able to use VCs to\ndrive up the valuation of an angel round.There is a danger of having VCs in an angel round: the so-called\nsignalling risk. If VCs are only doing it in the hope of investing\nmore later, what happens if they don't? That's a signal to everyone\nelse that they think you're lame.How much should you worry about that? The seriousness of signalling\nrisk depends on how far along you are. If by the next time you\nneed to raise money, you have graphs showing rising revenue or\ntraffic month after month, you don't have to worry about any signals\nyour existing investors are sending. Your results will speak for\nthemselves. \n[7]Whereas if the next time you need to raise money you won't yet have\nconcrete results, you may need to think more about the message your\ninvestors might send if they don't invest more. I'm not sure yet\nhow much you have to worry, because this whole phenomenon of VCs\ndoing angel investments is so new. But my instincts tell me you\ndon't have to worry much. Signalling risk smells like one of those\nthings founders worry about that's not a real problem. As a rule,\nthe only thing that can kill a good startup is the startup itself.\nStartups hurt themselves way more often than competitors hurt them,\nfor example. I suspect signalling risk is in this category too.One thing YC-funded startups have been doing to mitigate the risk\nof taking money from VCs in angel rounds is not to take too much\nfrom any one VC. Maybe that will help, if you have the luxury of\nturning down money.Fortunately, more and more startups will. After decades of competition\nthat could best be described as intramural, the startup funding\nbusiness is finally getting some real competition. That should\nlast several years at least, and maybe a lot longer. Unless there's\nsome huge market crash, the next couple years are going to be a\ngood time for startups to raise money. And that's exciting because\nit means lots more startups will happen.\nNotes[1]\nI've also heard them called \"Mini-VCs\" and \"Micro-VCs.\" I\ndon't know which name will stick.There were a couple predecessors. Ron Conway had angel funds\nstarting in the 1990s, and in some ways First Round Capital is closer to a\nsuper-angel than a VC fund.[2]\nIt wouldn't cut their overall returns tenfold, because investing\nlater would probably (a) cause them to lose less on investments\nthat failed, and (b) not allow them to get as large a percentage\nof startups as they do now. So it's hard to predict precisely what\nwould happen to their returns.[3]\nThe brand of an investor derives mostly from the success of\ntheir portfolio companies. The top VCs thus have a big brand\nadvantage over the super-angels. They could make it self-perpetuating\nif they used it to get all the best new startups. But I don't think\nthey'll be able to. To get all the best startups, you have to do\nmore than make them want you. You also have to want them; you have\nto recognize them when you see them, and that's much harder.\nSuper-angels will snap up stars that VCs miss. And that will cause\nthe brand gap between the top VCs and the super-angels gradually\nto erode.[4]\nThough in a traditional series A round VCs put two partners\non your board, there are signs now that VCs may begin to conserve\nboard seats by switching to what used to be considered an angel-round\nboard, consisting of two founders and one VC. Which is also to the\nfounders' advantage if it means they still control the company.[5]\nIn a series A round, you usually have to give up more than\nthe actual amount of stock the VCs buy, because they insist you\ndilute yourselves to set aside an \"option pool\" as well. I predict\nthis practice will gradually disappear though.[6]\nThe best thing for founders, if they can get it, is a convertible\nnote with no valuation cap at all. In that case the money invested\nin the angel round just converts into stock at the valuation of the\nnext round, no matter how large. Angels and super-angels tend not\nto like uncapped notes. They have no idea how much of the company\nthey're buying. If the company does well and the valuation of the\nnext round is high, they may end up with only a sliver of it. So\nby agreeing to uncapped notes, VCs who don't care about valuations\nin angel rounds can make offers that super-angels hate to match.[7]\nObviously signalling risk is also not a problem if you'll\nnever need to raise more money. But startups are often mistaken\nabout that.Thanks to Sam Altman, John Bautista, Patrick Collison, James\nLindenbaum, Reid Hoffman, Jessica Livingston and Harj Taggar\nfor reading drafts\nof this." }, { "path": "data/PaulGrahamEssaysLarge/todo.txt", "content": "April 2012A palliative care nurse called Bronnie Ware made a list of the\nbiggest regrets\nof the dying. Her list seems plausible. I could see\nmyself — can see myself — making at least 4 of these\n5 mistakes.If you had to compress them into a single piece of advice, it might\nbe: don't be a cog. The 5 regrets paint a portrait of post-industrial\nman, who shrinks himself into a shape that fits his circumstances,\nthen turns dutifully till he stops.The alarming thing is, the mistakes that produce these regrets are\nall errors of omission. You forget your dreams, ignore your family,\nsuppress your feelings, neglect your friends, and forget to be\nhappy. Errors of omission are a particularly dangerous type of\nmistake, because you make them by default.I would like to avoid making these mistakes. But how do you avoid\nmistakes you make by default? Ideally you transform your life so\nit has other defaults. But it may not be possible to do that\ncompletely. As long as these mistakes happen by default, you probably\nhave to be reminded not to make them. So I inverted the 5 regrets,\nyielding a list of 5 commands\n\n Don't ignore your dreams; don't work too much; say what you\n think; cultivate friendships; be happy.\n\nwhich I then put at the top of the file I use as a todo list." }, { "path": "data/PaulGrahamEssaysLarge/unions.txt", "content": "May 2007People who worry about the increasing gap between rich and poor\ngenerally look back on the mid twentieth century as a golden age.\nIn those days we had a large number of high-paying union manufacturing\njobs that boosted the median income. I wouldn't quite call the\nhigh-paying union job a myth, but I think people who dwell on it\nare reading too much into it.Oddly enough, it was working with startups that made me realize\nwhere the high-paying union job came from. In a rapidly growing\nmarket, you don't worry too much about efficiency. It's more\nimportant to grow fast. If there's some mundane problem getting\nin your way, and there's a simple solution that's somewhat expensive,\njust take it and get on with more important things. EBay didn't\nwin by paying less for servers than their competitors.Difficult though it may be to imagine now, manufacturing was a\ngrowth industry in the mid twentieth century. This was an era when\nsmall firms making everything from cars to candy were getting\nconsolidated into a new kind of corporation with national reach and\nhuge economies of scale. You had to grow fast or die. Workers\nwere for these companies what servers are for an Internet startup.\nA reliable supply was more important than low cost.If you looked in the head of a 1950s auto executive, the attitude\nmust have been: sure, give 'em whatever they ask for, so long as\nthe new model isn't delayed.In other words, those workers were not paid what their work was\nworth. Circumstances being what they were, companies would have\nbeen stupid to insist on paying them so little.If you want a less controversial example of this phenomenon, ask\nanyone who worked as a consultant building web sites during the\nInternet Bubble. In the late nineties you could get paid huge sums\nof money for building the most trivial things. And yet does anyone\nwho was there have any expectation those days will ever return? I\ndoubt it. Surely everyone realizes that was just a temporary\naberration.The era of labor unions seems to have been the same kind of aberration, \njust spread\nover a longer period, and mixed together with a lot of ideology\nthat prevents people from viewing it with as cold an eye as they\nwould something like consulting during the Bubble.Basically, unions were just Razorfish.People who think the labor movement was the creation of heroic union\norganizers have a problem to explain: why are unions shrinking now?\nThe best they can do is fall back on the default explanation of\npeople living in fallen civilizations. Our ancestors were giants.\nThe workers of the early twentieth century must have had a moral\ncourage that's lacking today.In fact there's a simpler explanation. The early twentieth century\nwas just a fast-growing startup overpaying for infrastructure. And\nwe in the present are not a fallen people, who have abandoned\nwhatever mysterious high-minded principles produced the high-paying\nunion job. We simply live in a time when the fast-growing companies\noverspend on different things." }, { "path": "data/PaulGrahamEssaysLarge/useful.txt", "content": "February 2020What should an essay be? Many people would say persuasive. That's\nwhat a lot of us were taught essays should be. But I think we can\naim for something more ambitious: that an essay should be useful.To start with, that means it should be correct. But it's not enough\nmerely to be correct. It's easy to make a statement correct by\nmaking it vague. That's a common flaw in academic writing, for\nexample. If you know nothing at all about an issue, you can't go\nwrong by saying that the issue is a complex one, that there are\nmany factors to be considered, that it's a mistake to take too\nsimplistic a view of it, and so on.Though no doubt correct, such statements tell the reader nothing.\nUseful writing makes claims that are as strong as they can be made\nwithout becoming false.For example, it's more useful to say that Pike's Peak is near the\nmiddle of Colorado than merely somewhere in Colorado. But if I say\nit's in the exact middle of Colorado, I've now gone too far, because\nit's a bit east of the middle.Precision and correctness are like opposing forces. It's easy to\nsatisfy one if you ignore the other. The converse of vaporous\nacademic writing is the bold, but false, rhetoric of demagogues.\nUseful writing is bold, but true.It's also two other things: it tells people something important,\nand that at least some of them didn't already know.Telling people something they didn't know doesn't always mean\nsurprising them. Sometimes it means telling them something they\nknew unconsciously but had never put into words. In fact those may\nbe the more valuable insights, because they tend to be more\nfundamental.Let's put them all together. Useful writing tells people something\ntrue and important that they didn't already know, and tells them\nas unequivocally as possible.Notice these are all a matter of degree. For example, you can't\nexpect an idea to be novel to everyone. Any insight that you have\nwill probably have already been had by at least one of the world's\n7 billion people. But it's sufficient if an idea is novel to a lot\nof readers.Ditto for correctness, importance, and strength. In effect the four\ncomponents are like numbers you can multiply together to get a score\nfor usefulness. Which I realize is almost awkwardly reductive, but\nnonetheless true._____\nHow can you ensure that the things you say are true and novel and\nimportant? Believe it or not, there is a trick for doing this. I\nlearned it from my friend Robert Morris, who has a horror of saying\nanything dumb. His trick is not to say anything unless he's sure\nit's worth hearing. This makes it hard to get opinions out of him,\nbut when you do, they're usually right.Translated into essay writing, what this means is that if you write\na bad sentence, you don't publish it. You delete it and try again.\nOften you abandon whole branches of four or five paragraphs. Sometimes\na whole essay.You can't ensure that every idea you have is good, but you can\nensure that every one you publish is, by simply not publishing the\nones that aren't.In the sciences, this is called publication bias, and is considered\nbad. When some hypothesis you're exploring gets inconclusive results,\nyou're supposed to tell people about that too. But with essay\nwriting, publication bias is the way to go.My strategy is loose, then tight. I write the first draft of an\nessay fast, trying out all kinds of ideas. Then I spend days rewriting\nit very carefully.I've never tried to count how many times I proofread essays, but\nI'm sure there are sentences I've read 100 times before publishing\nthem. When I proofread an essay, there are usually passages that\nstick out in an annoying way, sometimes because they're clumsily\nwritten, and sometimes because I'm not sure they're true. The\nannoyance starts out unconscious, but after the tenth reading or\nso I'm saying \"Ugh, that part\" each time I hit it. They become like\nbriars that catch your sleeve as you walk past. Usually I won't\npublish an essay till they're all gone — till I can read through\nthe whole thing without the feeling of anything catching.I'll sometimes let through a sentence that seems clumsy, if I can't\nthink of a way to rephrase it, but I will never knowingly let through\none that doesn't seem correct. You never have to. If a sentence\ndoesn't seem right, all you have to do is ask why it doesn't, and\nyou've usually got the replacement right there in your head.This is where essayists have an advantage over journalists. You\ndon't have a deadline. You can work for as long on an essay as you\nneed to get it right. You don't have to publish the essay at all,\nif you can't get it right. Mistakes seem to lose courage in the\nface of an enemy with unlimited resources. Or that's what it feels\nlike. What's really going on is that you have different expectations\nfor yourself. You're like a parent saying to a child \"we can sit\nhere all night till you eat your vegetables.\" Except you're the\nchild too.I'm not saying no mistake gets through. For example, I added condition\n(c) in \"A Way to Detect Bias\" \nafter readers pointed out that I'd\nomitted it. But in practice you can catch nearly all of them.There's a trick for getting importance too. It's like the trick I\nsuggest to young founders for getting startup ideas: to make something\nyou yourself want. You can use yourself as a proxy for the reader.\nThe reader is not completely unlike you, so if you write about\ntopics that seem important to you, they'll probably seem important\nto a significant number of readers as well.Importance has two factors. It's the number of people something\nmatters to, times how much it matters to them. Which means of course\nthat it's not a rectangle, but a sort of ragged comb, like a Riemann\nsum.The way to get novelty is to write about topics you've thought about\na lot. Then you can use yourself as a proxy for the reader in this\ndepartment too. Anything you notice that surprises you, who've\nthought about the topic a lot, will probably also surprise a\nsignificant number of readers. And here, as with correctness and\nimportance, you can use the Morris technique to ensure that you\nwill. If you don't learn anything from writing an essay, don't\npublish it.You need humility to measure novelty, because acknowledging the\nnovelty of an idea means acknowledging your previous ignorance of\nit. Confidence and humility are often seen as opposites, but in\nthis case, as in many others, confidence helps you to be humble.\nIf you know you're an expert on some topic, you can freely admit\nwhen you learn something you didn't know, because you can be confident\nthat most other people wouldn't know it either.The fourth component of useful writing, strength, comes from two\nthings: thinking well, and the skillful use of qualification. These\ntwo counterbalance each other, like the accelerator and clutch in\na car with a manual transmission. As you try to refine the expression\nof an idea, you adjust the qualification accordingly. Something\nyou're sure of, you can state baldly with no qualification at all,\nas I did the four components of useful writing. Whereas points that\nseem dubious have to be held at arm's length with perhapses.As you refine an idea, you're pushing in the direction of less\nqualification. But you can rarely get it down to zero. Sometimes\nyou don't even want to, if it's a side point and a fully refined\nversion would be too long.Some say that qualifications weaken writing. For example, that you\nshould never begin a sentence in an essay with \"I think,\" because\nif you're saying it, then of course you think it. And it's true\nthat \"I think x\" is a weaker statement than simply \"x.\" Which is\nexactly why you need \"I think.\" You need it to express your degree\nof certainty.But qualifications are not scalars. They're not just experimental\nerror. There must be 50 things they can express: how broadly something\napplies, how you know it, how happy you are it's so, even how it\ncould be falsified. I'm not going to try to explore the structure\nof qualification here. It's probably more complex than the whole\ntopic of writing usefully. Instead I'll just give you a practical\ntip: Don't underestimate qualification. It's an important skill in\nits own right, not just a sort of tax you have to pay in order to\navoid saying things that are false. So learn and use its full range.\nIt may not be fully half of having good ideas, but it's part of\nhaving them.There's one other quality I aim for in essays: to say things as\nsimply as possible. But I don't think this is a component of\nusefulness. It's more a matter of consideration for the reader. And\nit's a practical aid in getting things right; a mistake is more\nobvious when expressed in simple language. But I'll admit that the\nmain reason I write simply is not for the reader's sake or because\nit helps get things right, but because it bothers me to use more\nor fancier words than I need to. It seems inelegant, like a program\nthat's too long.I realize florid writing works for some people. But unless you're\nsure you're one of them, the best advice is to write as simply as\nyou can._____\nI believe the formula I've given you, importance + novelty +\ncorrectness + strength, is the recipe for a good essay. But I should\nwarn you that it's also a recipe for making people mad.The root of the problem is novelty. When you tell people something\nthey didn't know, they don't always thank you for it. Sometimes the\nreason people don't know something is because they don't want to\nknow it. Usually because it contradicts some cherished belief. And\nindeed, if you're looking for novel ideas, popular but mistaken\nbeliefs are a good place to find them. Every popular mistaken belief\ncreates a dead zone of ideas around \nit that are relatively unexplored because they contradict it.The strength component just makes things worse. If there's anything\nthat annoys people more than having their cherished assumptions\ncontradicted, it's having them flatly contradicted.Plus if you've used the Morris technique, your writing will seem\nquite confident. Perhaps offensively confident, to people who\ndisagree with you. The reason you'll seem confident is that you are\nconfident: you've cheated, by only publishing the things you're\nsure of. It will seem to people who try to disagree with you that\nyou never admit you're wrong. In fact you constantly admit you're\nwrong. You just do it before publishing instead of after.And if your writing is as simple as possible, that just makes things\nworse. Brevity is the diction of command. If you watch someone\ndelivering unwelcome news from a position of inferiority, you'll\nnotice they tend to use lots of words, to soften the blow. Whereas\nto be short with someone is more or less to be rude to them.It can sometimes work to deliberately phrase statements more weakly\nthan you mean. To put \"perhaps\" in front of something you're actually\nquite sure of. But you'll notice that when writers do this, they\nusually do it with a wink.I don't like to do this too much. It's cheesy to adopt an ironic\ntone for a whole essay. I think we just have to face the fact that\nelegance and curtness are two names for the same thing.You might think that if you work sufficiently hard to ensure that\nan essay is correct, it will be invulnerable to attack. That's sort\nof true. It will be invulnerable to valid attacks. But in practice\nthat's little consolation.In fact, the strength component of useful writing will make you\nparticularly vulnerable to misrepresentation. If you've stated an\nidea as strongly as you could without making it false, all anyone\nhas to do is to exaggerate slightly what you said, and now it is\nfalse.Much of the time they're not even doing it deliberately. One of the\nmost surprising things you'll discover, if you start writing essays,\nis that people who disagree with you rarely disagree with what\nyou've actually written. Instead they make up something you said\nand disagree with that.For what it's worth, the countermove is to ask someone who does\nthis to quote a specific sentence or passage you wrote that they\nbelieve is false, and explain why. I say \"for what it's worth\"\nbecause they never do. So although it might seem that this could\nget a broken discussion back on track, the truth is that it was\nnever on track in the first place.Should you explicitly forestall likely misinterpretations? Yes, if\nthey're misinterpretations a reasonably smart and well-intentioned\nperson might make. In fact it's sometimes better to say something\nslightly misleading and then add the correction than to try to get\nan idea right in one shot. That can be more efficient, and can also\nmodel the way such an idea would be discovered.But I don't think you should explicitly forestall intentional\nmisinterpretations in the body of an essay. An essay is a place to\nmeet honest readers. You don't want to spoil your house by putting\nbars on the windows to protect against dishonest ones. The place\nto protect against intentional misinterpretations is in end-notes.\nBut don't think you can predict them all. People are as ingenious\nat misrepresenting you when you say something they don't want to\nhear as they are at coming up with rationalizations for things they\nwant to do but know they shouldn't. I suspect it's the same skill._____\nAs with most other things, the way to get better at writing essays\nis to practice. But how do you start? Now that we've examined the\nstructure of useful writing, we can rephrase that question more\nprecisely. Which constraint do you relax initially? The answer is,\nthe first component of importance: the number of people who care\nabout what you write.If you narrow the topic sufficiently, you can probably find something\nyou're an expert on. Write about that to start with. If you only\nhave ten readers who care, that's fine. You're helping them, and\nyou're writing. Later you can expand the breadth of topics you write\nabout.The other constraint you can relax is a little surprising: publication.\nWriting essays doesn't have to mean publishing them. That may seem\nstrange now that the trend is to publish every random thought, but\nit worked for me. I wrote what amounted to essays in notebooks for\nabout 15 years. I never published any of them and never expected\nto. I wrote them as a way of figuring things out. But when the web\ncame along I'd had a lot of practice.Incidentally, \nSteve \nWozniak did the same thing. In high school he\ndesigned computers on paper for fun. He couldn't build them because\nhe couldn't afford the components. But when Intel launched 4K DRAMs\nin 1975, he was ready._____\nHow many essays are there left to write though? The answer to that\nquestion is probably the most exciting thing I've learned about\nessay writing. Nearly all of them are left to write.Although the essay \nis an old form, it hasn't been assiduously\ncultivated. In the print era, publication was expensive, and there\nwasn't enough demand for essays to publish that many. You could\npublish essays if you were already well known for writing something\nelse, like novels. Or you could write book reviews that you took\nover to express your own ideas. But there was not really a direct\npath to becoming an essayist. Which meant few essays got written,\nand those that did tended to be about a narrow range of subjects.Now, thanks to the internet, there's a path. Anyone can publish\nessays online. You start in obscurity, perhaps, but at least you\ncan start. You don't need anyone's permission.It sometimes happens that an area of knowledge sits quietly for\nyears, till some change makes it explode. Cryptography did this to\nnumber theory. The internet is doing it to the essay.The exciting thing is not that there's a lot left to write, but\nthat there's a lot left to discover. There's a certain kind of idea\nthat's best discovered by writing essays. If most essays are still\nunwritten, most such ideas are still undiscovered.Notes[1] Put railings on the balconies, but don't put bars on the windows.[2] Even now I sometimes write essays that are not meant for\npublication. I wrote several to figure out what Y Combinator should\ndo, and they were really helpful.Thanks to Trevor Blackwell, Daniel Gackle, Jessica Livingston, and\nRobert Morris for reading drafts of this." }, { "path": "data/PaulGrahamEssaysLarge/vb.txt", "content": "January 2016Life is short, as everyone knows. When I was a kid I used to wonder\nabout this. Is life actually short, or are we really complaining\nabout its finiteness? Would we be just as likely to feel life was\nshort if we lived 10 times as long?Since there didn't seem any way to answer this question, I stopped\nwondering about it. Then I had kids. That gave me a way to answer\nthe question, and the answer is that life actually is short.Having kids showed me how to convert a continuous quantity, time,\ninto discrete quantities. You only get 52 weekends with your 2 year\nold. If Christmas-as-magic lasts from say ages 3 to 10, you only\nget to watch your child experience it 8 times. And while it's\nimpossible to say what is a lot or a little of a continuous quantity\nlike time, 8 is not a lot of something. If you had a handful of 8\npeanuts, or a shelf of 8 books to choose from, the quantity would\ndefinitely seem limited, no matter what your lifespan was.Ok, so life actually is short. Does it make any difference to know\nthat?It has for me. It means arguments of the form \"Life is too short\nfor x\" have great force. It's not just a figure of speech to say\nthat life is too short for something. It's not just a synonym for\nannoying. If you find yourself thinking that life is too short for\nsomething, you should try to eliminate it if you can.When I ask myself what I've found life is too short for, the word\nthat pops into my head is \"bullshit.\" I realize that answer is\nsomewhat tautological. It's almost the definition of bullshit that\nit's the stuff that life is too short for. And yet bullshit does\nhave a distinctive character. There's something fake about it.\nIt's the junk food of experience.\n[1]If you ask yourself what you spend your time on that's bullshit,\nyou probably already know the answer. Unnecessary meetings, pointless\ndisputes, bureaucracy, posturing, dealing with other people's\nmistakes, traffic jams, addictive but unrewarding pastimes.There are two ways this kind of thing gets into your life: it's\neither forced on you, or it tricks you. To some extent you have to\nput up with the bullshit forced on you by circumstances. You need\nto make money, and making money consists mostly of errands. Indeed,\nthe law of supply and demand insures that: the more rewarding some\nkind of work is, the cheaper people will do it. It may be that\nless bullshit is forced on you than you think, though. There has\nalways been a stream of people who opt out of the default grind and\ngo live somewhere where opportunities are fewer in the conventional\nsense, but life feels more authentic. This could become more common.You can do it on a smaller scale without moving. The amount of\ntime you have to spend on bullshit varies between employers. Most\nlarge organizations (and many small ones) are steeped in it. But\nif you consciously prioritize bullshit avoidance over other factors\nlike money and prestige, you can probably find employers that will\nwaste less of your time.If you're a freelancer or a small company, you can do this at the\nlevel of individual customers. If you fire or avoid toxic customers,\nyou can decrease the amount of bullshit in your life by more than\nyou decrease your income.But while some amount of bullshit is inevitably forced on you, the\nbullshit that sneaks into your life by tricking you is no one's\nfault but your own. And yet the bullshit you choose may be harder\nto eliminate than the bullshit that's forced on you. Things that\nlure you into wasting your time have to be really good at\ntricking you. An example that will be familiar to a lot of people\nis arguing online. When someone\ncontradicts you, they're in a sense attacking you. Sometimes pretty\novertly. Your instinct when attacked is to defend yourself. But\nlike a lot of instincts, this one wasn't designed for the world we\nnow live in. Counterintuitive as it feels, it's better most of\nthe time not to defend yourself. Otherwise these people are literally\ntaking your life.\n[2]Arguing online is only incidentally addictive. There are more\ndangerous things than that. As I've written before, one byproduct\nof technical progress is that things we like tend to become more\naddictive. Which means we will increasingly have to make a conscious\neffort to avoid addictions — to stand outside ourselves and ask \"is\nthis how I want to be spending my time?\"As well as avoiding bullshit, one should actively seek out things\nthat matter. But different things matter to different people, and\nmost have to learn what matters to them. A few are lucky and realize\nearly on that they love math or taking care of animals or writing,\nand then figure out a way to spend a lot of time doing it. But\nmost people start out with a life that's a mix of things that\nmatter and things that don't, and only gradually learn to distinguish\nbetween them.For the young especially, much of this confusion is induced by the\nartificial situations they find themselves in. In middle school and\nhigh school, what the other kids think of you seems the most important\nthing in the world. But when you ask adults what they got wrong\nat that age, nearly all say they cared too much what other kids\nthought of them.One heuristic for distinguishing stuff that matters is to ask\nyourself whether you'll care about it in the future. Fake stuff\nthat matters usually has a sharp peak of seeming to matter. That's\nhow it tricks you. The area under the curve is small, but its shape\njabs into your consciousness like a pin.The things that matter aren't necessarily the ones people would\ncall \"important.\" Having coffee with a friend matters. You won't\nfeel later like that was a waste of time.One great thing about having small children is that they make you\nspend time on things that matter: them. They grab your sleeve as\nyou're staring at your phone and say \"will you play with me?\" And\nodds are that is in fact the bullshit-minimizing option.If life is short, we should expect its shortness to take us by\nsurprise. And that is just what tends to happen. You take things\nfor granted, and then they're gone. You think you can always write\nthat book, or climb that mountain, or whatever, and then you realize\nthe window has closed. The saddest windows close when other people\ndie. Their lives are short too. After my mother died, I wished I'd\nspent more time with her. I lived as if she'd always be there.\nAnd in her typical quiet way she encouraged that illusion. But an\nillusion it was. I think a lot of people make the same mistake I\ndid.The usual way to avoid being taken by surprise by something is to\nbe consciously aware of it. Back when life was more precarious,\npeople used to be aware of death to a degree that would now seem a\nbit morbid. I'm not sure why, but it doesn't seem the right answer\nto be constantly reminding oneself of the grim reaper hovering at\neveryone's shoulder. Perhaps a better solution is to look at the\nproblem from the other end. Cultivate a habit of impatience about\nthe things you most want to do. Don't wait before climbing that\nmountain or writing that book or visiting your mother. You don't\nneed to be constantly reminding yourself why you shouldn't wait.\nJust don't wait.I can think of two more things one does when one doesn't have much\nof something: try to get more of it, and savor what one has. Both\nmake sense here.How you live affects how long you live. Most people could do better.\nMe among them.But you can probably get even more effect by paying closer attention\nto the time you have. It's easy to let the days rush by. The\n\"flow\" that imaginative people love so much has a darker cousin\nthat prevents you from pausing to savor life amid the daily slurry\nof errands and alarms. One of the most striking things I've read\nwas not in a book, but the title of one: James Salter's Burning\nthe Days.It is possible to slow time somewhat. I've gotten better at it.\nKids help. When you have small children, there are a lot of moments\nso perfect that you can't help noticing.It does help too to feel that you've squeezed everything out of\nsome experience. The reason I'm sad about my mother is not just\nthat I miss her but that I think of all the things we could have\ndone that we didn't. My oldest son will be 7 soon. And while I\nmiss the 3 year old version of him, I at least don't have any regrets\nover what might have been. We had the best time a daddy and a 3\nyear old ever had.Relentlessly prune bullshit, don't wait to do things that matter,\nand savor the time you have. That's what you do when life is short.Notes[1]\nAt first I didn't like it that the word that came to mind was\none that had other meanings. But then I realized the other meanings\nare fairly closely related. Bullshit in the sense of things you\nwaste your time on is a lot like intellectual bullshit.[2]\nI chose this example deliberately as a note to self. I get\nattacked a lot online. People tell the craziest lies about me.\nAnd I have so far done a pretty mediocre job of suppressing the\nnatural human inclination to say \"Hey, that's not true!\"Thanks to Jessica Livingston and Geoff Ralston for reading drafts\nof this." }, { "path": "data/PaulGrahamEssaysLarge/vcsqueeze.txt", "content": "November 2005In the next few years, venture capital funds will find themselves\nsqueezed from four directions. They're already stuck with a seller's\nmarket, because of the huge amounts they raised at the end of the\nBubble and still haven't invested. This by itself is not the end\nof the world. In fact, it's just a more extreme version of the\nnorm\nin the VC business: too much money chasing too few deals.Unfortunately, those few deals now want less and less money, because\nit's getting so cheap to start a startup. The four causes: open\nsource, which makes software free; Moore's law, which makes hardware\ngeometrically closer to free; the Web, which makes promotion free\nif you're good; and better languages, which make development a lot\ncheaper.When we started our startup in 1995, the first three were our biggest\nexpenses. We had to pay $5000 for the Netscape Commerce Server,\nthe only software that then supported secure http connections. We\npaid $3000 for a server with a 90 MHz processor and 32 meg of\nmemory. And we paid a PR firm about $30,000 to promote our launch.Now you could get all three for nothing. You can get the software\nfor free; people throw away computers more powerful than our first\nserver; and if you make something good you can generate ten times\nas much traffic by word of mouth online than our first PR firm got\nthrough the print media.And of course another big change for the average startup is that\nprogramming languages have improved-- or rather, the median language has. At most startups ten years\nago, software development meant ten programmers writing code in\nC++. Now the same work might be done by one or two using Python\nor Ruby.During the Bubble, a lot of people predicted that startups would\noutsource their development to India. I think a better model for\nthe future is David Heinemeier Hansson, who outsourced his development\nto a more powerful language instead. A lot of well-known applications\nare now, like BaseCamp, written by just one programmer. And one\nguy is more than 10x cheaper than ten, because (a) he won't waste\nany time in meetings, and (b) since he's probably a founder, he can\npay himself nothing.Because starting a startup is so cheap, venture capitalists now\noften want to give startups more money than the startups want to\ntake. VCs like to invest several million at a time. But as one\nVC told me after a startup he funded would only take about half a\nmillion, \"I don't know what we're going to do. Maybe we'll just\nhave to give some of it back.\" Meaning give some of the fund back\nto the institutional investors who supplied it, because it wasn't\ngoing to be possible to invest it all.Into this already bad situation comes the third problem: Sarbanes-Oxley.\nSarbanes-Oxley is a law, passed after the Bubble, that drastically\nincreases the regulatory burden on public companies. And in addition\nto the cost of compliance, which is at least two million dollars a\nyear, the law introduces frightening legal exposure for corporate\nofficers. An experienced CFO I know said flatly: \"I would not\nwant to be CFO of a public company now.\"You might think that responsible corporate governance is an area\nwhere you can't go too far. But you can go too far in any law, and\nthis remark convinced me that Sarbanes-Oxley must have. This CFO\nis both the smartest and the most upstanding money guy I know. If\nSarbanes-Oxley deters people like him from being CFOs of public \ncompanies, that's proof enough that it's broken.Largely because of Sarbanes-Oxley, few startups go public now. For\nall practical purposes, succeeding now equals getting bought. Which\nmeans VCs are now in the business of finding promising little 2-3\nman startups and pumping them up into companies that cost $100\nmillion to acquire. They didn't mean to be in this business; it's\njust what their business has evolved into.Hence the fourth problem: the acquirers have begun to realize they\ncan buy wholesale. Why should they wait for VCs to make the startups\nthey want more expensive? Most of what the VCs add, acquirers don't\nwant anyway. The acquirers already have brand recognition and HR\ndepartments. What they really want is the software and the developers,\nand that's what the startup is in the early phase: concentrated\nsoftware and developers.Google, typically, seems to have been the first to figure this out.\n\"Bring us your startups early,\" said Google's speaker at the Startup School. They're quite\nexplicit about it: they like to acquire startups at just the point\nwhere they would do a Series A round. (The Series A round is the\nfirst round of real VC funding; it usually happens in the first\nyear.) It is a brilliant strategy, and one that other big technology\ncompanies will no doubt try to duplicate. Unless they want to have \nstill more of their lunch eaten by Google.Of course, Google has an advantage in buying startups: a lot of the\npeople there are rich, or expect to be when their options vest.\nOrdinary employees find it very hard to recommend an acquisition;\nit's just too annoying to see a bunch of twenty year olds get rich\nwhen you're still working for salary. Even if it's the right thing \nfor your company to do.The Solution(s)Bad as things look now, there is a way for VCs to save themselves.\nThey need to do two things, one of which won't surprise them, and \nanother that will seem an anathema.Let's start with the obvious one: lobby to get Sarbanes-Oxley \nloosened. This law was created to prevent future Enrons, not to\ndestroy the IPO market. Since the IPO market was practically dead\nwhen it passed, few saw what bad effects it would have. But now \nthat technology has recovered from the last bust, we can see clearly\nwhat a bottleneck Sarbanes-Oxley has become.Startups are fragile plants—seedlings, in fact. These seedlings\nare worth protecting, because they grow into the trees of the\neconomy. Much of the economy's growth is their growth. I think\nmost politicians realize that. But they don't realize just how \nfragile startups are, and how easily they can become collateral\ndamage of laws meant to fix some other problem.Still more dangerously, when you destroy startups, they make very\nlittle noise. If you step on the toes of the coal industry, you'll\nhear about it. But if you inadvertantly squash the startup industry,\nall that happens is that the founders of the next Google stay in \ngrad school instead of starting a company.My second suggestion will seem shocking to VCs: let founders cash \nout partially in the Series A round. At the moment, when VCs invest\nin a startup, all the stock they get is newly issued and all the \nmoney goes to the company. They could buy some stock directly from\nthe founders as well.Most VCs have an almost religious rule against doing this. They\ndon't want founders to get a penny till the company is sold or goes\npublic. VCs are obsessed with control, and they worry that they'll\nhave less leverage over the founders if the founders have any money.This is a dumb plan. In fact, letting the founders sell a little stock\nearly would generally be better for the company, because it would\ncause the founders' attitudes toward risk to be aligned with the\nVCs'. As things currently work, their attitudes toward risk tend\nto be diametrically opposed: the founders, who have nothing, would\nprefer a 100% chance of $1 million to a 20% chance of $10 million,\nwhile the VCs can afford to be \"rational\" and prefer the latter.Whatever they say, the reason founders are selling their companies\nearly instead of doing Series A rounds is that they get paid up\nfront. That first million is just worth so much more than the\nsubsequent ones. If founders could sell a little stock early,\nthey'd be happy to take VC money and bet the rest on a bigger\noutcome.So why not let the founders have that first million, or at least\nhalf million? The VCs would get same number of shares for the \nmoney. So what if some of the money would go to the \nfounders instead of the company?Some VCs will say this is\nunthinkable—that they want all their money to be put to work\ngrowing the company. But the fact is, the huge size of current VC\ninvestments is dictated by the structure\nof VC funds, not the needs of startups. Often as not these large \ninvestments go to work destroying the company rather than growing\nit.The angel investors who funded our startup let the founders sell\nsome stock directly to them, and it was a good deal for everyone. \nThe angels made a huge return on that investment, so they're happy.\nAnd for us founders it blunted the terrifying all-or-nothingness\nof a startup, which in its raw form is more a distraction than a\nmotivator.If VCs are frightened at the idea of letting founders partially\ncash out, let me tell them something still more frightening: you\nare now competing directly with Google.\nThanks to Trevor Blackwell, Sarah Harlin, Jessica\nLivingston, and Robert Morris for reading drafts of this." }, { "path": "data/PaulGrahamEssaysLarge/vw.txt", "content": "January 2012A few hours before the Yahoo acquisition was announced in June 1998\nI took a snapshot of Viaweb's\nsite. I thought it might be interesting to look at one day.The first thing one notices is is how tiny the pages are. Screens\nwere a lot smaller in 1998. If I remember correctly, our frontpage\nused to just fit in the size window people typically used then.Browsers then (IE 6 was still 3 years in the future) had few fonts\nand they weren't antialiased. If you wanted to make pages that\nlooked good, you had to render display text as images.You may notice a certain similarity between the Viaweb and Y Combinator logos. We did that\nas an inside joke when we started YC. Considering how basic a red\ncircle is, it seemed surprising to me when we started Viaweb how\nfew other companies used one as their logo. A bit later I realized\nwhy.On the Company\npage you'll notice a mysterious individual called John McArtyem.\nRobert Morris (aka Rtm) was so publicity averse after the \nWorm that he\ndidn't want his name on the site. I managed to get him to agree\nto a compromise: we could use his bio but not his name. He has\nsince relaxed a bit\non that point.Trevor graduated at about the same time the acquisition closed, so in the\ncourse of 4 days he went from impecunious grad student to millionaire\nPhD. The culmination of my career as a writer of press releases\nwas one celebrating\nhis graduation, illustrated with a drawing I did of him during\na meeting.(Trevor also appears as Trevino\nBagwell in our directory of web designers merchants could hire\nto build stores for them. We inserted him as a ringer in case some\ncompetitor tried to spam our web designers. We assumed his logo\nwould deter any actual customers, but it did not.)Back in the 90s, to get users you had to get mentioned in magazines\nand newspapers. There were not the same ways to get found online\nthat there are today. So we used to pay a PR\nfirm $16,000 a month to get us mentioned in the press. Fortunately\nreporters liked\nus.In our advice about\ngetting traffic from search engines (I don't think the term SEO\nhad been coined yet), we say there are only 7 that matter: Yahoo,\nAltaVista, Excite, WebCrawler, InfoSeek, Lycos, and HotBot. Notice\nanything missing? Google was incorporated that September.We supported online transactions via a company called \nCybercash,\nsince if we lacked that feature we'd have gotten beaten up in product\ncomparisons. But Cybercash was so bad and most stores' order volumes\nwere so low that it was better if merchants processed orders like phone orders. We had a page in our site trying to talk merchants\nout of doing real time authorizations.The whole site was organized like a funnel, directing people to the\ntest drive.\nIt was a novel thing to be able to try out software online. We put\ncgi-bin in our dynamic urls to fool competitors about how our\nsoftware worked.We had some well\nknown users. Needless to say, Frederick's of Hollywood got the\nmost traffic. We charged a flat fee of $300/month for big stores,\nso it was a little alarming to have users who got lots of traffic.\nI once calculated how much Frederick's was costing us in bandwidth,\nand it was about $300/month.Since we hosted all the stores, which together were getting just\nover 10 million page views per month in June 1998, we consumed what\nat the time seemed a lot of bandwidth. We had 2 T1s (3 Mb/sec)\ncoming into our offices. In those days there was no AWS. Even\ncolocating servers seemed too risky, considering how often things\nwent wrong with them. So we had our servers in our offices. Or\nmore precisely, in Trevor's office. In return for the unique\nprivilege of sharing his office with no other humans, he had to\nshare it with 6 shrieking tower servers. His office was nicknamed\nthe Hot Tub on account of the heat they generated. Most days his\nstack of window air conditioners could keep up.For describing pages, we had a template language called RTML, which\nsupposedly stood for something, but which in fact I named after\nRtm. RTML was Common Lisp augmented by some macros and libraries,\nand concealed under a structure editor that made it look like it\nhad syntax.Since we did continuous releases, our software didn't actually have\nversions. But in those days the trade press expected versions, so\nwe made them up. If we wanted to get lots of attention, we made\nthe version number an\ninteger. That \"version 4.0\" icon was generated by our own\nbutton generator, incidentally. The whole Viaweb site was made\nwith our software, even though it wasn't an online store, because\nwe wanted to experience what our users did.At the end of 1997, we released a general purpose shopping search\nengine called Shopfind. It\nwas pretty advanced for the time. It had a programmable crawler\nthat could crawl most of the different stores online and pick out\nthe products." }, { "path": "data/PaulGrahamEssaysLarge/want.txt", "content": "November 2022Since I was about 9 I've been puzzled by the apparent contradiction\nbetween being made of matter that behaves in a predictable way, and\nthe feeling that I could choose to do whatever I wanted. At the\ntime I had a self-interested motive for exploring the question. At\nthat age (like most succeeding ages) I was always in trouble with\nthe authorities, and it seemed to me that there might possibly be\nsome way to get out of trouble by arguing that I wasn't responsible\nfor my actions. I gradually lost hope of that, but the puzzle\nremained: How do you reconcile being a machine made of matter with\nthe feeling that you're free to choose what you do?\n[1]The best way to explain the answer may be to start with a slightly\nwrong version, and then fix it. The wrong version is: You can do\nwhat you want, but you can't want what you want. Yes, you can control\nwhat you do, but you'll do what you want, and you can't control\nthat.The reason this is mistaken is that people do sometimes change what\nthey want. People who don't want to want something — drug addicts,\nfor example — can sometimes make themselves stop wanting it. And\npeople who want to want something — who want to like classical\nmusic, or broccoli — sometimes succeed.So we modify our initial statement: You can do what you want, but\nyou can't want to want what you want.That's still not quite true. It's possible to change what you want\nto want. I can imagine someone saying \"I decided to stop wanting\nto like classical music.\" But we're getting closer to the truth.\nIt's rare for people to change what they want to want, and the more\n\"want to\"s we add, the rarer it gets.We can get arbitrarily close to a true statement by adding more \"want\nto\"s in much the same way we can get arbitrarily close to 1 by adding\nmore 9s to a string of 9s following a decimal point. In practice\nthree or four \"want to\"s must surely be enough. It's hard even to\nenvision what it would mean to change what you want to want to want\nto want, let alone actually do it.So one way to express the correct answer is to use a regular\nexpression. You can do what you want, but there's some statement\nof the form \"you can't (want to)* want what you want\" that's true.\nUltimately you get back to a want that you don't control.\n[2]\nNotes[1]\nI didn't know when I was 9 that matter might behave randomly,\nbut I don't think it affects the problem much. Randomness destroys\nthe ghost in the machine as effectively as determinism.[2]\nIf you don't like using an expression, you can make the same\npoint using higher-order desires: There is some n such that you\ndon't control your nth-order desires.\nThanks to Trevor Blackwell,\nJessica Livingston, Robert Morris, and\nMichael Nielsen for reading drafts of this." }, { "path": "data/PaulGrahamEssaysLarge/web20.txt", "content": "\n\nWant to start a startup? Get funded by\nY Combinator.\n\n\n\n\nNovember 2005Does \"Web 2.0\" mean anything? Till recently I thought it didn't,\nbut the truth turns out to be more complicated. Originally, yes,\nit was meaningless. Now it seems to have acquired a meaning. And\nyet those who dislike the term are probably right, because if it\nmeans what I think it does, we don't need it.I first heard the phrase \"Web 2.0\" in the name of the Web 2.0\nconference in 2004. At the time it was supposed to mean using \"the\nweb as a platform,\" which I took to refer to web-based applications.\n[1]So I was surprised at a conference this summer when Tim O'Reilly\nled a session intended to figure out a definition of \"Web 2.0.\"\nDidn't it already mean using the web as a platform? And if it\ndidn't already mean something, why did we need the phrase at all?OriginsTim says the phrase \"Web 2.0\" first\narose in \"a brainstorming session between\nO'Reilly and Medialive International.\" What is Medialive International?\n\"Producers of technology tradeshows and conferences,\" according to\ntheir site. So presumably that's what this brainstorming session\nwas about. O'Reilly wanted to organize a conference about the web,\nand they were wondering what to call it.I don't think there was any deliberate plan to suggest there was a\nnew version of the web. They just wanted to make the point\nthat the web mattered again. It was a kind of semantic deficit\nspending: they knew new things were coming, and the \"2.0\" referred\nto whatever those might turn out to be.And they were right. New things were coming. But the new version\nnumber led to some awkwardness in the short term. In the process\nof developing the pitch for the first conference, someone must have\ndecided they'd better take a stab at explaining what that \"2.0\"\nreferred to. Whatever it meant, \"the web as a platform\" was at\nleast not too constricting.The story about \"Web 2.0\" meaning the web as a platform didn't live\nmuch past the first conference. By the second conference, what\n\"Web 2.0\" seemed to mean was something about democracy. At least,\nit did when people wrote about it online. The conference itself\ndidn't seem very grassroots. It cost $2800, so the only people who\ncould afford to go were VCs and people from big companies.And yet, oddly enough, Ryan Singel's article\nabout the conference in Wired News spoke of \"throngs of\ngeeks.\" When a friend of mine asked Ryan about this, it was news\nto him. He said he'd originally written something like \"throngs\nof VCs and biz dev guys\" but had later shortened it just to \"throngs,\"\nand that this must have in turn been expanded by the editors into\n\"throngs of geeks.\" After all, a Web 2.0 conference would presumably\nbe full of geeks, right?Well, no. There were about 7. Even Tim O'Reilly was wearing a \nsuit, a sight so alien I couldn't parse it at first. I saw\nhim walk by and said to one of the O'Reilly people \"that guy looks\njust like Tim.\"\"Oh, that's Tim. He bought a suit.\"\nI ran after him, and sure enough, it was. He explained that he'd\njust bought it in Thailand.The 2005 Web 2.0 conference reminded me of Internet trade shows\nduring the Bubble, full of prowling VCs looking for the next hot\nstartup. There was that same odd atmosphere created by a large \nnumber of people determined not to miss out. Miss out on what?\nThey didn't know. Whatever was going to happen—whatever Web 2.0\nturned out to be.I wouldn't quite call it \"Bubble 2.0\" just because VCs are eager\nto invest again. The Internet is a genuinely big deal. The bust\nwas as much an overreaction as\nthe boom. It's to be expected that once we started to pull out of\nthe bust, there would be a lot of growth in this area, just as there\nwas in the industries that spiked the sharpest before the Depression.The reason this won't turn into a second Bubble is that the IPO\nmarket is gone. Venture investors\nare driven by exit strategies. The reason they were funding all \nthose laughable startups during the late 90s was that they hoped\nto sell them to gullible retail investors; they hoped to be laughing\nall the way to the bank. Now that route is closed. Now the default\nexit strategy is to get bought, and acquirers are less prone to\nirrational exuberance than IPO investors. The closest you'll get \nto Bubble valuations is Rupert Murdoch paying $580 million for \nMyspace. That's only off by a factor of 10 or so.1. AjaxDoes \"Web 2.0\" mean anything more than the name of a conference\nyet? I don't like to admit it, but it's starting to. When people\nsay \"Web 2.0\" now, I have some idea what they mean. And the fact\nthat I both despise the phrase and understand it is the surest proof\nthat it has started to mean something.One ingredient of its meaning is certainly Ajax, which I can still\nonly just bear to use without scare quotes. Basically, what \"Ajax\"\nmeans is \"Javascript now works.\" And that in turn means that\nweb-based applications can now be made to work much more like desktop\nones.As you read this, a whole new generation\nof software is being written to take advantage of Ajax. There\nhasn't been such a wave of new applications since microcomputers\nfirst appeared. Even Microsoft sees it, but it's too late for them\nto do anything more than leak \"internal\" \ndocuments designed to give the impression they're on top of this\nnew trend.In fact the new generation of software is being written way too\nfast for Microsoft even to channel it, let alone write their own\nin house. Their only hope now is to buy all the best Ajax startups\nbefore Google does. And even that's going to be hard, because\nGoogle has as big a head start in buying microstartups as it did\nin search a few years ago. After all, Google Maps, the canonical\nAjax application, was the result of a startup they bought.So ironically the original description of the Web 2.0 conference\nturned out to be partially right: web-based applications are a big\ncomponent of Web 2.0. But I'm convinced they got this right by \naccident. The Ajax boom didn't start till early 2005, when Google\nMaps appeared and the term \"Ajax\" was coined.2. DemocracyThe second big element of Web 2.0 is democracy. We now have several\nexamples to prove that amateurs can \nsurpass professionals, when they have the right kind of system to \nchannel their efforts. Wikipedia\nmay be the most famous. Experts have given Wikipedia middling\nreviews, but they miss the critical point: it's good enough. And \nit's free, which means people actually read it. On the web, articles\nyou have to pay for might as well not exist. Even if you were \nwilling to pay to read them yourself, you can't link to them. \nThey're not part of the conversation.Another place democracy seems to win is in deciding what counts as\nnews. I never look at any news site now except Reddit.\n[2]\n I know if something major\nhappens, or someone writes a particularly interesting article, it \nwill show up there. Why bother checking the front page of any\nspecific paper or magazine? Reddit's like an RSS feed for the whole\nweb, with a filter for quality. Similar sites include Digg, a technology news site that's\nrapidly approaching Slashdot in popularity, and del.icio.us, the collaborative\nbookmarking network that set off the \"tagging\" movement. And whereas\nWikipedia's main appeal is that it's good enough and free, these\nsites suggest that voters do a significantly better job than human\neditors.The most dramatic example of Web 2.0 democracy is not in the selection\nof ideas, but their production. \nI've noticed for a while that the stuff I read on individual people's\nsites is as good as or better than the stuff I read in newspapers\nand magazines. And now I have independent evidence: the top links\non Reddit are generally links to individual people's sites rather \nthan to magazine articles or news stories.My experience of writing\nfor magazines suggests an explanation. Editors. They control the\ntopics you can write about, and they can generally rewrite whatever\nyou produce. The result is to damp extremes. Editing yields 95th\npercentile writing—95% of articles are improved by it, but 5% are\ndragged down. 5% of the time you get \"throngs of geeks.\"On the web, people can publish whatever they want. Nearly all of\nit falls short of the editor-damped writing in print publications.\nBut the pool of writers is very, very large. If it's large enough,\nthe lack of damping means the best writing online should surpass \nthe best in print.\n[3] \nAnd now that the web has evolved mechanisms\nfor selecting good stuff, the web wins net. Selection beats damping,\nfor the same reason market economies beat centrally planned ones.Even the startups are different this time around. They are to the \nstartups of the Bubble what bloggers are to the print media. During\nthe Bubble, a startup meant a company headed by an MBA that was \nblowing through several million dollars of VC money to \"get big\nfast\" in the most literal sense. Now it means a smaller, younger, more technical group that just \ndecided to make something great. They'll decide later if they want \nto raise VC-scale funding, and if they take it, they'll take it on\ntheir terms.3. Don't Maltreat UsersI think everyone would agree that democracy and Ajax are elements\nof \"Web 2.0.\" I also see a third: not to maltreat users. During\nthe Bubble a lot of popular sites were quite high-handed with users.\nAnd not just in obvious ways, like making them register, or subjecting\nthem to annoying ads. The very design of the average site in the \nlate 90s was an abuse. Many of the most popular sites were loaded\nwith obtrusive branding that made them slow to load and sent the\nuser the message: this is our site, not yours. (There's a physical\nanalog in the Intel and Microsoft stickers that come on some\nlaptops.)I think the root of the problem was that sites felt they were giving\nsomething away for free, and till recently a company giving anything\naway for free could be pretty high-handed about it. Sometimes it\nreached the point of economic sadism: site owners assumed that the\nmore pain they caused the user, the more benefit it must be to them. \nThe most dramatic remnant of this model may be at salon.com, where \nyou can read the beginning of a story, but to get the rest you have\nsit through a movie.At Y Combinator we advise all the startups we fund never to lord\nit over users. Never make users register, unless you need to in\norder to store something for them. If you do make users register, \nnever make them wait for a confirmation link in an email; in fact,\ndon't even ask for their email address unless you need it for some\nreason. Don't ask them any unnecessary questions. Never send them\nemail unless they explicitly ask for it. Never frame pages you\nlink to, or open them in new windows. If you have a free version \nand a pay version, don't make the free version too restricted. And\nif you find yourself asking \"should we allow users to do x?\" just \nanswer \"yes\" whenever you're unsure. Err on the side of generosity.In How to Start a Startup I advised startups\nnever to let anyone fly under them, meaning never to let any other\ncompany offer a cheaper, easier solution. Another way to fly low \nis to give users more power. Let users do what they want. If you \ndon't and a competitor does, you're in trouble.iTunes is Web 2.0ish in this sense. Finally you can buy individual\nsongs instead of having to buy whole albums. The recording industry\nhated the idea and resisted it as long as possible. But it was\nobvious what users wanted, so Apple flew under the labels.\n[4]\nThough really it might be better to describe iTunes as Web 1.5. \nWeb 2.0 applied to music would probably mean individual bands giving\naway DRMless songs for free.The ultimate way to be nice to users is to give them something for\nfree that competitors charge for. During the 90s a lot of people \nprobably thought we'd have some working system for micropayments \nby now. In fact things have gone in the other direction. The most \nsuccessful sites are the ones that figure out new ways to give stuff\naway for free. Craigslist has largely destroyed the classified ad\nsites of the 90s, and OkCupid looks likely to do the same to the\nprevious generation of dating sites.Serving web pages is very, very cheap. If you can make even a \nfraction of a cent per page view, you can make a profit. And\ntechnology for targeting ads continues to improve. I wouldn't be\nsurprised if ten years from now eBay had been supplanted by an \nad-supported freeBay (or, more likely, gBay).Odd as it might sound, we tell startups that they should try to\nmake as little money as possible. If you can figure out a way to\nturn a billion dollar industry into a fifty million dollar industry,\nso much the better, if all fifty million go to you. Though indeed,\nmaking things cheaper often turns out to generate more money in the\nend, just as automating things often turns out to generate more\njobs.The ultimate target is Microsoft. What a bang that balloon is going\nto make when someone pops it by offering a free web-based alternative \nto MS Office.\n[5]\nWho will? Google? They seem to be taking their\ntime. I suspect the pin will be wielded by a couple of 20 year old\nhackers who are too naive to be intimidated by the idea. (How hard\ncan it be?)The Common ThreadAjax, democracy, and not dissing users. What do they all have in \ncommon? I didn't realize they had anything in common till recently,\nwhich is one of the reasons I disliked the term \"Web 2.0\" so much.\nIt seemed that it was being used as a label for whatever happened\nto be new—that it didn't predict anything.But there is a common thread. Web 2.0 means using the web the way\nit's meant to be used. The \"trends\" we're seeing now are simply\nthe inherent nature of the web emerging from under the broken models\nthat got imposed on it during the Bubble.I realized this when I read an interview with\nJoe Kraus, the co-founder of Excite.\n[6]\n\n Excite really never got the business model right at all. We fell \n into the classic problem of how when a new medium comes out it\n adopts the practices, the content, the business models of the old\n medium—which fails, and then the more appropriate models get\n figured out.\n\nIt may have seemed as if not much was happening during the years\nafter the Bubble burst. But in retrospect, something was happening:\nthe web was finding its natural angle of repose. The democracy \ncomponent, for example—that's not an innovation, in the sense of\nsomething someone made happen. That's what the web naturally tends\nto produce.Ditto for the idea of delivering desktop-like applications over the\nweb. That idea is almost as old as the web. But the first time \naround it was co-opted by Sun, and we got Java applets. Java has\nsince been remade into a generic replacement for C++, but in 1996\nthe story about Java was that it represented a new model of software.\nInstead of desktop applications, you'd run Java \"applets\" delivered\nfrom a server.This plan collapsed under its own weight. Microsoft helped kill it,\nbut it would have died anyway. There was no uptake among hackers.\nWhen you find PR firms promoting\nsomething as the next development platform, you can be sure it's\nnot. If it were, you wouldn't need PR firms to tell you, because \nhackers would already be writing stuff on top of it, the way sites \nlike Busmonster used Google Maps as a\nplatform before Google even meant it to be one.The proof that Ajax is the next hot platform is that thousands of \nhackers have spontaneously started building things on top\nof it. Mikey likes it.There's another thing all three components of Web 2.0 have in common.\nHere's a clue. Suppose you approached investors with the following\nidea for a Web 2.0 startup:\n\n Sites like del.icio.us and flickr allow users to \"tag\" content\n with descriptive tokens. But there is also huge source of\n implicit tags that they ignore: the text within web links.\n Moreover, these links represent a social network connecting the \n individuals and organizations who created the pages, and by using\n graph theory we can compute from this network an estimate of the\n reputation of each member. We plan to mine the web for these \n implicit tags, and use them together with the reputation hierarchy\n they embody to enhance web searches.\n\nHow long do you think it would take them on average to realize that\nit was a description of Google?Google was a pioneer in all three components of Web 2.0: their core\nbusiness sounds crushingly hip when described in Web 2.0 terms, \n\"Don't maltreat users\" is a subset of \"Don't be evil,\" and of course\nGoogle set off the whole Ajax boom with Google Maps.Web 2.0 means using the web as it was meant to be used, and Google\ndoes. That's their secret. They're sailing with the wind, instead of sitting \nbecalmed praying for a business model, like the print media, or \ntrying to tack upwind by suing their customers, like Microsoft and \nthe record labels.\n[7]Google doesn't try to force things to happen their way. They try \nto figure out what's going to happen, and arrange to be standing \nthere when it does. That's the way to approach technology—and \nas business includes an ever larger technological component, the\nright way to do business.The fact that Google is a \"Web 2.0\" company shows that, while\nmeaningful, the term is also rather bogus. It's like the word\n\"allopathic.\" It just means doing things right, and it's a bad \nsign when you have a special word for that.\nNotes[1]\nFrom the conference\nsite, June 2004: \"While the first wave of the Web was closely \ntied to the browser, the second wave extends applications across \nthe web and enables a new generation of services and business\nopportunities.\" To the extent this means anything, it seems to be\nabout \nweb-based applications.[2]\nDisclosure: Reddit was funded by \nY Combinator. But although\nI started using it out of loyalty to the home team, I've become a\ngenuine addict. While we're at it, I'm also an investor in\n!MSFT, having sold all my shares earlier this year.[3]\nI'm not against editing. I spend more time editing than\nwriting, and I have a group of picky friends who proofread almost\neverything I write. What I dislike is editing done after the fact \nby someone else.[4]\nObvious is an understatement. Users had been climbing in through \nthe window for years before Apple finally moved the door.[5]\nHint: the way to create a web-based alternative to Office may\nnot be to write every component yourself, but to establish a protocol\nfor web-based apps to share a virtual home directory spread across\nmultiple servers. Or it may be to write it all yourself.[6]\nIn Jessica Livingston's\nFounders at\nWork.[7]\nMicrosoft didn't sue their customers directly, but they seem \nto have done all they could to help SCO sue them.Thanks to Trevor Blackwell, Sarah Harlin, Jessica Livingston, Peter\nNorvig, Aaron Swartz, and Jeff Weiner for reading drafts of this, and to the\nguys at O'Reilly and Adaptive Path for answering my questions." }, { "path": "data/PaulGrahamEssaysLarge/weird.txt", "content": "August 2021When people say that in their experience all programming languages\nare basically equivalent, they're making a statement not about\nlanguages but about the kind of programming they've done.99.5% of programming consists of gluing together calls to library\nfunctions. All popular languages are equally good at this. So one\ncan easily spend one's whole career operating in the intersection\nof popular programming languages.But the other .5% of programming is disproportionately interesting.\nIf you want to learn what it consists of, the weirdness of weird\nlanguages is a good clue to follow.Weird languages aren't weird by accident. Not the good ones, at\nleast. The weirdness of the good ones usually implies the existence\nof some form of programming that's not just the usual gluing together\nof library calls.A concrete example: Lisp macros. Lisp macros seem weird even to\nmany Lisp programmers. They're not only not in the intersection of\npopular languages, but by their nature would be hard to implement\nproperly in a language without turning it into a dialect of\nLisp. And macros are definitely evidence of techniques that go\nbeyond glue programming. For example, solving problems by first\nwriting a language for problems of that type, and then writing\nyour specific application in it. Nor is this all you can do with\nmacros; it's just one region in a space of program-manipulating\ntechniques that even now is far from fully explored.So if you want to expand your concept of what programming can be,\none way to do it is by learning weird languages. Pick a language\nthat most programmers consider weird but whose median user is smart,\nand then focus on the differences between this language and the\nintersection of popular languages. What can you say in this language\nthat would be impossibly inconvenient to say in others? In the\nprocess of learning how to say things you couldn't previously say,\nyou'll probably be learning how to think things you couldn't\npreviously think.\nThanks to Trevor Blackwell, Patrick Collison, Daniel Gackle, Amjad\nMasad, and Robert Morris for reading drafts of this.\n" }, { "path": "data/PaulGrahamEssaysLarge/wisdom.txt", "content": "February 2007A few days ago I finally figured out something I've wondered about\nfor 25 years: the relationship between wisdom and intelligence.\nAnyone can see they're not the same by the number of people who are\nsmart, but not very wise. And yet intelligence and wisdom do seem\nrelated. How?What is wisdom? I'd say it's knowing what to do in a lot of\nsituations. I'm not trying to make a deep point here about the\ntrue nature of wisdom, just to figure out how we use the word. A\nwise person is someone who usually knows the right thing to do.And yet isn't being smart also knowing what to do in certain\nsituations? For example, knowing what to do when the teacher tells\nyour elementary school class to add all the numbers from 1 to 100?\n[1]Some say wisdom and intelligence apply to different types of\nproblems—wisdom to human problems and intelligence to abstract\nones. But that isn't true. Some wisdom has nothing to do with\npeople: for example, the wisdom of the engineer who knows certain\nstructures are less prone to failure than others. And certainly\nsmart people can find clever solutions to human problems as well\nas abstract ones. \n[2]Another popular explanation is that wisdom comes from experience\nwhile intelligence is innate. But people are not simply wise in\nproportion to how much experience they have. Other things must\ncontribute to wisdom besides experience, and some may be innate: a\nreflective disposition, for example.Neither of the conventional explanations of the difference between\nwisdom and intelligence stands up to scrutiny. So what is the\ndifference? If we look at how people use the words \"wise\" and\n\"smart,\" what they seem to mean is different shapes of performance.Curve\"Wise\" and \"smart\" are both ways of saying someone knows what to\ndo. The difference is that \"wise\" means one has a high average\noutcome across all situations, and \"smart\" means one does spectacularly\nwell in a few. That is, if you had a graph in which the x axis\nrepresented situations and the y axis the outcome, the graph of the\nwise person would be high overall, and the graph of the smart person\nwould have high peaks.The distinction is similar to the rule that one should judge talent\nat its best and character at its worst. Except you judge intelligence\nat its best, and wisdom by its average. That's how the two are\nrelated: they're the two different senses in which the same curve\ncan be high.So a wise person knows what to do in most situations, while a smart\nperson knows what to do in situations where few others could. We\nneed to add one more qualification: we should ignore cases where\nsomeone knows what to do because they have inside information. \n[3]\nBut aside from that, I don't think we can get much more specific\nwithout starting to be mistaken.Nor do we need to. Simple as it is, this explanation predicts, or\nat least accords with, both of the conventional stories about the\ndistinction between wisdom and intelligence. Human problems are\nthe most common type, so being good at solving those is key in\nachieving a high average outcome. And it seems natural that a\nhigh average outcome depends mostly on experience, but that dramatic\npeaks can only be achieved by people with certain rare, innate\nqualities; nearly anyone can learn to be a good swimmer, but to be\nan Olympic swimmer you need a certain body type.This explanation also suggests why wisdom is such an elusive concept:\nthere's no such thing. \"Wise\" means something—that one is\non average good at making the right choice. But giving the name\n\"wisdom\" to the supposed quality that enables one to do that doesn't\nmean such a thing exists. To the extent \"wisdom\" means anything,\nit refers to a grab-bag of qualities as various as self-discipline,\nexperience, and empathy. \n[4]Likewise, though \"intelligent\" means something, we're asking for\ntrouble if we insist on looking for a single thing called \"intelligence.\"\nAnd whatever its components, they're not all innate. We use the\nword \"intelligent\" as an indication of ability: a smart person can\ngrasp things few others could. It does seem likely there's some\ninborn predisposition to intelligence (and wisdom too), but this\npredisposition is not itself intelligence.One reason we tend to think of intelligence as inborn is that people\ntrying to measure it have concentrated on the aspects of it that\nare most measurable. A quality that's inborn will obviously be\nmore convenient to work with than one that's influenced by experience,\nand thus might vary in the course of a study. The problem comes\nwhen we drag the word \"intelligence\" over onto what they're measuring.\nIf they're measuring something inborn, they can't be measuring\nintelligence. Three year olds aren't smart. When we describe one\nas smart, it's shorthand for \"smarter than other three year olds.\"SplitPerhaps it's a technicality to point out that a predisposition to\nintelligence is not the same as intelligence. But it's an important\ntechnicality, because it reminds us that we can become smarter,\njust as we can become wiser.The alarming thing is that we may have to choose between the two.If wisdom and intelligence are the average and peaks of the same\ncurve, then they converge as the number of points on the curve\ndecreases. If there's just one point, they're identical: the average\nand maximum are the same. But as the number of points increases,\nwisdom and intelligence diverge. And historically the number of\npoints on the curve seems to have been increasing: our ability is\ntested in an ever wider range of situations.In the time of Confucius and Socrates, people seem to have regarded\nwisdom, learning, and intelligence as more closely related than we\ndo. Distinguishing between \"wise\" and \"smart\" is a modern habit.\n[5]\nAnd the reason we do is that they've been diverging. As knowledge\ngets more specialized, there are more points on the curve, and the\ndistinction between the spikes and the average becomes sharper,\nlike a digital image rendered with more pixels.One consequence is that some old recipes may have become obsolete.\nAt the very least we have to go back and figure out if they were\nreally recipes for wisdom or intelligence. But the really striking\nchange, as intelligence and wisdom drift apart, is that we may have\nto decide which we prefer. We may not be able to optimize for both\nsimultaneously.Society seems to have voted for intelligence. We no longer admire\nthe sage—not the way people did two thousand years ago. Now\nwe admire the genius. Because in fact the distinction we began\nwith has a rather brutal converse: just as you can be smart without\nbeing very wise, you can be wise without being very smart. That\ndoesn't sound especially admirable. That gets you James Bond, who\nknows what to do in a lot of situations, but has to rely on Q for\nthe ones involving math.Intelligence and wisdom are obviously not mutually exclusive. In\nfact, a high average may help support high peaks. But there are\nreasons to believe that at some point you have to choose between\nthem. One is the example of very smart people, who are so often\nunwise that in popular culture this now seems to be regarded as the\nrule rather than the exception. Perhaps the absent-minded professor\nis wise in his way, or wiser than he seems, but he's not wise in\nthe way Confucius or Socrates wanted people to be. \n[6]NewFor both Confucius and Socrates, wisdom, virtue, and happiness were\nnecessarily related. The wise man was someone who knew what the\nright choice was and always made it; to be the right choice, it had\nto be morally right; he was therefore always happy, knowing he'd\ndone the best he could. I can't think of many ancient philosophers\nwho would have disagreed with that, so far as it goes.\"The superior man is always happy; the small man sad,\" said Confucius.\n[7]Whereas a few years ago I read an interview with a mathematician\nwho said that most nights he went to bed discontented, feeling he\nhadn't made enough progress. \n[8]\nThe Chinese and Greek words we\ntranslate as \"happy\" didn't mean exactly what we do by it, but\nthere's enough overlap that this remark contradicts them.Is the mathematician a small man because he's discontented? No;\nhe's just doing a kind of work that wasn't very common in Confucius's\nday.Human knowledge seems to grow fractally. Time after time, something\nthat seemed a small and uninteresting area—experimental error,\neven—turns out, when examined up close, to have as much in\nit as all knowledge up to that point. Several of the fractal buds\nthat have exploded since ancient times involve inventing and\ndiscovering new things. Math, for example, used to be something a\nhandful of people did part-time. Now it's the career of thousands.\nAnd in work that involves making new things, some old rules don't\napply.Recently I've spent some time advising people, and there I find the\nancient rule still works: try to understand the situation as well\nas you can, give the best advice you can based on your experience,\nand then don't worry about it, knowing you did all you could. But\nI don't have anything like this serenity when I'm writing an essay.\nThen I'm worried. What if I run out of ideas? And when I'm writing,\nfour nights out of five I go to bed discontented, feeling I didn't\nget enough done.Advising people and writing are fundamentally different types of\nwork. When people come to you with a problem and you have to figure\nout the right thing to do, you don't (usually) have to invent\nanything. You just weigh the alternatives and try to judge which\nis the prudent choice. But prudence can't tell me what sentence\nto write next. The search space is too big.Someone like a judge or a military officer can in much of his work\nbe guided by duty, but duty is no guide in making things. Makers\ndepend on something more precarious: inspiration. And like most\npeople who lead a precarious existence, they tend to be worried,\nnot contented. In that respect they're more like the small man of\nConfucius's day, always one bad harvest (or ruler) away from\nstarvation. Except instead of being at the mercy of weather and\nofficials, they're at the mercy of their own imagination.LimitsTo me it was a relief just to realize it might be ok to be discontented.\nThe idea that a successful person should be happy has thousands of\nyears of momentum behind it. If I was any good, why didn't I have\nthe easy confidence winners are supposed to have? But that, I now\nbelieve, is like a runner asking \"If I'm such a good athlete, why\ndo I feel so tired?\" Good runners still get tired; they just get\ntired at higher speeds.People whose work is to invent or discover things are in the same\nposition as the runner. There's no way for them to do the best\nthey can, because there's no limit to what they could do. The\nclosest you can come is to compare yourself to other people. But\nthe better you do, the less this matters. An undergrad who gets\nsomething published feels like a star. But for someone at the top\nof the field, what's the test of doing well? Runners can at least\ncompare themselves to others doing exactly the same thing; if you\nwin an Olympic gold medal, you can be fairly content, even if you\nthink you could have run a bit faster. But what is a novelist to\ndo?Whereas if you're doing the kind of work in which problems are\npresented to you and you have to choose between several alternatives,\nthere's an upper bound on your performance: choosing the best every\ntime. In ancient societies, nearly all work seems to have been of\nthis type. The peasant had to decide whether a garment was worth\nmending, and the king whether or not to invade his neighbor, but\nneither was expected to invent anything. In principle they could\nhave; the king could have invented firearms, then invaded his\nneighbor. But in practice innovations were so rare that they weren't\nexpected of you, any more than goalkeepers are expected to score\ngoals. \n[9]\nIn practice, it seemed as if there was a correct decision\nin every situation, and if you made it you'd done your job perfectly,\njust as a goalkeeper who prevents the other team from scoring is\nconsidered to have played a perfect game.In this world, wisdom seemed paramount. \n[10]\nEven now, most people\ndo work in which problems are put before them and they have to\nchoose the best alternative. But as knowledge has grown more\nspecialized, there are more and more types of work in which people\nhave to make up new things, and in which performance is therefore\nunbounded. Intelligence has become increasingly important relative\nto wisdom because there is more room for spikes.RecipesAnother sign we may have to choose between intelligence and wisdom\nis how different their recipes are. Wisdom seems to come largely\nfrom curing childish qualities, and intelligence largely from\ncultivating them.Recipes for wisdom, particularly ancient ones, tend to have a\nremedial character. To achieve wisdom one must cut away all the\ndebris that fills one's head on emergence from childhood, leaving\nonly the important stuff. Both self-control and experience have\nthis effect: to eliminate the random biases that come from your own\nnature and from the circumstances of your upbringing respectively.\nThat's not all wisdom is, but it's a large part of it. Much of\nwhat's in the sage's head is also in the head of every twelve year\nold. The difference is that in the head of the twelve year old\nit's mixed together with a lot of random junk.The path to intelligence seems to be through working on hard problems.\nYou develop intelligence as you might develop muscles, through\nexercise. But there can't be too much compulsion here. No amount\nof discipline can replace genuine curiosity. So cultivating\nintelligence seems to be a matter of identifying some bias in one's\ncharacter—some tendency to be interested in certain types of\nthings—and nurturing it. Instead of obliterating your\nidiosyncrasies in an effort to make yourself a neutral vessel for\nthe truth, you select one and try to grow it from a seedling into\na tree.The wise are all much alike in their wisdom, but very smart people\ntend to be smart in distinctive ways.Most of our educational traditions aim at wisdom. So perhaps one\nreason schools work badly is that they're trying to make intelligence\nusing recipes for wisdom. Most recipes for wisdom have an element\nof subjection. At the very least, you're supposed to do what the\nteacher says. The more extreme recipes aim to break down your\nindividuality the way basic training does. But that's not the route\nto intelligence. Whereas wisdom comes through humility, it may\nactually help, in cultivating intelligence, to have a mistakenly\nhigh opinion of your abilities, because that encourages you to keep\nworking. Ideally till you realize how mistaken you were.(The reason it's hard to learn new skills late in life is not just\nthat one's brain is less malleable. Another probably even worse\nobstacle is that one has higher standards.)I realize we're on dangerous ground here. I'm not proposing the\nprimary goal of education should be to increase students' \"self-esteem.\"\nThat just breeds laziness. And in any case, it doesn't really fool\nthe kids, not the smart ones. They can tell at a young age that a\ncontest where everyone wins is a fraud.A teacher has to walk a narrow path: you want to encourage kids to\ncome up with things on their own, but you can't simply applaud\neverything they produce. You have to be a good audience: appreciative,\nbut not too easily impressed. And that's a lot of work. You have\nto have a good enough grasp of kids' capacities at different ages\nto know when to be surprised.That's the opposite of traditional recipes for education. Traditionally\nthe student is the audience, not the teacher; the student's job is\nnot to invent, but to absorb some prescribed body of material. (The\nuse of the term \"recitation\" for sections in some colleges is a\nfossil of this.) The problem with these old traditions is that\nthey're too much influenced by recipes for wisdom.DifferentI deliberately gave this essay a provocative title; of course it's\nworth being wise. But I think it's important to understand the\nrelationship between intelligence and wisdom, and particularly what\nseems to be the growing gap between them. That way we can avoid\napplying rules and standards to intelligence that are really meant\nfor wisdom. These two senses of \"knowing what to do\" are more\ndifferent than most people realize. The path to wisdom is through\ndiscipline, and the path to intelligence through carefully selected\nself-indulgence. Wisdom is universal, and intelligence idiosyncratic.\nAnd while wisdom yields calmness, intelligence much of the time\nleads to discontentment.That's particularly worth remembering. A physicist friend recently\ntold me half his department was on Prozac. Perhaps if we acknowledge\nthat some amount of frustration is inevitable in certain kinds\nof work, we can mitigate its effects. Perhaps we can box it up and\nput it away some of the time, instead of letting it flow together\nwith everyday sadness to produce what seems an alarmingly large\npool. At the very least, we can avoid being discontented about\nbeing discontented.If you feel exhausted, it's not necessarily because there's something\nwrong with you. Maybe you're just running fast.Notes[1]\nGauss was supposedly asked this when he was 10. Instead of\nlaboriously adding together the numbers like the other students,\nhe saw that they consisted of 50 pairs that each summed to 101 (100\n+ 1, 99 + 2, etc), and that he could just multiply 101 by 50 to get\nthe answer, 5050.[2]\nA variant is that intelligence is the ability to solve problems,\nand wisdom the judgement to know how to use those solutions. But\nwhile this is certainly an important relationship between wisdom\nand intelligence, it's not the distinction between them. Wisdom\nis useful in solving problems too, and intelligence can help in\ndeciding what to do with the solutions.[3]\nIn judging both intelligence and wisdom we have to factor out\nsome knowledge. People who know the combination of a safe will be\nbetter at opening it than people who don't, but no one would say\nthat was a test of intelligence or wisdom.But knowledge overlaps with wisdom and probably also intelligence.\nA knowledge of human nature is certainly part of wisdom. So where\ndo we draw the line?Perhaps the solution is to discount knowledge that at some point\nhas a sharp drop in utility. For example, understanding French\nwill help you in a large number of situations, but its value drops\nsharply as soon as no one else involved knows French. Whereas the\nvalue of understanding vanity would decline more gradually.The knowledge whose utility drops sharply is the kind that has\nlittle relation to other knowledge. This includes mere conventions,\nlike languages and safe combinations, and also what we'd call\n\"random\" facts, like movie stars' birthdays, or how to distinguish\n1956 from 1957 Studebakers.[4]\nPeople seeking some single thing called \"wisdom\" have been\nfooled by grammar. Wisdom is just knowing the right thing to do,\nand there are a hundred and one different qualities that help in\nthat. Some, like selflessness, might come from meditating in an\nempty room, and others, like a knowledge of human nature, might\ncome from going to drunken parties.Perhaps realizing this will help dispel the cloud of semi-sacred\nmystery that surrounds wisdom in so many people's eyes. The mystery\ncomes mostly from looking for something that doesn't exist. And\nthe reason there have historically been so many different schools\nof thought about how to achieve wisdom is that they've focused on\ndifferent components of it.When I use the word \"wisdom\" in this essay, I mean no more than\nwhatever collection of qualities helps people make the right choice\nin a wide variety of situations.[5]\nEven in English, our sense of the word \"intelligence\" is\nsurprisingly recent. Predecessors like \"understanding\" seem to\nhave had a broader meaning.[6]\nThere is of course some uncertainty about how closely the remarks\nattributed to Confucius and Socrates resemble their actual opinions.\nI'm using these names as we use the name \"Homer,\" to mean the\nhypothetical people who said the things attributed to them.[7]\nAnalects VII:36, Fung trans.Some translators use \"calm\" instead of \"happy.\" One source of\ndifficulty here is that present-day English speakers have a different\nidea of happiness from many older societies. Every language probably\nhas a word meaning \"how one feels when things are going well,\" but\ndifferent cultures react differently when things go well. We react\nlike children, with smiles and laughter. But in a more reserved\nsociety, or in one where life was tougher, the reaction might be a\nquiet contentment.[8]\nIt may have been Andrew Wiles, but I'm not sure. If anyone\nremembers such an interview, I'd appreciate hearing from you.[9]\nConfucius claimed proudly that he had never invented\nanything—that he had simply passed on an accurate account of\nancient traditions. [Analects VII:1] It's hard for us now to\nappreciate how important a duty it must have been in preliterate\nsocieties to remember and pass on the group's accumulated knowledge.\nEven in Confucius's time it still seems to have been the first duty\nof the scholar.[10]\nThe bias toward wisdom in ancient philosophy may be exaggerated\nby the fact that, in both Greece and China, many of the first\nphilosophers (including Confucius and Plato) saw themselves as\nteachers of administrators, and so thought disproportionately about\nsuch matters. The few people who did invent things, like storytellers,\nmust have seemed an outlying data point that could be ignored.Thanks to Trevor Blackwell, Sarah Harlin, Jessica Livingston,\nand Robert Morris for reading drafts of this." }, { "path": "data/PaulGrahamEssaysLarge/worked.txt", "content": "February 2021Before college the two main things I worked on, outside of school,\r\nwere writing and programming. I didn't write essays. I wrote what\r\nbeginning writers were supposed to write then, and probably still\r\nare: short stories. My stories were awful. They had hardly any plot,\r\njust characters with strong feelings, which I imagined made them\r\ndeep.The first programs I tried writing were on the IBM 1401 that our\r\nschool district used for what was then called \"data processing.\"\r\nThis was in 9th grade, so I was 13 or 14. The school district's\r\n1401 happened to be in the basement of our junior high school, and\r\nmy friend Rich Draves and I got permission to use it. It was like\r\na mini Bond villain's lair down there, with all these alien-looking\r\nmachines — CPU, disk drives, printer, card reader — sitting up\r\non a raised floor under bright fluorescent lights.The language we used was an early version of Fortran. You had to\r\ntype programs on punch cards, then stack them in the card reader\r\nand press a button to load the program into memory and run it. The\r\nresult would ordinarily be to print something on the spectacularly\r\nloud printer.I was puzzled by the 1401. I couldn't figure out what to do with\r\nit. And in retrospect there's not much I could have done with it.\r\nThe only form of input to programs was data stored on punched cards,\r\nand I didn't have any data stored on punched cards. The only other\r\noption was to do things that didn't rely on any input, like calculate\r\napproximations of pi, but I didn't know enough math to do anything\r\ninteresting of that type. So I'm not surprised I can't remember any\r\nprograms I wrote, because they can't have done much. My clearest\r\nmemory is of the moment I learned it was possible for programs not\r\nto terminate, when one of mine didn't. On a machine without\r\ntime-sharing, this was a social as well as a technical error, as\r\nthe data center manager's expression made clear.With microcomputers, everything changed. Now you could have a\r\ncomputer sitting right in front of you, on a desk, that could respond\r\nto your keystrokes as it was running instead of just churning through\r\na stack of punch cards and then stopping. \r\n[1]The first of my friends to get a microcomputer built it himself.\r\nIt was sold as a kit by Heathkit. I remember vividly how impressed\r\nand envious I felt watching him sitting in front of it, typing\r\nprograms right into the computer.Computers were expensive in those days and it took me years of\r\nnagging before I convinced my father to buy one, a TRS-80, in about\r\n1980. The gold standard then was the Apple II, but a TRS-80 was\r\ngood enough. This was when I really started programming. I wrote\r\nsimple games, a program to predict how high my model rockets would\r\nfly, and a word processor that my father used to write at least one\r\nbook. There was only room in memory for about 2 pages of text, so\r\nhe'd write 2 pages at a time and then print them out, but it was a\r\nlot better than a typewriter.Though I liked programming, I didn't plan to study it in college.\r\nIn college I was going to study philosophy, which sounded much more\r\npowerful. It seemed, to my naive high school self, to be the study\r\nof the ultimate truths, compared to which the things studied in\r\nother fields would be mere domain knowledge. What I discovered when\r\nI got to college was that the other fields took up so much of the\r\nspace of ideas that there wasn't much left for these supposed\r\nultimate truths. All that seemed left for philosophy were edge cases\r\nthat people in other fields felt could safely be ignored.I couldn't have put this into words when I was 18. All I knew at\r\nthe time was that I kept taking philosophy courses and they kept\r\nbeing boring. So I decided to switch to AI.AI was in the air in the mid 1980s, but there were two things\r\nespecially that made me want to work on it: a novel by Heinlein\r\ncalled The Moon is a Harsh Mistress, which featured an intelligent\r\ncomputer called Mike, and a PBS documentary that showed Terry\r\nWinograd using SHRDLU. I haven't tried rereading The Moon is a Harsh\r\nMistress, so I don't know how well it has aged, but when I read it\r\nI was drawn entirely into its world. It seemed only a matter of\r\ntime before we'd have Mike, and when I saw Winograd using SHRDLU,\r\nit seemed like that time would be a few years at most. All you had\r\nto do was teach SHRDLU more words.There weren't any classes in AI at Cornell then, not even graduate\r\nclasses, so I started trying to teach myself. Which meant learning\r\nLisp, since in those days Lisp was regarded as the language of AI.\r\nThe commonly used programming languages then were pretty primitive,\r\nand programmers' ideas correspondingly so. The default language at\r\nCornell was a Pascal-like language called PL/I, and the situation\r\nwas similar elsewhere. Learning Lisp expanded my concept of a program\r\nso fast that it was years before I started to have a sense of where\r\nthe new limits were. This was more like it; this was what I had\r\nexpected college to do. It wasn't happening in a class, like it was\r\nsupposed to, but that was ok. For the next couple years I was on a\r\nroll. I knew what I was going to do.For my undergraduate thesis, I reverse-engineered SHRDLU. My God\r\ndid I love working on that program. It was a pleasing bit of code,\r\nbut what made it even more exciting was my belief — hard to imagine\r\nnow, but not unique in 1985 — that it was already climbing the\r\nlower slopes of intelligence.I had gotten into a program at Cornell that didn't make you choose\r\na major. You could take whatever classes you liked, and choose\r\nwhatever you liked to put on your degree. I of course chose \"Artificial\r\nIntelligence.\" When I got the actual physical diploma, I was dismayed\r\nto find that the quotes had been included, which made them read as\r\nscare-quotes. At the time this bothered me, but now it seems amusingly\r\naccurate, for reasons I was about to discover.I applied to 3 grad schools: MIT and Yale, which were renowned for\r\nAI at the time, and Harvard, which I'd visited because Rich Draves\r\nwent there, and was also home to Bill Woods, who'd invented the\r\ntype of parser I used in my SHRDLU clone. Only Harvard accepted me,\r\nso that was where I went.I don't remember the moment it happened, or if there even was a\r\nspecific moment, but during the first year of grad school I realized\r\nthat AI, as practiced at the time, was a hoax. By which I mean the\r\nsort of AI in which a program that's told \"the dog is sitting on\r\nthe chair\" translates this into some formal representation and adds\r\nit to the list of things it knows.What these programs really showed was that there's a subset of\r\nnatural language that's a formal language. But a very proper subset.\r\nIt was clear that there was an unbridgeable gap between what they\r\ncould do and actually understanding natural language. It was not,\r\nin fact, simply a matter of teaching SHRDLU more words. That whole\r\nway of doing AI, with explicit data structures representing concepts,\r\nwas not going to work. Its brokenness did, as so often happens,\r\ngenerate a lot of opportunities to write papers about various\r\nband-aids that could be applied to it, but it was never going to\r\nget us Mike.So I looked around to see what I could salvage from the wreckage\r\nof my plans, and there was Lisp. I knew from experience that Lisp\r\nwas interesting for its own sake and not just for its association\r\nwith AI, even though that was the main reason people cared about\r\nit at the time. So I decided to focus on Lisp. In fact, I decided\r\nto write a book about Lisp hacking. It's scary to think how little\r\nI knew about Lisp hacking when I started writing that book. But\r\nthere's nothing like writing a book about something to help you\r\nlearn it. The book, On Lisp, wasn't published till 1993, but I wrote\r\nmuch of it in grad school.Computer Science is an uneasy alliance between two halves, theory\r\nand systems. The theory people prove things, and the systems people\r\nbuild things. I wanted to build things. I had plenty of respect for\r\ntheory — indeed, a sneaking suspicion that it was the more admirable\r\nof the two halves — but building things seemed so much more exciting.The problem with systems work, though, was that it didn't last.\r\nAny program you wrote today, no matter how good, would be obsolete\r\nin a couple decades at best. People might mention your software in\r\nfootnotes, but no one would actually use it. And indeed, it would\r\nseem very feeble work. Only people with a sense of the history of\r\nthe field would even realize that, in its time, it had been good.There were some surplus Xerox Dandelions floating around the computer\r\nlab at one point. Anyone who wanted one to play around with could\r\nhave one. I was briefly tempted, but they were so slow by present\r\nstandards; what was the point? No one else wanted one either, so\r\noff they went. That was what happened to systems work.I wanted not just to build things, but to build things that would\r\nlast.In this dissatisfied state I went in 1988 to visit Rich Draves at\r\nCMU, where he was in grad school. One day I went to visit the\r\nCarnegie Institute, where I'd spent a lot of time as a kid. While\r\nlooking at a painting there I realized something that might seem\r\nobvious, but was a big surprise to me. There, right on the wall,\r\nwas something you could make that would last. Paintings didn't\r\nbecome obsolete. Some of the best ones were hundreds of years old.And moreover this was something you could make a living doing. Not\r\nas easily as you could by writing software, of course, but I thought\r\nif you were really industrious and lived really cheaply, it had to\r\nbe possible to make enough to survive. And as an artist you could\r\nbe truly independent. You wouldn't have a boss, or even need to get\r\nresearch funding.I had always liked looking at paintings. Could I make them? I had\r\nno idea. I'd never imagined it was even possible. I knew intellectually\r\nthat people made art — that it didn't just appear spontaneously\r\n— but it was as if the people who made it were a different species.\r\nThey either lived long ago or were mysterious geniuses doing strange\r\nthings in profiles in Life magazine. The idea of actually being\r\nable to make art, to put that verb before that noun, seemed almost\r\nmiraculous.That fall I started taking art classes at Harvard. Grad students\r\ncould take classes in any department, and my advisor, Tom Cheatham,\r\nwas very easy going. If he even knew about the strange classes I\r\nwas taking, he never said anything.So now I was in a PhD program in computer science, yet planning to\r\nbe an artist, yet also genuinely in love with Lisp hacking and\r\nworking away at On Lisp. In other words, like many a grad student,\r\nI was working energetically on multiple projects that were not my\r\nthesis.I didn't see a way out of this situation. I didn't want to drop out\r\nof grad school, but how else was I going to get out? I remember\r\nwhen my friend Robert Morris got kicked out of Cornell for writing\r\nthe internet worm of 1988, I was envious that he'd found such a\r\nspectacular way to get out of grad school.Then one day in April 1990 a crack appeared in the wall. I ran into\r\nprofessor Cheatham and he asked if I was far enough along to graduate\r\nthat June. I didn't have a word of my dissertation written, but in\r\nwhat must have been the quickest bit of thinking in my life, I\r\ndecided to take a shot at writing one in the 5 weeks or so that\r\nremained before the deadline, reusing parts of On Lisp where I\r\ncould, and I was able to respond, with no perceptible delay \"Yes,\r\nI think so. I'll give you something to read in a few days.\"I picked applications of continuations as the topic. In retrospect\r\nI should have written about macros and embedded languages. There's\r\na whole world there that's barely been explored. But all I wanted\r\nwas to get out of grad school, and my rapidly written dissertation\r\nsufficed, just barely.Meanwhile I was applying to art schools. I applied to two: RISD in\r\nthe US, and the Accademia di Belli Arti in Florence, which, because\r\nit was the oldest art school, I imagined would be good. RISD accepted\r\nme, and I never heard back from the Accademia, so off to Providence\r\nI went.I'd applied for the BFA program at RISD, which meant in effect that\r\nI had to go to college again. This was not as strange as it sounds,\r\nbecause I was only 25, and art schools are full of people of different\r\nages. RISD counted me as a transfer sophomore and said I had to do\r\nthe foundation that summer. The foundation means the classes that\r\neveryone has to take in fundamental subjects like drawing, color,\r\nand design.Toward the end of the summer I got a big surprise: a letter from\r\nthe Accademia, which had been delayed because they'd sent it to\r\nCambridge England instead of Cambridge Massachusetts, inviting me\r\nto take the entrance exam in Florence that fall. This was now only\r\nweeks away. My nice landlady let me leave my stuff in her attic. I\r\nhad some money saved from consulting work I'd done in grad school;\r\nthere was probably enough to last a year if I lived cheaply. Now\r\nall I had to do was learn Italian.Only stranieri (foreigners) had to take this entrance exam. In\r\nretrospect it may well have been a way of excluding them, because\r\nthere were so many stranieri attracted by the idea of studying\r\nart in Florence that the Italian students would otherwise have been\r\noutnumbered. I was in decent shape at painting and drawing from the\r\nRISD foundation that summer, but I still don't know how I managed\r\nto pass the written exam. I remember that I answered the essay\r\nquestion by writing about Cezanne, and that I cranked up the\r\nintellectual level as high as I could to make the most of my limited\r\nvocabulary. \r\n[2]I'm only up to age 25 and already there are such conspicuous patterns.\r\nHere I was, yet again about to attend some august institution in\r\nthe hopes of learning about some prestigious subject, and yet again\r\nabout to be disappointed. The students and faculty in the painting\r\ndepartment at the Accademia were the nicest people you could imagine,\r\nbut they had long since arrived at an arrangement whereby the\r\nstudents wouldn't require the faculty to teach anything, and in\r\nreturn the faculty wouldn't require the students to learn anything.\r\nAnd at the same time all involved would adhere outwardly to the\r\nconventions of a 19th century atelier. We actually had one of those\r\nlittle stoves, fed with kindling, that you see in 19th century\r\nstudio paintings, and a nude model sitting as close to it as possible\r\nwithout getting burned. Except hardly anyone else painted her besides\r\nme. The rest of the students spent their time chatting or occasionally\r\ntrying to imitate things they'd seen in American art magazines.Our model turned out to live just down the street from me. She made\r\na living from a combination of modelling and making fakes for a\r\nlocal antique dealer. She'd copy an obscure old painting out of a\r\nbook, and then he'd take the copy and maltreat it to make it look\r\nold. \r\n[3]While I was a student at the Accademia I started painting still\r\nlives in my bedroom at night. These paintings were tiny, because\r\nthe room was, and because I painted them on leftover scraps of\r\ncanvas, which was all I could afford at the time. Painting still\r\nlives is different from painting people, because the subject, as\r\nits name suggests, can't move. People can't sit for more than about\r\n15 minutes at a time, and when they do they don't sit very still.\r\nSo the traditional m.o. for painting people is to know how to paint\r\na generic person, which you then modify to match the specific person\r\nyou're painting. Whereas a still life you can, if you want, copy\r\npixel by pixel from what you're seeing. You don't want to stop\r\nthere, of course, or you get merely photographic accuracy, and what\r\nmakes a still life interesting is that it's been through a head.\r\nYou want to emphasize the visual cues that tell you, for example,\r\nthat the reason the color changes suddenly at a certain point is\r\nthat it's the edge of an object. By subtly emphasizing such things\r\nyou can make paintings that are more realistic than photographs not\r\njust in some metaphorical sense, but in the strict information-theoretic\r\nsense. \r\n[4]I liked painting still lives because I was curious about what I was\r\nseeing. In everyday life, we aren't consciously aware of much we're\r\nseeing. Most visual perception is handled by low-level processes\r\nthat merely tell your brain \"that's a water droplet\" without telling\r\nyou details like where the lightest and darkest points are, or\r\n\"that's a bush\" without telling you the shape and position of every\r\nleaf. This is a feature of brains, not a bug. In everyday life it\r\nwould be distracting to notice every leaf on every bush. But when\r\nyou have to paint something, you have to look more closely, and\r\nwhen you do there's a lot to see. You can still be noticing new\r\nthings after days of trying to paint something people usually take\r\nfor granted, just as you can after\r\ndays of trying to write an essay about something people usually\r\ntake for granted.This is not the only way to paint. I'm not 100% sure it's even a\r\ngood way to paint. But it seemed a good enough bet to be worth\r\ntrying.Our teacher, professor Ulivi, was a nice guy. He could see I worked\r\nhard, and gave me a good grade, which he wrote down in a sort of\r\npassport each student had. But the Accademia wasn't teaching me\r\nanything except Italian, and my money was running out, so at the\r\nend of the first year I went back to the US.I wanted to go back to RISD, but I was now broke and RISD was very\r\nexpensive, so I decided to get a job for a year and then return to\r\nRISD the next fall. I got one at a company called Interleaf, which\r\nmade software for creating documents. You mean like Microsoft Word?\r\nExactly. That was how I learned that low end software tends to eat\r\nhigh end software. But Interleaf still had a few years to live yet.\r\n[5]Interleaf had done something pretty bold. Inspired by Emacs, they'd\r\nadded a scripting language, and even made the scripting language a\r\ndialect of Lisp. Now they wanted a Lisp hacker to write things in\r\nit. This was the closest thing I've had to a normal job, and I\r\nhereby apologize to my boss and coworkers, because I was a bad\r\nemployee. Their Lisp was the thinnest icing on a giant C cake, and\r\nsince I didn't know C and didn't want to learn it, I never understood\r\nmost of the software. Plus I was terribly irresponsible. This was\r\nback when a programming job meant showing up every day during certain\r\nworking hours. That seemed unnatural to me, and on this point the\r\nrest of the world is coming around to my way of thinking, but at\r\nthe time it caused a lot of friction. Toward the end of the year I\r\nspent much of my time surreptitiously working on On Lisp, which I\r\nhad by this time gotten a contract to publish.The good part was that I got paid huge amounts of money, especially\r\nby art student standards. In Florence, after paying my part of the\r\nrent, my budget for everything else had been $7 a day. Now I was\r\ngetting paid more than 4 times that every hour, even when I was\r\njust sitting in a meeting. By living cheaply I not only managed to\r\nsave enough to go back to RISD, but also paid off my college loans.I learned some useful things at Interleaf, though they were mostly\r\nabout what not to do. I learned that it's better for technology\r\ncompanies to be run by product people than sales people (though\r\nsales is a real skill and people who are good at it are really good\r\nat it), that it leads to bugs when code is edited by too many people,\r\nthat cheap office space is no bargain if it's depressing, that\r\nplanned meetings are inferior to corridor conversations, that big,\r\nbureaucratic customers are a dangerous source of money, and that\r\nthere's not much overlap between conventional office hours and the\r\noptimal time for hacking, or conventional offices and the optimal\r\nplace for it.But the most important thing I learned, and which I used in both\r\nViaweb and Y Combinator, is that the low end eats the high end:\r\nthat it's good to be the \"entry level\" option, even though that\r\nwill be less prestigious, because if you're not, someone else will\r\nbe, and will squash you against the ceiling. Which in turn means\r\nthat prestige is a danger sign.When I left to go back to RISD the next fall, I arranged to do\r\nfreelance work for the group that did projects for customers, and\r\nthis was how I survived for the next several years. When I came\r\nback to visit for a project later on, someone told me about a new\r\nthing called HTML, which was, as he described it, a derivative of\r\nSGML. Markup language enthusiasts were an occupational hazard at\r\nInterleaf and I ignored him, but this HTML thing later became a big\r\npart of my life.In the fall of 1992 I moved back to Providence to continue at RISD.\r\nThe foundation had merely been intro stuff, and the Accademia had\r\nbeen a (very civilized) joke. Now I was going to see what real art\r\nschool was like. But alas it was more like the Accademia than not.\r\nBetter organized, certainly, and a lot more expensive, but it was\r\nnow becoming clear that art school did not bear the same relationship\r\nto art that medical school bore to medicine. At least not the\r\npainting department. The textile department, which my next door\r\nneighbor belonged to, seemed to be pretty rigorous. No doubt\r\nillustration and architecture were too. But painting was post-rigorous.\r\nPainting students were supposed to express themselves, which to the\r\nmore worldly ones meant to try to cook up some sort of distinctive\r\nsignature style.A signature style is the visual equivalent of what in show business\r\nis known as a \"schtick\": something that immediately identifies the\r\nwork as yours and no one else's. For example, when you see a painting\r\nthat looks like a certain kind of cartoon, you know it's by Roy\r\nLichtenstein. So if you see a big painting of this type hanging in\r\nthe apartment of a hedge fund manager, you know he paid millions\r\nof dollars for it. That's not always why artists have a signature\r\nstyle, but it's usually why buyers pay a lot for such work.\r\n[6]There were plenty of earnest students too: kids who \"could draw\"\r\nin high school, and now had come to what was supposed to be the\r\nbest art school in the country, to learn to draw even better. They\r\ntended to be confused and demoralized by what they found at RISD,\r\nbut they kept going, because painting was what they did. I was not\r\none of the kids who could draw in high school, but at RISD I was\r\ndefinitely closer to their tribe than the tribe of signature style\r\nseekers.I learned a lot in the color class I took at RISD, but otherwise I\r\nwas basically teaching myself to paint, and I could do that for\r\nfree. So in 1993 I dropped out. I hung around Providence for a bit,\r\nand then my college friend Nancy Parmet did me a big favor. A\r\nrent-controlled apartment in a building her mother owned in New\r\nYork was becoming vacant. Did I want it? It wasn't much more than\r\nmy current place, and New York was supposed to be where the artists\r\nwere. So yes, I wanted it!\r\n[7]Asterix comics begin by zooming in on a tiny corner of Roman Gaul\r\nthat turns out not to be controlled by the Romans. You can do\r\nsomething similar on a map of New York City: if you zoom in on the\r\nUpper East Side, there's a tiny corner that's not rich, or at least\r\nwasn't in 1993. It's called Yorkville, and that was my new home.\r\nNow I was a New York artist — in the strictly technical sense of\r\nmaking paintings and living in New York.I was nervous about money, because I could sense that Interleaf was\r\non the way down. Freelance Lisp hacking work was very rare, and I\r\ndidn't want to have to program in another language, which in those\r\ndays would have meant C++ if I was lucky. So with my unerring nose\r\nfor financial opportunity, I decided to write another book on Lisp.\r\nThis would be a popular book, the sort of book that could be used\r\nas a textbook. I imagined myself living frugally off the royalties\r\nand spending all my time painting. (The painting on the cover of\r\nthis book, ANSI Common Lisp, is one that I painted around this\r\ntime.)The best thing about New York for me was the presence of Idelle and\r\nJulian Weber. Idelle Weber was a painter, one of the early\r\nphotorealists, and I'd taken her painting class at Harvard. I've\r\nnever known a teacher more beloved by her students. Large numbers\r\nof former students kept in touch with her, including me. After I\r\nmoved to New York I became her de facto studio assistant.She liked to paint on big, square canvases, 4 to 5 feet on a side.\r\nOne day in late 1994 as I was stretching one of these monsters there\r\nwas something on the radio about a famous fund manager. He wasn't\r\nthat much older than me, and was super rich. The thought suddenly\r\noccurred to me: why don't I become rich? Then I'll be able to work\r\non whatever I want.Meanwhile I'd been hearing more and more about this new thing called\r\nthe World Wide Web. Robert Morris showed it to me when I visited\r\nhim in Cambridge, where he was now in grad school at Harvard. It\r\nseemed to me that the web would be a big deal. I'd seen what graphical\r\nuser interfaces had done for the popularity of microcomputers. It\r\nseemed like the web would do the same for the internet.If I wanted to get rich, here was the next train leaving the station.\r\nI was right about that part. What I got wrong was the idea. I decided\r\nwe should start a company to put art galleries online. I can't\r\nhonestly say, after reading so many Y Combinator applications, that\r\nthis was the worst startup idea ever, but it was up there. Art\r\ngalleries didn't want to be online, and still don't, not the fancy\r\nones. That's not how they sell. I wrote some software to generate\r\nweb sites for galleries, and Robert wrote some to resize images and\r\nset up an http server to serve the pages. Then we tried to sign up\r\ngalleries. To call this a difficult sale would be an understatement.\r\nIt was difficult to give away. A few galleries let us make sites\r\nfor them for free, but none paid us.Then some online stores started to appear, and I realized that\r\nexcept for the order buttons they were identical to the sites we'd\r\nbeen generating for galleries. This impressive-sounding thing called\r\nan \"internet storefront\" was something we already knew how to build.So in the summer of 1995, after I submitted the camera-ready copy\r\nof ANSI Common Lisp to the publishers, we started trying to write\r\nsoftware to build online stores. At first this was going to be\r\nnormal desktop software, which in those days meant Windows software.\r\nThat was an alarming prospect, because neither of us knew how to\r\nwrite Windows software or wanted to learn. We lived in the Unix\r\nworld. But we decided we'd at least try writing a prototype store\r\nbuilder on Unix. Robert wrote a shopping cart, and I wrote a new\r\nsite generator for stores — in Lisp, of course.We were working out of Robert's apartment in Cambridge. His roommate\r\nwas away for big chunks of time, during which I got to sleep in his\r\nroom. For some reason there was no bed frame or sheets, just a\r\nmattress on the floor. One morning as I was lying on this mattress\r\nI had an idea that made me sit up like a capital L. What if we ran\r\nthe software on the server, and let users control it by clicking\r\non links? Then we'd never have to write anything to run on users'\r\ncomputers. We could generate the sites on the same server we'd serve\r\nthem from. Users wouldn't need anything more than a browser.This kind of software, known as a web app, is common now, but at\r\nthe time it wasn't clear that it was even possible. To find out,\r\nwe decided to try making a version of our store builder that you\r\ncould control through the browser. A couple days later, on August\r\n12, we had one that worked. The UI was horrible, but it proved you\r\ncould build a whole store through the browser, without any client\r\nsoftware or typing anything into the command line on the server.Now we felt like we were really onto something. I had visions of a\r\nwhole new generation of software working this way. You wouldn't\r\nneed versions, or ports, or any of that crap. At Interleaf there\r\nhad been a whole group called Release Engineering that seemed to\r\nbe at least as big as the group that actually wrote the software.\r\nNow you could just update the software right on the server.We started a new company we called Viaweb, after the fact that our\r\nsoftware worked via the web, and we got $10,000 in seed funding\r\nfrom Idelle's husband Julian. In return for that and doing the\r\ninitial legal work and giving us business advice, we gave him 10%\r\nof the company. Ten years later this deal became the model for Y\r\nCombinator's. We knew founders needed something like this, because\r\nwe'd needed it ourselves.At this stage I had a negative net worth, because the thousand\r\ndollars or so I had in the bank was more than counterbalanced by\r\nwhat I owed the government in taxes. (Had I diligently set aside\r\nthe proper proportion of the money I'd made consulting for Interleaf?\r\nNo, I had not.) So although Robert had his graduate student stipend,\r\nI needed that seed funding to live on.We originally hoped to launch in September, but we got more ambitious\r\nabout the software as we worked on it. Eventually we managed to\r\nbuild a WYSIWYG site builder, in the sense that as you were creating\r\npages, they looked exactly like the static ones that would be\r\ngenerated later, except that instead of leading to static pages,\r\nthe links all referred to closures stored in a hash table on the\r\nserver.It helped to have studied art, because the main goal of an online\r\nstore builder is to make users look legit, and the key to looking\r\nlegit is high production values. If you get page layouts and fonts\r\nand colors right, you can make a guy running a store out of his\r\nbedroom look more legit than a big company.(If you're curious why my site looks so old-fashioned, it's because\r\nit's still made with this software. It may look clunky today, but\r\nin 1996 it was the last word in slick.)In September, Robert rebelled. \"We've been working on this for a\r\nmonth,\" he said, \"and it's still not done.\" This is funny in\r\nretrospect, because he would still be working on it almost 3 years\r\nlater. But I decided it might be prudent to recruit more programmers,\r\nand I asked Robert who else in grad school with him was really good.\r\nHe recommended Trevor Blackwell, which surprised me at first, because\r\nat that point I knew Trevor mainly for his plan to reduce everything\r\nin his life to a stack of notecards, which he carried around with\r\nhim. But Rtm was right, as usual. Trevor turned out to be a\r\nfrighteningly effective hacker.It was a lot of fun working with Robert and Trevor. They're the two\r\nmost independent-minded people \r\nI know, and in completely different\r\nways. If you could see inside Rtm's brain it would look like a\r\ncolonial New England church, and if you could see inside Trevor's\r\nit would look like the worst excesses of Austrian Rococo.We opened for business, with 6 stores, in January 1996. It was just\r\nas well we waited a few months, because although we worried we were\r\nlate, we were actually almost fatally early. There was a lot of\r\ntalk in the press then about ecommerce, but not many people actually\r\nwanted online stores.\r\n[8]There were three main parts to the software: the editor, which\r\npeople used to build sites and which I wrote, the shopping cart,\r\nwhich Robert wrote, and the manager, which kept track of orders and\r\nstatistics, and which Trevor wrote. In its time, the editor was one\r\nof the best general-purpose site builders. I kept the code tight\r\nand didn't have to integrate with any other software except Robert's\r\nand Trevor's, so it was quite fun to work on. If all I'd had to do\r\nwas work on this software, the next 3 years would have been the\r\neasiest of my life. Unfortunately I had to do a lot more, all of\r\nit stuff I was worse at than programming, and the next 3 years were\r\ninstead the most stressful.There were a lot of startups making ecommerce software in the second\r\nhalf of the 90s. We were determined to be the Microsoft Word, not\r\nthe Interleaf. Which meant being easy to use and inexpensive. It\r\nwas lucky for us that we were poor, because that caused us to make\r\nViaweb even more inexpensive than we realized. We charged $100 a\r\nmonth for a small store and $300 a month for a big one. This low\r\nprice was a big attraction, and a constant thorn in the sides of\r\ncompetitors, but it wasn't because of some clever insight that we\r\nset the price low. We had no idea what businesses paid for things.\r\n$300 a month seemed like a lot of money to us.We did a lot of things right by accident like that. For example,\r\nwe did what's now called \"doing things that \r\ndon't scale,\" although\r\nat the time we would have described it as \"being so lame that we're\r\ndriven to the most desperate measures to get users.\" The most common\r\nof which was building stores for them. This seemed particularly\r\nhumiliating, since the whole raison d'etre of our software was that\r\npeople could use it to make their own stores. But anything to get\r\nusers.We learned a lot more about retail than we wanted to know. For\r\nexample, that if you could only have a small image of a man's shirt\r\n(and all images were small then by present standards), it was better\r\nto have a closeup of the collar than a picture of the whole shirt.\r\nThe reason I remember learning this was that it meant I had to\r\nrescan about 30 images of men's shirts. My first set of scans were\r\nso beautiful too.Though this felt wrong, it was exactly the right thing to be doing.\r\nBuilding stores for users taught us about retail, and about how it\r\nfelt to use our software. I was initially both mystified and repelled\r\nby \"business\" and thought we needed a \"business person\" to be in\r\ncharge of it, but once we started to get users, I was converted,\r\nin much the same way I was converted to \r\nfatherhood once I had kids.\r\nWhatever users wanted, I was all theirs. Maybe one day we'd have\r\nso many users that I couldn't scan their images for them, but in\r\nthe meantime there was nothing more important to do.Another thing I didn't get at the time is that \r\ngrowth rate is the\r\nultimate test of a startup. Our growth rate was fine. We had about\r\n70 stores at the end of 1996 and about 500 at the end of 1997. I\r\nmistakenly thought the thing that mattered was the absolute number\r\nof users. And that is the thing that matters in the sense that\r\nthat's how much money you're making, and if you're not making enough,\r\nyou might go out of business. But in the long term the growth rate\r\ntakes care of the absolute number. If we'd been a startup I was\r\nadvising at Y Combinator, I would have said: Stop being so stressed\r\nout, because you're doing fine. You're growing 7x a year. Just don't\r\nhire too many more people and you'll soon be profitable, and then\r\nyou'll control your own destiny.Alas I hired lots more people, partly because our investors wanted\r\nme to, and partly because that's what startups did during the\r\nInternet Bubble. A company with just a handful of employees would\r\nhave seemed amateurish. So we didn't reach breakeven until about\r\nwhen Yahoo bought us in the summer of 1998. Which in turn meant we\r\nwere at the mercy of investors for the entire life of the company.\r\nAnd since both we and our investors were noobs at startups, the\r\nresult was a mess even by startup standards.It was a huge relief when Yahoo bought us. In principle our Viaweb\r\nstock was valuable. It was a share in a business that was profitable\r\nand growing rapidly. But it didn't feel very valuable to me; I had\r\nno idea how to value a business, but I was all too keenly aware of\r\nthe near-death experiences we seemed to have every few months. Nor\r\nhad I changed my grad student lifestyle significantly since we\r\nstarted. So when Yahoo bought us it felt like going from rags to\r\nriches. Since we were going to California, I bought a car, a yellow\r\n1998 VW GTI. I remember thinking that its leather seats alone were\r\nby far the most luxurious thing I owned.The next year, from the summer of 1998 to the summer of 1999, must\r\nhave been the least productive of my life. I didn't realize it at\r\nthe time, but I was worn out from the effort and stress of running\r\nViaweb. For a while after I got to California I tried to continue\r\nmy usual m.o. of programming till 3 in the morning, but fatigue\r\ncombined with Yahoo's prematurely aged\r\nculture and grim cube farm\r\nin Santa Clara gradually dragged me down. After a few months it\r\nfelt disconcertingly like working at Interleaf.Yahoo had given us a lot of options when they bought us. At the\r\ntime I thought Yahoo was so overvalued that they'd never be worth\r\nanything, but to my astonishment the stock went up 5x in the next\r\nyear. I hung on till the first chunk of options vested, then in the\r\nsummer of 1999 I left. It had been so long since I'd painted anything\r\nthat I'd half forgotten why I was doing this. My brain had been\r\nentirely full of software and men's shirts for 4 years. But I had\r\ndone this to get rich so I could paint, I reminded myself, and now\r\nI was rich, so I should go paint.When I said I was leaving, my boss at Yahoo had a long conversation\r\nwith me about my plans. I told him all about the kinds of pictures\r\nI wanted to paint. At the time I was touched that he took such an\r\ninterest in me. Now I realize it was because he thought I was lying.\r\nMy options at that point were worth about $2 million a month. If I\r\nwas leaving that kind of money on the table, it could only be to\r\ngo and start some new startup, and if I did, I might take people\r\nwith me. This was the height of the Internet Bubble, and Yahoo was\r\nground zero of it. My boss was at that moment a billionaire. Leaving\r\nthen to start a new startup must have seemed to him an insanely,\r\nand yet also plausibly, ambitious plan.But I really was quitting to paint, and I started immediately.\r\nThere was no time to lose. I'd already burned 4 years getting rich.\r\nNow when I talk to founders who are leaving after selling their\r\ncompanies, my advice is always the same: take a vacation. That's\r\nwhat I should have done, just gone off somewhere and done nothing\r\nfor a month or two, but the idea never occurred to me.So I tried to paint, but I just didn't seem to have any energy or\r\nambition. Part of the problem was that I didn't know many people\r\nin California. I'd compounded this problem by buying a house up in\r\nthe Santa Cruz Mountains, with a beautiful view but miles from\r\nanywhere. I stuck it out for a few more months, then in desperation\r\nI went back to New York, where unless you understand about rent\r\ncontrol you'll be surprised to hear I still had my apartment, sealed\r\nup like a tomb of my old life. Idelle was in New York at least, and\r\nthere were other people trying to paint there, even though I didn't\r\nknow any of them.When I got back to New York I resumed my old life, except now I was\r\nrich. It was as weird as it sounds. I resumed all my old patterns,\r\nexcept now there were doors where there hadn't been. Now when I was\r\ntired of walking, all I had to do was raise my hand, and (unless\r\nit was raining) a taxi would stop to pick me up. Now when I walked\r\npast charming little restaurants I could go in and order lunch. It\r\nwas exciting for a while. Painting started to go better. I experimented\r\nwith a new kind of still life where I'd paint one painting in the\r\nold way, then photograph it and print it, blown up, on canvas, and\r\nthen use that as the underpainting for a second still life, painted\r\nfrom the same objects (which hopefully hadn't rotted yet).Meanwhile I looked for an apartment to buy. Now I could actually\r\nchoose what neighborhood to live in. Where, I asked myself and\r\nvarious real estate agents, is the Cambridge of New York? Aided by\r\noccasional visits to actual Cambridge, I gradually realized there\r\nwasn't one. Huh.Around this time, in the spring of 2000, I had an idea. It was clear\r\nfrom our experience with Viaweb that web apps were the future. Why\r\nnot build a web app for making web apps? Why not let people edit\r\ncode on our server through the browser, and then host the resulting\r\napplications for them?\r\n[9]\r\nYou could run all sorts of services\r\non the servers that these applications could use just by making an\r\nAPI call: making and receiving phone calls, manipulating images,\r\ntaking credit card payments, etc.I got so excited about this idea that I couldn't think about anything\r\nelse. It seemed obvious that this was the future. I didn't particularly\r\nwant to start another company, but it was clear that this idea would\r\nhave to be embodied as one, so I decided to move to Cambridge and\r\nstart it. I hoped to lure Robert into working on it with me, but\r\nthere I ran into a hitch. Robert was now a postdoc at MIT, and\r\nthough he'd made a lot of money the last time I'd lured him into\r\nworking on one of my schemes, it had also been a huge time sink.\r\nSo while he agreed that it sounded like a plausible idea, he firmly\r\nrefused to work on it.Hmph. Well, I'd do it myself then. I recruited Dan Giffin, who had\r\nworked for Viaweb, and two undergrads who wanted summer jobs, and\r\nwe got to work trying to build what it's now clear is about twenty\r\ncompanies and several open source projects worth of software. The\r\nlanguage for defining applications would of course be a dialect of\r\nLisp. But I wasn't so naive as to assume I could spring an overt\r\nLisp on a general audience; we'd hide the parentheses, like Dylan\r\ndid.By then there was a name for the kind of company Viaweb was, an\r\n\"application service provider,\" or ASP. This name didn't last long\r\nbefore it was replaced by \"software as a service,\" but it was current\r\nfor long enough that I named this new company after it: it was going\r\nto be called Aspra.I started working on the application builder, Dan worked on network\r\ninfrastructure, and the two undergrads worked on the first two\r\nservices (images and phone calls). But about halfway through the\r\nsummer I realized I really didn't want to run a company — especially\r\nnot a big one, which it was looking like this would have to be. I'd\r\nonly started Viaweb because I needed the money. Now that I didn't\r\nneed money anymore, why was I doing this? If this vision had to be\r\nrealized as a company, then screw the vision. I'd build a subset\r\nthat could be done as an open source project.Much to my surprise, the time I spent working on this stuff was not\r\nwasted after all. After we started Y Combinator, I would often\r\nencounter startups working on parts of this new architecture, and\r\nit was very useful to have spent so much time thinking about it and\r\neven trying to write some of it.The subset I would build as an open source project was the new Lisp,\r\nwhose parentheses I now wouldn't even have to hide. A lot of Lisp\r\nhackers dream of building a new Lisp, partly because one of the\r\ndistinctive features of the language is that it has dialects, and\r\npartly, I think, because we have in our minds a Platonic form of\r\nLisp that all existing dialects fall short of. I certainly did. So\r\nat the end of the summer Dan and I switched to working on this new\r\ndialect of Lisp, which I called Arc, in a house I bought in Cambridge.The following spring, lightning struck. I was invited to give a\r\ntalk at a Lisp conference, so I gave one about how we'd used Lisp\r\nat Viaweb. Afterward I put a postscript file of this talk online,\r\non paulgraham.com, which I'd created years before using Viaweb but\r\nhad never used for anything. In one day it got 30,000 page views.\r\nWhat on earth had happened? The referring urls showed that someone\r\nhad posted it on Slashdot.\r\n[10]Wow, I thought, there's an audience. If I write something and put\r\nit on the web, anyone can read it. That may seem obvious now, but\r\nit was surprising then. In the print era there was a narrow channel\r\nto readers, guarded by fierce monsters known as editors. The only\r\nway to get an audience for anything you wrote was to get it published\r\nas a book, or in a newspaper or magazine. Now anyone could publish\r\nanything.This had been possible in principle since 1993, but not many people\r\nhad realized it yet. I had been intimately involved with building\r\nthe infrastructure of the web for most of that time, and a writer\r\nas well, and it had taken me 8 years to realize it. Even then it\r\ntook me several years to understand the implications. It meant there\r\nwould be a whole new generation of \r\nessays.\r\n[11]In the print era, the channel for publishing essays had been\r\nvanishingly small. Except for a few officially anointed thinkers\r\nwho went to the right parties in New York, the only people allowed\r\nto publish essays were specialists writing about their specialties.\r\nThere were so many essays that had never been written, because there\r\nhad been no way to publish them. Now they could be, and I was going\r\nto write them.\r\n[12]I've worked on several different things, but to the extent there\r\nwas a turning point where I figured out what to work on, it was\r\nwhen I started publishing essays online. From then on I knew that\r\nwhatever else I did, I'd always write essays too.I knew that online essays would be a \r\nmarginal medium at first.\r\nSocially they'd seem more like rants posted by nutjobs on their\r\nGeoCities sites than the genteel and beautifully typeset compositions\r\npublished in The New Yorker. But by this point I knew enough to\r\nfind that encouraging instead of discouraging.One of the most conspicuous patterns I've noticed in my life is how\r\nwell it has worked, for me at least, to work on things that weren't\r\nprestigious. Still life has always been the least prestigious form\r\nof painting. Viaweb and Y Combinator both seemed lame when we started\r\nthem. I still get the glassy eye from strangers when they ask what\r\nI'm writing, and I explain that it's an essay I'm going to publish\r\non my web site. Even Lisp, though prestigious intellectually in\r\nsomething like the way Latin is, also seems about as hip.It's not that unprestigious types of work are good per se. But when\r\nyou find yourself drawn to some kind of work despite its current\r\nlack of prestige, it's a sign both that there's something real to\r\nbe discovered there, and that you have the right kind of motives.\r\nImpure motives are a big danger for the ambitious. If anything is\r\ngoing to lead you astray, it will be the desire to impress people.\r\nSo while working on things that aren't prestigious doesn't guarantee\r\nyou're on the right track, it at least guarantees you're not on the\r\nmost common type of wrong one.Over the next several years I wrote lots of essays about all kinds\r\nof different topics. O'Reilly reprinted a collection of them as a\r\nbook, called Hackers & Painters after one of the essays in it. I\r\nalso worked on spam filters, and did some more painting. I used to\r\nhave dinners for a group of friends every thursday night, which\r\ntaught me how to cook for groups. And I bought another building in\r\nCambridge, a former candy factory (and later, twas said, porn\r\nstudio), to use as an office.One night in October 2003 there was a big party at my house. It was\r\na clever idea of my friend Maria Daniels, who was one of the thursday\r\ndiners. Three separate hosts would all invite their friends to one\r\nparty. So for every guest, two thirds of the other guests would be\r\npeople they didn't know but would probably like. One of the guests\r\nwas someone I didn't know but would turn out to like a lot: a woman\r\ncalled Jessica Livingston. A couple days later I asked her out.Jessica was in charge of marketing at a Boston investment bank.\r\nThis bank thought it understood startups, but over the next year,\r\nas she met friends of mine from the startup world, she was surprised\r\nhow different reality was. And how colorful their stories were. So\r\nshe decided to compile a book of \r\ninterviews with startup founders.When the bank had financial problems and she had to fire half her\r\nstaff, she started looking for a new job. In early 2005 she interviewed\r\nfor a marketing job at a Boston VC firm. It took them weeks to make\r\nup their minds, and during this time I started telling her about\r\nall the things that needed to be fixed about venture capital. They\r\nshould make a larger number of smaller investments instead of a\r\nhandful of giant ones, they should be funding younger, more technical\r\nfounders instead of MBAs, they should let the founders remain as\r\nCEO, and so on.One of my tricks for writing essays had always been to give talks.\r\nThe prospect of having to stand up in front of a group of people\r\nand tell them something that won't waste their time is a great\r\nspur to the imagination. When the Harvard Computer Society, the\r\nundergrad computer club, asked me to give a talk, I decided I would\r\ntell them how to start a startup. Maybe they'd be able to avoid the\r\nworst of the mistakes we'd made.So I gave this talk, in the course of which I told them that the\r\nbest sources of seed funding were successful startup founders,\r\nbecause then they'd be sources of advice too. Whereupon it seemed\r\nthey were all looking expectantly at me. Horrified at the prospect\r\nof having my inbox flooded by business plans (if I'd only known),\r\nI blurted out \"But not me!\" and went on with the talk. But afterward\r\nit occurred to me that I should really stop procrastinating about\r\nangel investing. I'd been meaning to since Yahoo bought us, and now\r\nit was 7 years later and I still hadn't done one angel investment.Meanwhile I had been scheming with Robert and Trevor about projects\r\nwe could work on together. I missed working with them, and it seemed\r\nlike there had to be something we could collaborate on.As Jessica and I were walking home from dinner on March 11, at the\r\ncorner of Garden and Walker streets, these three threads converged.\r\nScrew the VCs who were taking so long to make up their minds. We'd\r\nstart our own investment firm and actually implement the ideas we'd\r\nbeen talking about. I'd fund it, and Jessica could quit her job and\r\nwork for it, and we'd get Robert and Trevor as partners too.\r\n[13]Once again, ignorance worked in our favor. We had no idea how to\r\nbe angel investors, and in Boston in 2005 there were no Ron Conways\r\nto learn from. So we just made what seemed like the obvious choices,\r\nand some of the things we did turned out to be novel.There are multiple components to Y Combinator, and we didn't figure\r\nthem all out at once. The part we got first was to be an angel firm.\r\nIn those days, those two words didn't go together. There were VC\r\nfirms, which were organized companies with people whose job it was\r\nto make investments, but they only did big, million dollar investments.\r\nAnd there were angels, who did smaller investments, but these were\r\nindividuals who were usually focused on other things and made\r\ninvestments on the side. And neither of them helped founders enough\r\nin the beginning. We knew how helpless founders were in some respects,\r\nbecause we remembered how helpless we'd been. For example, one thing\r\nJulian had done for us that seemed to us like magic was to get us\r\nset up as a company. We were fine writing fairly difficult software,\r\nbut actually getting incorporated, with bylaws and stock and all\r\nthat stuff, how on earth did you do that? Our plan was not only to\r\nmake seed investments, but to do for startups everything Julian had\r\ndone for us.YC was not organized as a fund. It was cheap enough to run that we\r\nfunded it with our own money. That went right by 99% of readers,\r\nbut professional investors are thinking \"Wow, that means they got\r\nall the returns.\" But once again, this was not due to any particular\r\ninsight on our part. We didn't know how VC firms were organized.\r\nIt never occurred to us to try to raise a fund, and if it had, we\r\nwouldn't have known where to start.\r\n[14]The most distinctive thing about YC is the batch model: to fund a\r\nbunch of startups all at once, twice a year, and then to spend three\r\nmonths focusing intensively on trying to help them. That part we\r\ndiscovered by accident, not merely implicitly but explicitly due\r\nto our ignorance about investing. We needed to get experience as\r\ninvestors. What better way, we thought, than to fund a whole bunch\r\nof startups at once? We knew undergrads got temporary jobs at tech\r\ncompanies during the summer. Why not organize a summer program where\r\nthey'd start startups instead? We wouldn't feel guilty for being\r\nin a sense fake investors, because they would in a similar sense\r\nbe fake founders. So while we probably wouldn't make much money out\r\nof it, we'd at least get to practice being investors on them, and\r\nthey for their part would probably have a more interesting summer\r\nthan they would working at Microsoft.We'd use the building I owned in Cambridge as our headquarters.\r\nWe'd all have dinner there once a week — on tuesdays, since I was\r\nalready cooking for the thursday diners on thursdays — and after\r\ndinner we'd bring in experts on startups to give talks.We knew undergrads were deciding then about summer jobs, so in a\r\nmatter of days we cooked up something we called the Summer Founders\r\nProgram, and I posted an \r\nannouncement \r\non my site, inviting undergrads\r\nto apply. I had never imagined that writing essays would be a way\r\nto get \"deal flow,\" as investors call it, but it turned out to be\r\nthe perfect source.\r\n[15]\r\nWe got 225 applications for the Summer\r\nFounders Program, and we were surprised to find that a lot of them\r\nwere from people who'd already graduated, or were about to that\r\nspring. Already this SFP thing was starting to feel more serious\r\nthan we'd intended.We invited about 20 of the 225 groups to interview in person, and\r\nfrom those we picked 8 to fund. They were an impressive group. That\r\nfirst batch included reddit, Justin Kan and Emmett Shear, who went\r\non to found Twitch, Aaron Swartz, who had already helped write the\r\nRSS spec and would a few years later become a martyr for open access,\r\nand Sam Altman, who would later become the second president of YC.\r\nI don't think it was entirely luck that the first batch was so good.\r\nYou had to be pretty bold to sign up for a weird thing like the\r\nSummer Founders Program instead of a summer job at a legit place\r\nlike Microsoft or Goldman Sachs.The deal for startups was based on a combination of the deal we did\r\nwith Julian ($10k for 10%) and what Robert said MIT grad students\r\ngot for the summer ($6k). We invested $6k per founder, which in the\r\ntypical two-founder case was $12k, in return for 6%. That had to\r\nbe fair, because it was twice as good as the deal we ourselves had\r\ntaken. Plus that first summer, which was really hot, Jessica brought\r\nthe founders free air conditioners.\r\n[16]Fairly quickly I realized that we had stumbled upon the way to scale\r\nstartup funding. Funding startups in batches was more convenient\r\nfor us, because it meant we could do things for a lot of startups\r\nat once, but being part of a batch was better for the startups too.\r\nIt solved one of the biggest problems faced by founders: the\r\nisolation. Now you not only had colleagues, but colleagues who\r\nunderstood the problems you were facing and could tell you how they\r\nwere solving them.As YC grew, we started to notice other advantages of scale. The\r\nalumni became a tight community, dedicated to helping one another,\r\nand especially the current batch, whose shoes they remembered being\r\nin. We also noticed that the startups were becoming one another's\r\ncustomers. We used to refer jokingly to the \"YC GDP,\" but as YC\r\ngrows this becomes less and less of a joke. Now lots of startups\r\nget their initial set of customers almost entirely from among their\r\nbatchmates.I had not originally intended YC to be a full-time job. I was going\r\nto do three things: hack, write essays, and work on YC. As YC grew,\r\nand I grew more excited about it, it started to take up a lot more\r\nthan a third of my attention. But for the first few years I was\r\nstill able to work on other things.In the summer of 2006, Robert and I started working on a new version\r\nof Arc. This one was reasonably fast, because it was compiled into\r\nScheme. To test this new Arc, I wrote Hacker News in it. It was\r\noriginally meant to be a news aggregator for startup founders and\r\nwas called Startup News, but after a few months I got tired of\r\nreading about nothing but startups. Plus it wasn't startup founders\r\nwe wanted to reach. It was future startup founders. So I changed\r\nthe name to Hacker News and the topic to whatever engaged one's\r\nintellectual curiosity.HN was no doubt good for YC, but it was also by far the biggest\r\nsource of stress for me. If all I'd had to do was select and help\r\nfounders, life would have been so easy. And that implies that HN\r\nwas a mistake. Surely the biggest source of stress in one's work\r\nshould at least be something close to the core of the work. Whereas\r\nI was like someone who was in pain while running a marathon not\r\nfrom the exertion of running, but because I had a blister from an\r\nill-fitting shoe. When I was dealing with some urgent problem during\r\nYC, there was about a 60% chance it had to do with HN, and a 40%\r\nchance it had do with everything else combined.\r\n[17]As well as HN, I wrote all of YC's internal software in Arc. But\r\nwhile I continued to work a good deal in Arc, I gradually stopped\r\nworking on Arc, partly because I didn't have time to, and partly\r\nbecause it was a lot less attractive to mess around with the language\r\nnow that we had all this infrastructure depending on it. So now my\r\nthree projects were reduced to two: writing essays and working on\r\nYC.YC was different from other kinds of work I've done. Instead of\r\ndeciding for myself what to work on, the problems came to me. Every\r\n6 months there was a new batch of startups, and their problems,\r\nwhatever they were, became our problems. It was very engaging work,\r\nbecause their problems were quite varied, and the good founders\r\nwere very effective. If you were trying to learn the most you could\r\nabout startups in the shortest possible time, you couldn't have\r\npicked a better way to do it.There were parts of the job I didn't like. Disputes between cofounders,\r\nfiguring out when people were lying to us, fighting with people who\r\nmaltreated the startups, and so on. But I worked hard even at the\r\nparts I didn't like. I was haunted by something Kevin Hale once\r\nsaid about companies: \"No one works harder than the boss.\" He meant\r\nit both descriptively and prescriptively, and it was the second\r\npart that scared me. I wanted YC to be good, so if how hard I worked\r\nset the upper bound on how hard everyone else worked, I'd better\r\nwork very hard.One day in 2010, when he was visiting California for interviews,\r\nRobert Morris did something astonishing: he offered me unsolicited\r\nadvice. I can only remember him doing that once before. One day at\r\nViaweb, when I was bent over double from a kidney stone, he suggested\r\nthat it would be a good idea for him to take me to the hospital.\r\nThat was what it took for Rtm to offer unsolicited advice. So I\r\nremember his exact words very clearly. \"You know,\" he said, \"you\r\nshould make sure Y Combinator isn't the last cool thing you do.\"At the time I didn't understand what he meant, but gradually it\r\ndawned on me that he was saying I should quit. This seemed strange\r\nadvice, because YC was doing great. But if there was one thing rarer\r\nthan Rtm offering advice, it was Rtm being wrong. So this set me\r\nthinking. It was true that on my current trajectory, YC would be\r\nthe last thing I did, because it was only taking up more of my\r\nattention. It had already eaten Arc, and was in the process of\r\neating essays too. Either YC was my life's work or I'd have to leave\r\neventually. And it wasn't, so I would.In the summer of 2012 my mother had a stroke, and the cause turned\r\nout to be a blood clot caused by colon cancer. The stroke destroyed\r\nher balance, and she was put in a nursing home, but she really\r\nwanted to get out of it and back to her house, and my sister and I\r\nwere determined to help her do it. I used to fly up to Oregon to\r\nvisit her regularly, and I had a lot of time to think on those\r\nflights. On one of them I realized I was ready to hand YC over to\r\nsomeone else.I asked Jessica if she wanted to be president, but she didn't, so\r\nwe decided we'd try to recruit Sam Altman. We talked to Robert and\r\nTrevor and we agreed to make it a complete changing of the guard.\r\nUp till that point YC had been controlled by the original LLC we\r\nfour had started. But we wanted YC to last for a long time, and to\r\ndo that it couldn't be controlled by the founders. So if Sam said\r\nyes, we'd let him reorganize YC. Robert and I would retire, and\r\nJessica and Trevor would become ordinary partners.When we asked Sam if he wanted to be president of YC, initially he\r\nsaid no. He wanted to start a startup to make nuclear reactors.\r\nBut I kept at it, and in October 2013 he finally agreed. We decided\r\nhe'd take over starting with the winter 2014 batch. For the rest\r\nof 2013 I left running YC more and more to Sam, partly so he could\r\nlearn the job, and partly because I was focused on my mother, whose\r\ncancer had returned.She died on January 15, 2014. We knew this was coming, but it was\r\nstill hard when it did.I kept working on YC till March, to help get that batch of startups\r\nthrough Demo Day, then I checked out pretty completely. (I still\r\ntalk to alumni and to new startups working on things I'm interested\r\nin, but that only takes a few hours a week.)What should I do next? Rtm's advice hadn't included anything about\r\nthat. I wanted to do something completely different, so I decided\r\nI'd paint. I wanted to see how good I could get if I really focused\r\non it. So the day after I stopped working on YC, I started painting.\r\nI was rusty and it took a while to get back into shape, but it was\r\nat least completely engaging.\r\n[18]I spent most of the rest of 2014 painting. I'd never been able to\r\nwork so uninterruptedly before, and I got to be better than I had\r\nbeen. Not good enough, but better. Then in November, right in the\r\nmiddle of a painting, I ran out of steam. Up till that point I'd\r\nalways been curious to see how the painting I was working on would\r\nturn out, but suddenly finishing this one seemed like a chore. So\r\nI stopped working on it and cleaned my brushes and haven't painted\r\nsince. So far anyway.I realize that sounds rather wimpy. But attention is a zero sum\r\ngame. If you can choose what to work on, and you choose a project\r\nthat's not the best one (or at least a good one) for you, then it's\r\ngetting in the way of another project that is. And at 50 there was\r\nsome opportunity cost to screwing around.I started writing essays again, and wrote a bunch of new ones over\r\nthe next few months. I even wrote a couple that \r\nweren't about\r\nstartups. Then in March 2015 I started working on Lisp again.The distinctive thing about Lisp is that its core is a language\r\ndefined by writing an interpreter in itself. It wasn't originally\r\nintended as a programming language in the ordinary sense. It was\r\nmeant to be a formal model of computation, an alternative to the\r\nTuring machine. If you want to write an interpreter for a language\r\nin itself, what's the minimum set of predefined operators you need?\r\nThe Lisp that John McCarthy invented, or more accurately discovered,\r\nis an answer to that question.\r\n[19]McCarthy didn't realize this Lisp could even be used to program\r\ncomputers till his grad student Steve Russell suggested it. Russell\r\ntranslated McCarthy's interpreter into IBM 704 machine language,\r\nand from that point Lisp started also to be a programming language\r\nin the ordinary sense. But its origins as a model of computation\r\ngave it a power and elegance that other languages couldn't match.\r\nIt was this that attracted me in college, though I didn't understand\r\nwhy at the time.McCarthy's 1960 Lisp did nothing more than interpret Lisp expressions.\r\nIt was missing a lot of things you'd want in a programming language.\r\nSo these had to be added, and when they were, they weren't defined\r\nusing McCarthy's original axiomatic approach. That wouldn't have\r\nbeen feasible at the time. McCarthy tested his interpreter by\r\nhand-simulating the execution of programs. But it was already getting\r\nclose to the limit of interpreters you could test that way — indeed,\r\nthere was a bug in it that McCarthy had overlooked. To test a more\r\ncomplicated interpreter, you'd have had to run it, and computers\r\nthen weren't powerful enough.Now they are, though. Now you could continue using McCarthy's\r\naxiomatic approach till you'd defined a complete programming language.\r\nAnd as long as every change you made to McCarthy's Lisp was a\r\ndiscoveredness-preserving transformation, you could, in principle,\r\nend up with a complete language that had this quality. Harder to\r\ndo than to talk about, of course, but if it was possible in principle,\r\nwhy not try? So I decided to take a shot at it. It took 4 years,\r\nfrom March 26, 2015 to October 12, 2019. It was fortunate that I\r\nhad a precisely defined goal, or it would have been hard to keep\r\nat it for so long.I wrote this new Lisp, called Bel, \r\nin itself in Arc. That may sound\r\nlike a contradiction, but it's an indication of the sort of trickery\r\nI had to engage in to make this work. By means of an egregious\r\ncollection of hacks I managed to make something close enough to an\r\ninterpreter written in itself that could actually run. Not fast,\r\nbut fast enough to test.I had to ban myself from writing essays during most of this time,\r\nor I'd never have finished. In late 2015 I spent 3 months writing\r\nessays, and when I went back to working on Bel I could barely\r\nunderstand the code. Not so much because it was badly written as\r\nbecause the problem is so convoluted. When you're working on an\r\ninterpreter written in itself, it's hard to keep track of what's\r\nhappening at what level, and errors can be practically encrypted\r\nby the time you get them.So I said no more essays till Bel was done. But I told few people\r\nabout Bel while I was working on it. So for years it must have\r\nseemed that I was doing nothing, when in fact I was working harder\r\nthan I'd ever worked on anything. Occasionally after wrestling for\r\nhours with some gruesome bug I'd check Twitter or HN and see someone\r\nasking \"Does Paul Graham still code?\"Working on Bel was hard but satisfying. I worked on it so intensively\r\nthat at any given time I had a decent chunk of the code in my head\r\nand could write more there. I remember taking the boys to the\r\ncoast on a sunny day in 2015 and figuring out how to deal with some\r\nproblem involving continuations while I watched them play in the\r\ntide pools. It felt like I was doing life right. I remember that\r\nbecause I was slightly dismayed at how novel it felt. The good news\r\nis that I had more moments like this over the next few years.In the summer of 2016 we moved to England. We wanted our kids to\r\nsee what it was like living in another country, and since I was a\r\nBritish citizen by birth, that seemed the obvious choice. We only\r\nmeant to stay for a year, but we liked it so much that we still\r\nlive there. So most of Bel was written in England.In the fall of 2019, Bel was finally finished. Like McCarthy's\r\noriginal Lisp, it's a spec rather than an implementation, although\r\nlike McCarthy's Lisp it's a spec expressed as code.Now that I could write essays again, I wrote a bunch about topics\r\nI'd had stacked up. I kept writing essays through 2020, but I also\r\nstarted to think about other things I could work on. How should I\r\nchoose what to do? Well, how had I chosen what to work on in the\r\npast? I wrote an essay for myself to answer that question, and I\r\nwas surprised how long and messy the answer turned out to be. If\r\nthis surprised me, who'd lived it, then I thought perhaps it would\r\nbe interesting to other people, and encouraging to those with\r\nsimilarly messy lives. So I wrote a more detailed version for others\r\nto read, and this is the last sentence of it.\nNotes[1]\r\nMy experience skipped a step in the evolution of computers:\r\ntime-sharing machines with interactive OSes. I went straight from\r\nbatch processing to microcomputers, which made microcomputers seem\r\nall the more exciting.[2]\r\nItalian words for abstract concepts can nearly always be\r\npredicted from their English cognates (except for occasional traps\r\nlike polluzione). It's the everyday words that differ. So if you\r\nstring together a lot of abstract concepts with a few simple verbs,\r\nyou can make a little Italian go a long way.[3]\r\nI lived at Piazza San Felice 4, so my walk to the Accademia\r\nwent straight down the spine of old Florence: past the Pitti, across\r\nthe bridge, past Orsanmichele, between the Duomo and the Baptistery,\r\nand then up Via Ricasoli to Piazza San Marco. I saw Florence at\r\nstreet level in every possible condition, from empty dark winter\r\nevenings to sweltering summer days when the streets were packed with\r\ntourists.[4]\r\nYou can of course paint people like still lives if you want\r\nto, and they're willing. That sort of portrait is arguably the apex\r\nof still life painting, though the long sitting does tend to produce\r\npained expressions in the sitters.[5]\r\nInterleaf was one of many companies that had smart people and\r\nbuilt impressive technology, and yet got crushed by Moore's Law.\r\nIn the 1990s the exponential growth in the power of commodity (i.e.\r\nIntel) processors rolled up high-end, special-purpose hardware and\r\nsoftware companies like a bulldozer.[6]\r\nThe signature style seekers at RISD weren't specifically\r\nmercenary. In the art world, money and coolness are tightly coupled.\r\nAnything expensive comes to be seen as cool, and anything seen as\r\ncool will soon become equally expensive.[7]\r\nTechnically the apartment wasn't rent-controlled but\r\nrent-stabilized, but this is a refinement only New Yorkers would\r\nknow or care about. The point is that it was really cheap, less\r\nthan half market price.[8]\r\nMost software you can launch as soon as it's done. But when\r\nthe software is an online store builder and you're hosting the\r\nstores, if you don't have any users yet, that fact will be painfully\r\nobvious. So before we could launch publicly we had to launch\r\nprivately, in the sense of recruiting an initial set of users and\r\nmaking sure they had decent-looking stores.[9]\r\nWe'd had a code editor in Viaweb for users to define their\r\nown page styles. They didn't know it, but they were editing Lisp\r\nexpressions underneath. But this wasn't an app editor, because the\r\ncode ran when the merchants' sites were generated, not when shoppers\r\nvisited them.[10]\r\nThis was the first instance of what is now a familiar experience,\r\nand so was what happened next, when I read the comments and found\r\nthey were full of angry people. How could I claim that Lisp was\r\nbetter than other languages? Weren't they all Turing complete?\r\nPeople who see the responses to essays I write sometimes tell me\r\nhow sorry they feel for me, but I'm not exaggerating when I reply\r\nthat it has always been like this, since the very beginning. It\r\ncomes with the territory. An essay must tell readers things they\r\ndon't already know, and some \r\npeople dislike being told such things.[11]\r\nPeople put plenty of stuff on the internet in the 90s of\r\ncourse, but putting something online is not the same as publishing\r\nit online. Publishing online means you treat the online version as\r\nthe (or at least a) primary version.[12]\r\nThere is a general lesson here that our experience with Y\r\nCombinator also teaches: Customs continue to constrain you long\r\nafter the restrictions that caused them have disappeared. Customary\r\nVC practice had once, like the customs about publishing essays,\r\nbeen based on real constraints. Startups had once been much more\r\nexpensive to start, and proportionally rare. Now they could be cheap\r\nand common, but the VCs' customs still reflected the old world,\r\njust as customs about writing essays still reflected the constraints\r\nof the print era.Which in turn implies that people who are independent-minded (i.e.\r\nless influenced by custom) will have an advantage in fields affected\r\nby rapid change (where customs are more likely to be obsolete).Here's an interesting point, though: you can't always predict which\r\nfields will be affected by rapid change. Obviously software and\r\nventure capital will be, but who would have predicted that essay\r\nwriting would be?[13]\r\nY Combinator was not the original name. At first we were\r\ncalled Cambridge Seed. But we didn't want a regional name, in case\r\nsomeone copied us in Silicon Valley, so we renamed ourselves after\r\none of the coolest tricks in the lambda calculus, the Y combinator.I picked orange as our color partly because it's the warmest, and\r\npartly because no VC used it. In 2005 all the VCs used staid colors\r\nlike maroon, navy blue, and forest green, because they were trying\r\nto appeal to LPs, not founders. The YC logo itself is an inside\r\njoke: the Viaweb logo had been a white V on a red circle, so I made\r\nthe YC logo a white Y on an orange square.[14]\r\nYC did become a fund for a couple years starting in 2009,\r\nbecause it was getting so big I could no longer afford to fund it\r\npersonally. But after Heroku got bought we had enough money to go\r\nback to being self-funded.[15]\r\nI've never liked the term \"deal flow,\" because it implies\r\nthat the number of new startups at any given time is fixed. This\r\nis not only false, but it's the purpose of YC to falsify it, by\r\ncausing startups to be founded that would not otherwise have existed.[16]\r\nShe reports that they were all different shapes and sizes,\r\nbecause there was a run on air conditioners and she had to get\r\nwhatever she could, but that they were all heavier than she could\r\ncarry now.[17]\r\nAnother problem with HN was a bizarre edge case that occurs\r\nwhen you both write essays and run a forum. When you run a forum,\r\nyou're assumed to see if not every conversation, at least every\r\nconversation involving you. And when you write essays, people post\r\nhighly imaginative misinterpretations of them on forums. Individually\r\nthese two phenomena are tedious but bearable, but the combination\r\nis disastrous. You actually have to respond to the misinterpretations,\r\nbecause the assumption that you're present in the conversation means\r\nthat not responding to any sufficiently upvoted misinterpretation\r\nreads as a tacit admission that it's correct. But that in turn\r\nencourages more; anyone who wants to pick a fight with you senses\r\nthat now is their chance.[18]\r\nThe worst thing about leaving YC was not working with Jessica\r\nanymore. We'd been working on YC almost the whole time we'd known\r\neach other, and we'd neither tried nor wanted to separate it from\r\nour personal lives, so leaving was like pulling up a deeply rooted\r\ntree.[19]\r\nOne way to get more precise about the concept of invented vs\r\ndiscovered is to talk about space aliens. Any sufficiently advanced\r\nalien civilization would certainly know about the Pythagorean\r\ntheorem, for example. I believe, though with less certainty, that\r\nthey would also know about the Lisp in McCarthy's 1960 paper.But if so there's no reason to suppose that this is the limit of\r\nthe language that might be known to them. Presumably aliens need\r\nnumbers and errors and I/O too. So it seems likely there exists at\r\nleast one path out of McCarthy's Lisp along which discoveredness\r\nis preserved.Thanks to Trevor Blackwell, John Collison, Patrick Collison, Daniel\r\nGackle, Ralph Hazell, Jessica Livingston, Robert Morris, and Harj\r\nTaggar for reading drafts of this." }, { "path": "data/Transcripts/MFMPod/mfm_pod_alex.txt", "content": "Alex Hormozi (0:00:00-0:00:40): Like, everybody here, we can all consume whatever we want so we can fly on whatever planes we want. Like, you know, you can fly private. You can stay in the nicest hotels, get the nicest airbnb's, go out to dinner every single other week at the five star restaurant at the Michelin Star, and you can do that for the rest of your life, but I can't buy that skyscraper right there, and I can't buy this huge company. And so what happens is, like, the things that you want to buy change, and so you create a new deficit for the amount of wealth that you want. Again, this is just assuming you like the game. And so, like, I like the game, so I just want to keep playing it. I feel like I could rule the world. I know I could be what I want to. I put my all in. It like, days off on the road. \n\nShaan Puri (0:00:41-0:01:02): Where should we start? Because you do a lot of these interviews. What's the fun version of this for you? Because I feel like if somebody actually wants to know an answer to something, it's been published. You got a book, you got a Twitter, you got 1000 YouTube videos. If you're motivated, you can go find the answer. Like, I tweeted out Alex coming on the pot. Say, what would you like to know? They're like, I'd like to know his thoughts on offers. \n\nAlex Hormozi (0:01:02-0:01:03): Making a sure offer. \n\nShaan Puri (0:01:03-0:01:21): Yes, literally his book. And I think the book is, like, free or $0.99. So that's just a lazy question at this point. But I know whenever I do interviews, there's some version of the conversations that are more fun, or I'm like, yeah, when we talk about that stuff, it's more interesting to me, and that kind of lights me up in a different way. What is that for you? \n\nAlex Hormozi (0:01:21-0:02:26): Well, I'll say there's two things that I've been probably focused a lot on. One is obviously acquisition.com. And so, like, what we're doing and kind of clarifying the mission between, well, all the stuff that we're actually doing every day. And then the other side of it is just that the leads book is coming out good. And so it's tough because I'm sure you guys have had stuff that you've worked on and it's like, been on its way coming out, and all of your energy is going into writing it or building it or recording stuff about it. And then you can't talk about it because I don't want to talk about it all the time until it's, like, ready to go off. And so the six weeks beforehand is when it's like, we have all this prerecorded stuff. I've got full courses, I've got all this shit that's going to drop when the next book comes out. But I haven't talked about anything leads related for, like, two years because I've known because I've been working on it for two years. For the next launch. So those are the two things that are, like, top of mind for me, like what we're doing on the Mosymedia side and acquisition.com and then the lead stuff. \n\nShaan Puri (0:02:26-0:02:49): What's the split between those two? So you got media, you got acquisitions.com. Give me the time split. So on a given month, what percent? If there's a pie chart, what are you spending on the content versus acquisitions? And then also on the money side, like, are you making more off the media or are you making more off acquisitions? What's the relative difference between the two? \n\nAlex Hormozi (0:02:49-0:03:36): Yeah, we lose money on media, so no, we don't make money, I think between AdSense. And if you consider book sales a part of that. But I give the book away for 99 sites. Actually, Amazon updated it because we re uploaded it with some fixits, and they wouldn't let us go below 190, which now makes all the times I said $0.99. Like, people be like, he's trying to get us. It sucks anyways. But no, I think the book does about a million bucks a year in profit in terms of what it makes. And then AdSense is probably like 500 grand a year. So it's like one and a half million. And that barely covers the media team. How big is the team right now? We've got ten, and then we've got vendors. \n\nSam Parr (0:03:36-0:03:38): Are you enjoying it? \n\nAlex Hormozi (0:03:38-0:04:00): Yeah, I dig it. It's fun right now. I report once to answer your question, Sean, about time split. We do one recording day every 14 days. That's like the direct to camera stuff. And then if I do a podcast, like, I got one of my guys here, Trevor, who's reporting our side of it so that they can clip this stuff later. Are you any adults plus one dedicated day twice a month? \n\nSam Parr (0:04:00-0:04:05): Are you enjoying the celebrity that comes with this, getting noticed and things like that? \n\nAlex Hormozi (0:04:06-0:04:33): Enjoys, probably. I feel like there's some people who love attention, and there's some people who hate attention. I'm like, right in the middle, you know what I mean? I was purposely, deliberately not public because I wanted to be rich and anonymous. And that was kind of like the mission for a long time for me. And then now that we are on there, I would say that there are pros and there are cons of increasing fame or what do you want to call it? Recognition. I think the pros outweigh the cons, but there are cons. \n\nSam Parr (0:04:33-0:04:34): Like what? \n\nAlex Hormozi (0:04:34-0:05:08): You get weirdos, you know what I mean? We have security, you know what I mean? I can't attend any event. I can't attend an event. I can't go to somebody's small, group, meet up. It's very hard because I can't enjoy anything because I'll have a line of people or asking for advice or signatures or pictures or whatever. And again, I am grateful this shit to everybody to do that. It's a different experience. So if I'm going to go to something, I go into it knowing that's what my experience is going to be, not whatever or whoever's on stage. \n\nShaan Puri (0:05:09-0:05:14): Yeah, it makes the online experience dope, but it makes the real life experience less different. \n\nAlex Hormozi (0:05:14-0:06:35): It's different. That's what he fundamentally just changes what the in person experience is. If I walk out. What's interesting is that I was able to, or have been able to mark how social media and the audience has grown by the number of real world interventions I had pre unit of time. And so I remember the first time I got recognized in public, and then it was once a month and it was once a week, and then it was once a day, and then it was every time I'd walk outside the door. And now it's about five times or six times. Every time I walk outside, I get recognized. And so I just imagine that that just continues to compound with time and with distribution. So it's different. But here's the pros. We get the best talent for our portfolio companies and for acquisition.com because so many people want to come here. We get them for at market rate or below because of all the learnings that they want. And the other people who are also pro players on the team, we get the best deal flow that's all proprietary. Companies that want to work specifically with us, they're not trying to exit to anyone or sell to anyone. They want to work with us deliberately to scale the company. So I continue to do it because I'm more rewarded for doing it than I am punished for doing it. But there are definitely you get weird letters and you get weird attacks and things like that. It comes with the territory and it's to be expected. And so for us, the pros outweigh the cons, but there are cons. \n\nSam Parr (0:06:35-0:07:41): I remember talking to Tim Ferriss and you could just tell from the outside, but I don't know if he's mainstream famous or not, or if I'm in a bubble, but he's popular enough that he has all these people listening to him and all that stuff. But the cool thing about him was he had high profile people and people who like, a lot of people who listen to you, you're like, I'm thankful that you listen, but I don't exactly want to go hang out with you. But he would actually have a ton of listeners who would reach out to him who are like the Matthew McConaugheys of the world or some football coach or Ryan Holiday has that too, where it's like someone who's like a big deal, who you're like, oh, my God, you listened to me. That's amazing. I would be honored to go and hang out with you. And he had stories like that, and Sean and I have had that a little bit where some business person who we both admire will be like, yeah, I heard your pot on this thing. And I'm like, oh, wow, you listened to that? Has that have you crossed that threshold where you have people who you admire who are messaging you and being like, man, what you said was really cool. I have a question about X, Y, and Z. And you're like, oh, man, that's amazing. My heroes want to talk to me now? \n\nAlex Hormozi (0:07:42-0:08:34): Yeah. I mean, yes. I don't want to put anyone on blast, but there have been some mega, mega influencers who followed me and hit me, and they were like, Dude, this is awesome. And I'm like, well, now I think less of you because you follow my content. So big red flag there. I told Leila the biggest red flag I had with her was that she was into it. No, I'm kidding. But, yeah, like, some NFL players that I used to really look up to, like, huge lob stars and huge, huge podcasters that followed me. And, yeah, it's been cool. One of the reverse situations is when I go to see, I'm like, oh, yeah, how is so and so celebrity? And I click and it says, like, Follow back. And I'm like, oh, shit. But no, I mean, it's surreal. I'm sure you guys have had it's surreal. \n\nSam Parr (0:08:34-0:08:59): Well, I grew up, like, admiring Lance Armstrong. I'm big into endurance sports. And one time I got an email and it was like, hey, just to let you know, I love the Hustle. And he signed it with Lance. And you could tell it was Lance Armstrong by his Gmail. And I was like, I don't believe this is really Lance Armstrong. If it is, here's my phone number. Call me right now. And he called me within, like, three minutes, and I was like he called. \n\nAlex Hormozi (0:08:59-0:09:00): He goes, Sam, what's going on? \n\nSam Parr (0:09:00-0:09:46): And I was like, Lance, is this really youthful? And then I had a couple of other athletes holler at us. And I remember thinking, like, growing up playing sports, I would have killed to have athlete like this recognize me. And I could never achieve the athletic greatness enough for them to acknowledge my talents. And then now you just take this total outside path and you get to it. Or like, one time we had like, this was really weird, but the lead singer of Lincoln Park, Mike, he tweeted out that he likes our pod and the Hustle, whatever, and I was like, oh, that'sick I would have wanted to have met you, but there's no way I could have gone down this normal path. But if we went this weird way, we finally kind of met. And I found that to be very strange and awesome. \n\nShaan Puri (0:09:46-0:09:58): Yeah, it's sort of that be so good they can't ignore you as a general advice for life. Whatever you want is on the other side of you being so good that you can't be ignored at anything. \n\nAlex Hormozi (0:09:59-0:10:00): At anything. \n\nShaan Puri (0:10:00-0:10:39): And also, I think that's kind of what you're saying, Sam, it doesn't have to be the thing you expect, right? Like, oh, you want to meet Warren Buffett someday. You don't have to be a stock picker. That's probably actually the least likely way that Warren Buffett is going to want to know you. And in general, you shouldn't really pick based on what they want. You should just pick based on the thing you can actually get so good at that you can't be ignored. And it's hard to do. Obviously, that's hard to do, but it's more of the right guidance than many other bits of advice you could take as far as, like, a North Star for what you're going to go for, right? \n\nAlex Hormozi (0:10:39-0:10:40): Exactly. \n\nSam Parr (0:10:40-0:11:07): And so anyway, it's cool that we're all kind of like seeing that in reality come true. Are you enjoying acquisitions.com? Because I know when we first talked to you, I think you are maybe only a year or two years in. You're relatively new. I think you had just sold Jim Launch. Are you happy with is it what you thought it was going to be? And do you actually like doing it? And by the way, explain what acquisitions what that is? \n\nAlex Hormozi (0:11:07-0:12:25): Yeah, so it's acquisition.com. The reason I emphasize that is because there's somebody who bought acquisitions, plural.com, and it's just not me. It's a different company. But acquisition.com is our portfolio of companies. So I'll give the TLDR in 92nd. So I had a chain of GMs, took that, licensed the IP to 5000 locations, started a supplement company, sell through that distribution base, and then started a software company. We exited all three of those companies in 2021. We taken about 40 million in distributions prior to the exit, and we sold for 46.2 million. And the software company I did separately or sold separately in a strategic deal that was all stock. And I said that because you guys probably laugh, because people are like, I Googled Altrumo's net worth, and it says 15 million. It's like, well, I sold the company for 46 and all cash. So, like, I don't know where you got that. And the only reason you do that and get that money is because it was making money. Anyways, that was pretty much 2021. So we closed December 25 or 6th, I can't remember. It was it was one of those days. It was right around Christmas 24th, christmas Eve. That's towards Christmas Eve we is we closed. And then we started acquisition the next day. And so that was when we, like, we made our kind of declaration. At that point, though, I'd already made three minority investments that had done really, really well, and that's why I wanted to make that kind of my next big thing. \n\nShaan Puri (0:12:25-0:12:45): If you started it the next day, that means you kind of had this idea cooking. So what was the genesis? What made you realize, oh, this is what I should do next. I should buy these minority stakes in companies like the one that I just built, and I should get this domain name, which I assume you had to buy. So how were you so ready to do that? What was the thought process? \n\nAlex Hormozi (0:12:45-0:15:17): So during COVID obviously, gyms were affected by COVID. We took a hit. We took a major hit. We were so profitable. But it was a big it was hard. And so to kind of get some space because there wasn't a lot, like, I couldn't do more. Obviously, we pushed things harder, but I was above the business enough that there was nothing I wasn't going to do anything right? And so I kind of just needed to take my mind off things. And so, by happenstance, a guy who owned a photography a single photography studio made his movie on my calendar. And this is not how you do this. Everyone like, do not do this. But I was actually still taking some calls for Alan because I wanted to do some testing. And this was before I had a big brand. So I was just kind of like, founder, talking to customers to get an idea of what was going on. But he knew me enough from just like I had written a small book in the gym space called Gym Launch Secrets that he had read that book, loved it, applied it to his photography business, and he took a sales call through my software company because he knew I was taking the calls. And so he hopped on and was like, I have no interest in your software. He's like, but can you please give you 20 minutes? And I was like, sure, man. All right. And I just liked his vibe. And so anyways, we ended up doing a deal. And so we took a minority percentage of the business. And that business, I think, had done they were doing 1.6 million a year at a single location, which was pretty awesome for a tiny, like, photography studio. And I think he had taken and this isn't all the book, clearly, because there's a million things, but he had taken some of the concepts from Jimmy Shaker's book, applied them, and it had grown the business a lot. And he had an agency for photographers to kind of, like, do the same model for them, right? And so we were having a conversation, and he was like, yeah, I did exactly what you said. And all the photographer studios add 400,000 a year to top line when they use our thing. I was like, they add 400,000 a year? He's like, yeah, on average. And I was like, okay, how much are we selling this thing for? And he's like, pennies. And I was like, okay, so let's not do that and let's own them all. And this is where the trust factor of what the inbound deal flow, which is what I love about acquisition.com, is that we have a lot of trust. And so he actually shut down a business that was making him, I think, 500,000 a year in profit that agency side and shut it down to zero because he believed that he believed me enough to go all in on this other direction of private ownership of all the locations. \n\nSam Parr (0:15:17-0:16:03): Do you ever wake up in the morning and dread the day or struggle with feelings of discontent? We all have. That's why I'm excited to share with you a new podcast called Practical Stoicism. Every Saturday morning, host Tanner Campbell examines the ancient texts of stoicism and delivers practical takeaways that you can use to find a more fulfilling life. Stoicism has been practiced by kings, presidents, entrepreneurs, and more. But don't be intimidated. You can benefit and learn from the principles of stoicism, just like George Washington and Adam Smith did. We highly recommend checking out Tanner's episodes with Centara Gonzalez about wisdom unlocked a stoicism based program that helps inmates transition to a stable life outside of jail. So if you're interested, you can check out Practical Stoicism on Apple, Spotify, or wherever else you get your podcasts. \n\nAlex Hormozi (0:16:03-0:16:18): And so as of today and that was 2020 as of today, we have 36 locations in that business, just 30 plus million a year, and it continues to grow by one or two locations every month. \n\nSam Parr (0:16:18-0:16:20): What's that business do? \n\nAlex Hormozi (0:16:20-0:16:23): Enchanted fairies. So it's children's photography, right? \n\nSam Parr (0:16:23-0:16:24): Dude, that's insane. \n\nShaan Puri (0:16:26-0:16:30): When we last had you on, I saw I went to the website, and I was like, okay, cool. What are the acquisitions? \n\nAlex Hormozi (0:16:30-0:16:31): Great. \n\nShaan Puri (0:16:31-0:16:35): What did they acquire? And I saw basically like, enchanted fairies. \n\nAlex Hormozi (0:16:35-0:16:36): And I was like, okay, cool. \n\nShaan Puri (0:16:36-0:16:58): They're doing, like, the gym launch playbook on this other space. That makes a lot of sense. And if I go there today, they're still those same companies. So how come you're not putting new acquisitions up there? I assume you've made a bunch of acquisitions, like, in the last 24 months or whatever. Why not put new companies up there? You're pretty open about other stuff, but in this case, you're not putting them up there. And then also let's start with that. \n\nAlex Hormozi (0:16:59-0:18:37): Yeah. Main reason. So there's two big reasons why we're not public about the acquisitions. Number one is that my brand has grown to such a degree that if I say, hey, this business is awesome, and it has a national ability, chain of ferries is less of an unless you're in one of those 30 markets. And also, my audience isn't like moms with kids. So it's arm's length enough that it doesn't affect the business. But as you can imagine, a lot of the businesses come to me are business services, and they're national, they're international, whatever companies. And so, like me endorsing a company would 510 X the company overnight. And so that comes with a couple of things. One is that I haven't negotiated those deals with a brand endorsement included. If I include a brand endorsement, then I own majority. I'm not going to risk my face on something I can't control. And so these are most of the most of the investments we have are minority. We do have a majority investment as well. But that was one that came in as a minority and then I just bought more because I love the business and it was up our wheelhouse. The second thing is that if we were to exit those businesses and I had done an endorsement in a minority position, then guess who has to go with the deal? Me. Right. As an acquirer, if there's some massive influencer that's associated with the brand, he's not getting out in a deal. And so our whole goal is to build value in the business so that the business is sellable and more valuable. And we use my face to bring deals in. And so that's why I've been really tight lipped about the businesses. \n\nSam Parr (0:18:38-0:18:40): How many deals have you done so far? \n\nAlex Hormozi (0:18:40-0:18:48): Right now we have eleven portfolio companies. Is it all your own money or you raised a fund? No, it's all private. It's all mine. Damn, dude. \n\nSam Parr (0:18:48-0:18:56): So you're going all in on this. And so I asked you originally, are you happy with how this is working out? Is it what you thought it was? \n\nShaan Puri (0:18:56-0:18:56): What's he going to say? \n\nAlex Hormozi (0:18:56-0:18:57): No. \n\nSam Parr (0:18:58-0:19:06): Yeah, I could be like, well he's like, well, I didn't realize this is actually just mostly a due diligence game and I don't know if I'd love that. \n\nShaan Puri (0:19:06-0:19:11): What's the worst part about it? What's something you didn't kind of what's the downside you didn't fully respect up front? \n\nAlex Hormozi (0:19:11-0:19:51): So I think there's like knowing something and then experiencing it are two kind of separate things. And so like, I know that in a minority position we have to use soft influence to try and move things forward. I know that. But I would say the most difficult part is half listened to advice. And so I'll give you an example. So if I say, hey, we think that this operator in your business blows and we need a new operator, person says, okay, and then we find them a new operator, and then they hire the new operator, but then they don't fire the old operator. Like what the fuck? \n\nShaan Puri (0:19:51-0:19:52): Right? \n\nAlex Hormozi (0:19:52-0:20:58): Very hard to win at that point. Right? So it's kind of like listening to half of someone's diet advice. It's like, yeah, I'm doing the cheat days, rushing the cheat days. It's like, yeah, but there's other days that you're in a deficit. Yeah, but you said cheat days raise your metabolism. Yeah, but you also need a deficit, you know what I mean? And so it's listening and completeness. And so I don't know, we may move to because the business that I would say transparently that I enjoy the most is the one that we have complete control. And so we bought majority of that business and we were growing that one like gangbusters. And the speed to action is so much faster. That being said, I would say the biggest wins we have been able Company that came to us at 16 million the year before did 50 last year. 20 million in EBITDA. That's the biggest company that we have. The portfolio we've had the enchanted various is obviously one that two ish with combining the two things. They're pacing two and a half million a month right now or 2.7, something like that. So we have a pretty ridiculous deal, right? \n\nShaan Puri (0:20:58-0:21:28): Like, I had a friend message me that was like, dude, Harmosi's playbook is obviously amazing, but he's like, this deal that they offered us. He's like, I don't know who would take this. And I don't know if this is actually the deal or not, but he's like, basically, it was like, no money. We'll give you no money, but we get ownership if we grow it above X. So it's kind of like, I think sounded like more of a risk free strategy in a way. But is there a standard deal structure? \n\nSam Parr (0:21:28-0:21:29): And is that it? \n\nShaan Puri (0:21:29-0:21:38): Where you're not putting capital in, you're basically saying, give us the equity. We guarantee we grow by this much. And if we don't, some claw back. \n\nAlex Hormozi (0:21:38-0:21:44): We've iterated it honestly a bunch of times. This is to answer your question, Sam, like, probably even more poignantly now that. \n\nSam Parr (0:21:44-0:21:44): We'Re getting into it. \n\nAlex Hormozi (0:21:45-0:24:55): One of the hardest things about the investment cycle is that when you're making a product or you're trying to sell a service, you can ideate it, create an MVP pitch. It see how it goes within like, 60 days. The whole thing. Souped to nuts. You can do that whole cycle. 60 days for deals. It's like you can think of an idea for a deal structure. It takes 90 days to six months to close the deal, and then it might take a year to see even just, like, some preliminaries of, like, how do we like this structure? How does it work, et cetera. And so I still feel like we are most in our infancy in the deal structures that we have. So, like, in terms of no money in, there are deals we put money in. There are deals that we don't put money in. It depends on the deal. The big one for money is. It depends on what the need of the business is. So, like, if we're opening up a lot of Brick and Mortar locations like we're about To, I Think We might have Actually closed today or tomorrow on a 28 location Chain. That one requires capital to open more locations. So that one I'm like. I know where the capital is going. I see what their turns on capital are. Let's get that right. If it's a national based service business. So let's say it's mortgage sales. There's no capex. They just need recruiting. They need the guys. That's how sales gets increased. And so that's the money. Where's The Money going and what is it used for? What I don't want to do is just like, someone got to go buys a mansion after I write a check. That's not the goal here. The goal is that we're both together wanting to grow this massive thing. And so it just really depends on what the nature of the deal is. So that's number one in terms of how we structure them. Originally, I had a grand slam offer type thing. Now it's just much more straightforward of, like, we're equity holders in the business. It's interesting because it's actually gotten less cute and less clever as time has gone on. It's just much more like, this is our deal. We own a big chunk of the business, and we're going to grow it. And, I mean, the thing is that for us, based on my holdco costs, I put 500,000 a year in labor into the businesses. And that's if I wanted to not mark up labor, that's hard cost. And so if a company, for example, is doing, whatever, 5 million a year in EBITDA, and I'm buying a one third stake or a 40% stake in the business, what are my value? That and how much of that value is going to come in the form of just work that we're going to do? And so that's where the valuation and how much cash in, et cetera, kind of becomes more like per deal basis. But yeah. So the long story short is one is soft influence has been something that I've been learning. We may, in the future, just do more majority deals where the founder stays on, because what I want to do is show how much more we grew this. I mean, we do have, obviously, some minority ones that have crushed too, but I want to murder this maturity deal and be like, wouldn't you like to have 49% of something ten times bigger or 100 times bigger? And so that's kind of the angle. But yeah, we're learning every day. \n\nSam Parr (0:24:56-0:25:23): We talked to our good friend is Andrew Wilkinson. He's done a similarish thing as you. And then we've had a handful of other friends that have done something, and they're like, well, I got really inspired when I read the Swarm Buffett book, and that taught me a little bit about compounding growth. And other people have cited other books or things that they learned where they're like, oh, no, this is the way to go. And that's why I got into this. What about you? What transitioned you from going to this almost PE model versus just one brand model? \n\nAlex Hormozi (0:25:24-0:30:19): Yeah, definitely. If I were to give us a name, it would be like a merger of a family office and a conglomerate, because family office, in that it's literally just family money. Like, I don't I don't have any outside investors. And then conglomerate in terms of, like, our business model, like, I'm not trying to exit anything. I would. Like to continue to compound the investments we have. If a founder absolutely needs to or wants to, or gets divorced and has to create the asset, then we will go down that route. But long term, we're long term holders. But in terms of the inspiration, it was actually because Gym Launch has there's only 50,000 micro gyms, like in the US. At least. And we had already gotten on the phone with 20,000. So, like, if you're a microgemonar, know who we are, probably. And I realized I went to this, this little meetup of entrepreneurs and it was like six or seven people and the whole room was doing in aggregate, like 500 million a year in revenue. And I think we were doing like mid thirty s at the time. And I was really excited to go because I was like, what do these guys have that I don't have? What am I missing? Right? And we had been there for like three years, we'd been in mid 30s for three years. And I felt like I was like something was wrong. And the big takeaway I had was not that they had better systems or they're better at marketing or better at sales or better at product. They just were going after a bit of market. Like every single one of them to a man had a market that was ten to 100 times the size of. And so I said that whatever I wanted to do next was going to be was going to go after a much bigger market and there are significantly more businesses than there are gyms. And so that was kind of the big thing is like, okay, well, it's something that can compound forever and that has a huge tam. And so we kind of walked backwards from there. And then in terms of the doing this model, we believe that people build the people and the people build the business. And so it was like 18 months of ideation. I know we're going full circle, but how did we start the next day? Well, these were the things that we were thinking through. And I said, Leila, if I were to die tomorrow, what business would you start? She was like, I would start a recruiting firm. I was like, I don't want to start a recruiting firm. I was like, is there a way that we could combine what you like and what I like into something cool? And so for us, the most hands on valuable thing that you can do for a business is find a players. Because if you find a players, you put them in the business, then they grow the business and then that value stays inside the enterprise of the business. Not holdco like not the goose but the egg, right? And so for us, we just recreate crazy talent because our competitive mode is that we have more influence than they do. And so we have a whole culture community of MOSY talent where our head of people continues to bring. We have tons of people every single day that are applying for portfolio positions, and then we can screen them, vet them, and then because we know the company and because we're long term incentivize, we don't just want to put a body in a seed. We want to find a killer that we know that if we only want to fill the role once, right, we want to fill it with somebody who matches the culture and matches the skill set of the business at this level. So a lot of times, like, first time entrepreneurs, they're at whatever, a million months, and they're like, okay, do I hire a bookkeeper? Do I hire a staff accountant? Do I hire a controller? Do I hire a CFO? Do I hire a director of finance? Who am I hiring right now, and what does that person look like? And so we've done this enough times to be like, okay, at this level, you probably need a controller who has experience going from a million a month to 3 million a month at that point. And we'll tell them upfront that we will bring a CFO who has transaction experience in the future. So they're not jostled when that happens, right? Same thing. They're scaling out the sales team. They're like, okay, well, I've got three good guys. It's like, cool, we need 20. So you can't just take your best closer and make him manager because he's never done this before. So we want somebody who's built at least one or two sales teams specific to, let's say it's inbound or might be outbound, depends on the sales process of the business. And they've built those types of teams and like, cool, we'll bring that guy in, we have our playbooks. Then we say, hey, on our interview process, we're like, this is how we do things during line with that. And if we do feel like there's alignment and they have the chops because we do skill tests, then we can say, hey, I think that you'll match. And obviously the founder still has final say because they have to like the person. The rise is going to work, but we do a lot of that heavy lifting because we might take 100 interviews at Holdco to find one guy for one specific role for one company, and that's where that labor cost comes in for us. But Willis Be put, like, the reason we took majority and it took majority, but majority of that business was we had built the entire executive team. We built the entire executive team, and we're like, okay, cool. And the fatter was like, you know what? I kind of want to do other things for the business. I know it's in good hands. I trust you guys. And so it was like, a very friendly deal. And now he just gets checks every month and likes his life a lot. And we just continue to run the business, which we're cool. \n\nSam Parr (0:30:19-0:31:07): There's this really cool video where you're with Grant Cardone and I think you were like in the process or pre process for selling Gym Launch and you were like and he said something like rich people sell their companies, wealthy people never sell. And cool is that I've sold a company before. Sean has sold some companies before you've sold a company. What's so funny is a lot of first time founders and second 3rd time, a lot of people, their whole business is selling, but after they sell, they go through this period and they're like, shit, I shouldn't sell ever again, actually. And you said you sold the business for 47 million. You said you had taken 40 million in distributions. So in my head I'm like, that's a pretty shit sale then. Do you wish that you would have just held onto it and never sold that company? \n\nAlex Hormozi (0:31:08-0:33:59): No. Because the person I was then wouldn't be able to do what I can do now. Could I do that today? Would I hold on to it? Yes. But I don't think I could have done it then. And so a lot of the reason transparently. If I had, I got more credibility from selling Gym Launch at 46 and it was valued at 150 before COVID So to your point, it was a shit sale. But I was done. I was emotionally done with the business. I just didn't want to do it anymore. I still own a third of the business. So like when they crush the exit, the next exit at $250,000,000, they'll get my 100 million dollar check from that. But I moved on. And my big thing is like, all my friends, all my close people were like, dude, you sound depressed as far. And I was like, dude, I want to do this new thing. And they're like, dude, you light up when you talk about this new thing. And so I actually walked away from the deal during the deal process and then came back. It's funny because people give me a lot of I'm glad you brought it up because a lot of people give me praise for that. But they don't have context. We done 30 million in EBITDA the 24 months prior to the deal. So selling a 46.2 is not like I told them I needed to be public about the number because I do know that the vast majority of people don't get it. And that is enough to give me credibility for fucking TikTok. But it's not like the transaction itself isn't necessarily one that I'm like, proud of. I'm proud of what we built and that the company's grown 40% since we sold it. They're going to kill on that deal. But now that I also understand how debt works, which I didn't understand that again, this is like knowing, experiencing. I understood that they were going to get debt below and I realized that 80 or 90% of the money that they put in, they then just immediately pulled right back out, leveraging the company's books. I was like, well, shit, I could have kept the whole fucking thing and gotten 90% of the money not personally guaranteed and derisked myself. But would that have created the same story of something that is sellable from a personal brand perspective? And I think the answer is no. And so I don't regret the sale. I think the sale was required for that step in my journey. I think that now, because we have the credibility, no one cared that I taking 40 million in distributions. No one gave a shit. They didn't matter. The day I sold, my neighbors were like, oh, I saw you on Forbes. Congratulations. I was like, I was richer before I did the transaction. I was wealthier before that point. But it allowed us to do acquisition.com because I don't think I could have because my brand was still so I was still the CEO, as far as people were concerned, of that company, and I needed to have that space so that I could create acquisition. \n\nSam Parr (0:33:59-0:34:02): Sean, what do you think? Would you have done that? \n\nShaan Puri (0:34:02-0:34:22): I think he explained it beautifully. I think he explained it exactly beautifully and honestly, which was that two things you just said that resonate deeply with me. One, this is the last thing you just said, which is, to have what you want, sometimes you just need to make space. And so this is like I learned this through relationships. You're dating somebody, they're not exactly what you want. \n\nAlex Hormozi (0:34:23-0:34:23): They're not bad. \n\nShaan Puri (0:34:23-0:34:34): There's nothing wrong. There's nothing terrible about it. So most people just stick with it for years and years and years, and then they're kind of like, well, if there was a much better option, then, yeah, I would feel more comfortable just. \n\nAlex Hormozi (0:34:34-0:34:36): Like, going being single. \n\nShaan Puri (0:34:36-0:35:23): But I've always been very quick to just if I know this isn't it, I'll break up. I don't need to have another great option ready or shown to me to make it real. I know that if I make space, then great things can appear. And sometimes you just got to do that. When we sold Bibo, it was the same thing. I had been doing this thing for six or seven years, and the business was doing okay at that point. But in my heart of hearts, I knew, this is never going to be massive. And we had all gone into that business with basically like, yo, let's do something massive. So by other people's standards, it might have been a good business. By our own mission, it was going to be a failure. I knew that. And so it was when I was out with a friend, and he was like, I don't get what you're doing. And he's like, you just need to shake things up. And I was shook. \n\nAlex Hormozi (0:35:23-0:35:24): I couldn't sleep. \n\nShaan Puri (0:35:24-0:35:52): I was like, he's right. Like, I've been doing this for too long. I need to shake things up. And so I went into our investor the next day, and I just said, I think it's time we change things up. I said, I need to change things up. I said, if you want to keep going, I will help you hire a CEO, and you can have somebody else take this over. I'll give you back my shares. I don't need a thing from this. I will do whatever I can. Or give me 30 days. I'm going to see if I can. \n\nSam Parr (0:35:52-0:35:55): Sell or I'm out. \n\nShaan Puri (0:35:55-0:37:15): Either way, in 30 days, this is going to change for me. I've just decided to make space, basically for something. He's like, well, what do you want to do next? And I was like, I have no idea. He's like, well, no, really? Usually people, when they come to me, it's because they already kind of lined up something else. I was like, no, honestly, I have no idea. I just know that I need to make some space. And so that part resonates with me. And also the idea of when I look back now and I'm like, oh, before I sold our company, if my company wasn't going to be the next big thing, I would just shut it down. Literally just turn it off, take a zero on it. And then I just started looking around, and I learned this word aqua hire in Silicon Valley. Oh, people just sell failing companies. And then I learned, like, the asset sale, it's like, oh, you could just sell the code and the assets. Like, Wait, who are these buyers? And I didn't even really understand what my options were. And so when you talk about basically, I could have refinanced, I could have just refinanced based on the business assets. Took 90% of the value. I felt that same stupidity later. But that's life. Life is basically looking back and being like, I was such an idiot. And that's how I mark years of time. Not by the calendar days, but by a number of times. I look back and say, god, I was so dumb. I didn't even understand this. I was sitting on something. I didn't really know what I should now, knowing what I know now, I know exactly what I should have done. And at that time, I wasn't even aware that I was making a mistake. \n\nSam Parr (0:37:15-0:37:40): Well, the difference is I think that us three actually have done. We are tacticians. So I understand how to grow shit. And I understand, like, you build this page, you do this thing, you write these words, here's the customer, you talk to them, whatever. I think the gap you have to bridge is becoming from tactics to strategy. And I used to make fun of all my buddies who are in finance. I'm like, Dude, you're just like an excel monkey. \n\nAlex Hormozi (0:37:40-0:37:41): You don't know anything. \n\nSam Parr (0:37:41-0:38:39): You're just this stupid fucking hedge fund and maybe it makes money, but you don't know shit. And then I realized when they talk about debt and stuff, I was like, I'm not going to pay attention to any of that because I think that's stupid. And then I realized how it starts working and I'm like, oh my God, that's strategy. So it's like, that's the strategy. And I was like, oh, I've got good vision. I understand how this shit works. And then I realized how money worked a little bit more with debt and borrowing other people's money to do this and taking money off the table and all these terms that I kind of heard about but I didn't exactly understand. I realized, shit, if I'm going to be really good at my job, I got to understand the tactics. You really also have to understand the strategy, which Alex, it seems like you're actually now you get the strategy of how money and business works, not just the tactics, which the whole 100 million dollar offer book, which I read. I think it's awesome. That's mostly tactical, but the strategic shit is what you're saying of like, oh, you can borrow other people's money and to do this. That's some big picture shit. \n\nAlex Hormozi (0:38:39-0:39:51): Yeah. Without a personal guarantee. Because I'll be like, why don't we debt on the business? Because I don't want to risk that. It's like you are not risking it like the business is risking in it. And if you're willing to do a sale for X, it's like, well are you willing to do because the business is going to take the risk on either way. I mean, depending on the acquirer. But if you're selling a private equity, I know you have a lot of a bigger tech audience, but I probably have a bigger, I would say everyday business audience. Guys who have massive roofing businesses or a huge chain of teeth whitening studios. Those types of businesses are the ones that tend to follow more of my stuff. And that's usually going to be a roll up or a private equity acquirer for the most part, right. Maybe a strategic if you have another big teeth whitening chain that wants to buy you. But that's about it. And I resonate with what you said, Sam. I always thought those guys, I was like, you don't even understand business. And I to a degree, I actually don't think they understand business, but they understand the macro level of business. And I think where you get really dangerous is when you know both, they both games because what they do is they do almost purely inorganic growth. They try and staple shit together. That okay. We bought four companies that do 3 million in EBITDA. And so now we have 12 million EBITDA and we're going to have some equity arbitrage and we're going to be able to sell this thing. \n\nShaan Puri (0:39:51-0:39:52): Financial engineering. \n\nAlex Hormozi (0:39:52-0:40:23): Yeah, saddle them up with debt and then it's just a math equation. Like, it doesn't even matter about growing the businesses, but it's like, what if do that? And you could also triple all the businesses. And it's like that's when you create these breathtaking home runs. And that's kind of what we're trying to do with acquisition. And I don't have a huge need for more money unless it's an enormous there's nothing I can do. Have you ever heard Felix Dennis's how to be rich? I think that's the name of the book. \n\nShaan Puri (0:40:24-0:40:32): We talk about that table a lot. Like the comfortably poor, comfortably rich. Then you get to, like, rich, rich, super resonated. \n\nAlex Hormozi (0:40:32-0:41:14): With me, it's like I'm the comfortably rich, not the super rich. Everybody here, we can all consume whatever we want, so we can fly on whatever planes we want. You can fly private. You can stay in the nicest hotels, get the nicest airbnbs, go out to dinner every single night of the week at the five star restaurant at the Michelin Star, and you can do that for the rest of your life. Your personal needs as a human being are satisfied, but I can't buy that skyscraper right there, and I can't buy this huge company. And so what happens is, like, the things that you want to buy change, and so you create a new deficit for the amount of wealth that you want. Again, this is just assuming you like the game. And so, like, I like the game, and so I just want to keep playing it. \n\nShaan Puri (0:41:15-0:42:12): The funny thing is that what you actually like is just playing the game. And if you just said, Well, I'm rich enough, then you'd have to stop playing the game you really love. And so instead, you start to come up with things you want that in actuality sound a little bit silly. It's like, actually, I don't even think you want that skyscraper or to buy that. I don't even think that's actually what motivates you. It's just that I'm actually peak loving the game right now. And the game only works if you care about the score. And so it is impossible to enjoy that. You can't play the game. If you've said, I've already scored the maximum number of points, then the game becomes kind of silly. And so it's funny, like, this is with all of our friends. It's like, well, why are you doing this? You kind of got enough money, man. And it's like, yeah, but I don't have enough enjoyment. The enjoyment game is infinite. And the thing I enjoy the most is playing this game. So I'm going to continue playing, but in order to do so, I have to construct these silly dreams that I'm not even sure I really care as much about as far as just playing the game. \n\nAlex Hormozi (0:42:12-0:46:39): Dude, that was huge. And as a side note, if you think there's kind of, like, I feel like two ways you can create a deficit, right? So one is like, you can create a financial deficit by saying, I want this thing. It costs a billion dollars, and so I need to go make a billion dollars. There's my deficit between where I am, where I want to go. The other side is what I was saying. When you ask, what are you excited it about? Because I know you said, what are the worst parts? But I'll tell you what's good right now is that we have finally separated MOSY Media, which is basically like my Layla's personal brand. And the content we put out, I would say the books kind of fall under that. Like the courses, the books, all the materials we give out to Mozimedia. And so what we originally were saying when we started acquisition.com is that the mission was to make real business knowledge accessible to everyone. That was the mission of the company. And that is still very much the mission of Mozimedia. What we realized is that holdco's team, so, like, our ex consultants are people who recruit talent, our heads of sales, who built out sales teams, our heads of marketing who built out marketing departments and marketing functions, our head of customer success, who builds out product in the client experience, et cetera. Those people didn't really resonate with making business education accessible to everyone. That wasn't actually what their mission was. And so we got really clear on what the mission of acquisition.com is, which is and this kind of came organically. So it's like, really exciting for me. But one of the things I've always envied about Elon is that every company he gets involved in basically saves the world. He finds a way to tie the mission of what he's doing to saving the world. Even Twitter, he was like, Free civilization needs free speech. And it's like, boom. I was like, man, how did he take a meme platform with tweets of arrogant dudes and turn it into free speech for civilization? That's where I think a lot of his genius is. And so for us, I was like, what's that thing? And so we have the external gap of like, yeah, I want to hit the billion or whatever, but I think the internal one is that we want to build a company off of praise and not punishment. And so we have this huge things. How we try to build things is like, you can punish people or you can praise them. And we believe that you get more performance out of praise. Now. You look at Goldman Sachs, you look at JP morgan, you look at McKinsey, you look at Bain, you look at these massive companies, even some of these huge ones, and a lot of people are like, man, it's a toxic work environment. It's really hard, blah, blah, blah. And so those are usually punishment driven cultures. What's happened is, by doing that, that has aligned all of our holdco team in terms of how we want to build these companies. And the billion dollar Alex mark is basically irrelevant because to really win by their standards, we need to build something that's ten or 50 or 100 billion, you know what I mean? And that might take the rest of my lifetime and it'll probably happen after I die. But if we can do that, then we can prove one thesis, which is like, people want to work, and most environments are set up to put people and all you do is you raise the bar of what it takes to not get punished. But what happens is people churn out of work, they burn out, they hate their jobs, they hate their lives. And I think that there's a better way. And Leila and I are going to try and dedicate the rest of our lives to trying to prove that. And so that is the mission of acquisition.com and what we do with the companies. And we can show that that it's not just like fluffy stuff. And I think if it were just Layla, it'd be a woman driven thing. People like, oh, it's a girl who's saying you should be nice to people. But I think I given how I look, how I talk, I can probably deliver that message and it may take the rest of my life to do it, but I haven't felt fucking amped about anything in a long time. The last time I was this pumped was when the mission of Gym launch was to take the gym industry from his knees to its feet. Because the average gym owner takes down $36,000 a year in personal income and has, like, maxed out credit cards and has like, 18 days of cash on hand. And I was like, I want to fix this. And what ended up happening is because I wasn't emotionally mature enough. I took enough licks from people really close to me, both clients and employees, that I just like I just needed to put distance. Like, I had 17 different people who worked for me try to start their version of my business, you know what I mean? I had clients try and start their because it was a business based on consulting. It was a consulting business. So once you had kind of the models, you could, in theory trying to be with us. Now no one has succeed. But it was enough that I was like, dude, you were bankrupt, on the brink of divorce and used all this stuff, and then you scaled to three locations and sold them, and now your family's financially set off and like, now you want to attack me. It happened times to your feet and then you kicked me. \n\nShaan Puri (0:46:40-0:46:41): This is how I get repaid for this. \n\nAlex Hormozi (0:46:42-0:47:12): That's how it felt. That's how it felt. And so I wasn't I think now I can handle it a lot better. But at the time, I felt so disenfranchised. I just felt hurt, honestly, because I really poured my soul into trying to fix the gym industry. And so when I felt that way, we created space, and then it just became an asset we owned, and that's why I was open to selling it. But I haven't felt like that until now. And maybe it took two or three years for me to refine what that big mission was, but that's something I can get behind. Like, that's something I'm fucking amped for. \n\nShaan Puri (0:47:12-0:47:50): It's so funny. You mentioned the Elon big mission thing. Like, this guy, he did it with Twitter too, which was really funny. And then while he was doing that deal, news came out. It's like oh, elon musk impregnates. Like this woman who worked for him, and he's like, overpopulation, underpopulation. We were at risk of population collapse. It's actually the biggest risk of all. And he's like, I'm just doing my part. And I was like, this guy. Teflon, don. How did he get away with it? He spun that shit. He did his whole, like, 540 on that thing, spitting that to be like, actually, I was also saving the planet with that one, too. \n\nAlex Hormozi (0:47:53-0:47:54): You're welcome. \n\nShaan Puri (0:47:55-0:48:08): What's that thing they call it where it's just like the male bullshit the abilities for some men to just absolutely bullshit their way out of everything. And Elon's got that. He is the world leader in that. \n\nAlex Hormozi (0:48:08-0:48:26): I think there's a minute, though, because even thinking if I wanted to create a stronger narrative because I'm already amped about this narrative, but I would just look up stats on worker involvement and talk about how it's the end of work unless something changes. And so it's like we're saving work. Yeah, it's all what story you're telling. \n\nShaan Puri (0:48:26-0:48:41): Yourself, because then you'll tell that story to others, and if that story serves you, then great. I mean, I personally, I think this is the Silicon Valley, like PTSD or whatever, where it's like anytime I hear a mission statement, I'm like, just shut the fuck up. \n\nAlex Hormozi (0:48:41-0:48:42): Tell the truth. \n\nShaan Puri (0:48:42-0:48:43): You want to make money? \n\nAlex Hormozi (0:48:43-0:48:44): Great. \n\nShaan Puri (0:48:44-0:50:05): You want your own life value to increase. And you realize that in order for you to get that value, you had to create more value in the world. And so you identified some people that needed something, and you provided that value in spades. Whether that was dentists need better software, or that the world needs a social network, or we want to send disappearing photos back and forth to each other's phones. You hear Evan Spiegel, you go look at the original landing page of Snapchat or the emails that he sent to the Sororities and Fraternities, where he's just like the landing page is like two chicks in a white bikini, kind of like taking like a naughty selfie, basically. And then there's a giant timer where the photo is going to disappear. And same thing when he's emailing the frats. And sororities telling me he's not saying, I'm trying to reinvent the way that. Humans communicate. Actually, 75% of our brains is wired for images, not text. And so I wanted to make a messaging app that was image based. And then you hear him do the pitch, and he's like, for too long, images have only been used for memories, but I wanted to use images for communication the way we originally did with Hieroglyphics and shit. It's like, Bro, it's okay that you thought this app was fun and cool and that it might be a hit. And it took off in these schools because people wanted to get around their teachers or parents being able to see. \n\nAlex Hormozi (0:50:05-0:50:06): Photos in their camera roll. \n\nShaan Puri (0:50:06-0:50:10): That's okay. But they always do this. They always tie it back to something. \n\nSam Parr (0:50:10-0:50:16): Now the word is a mission. Now. It's the D word. It's Democratized. We want Democratize. \n\nShaan Puri (0:50:17-0:50:19): Access to private limos. \n\nAlex Hormozi (0:50:19-0:50:20): Really? \n\nShaan Puri (0:50:20-0:50:33): And then, of course, what does it become, right? As the marketing teams get in there and the consultants get in there, they're like, our mission at Uber is to make transportation as readily available as running water. That became their mission statement. \n\nSam Parr (0:50:33-0:50:35): It sounds fucking yeah, but at first. \n\nAlex Hormozi (0:50:35-0:50:36): It was amazing, but I want to. \n\nSam Parr (0:50:36-0:50:41): Be really by showing up in a black limo, and literally the early stories. \n\nShaan Puri (0:50:41-0:50:53): Of anybody who knew Travis and Garrett at Uber was like they would be like, Dude, check this out. Push a button while they're at their Michelin Star dinner and be like, Watch. This car shows up. And they're like, yeah, that's right. \n\nAlex Hormozi (0:50:53-0:50:53): Baller rent. \n\nShaan Puri (0:50:53-0:51:26): I could see where he's at on the map. Like this is amazing. This is my private driver. I summon him through my app, and it's like, there's always, to me, like, the disconnect between what I think the truth is, which is a little bit skeptical and jaded, and then the revisionist history story that sounds really admirable and noble. And I personally have just come down, and I've landed on, like, I'm okay with the truth. I get the human nature. We're kind of just primal animals, and it's okay. You seek pleasure. You avoid pain. You like status, and you don't want to. Status. \n\nSam Parr (0:51:27-0:51:53): Alex's. Alex. Maybe it started. The mission of our company is to get your money and to put it in our bank account. We're changing our bank account, $1 at a time. And we're starting with your dollar by making it our dollar. Have you heard South Park, where Cartman has crack baby basketball league? \n\nAlex Hormozi (0:51:53-0:51:54): And he's like, no. \n\nSam Parr (0:51:54-0:52:02): Someone's like, look, we need to pay our babies, our athletes more money. He goes, look, ma'am, I don't make up the rules. I just think them up and write them down. \n\nAlex Hormozi (0:52:02-0:52:03): Like, what do you want me to do? \n\nSam Parr (0:52:05-0:52:19): Because inevitably, I imagine it started with, I just want to get rich and do dope shit. And then it changed to this pretty grand thing of changing work instead of using praise. When did that change? \n\nAlex Hormozi (0:52:19-0:54:16): I think it's a yes. And so Sean, I'm like the bullshit ometer et cetera. I fullheartedly hear you on that. And I think that one is that the truth can change. And what I mean by that is because we're not talking about a fact, we're talking about truth of why someone does something. And so why someone does something can change. So when I started Gym Launch, I've said this the mission of Gym Launch was to not be broke. That was the mission of gym launch. But what happened is after I saw the lives that got transformed from it and I was no longer broke, the mission had to change because I had accomplished that mission. So the mission had to get bigger in order to continue to expand. That because I had families who relied on me, employees, et cetera, customers. And so it did truly become to take its knees from its east to its gym industry, from its niece to his feet. Right? And so acquisition.com started with the thing that I was passionate about because the only thing I was passionate about was just spreading good business. Like I love talking about business. It's like my favorite thing in the whole world. I draw pictures about business, I write books about this, I make course about business, make content about business, and then I do business in the meantime. Like, I fucking love business. And so that was the only thing that I felt passionate about. And so that's what I made the mission about. But as we've walked the path realizing that the reason the businesses have done really well for us is because of the cultures that we create. And we believe that those cultures create better businesses and honestly also better working environment, generate really good bottom line, but also really great experiences for the people who work there. And so I haven't been amped about it. And so the truth of why I want to go there now and now I see that a much bigger picture than I did when we started it two or three years ago. I think your reasons evolve. And so I think that it makes sense that I think it's both honestly personal goals. He had transferred money from that person's account to his to the degree that he could buy whatever he wanted. And so I think you just think more about it and you're like, why do I want to do this? Because you have to have a reason. Otherwise you go into a ball of nothingness. \n\nSam Parr (0:54:16-0:54:28): Yeah, well, look, I think the best way to actually learn that we were talking about the last episode. We talked about what's the restaurant Panda Express guy and we were like. \n\nAlex Hormozi (0:54:30-0:54:30): He. \n\nSam Parr (0:54:30-0:55:22): Just sells like orange chicken. That's not exactly inspiring, but like he he employs like 20,000 people and he like gives these guys I think he we were talking about I have my notes here. He gives them all. Like he pays a little bit for them to go to Tony Robbins. He gives them, like, the thinking Grow Rich books and all these books, and he's like, yeah, like, the whole chicken shit. That's kind of cool and all, but I'm actually taking an hourly wage worker, and we're trying to elevate them. And so I'm like, oh, I can get behind that. I'm in on that. And if you look at a lot of non tech or non Silicon Valley companies, employ 30,000 people, and they're like, yeah, we sell tires, and that's cool, but I'm really just trying to, like, we create jobs, and that's very fascinating, and that's really exciting, and that's cool. It's better for the economy or some of these really boring brick and mortar businesses. I think that's actually where you see a lot of really cool missions. Or, like, if you I've read the have you read about the Koch brothers? \n\nAlex Hormozi (0:55:24-0:55:25): You mean coke? Like coke industries? \n\nSam Parr (0:55:25-0:56:09): Yeah, coke industries. So basically, it started with the dad. He was, like, an oil guy, and then they used the byproduct of creating oil to create all types of plastics and whatever. And so now it's arguably it goes back and forth as the biggest privately owned company in America. And he was like, no, my whole thing is, like, freedom for people, and I want to teach them that they have autonomy. And through working here, he's got a whole book on his management systems, and he's like, more so what I'm inspired about is empowering people. And so, anyway, when I read about those older companies, I actually think that that's a bit more inspiring than some doric saying that he's changing the world one computer ship at a time, when it's like, I don't know. That's not exactly inspiring. \n\nAlex Hormozi (0:56:09-0:56:10): Maybe it hasn't played out yet. \n\nSam Parr (0:56:11-0:56:12): Yeah. \n\nAlex Hormozi (0:56:13-0:57:03): Bill Gates said when he started was like, I want to have a computer, and everyone's like, okay. And then he did it. And so I think part of it is also, like, what snapshot on the timeline are we looking at? But I 100% agree with you, because basically it shifts from internal to external. Like, in the beginning, you do it for you, obviously. You do it because you get praised instead of punished. Like, you have good more good shit than bad shit. So you keep doing it, but once the thing that was good no longer, like, the diminishing return of the pleasure of more money isn't there anymore, then you have to find a new you find a new goal, like you said. And if it also coincides with other people being motivated by not making Alex rich, but by proving a point that we can create companies that reward instead of punish and actually have better returns, I'm juiced, and we haven't proved it yet. That's fine. We haven't proved it yet. We will. \n\nShaan Puri (0:57:03-0:57:47): I want to ask you two questions. The first is around people you admire. So we talked about the panda express guy on our Just on Our Own last episode because we were featuring those, like, crazy, rich Asians, basically was the third of the episode, and then it turns out he lives near you or whatever. You're both in Vegas. Who are some people that you admire? So I always find this interesting to hear who kind of stands out and why for different folks. So who are some people that you admire, either past or present? People that you've met? Because I know that this kind of, like, getting famous on YouTube thing opens up a bunch of doors. You meet a bunch of cool people that you otherwise, you expand your circle of people you get to know through this stuff. So who are some people that you admire? \n\nAlex Hormozi (0:57:47-1:00:35): Well, I definitely admire Andrew Patron from Panda Express because they're a married couple who built this whole thing, and they never I got outside money, and they've owned the whole thing. Privately, they have 2600 locations. They do 3.7 billion a year with 27% net margins, and they take $935,000,000 a year in personal income. And I think that's only possible because they have created a new vision for what they wanted the company to be about, which is about their employees. I am inspired by Warren Buffett, you know what I mean? I am because of the long term mentality that he has. And he built Berkshire Hathaway. And in some ways, I feel like he has, like, a beautiful life story of just believing in the power of compounding and patience. And that's what I feel like his virtues are that he's demonstrated in rational decision making. I would say that for us, it's like if we can build something like that, but just with our own spin, our own zest, which is around praise, not punishment, and building companies that we can win by their scoreboard, but we do it our way. So that's the Warren angle. And, I mean, I admire Elon a lot, a ton, just like what we were talking about earlier, his ability to see vision and connect to a larger mission. He's been able to masterfully do that in every single company he's been a part of. And his track record is incredibly fucking impressive, and he just continues to defy the laws of what seems to be normal or possible over and over and over again. And so I think just like how he just stares into the abyss and says, like, let's do it, I think that's something that I really, really admire. He obviously has flaws like all of us do, but I think he also has been really good about owning his flaws and being public about that. He's just a human, and I think he may create a new model for how big public CEOs run, and maybe that maybe we're in the beginning of that world. And I think on the totally other side of the coin, I think I admire what Mr. Beast has done from a personal branding perspective, I've been able to get to know him really well. Jim thinks really big and has a tremendous work ethic. And I think seeing the merger, seeing where all these things are, like, Elon has been able to build a personal brand, and in a lot of ways, if you're a fan of Elon, you want to buy all of the things. He just happens to have enormous Monetization vehicles. And to your point, Sam, about how they use, like, yeah, sure, we make tires. Yes, sure, we sell orange chicken. In a lot of ways, I see, like, all the companies we have in acquisition.com is like, yeah, of course we transact, we build businesses. But the reason we do it is this. And I think that's really dope. And so those are probably the if you were to mix, like, what are the things that I'm drawing inspiration from at Burn. And if you look at what we're doing, it probably would make sense to see all three of those as the three biggest kind of influencers. You got, like, Mr. Beast on personal brand side here. You've got Warren Buffett on the investment side and then Elon from the big vision. And I feel like those three things are probably where I draw the most inspiration from in terms of our day to day and what we're trying to do. \n\nSam Parr (1:00:35-1:00:49): What's interesting about you is that you're pretty good at you're very catchy. So, like, the whole knees to feet thing is pretty awesome. And then what was the line for your current company? It was reward versus punish. \n\nAlex Hormozi (1:00:52-1:00:54): We would have beat them at their game and we wouldn't do it our way. \n\nSam Parr (1:00:55-1:02:07): Well, you said we want to use their scoreboard, but do it our way. So you're quite lyrical. You've also done a few there's, like, actually a handful of things that you've talked about very casually that I've caught onto that I really like. So, for example, you say dessert. What do you say dessert every day or never skip dessert? Never skip dessert. And then you also because your whole dieting thing is you eat all of your protein earlier on, and then you're like, all right, now I have fat and carbs. We can go big on those. You've done a few things outside of business that I find almost more impressive or I actually use on my daily life, more so than your business stuff, which I actually found is pretty funny. You also have I don't know if you've seen this, Sean, but if you Google, there's this, like, 23 year old Alex who does a thing where he's like, I'm going to do a bulk over the next eight weeks. And he has, like, before, during and after photos and that stuff I look at significantly more than a lot of your business stuff. I find that some of your fitness and diet stuff, like, more interesting, applicable in my day to day life than the business stuff. I'm shocked that a living. \n\nAlex Hormozi (1:02:08-1:02:45): I joked about it in the comments once. I was like, people, like, admire our my way of thinking about things in business. And I was like, for a decade I did that with fitness. I just don't talk about it because everyone feels entitled to opinion because they have a body. I hate getting into that. They're like, well, what about salt? I'm like, Dude, just fuck off. I have so little patience for it because I'm like, look at you. And if you were more in shape and by the way, no one who's been more in shape than me has ever criticized any of the content I ever had. It's just like people who are wealthier than you never say shit about business advice. No one ahead of you ever should tell. \n\nSam Parr (1:02:45-1:03:14): Well, the cool thing about it is I use the fitness analogy a ton in business because I'm like, well, it's hard, but it's simple. In that if you lift this much weight and eat like this for a year, you're not necessarily going to look like Arnold or be lean or whatever, but you're going to be pretty good or better than where you are now. And you just got to do it for like, two years and you got to be fairly strict about it. So that's why the carryover is quite fun watching you do both of those things. \n\nAlex Hormozi (1:03:14-1:03:27): I appreciate it. Yeah. I mean, simple not easy, I feel like is the fucking theme of so many things like fitness, nutrition, marriage, business. Like simple to do or simple to understand, conceptually, very hard to do. \n\nShaan Puri (1:03:28-1:03:31): What's the simple not easy for marriage. \n\nAlex Hormozi (1:03:31-1:03:46): I think it's it's reward more than you punish. I mean, it actually comes down to that. So, like, okay, if I want my wife to scratch my back more, I have to wait until she scratches my back of her own volition, and then I have to reward her immediately. And then she will want reward more, and so she will do it again. \n\nShaan Puri (1:03:46-1:03:48): Very pavlovian of you. \n\nAlex Hormozi (1:03:48-1:03:59): Well, yeah, I mean, I think we're all though, you know what I mean? Fundamentally, there's three things you can do when anyone does anything around you is that you can punish them for doing it, you can ignore that they did it, or you can praise them for doing it. \n\nShaan Puri (1:03:59-1:04:01): Have you ever heard the Tony Robbins. \n\nAlex Hormozi (1:04:02-1:04:03): Like, I forget what he calls it. \n\nShaan Puri (1:04:03-1:04:37): But it's like the four styles of being in a relationship. He says something like this. Have you heard this thing? It's like the first one. Let me see if I can remember it off top of my head. So basically he goes, first one's like a baby. It's like, I need love and I don't have to give anything to you. So it's just like I cry, you give, and that's it. You better be happy with that arrangement. So that's like one relationship you can have, one style of relationship you can have, and obviously doesn't work out very well. Once you're an adult, you can't just cry, expect to be given everything you want and then not have to do anything in return. \n\nSam Parr (1:04:38-1:04:40): Baby love. So that's baby love. \n\nShaan Puri (1:04:40-1:05:21): Then he has the next one, which is basically tit for tat. And this is where almost everybody falls into. So this is probably going to sound familiar to at least to an extent, and it is probably the root of all problems in relationships is tit for tat, which is you measure what you get and then you give based on that. When you're given a lot, you give a lot. But then as soon as somebody breaks the cycle and they short you, consciously or unconsciously, they don't do what you wanted. You also withdraw or pull back some amount of giving and then they reciprocate. They also measure and pull back, and both sides do that. And you end up with sort of a race to the bottom. And so that's tit for tat, and that's where most people stand. And it's just a cycle that resets. \n\nAlex Hormozi (1:05:21-1:05:22): Over and over again. \n\nShaan Puri (1:05:23-1:05:46): The next one is unconditional love, which is basically I give regardless of what you give back. I give because that's who I am. I give because that's how I want to roll in my relationship, and I control what I control, and obviously that's way better. And to me, that's the simple not easy of being in a relationship is just go unconditional mode rather than TIFF or tat. And then he has some higher one, which is monk love or something like. \n\nSam Parr (1:05:46-1:05:48): That he calls it, where it's spiritual love. \n\nShaan Puri (1:05:48-1:06:08): It's like, I love you even though you hate me. Like, a monk can be like, I pray for and love even my enemies and those trying to hurt me. And he's like, nobody gets there. But that's aspirationally what you could get to as well is love. Like a monk who loves even their enemies and those who try to cause harm. And so those are the four levels. \n\nAlex Hormozi (1:06:08-1:06:09): Of love I remembered. \n\nSam Parr (1:06:10-1:06:28): Alex, do you ever so, like, I saw this video of you the other day, and now everyone's giving you a hard time or they're just teasing you in a good way about your outfit because you wear the same clothing all the time. So you made a funny video about it and you go instead of just saying, oh, it's comfortable, you go, Dude, I'm just more Darwinian to them. These shorts. \n\nAlex Hormozi (1:06:28-1:06:29): You want to go work out? \n\nSam Parr (1:06:29-1:06:30): I can go work out. \n\nAlex Hormozi (1:06:30-1:06:32): You want to go to restroom? \n\nSam Parr (1:06:32-1:06:42): Yeah, that's what he said. He goes, you want to go swimming? These are waterproof. You want to go out to a restaurant? He's like, Just good enough that I can go and do that. I can do anyone. I can do anything. I'm Darwinian. \n\nAlex Hormozi (1:06:42-1:06:42): You're not. \n\nSam Parr (1:06:42-1:06:43): I win. \n\nShaan Puri (1:06:43-1:07:11): You lose. I bought the shoes you invented because you were like, these sandals, these are the perfect sandal for working out, running through, walking through rain, climbing a hill, or being at the office. And in the comments, everyone's like, yeah, what's the sandal? What's the sandal? Where's the affiliate link? We can't find it. And then some dude, like, 50 comments down is like, dude, that's what it's this brand, the night shade color of this. All right? Respect to this guy for finding it. I'm going to go buy this thing. \n\nSam Parr (1:07:13-1:07:29): Does your mom and dad ever like, hey, quit being such a douche, and we just wear what we bought you? Because be nice? At what point are you like, this makes sense for me. And also it's good for the brand versus live a little and let's just fuck around? \n\nAlex Hormozi (1:07:30-1:08:25): Do you know what I mean? Yeah, good for the brand is actually not really a thought when it comes to it. I believe that brand comes as a result of rather than conscious, you know what I mean? People were like, so wouldn't you think of never skipped dessert? I was like, I was making fun of fitness people because my original audience was fitness people who obsessed about not eating cookies. And I was like, Fuck off. You know what I mean? Like, eat dessert. You know what I mean? But do it in a way that you can sell a six pack the whole time. So that was I never skipped. It was always like, never skip leg day. Never skip Monday. I was like, Never skip sir. Like, the calves thing is because I genuinely have started training. I start every training session since a girl told me that she thought that my calves weren't big. It's been like, twelve years, 14 years that I start every session with calves. And so my calves have grown a lot. And so everyone's like, Jeanette, my calves were sticks, and I trained the ship. So, like, is it part of my brand? Yeah, because it's in some ways, like it's true. \n\nShaan Puri (1:08:25-1:08:30): Lindsay, Lindsay, 14 years of fuel you gave me. \n\nAlex Hormozi (1:08:31-1:09:57): The outfit thing is actually because it's my content team that wanted to make content about it, because they're like, dude, you're fucking maniac with this. I feel like people should know this because everyone who knows you in person knows that when they walked in for almost a year and a half, there was stacks of shoeboxes, and I would wear different shoes for an hour a day a week. And they kind of graduated to like if they're good enough where I can walk around the apartment, then I'll walk around for their day. If I can walk around with them for a week. And I still like them. And most of them never got there. So I have a few finalists that got to that point, but I think I just obsessed about making things better. Same things. Like, if I do end up doing a you know, if there is a good enough company that does no strips like I'm going to iterate the product a bunch of times until I think it's absolutely untouchable. And then I'll say, this is the one I use. And I can say that. I say that with confidence because I did the work on it. For me, I just hate having to change. I don't know what it is. It means that I started my day not thinking about what I was going to do. So I was like, okay, well, if I can create a setup or a uniform for myself that I can be in the most environments. So for me, I'm really never in less than 40 degree weather, ever, because I usually tend to be in warmer spots of the country in general. And so this outfit goes 40 to 120 degrees, and I can go to the gym. I can go to the pool. I can walk for hours. I can walk all day. I can go to a nice restaurant. I can do all those things because. \n\nShaan Puri (1:09:57-1:09:59): If they need but that's crazy because. \n\nSam Parr (1:09:59-1:10:05): Your wife, who I've seen, she dresses lovely. She like, it's fashionable, so her hair always looks nice. \n\nAlex Hormozi (1:10:06-1:10:06): You know what I mean? \n\nShaan Puri (1:10:06-1:10:16): Like I said, it goes 40 to 120. Like a car goes zero to 60. This flannel jacket right here, this thing goes 40 to 120. \n\nAlex Hormozi (1:10:17-1:10:47): Once it's below 40, I get cold, so I have to put pants. But up until then, I'm pretty much good within that range. And so I can button think this thing can go full sleeves, and that's when I'm in mass cold mode. Or if I go to a restaurant that requires sleeves, I can have that, right? But otherwise, I'm in beater mode. We go to the gym, we go to the pool, we go to beach, we go wherever I'm going to be in beater mode. You know what I mean? I tried to drive. \n\nShaan Puri (1:10:51-1:10:52): Mode like a car. \n\nAlex Hormozi (1:10:52-1:12:02): Well, my whole outfit has sports mode. People are like proxy sport. Like, my whole outfit has sports mode and comfort mode and weather mode, and I can do that. I enjoyed finding each of these things almost as much as I enjoy wearing them every morning. And this is true every morning when I put this on, I get like a little boost where I'm like I know that I've picked every single one of these pieces out, and I have no doubt that this is the best thing for me for my day. And so I know that the brand of white beaver that I have on right now, I tried 40 or 50 other brands on, and I knew this one sat where I wanted to sit. It wasn't too thick on the shoulder or too thin. It didn't drop into some string on the back. Some people like that. I didn't want that. Beaters themselves are thinner than tank tops. They're ribs so that they fit right. I think even have you ever seen those Under Armour tank tops? Or those, like, shrink wrap ones? They don't look good. I think they look synthetic for me. I think they look like kind of synthetic. E like, I don't like it. I like cotton better. And so it was just a number of iterations. Like, if I talked about the shoe, I could tell you a zillion things that I looked at. I have, like, an Excel sheet that. \n\nSam Parr (1:12:02-1:12:21): I thought you would have. I have a few friends like that. I'm not as extreme, but I like buying and testing a ton of stuff. Sean wears ordered, like, 20 of the same shirts. What products this is actually interesting. I don't think this is like, too inside baseball, but what products and brands do you obsess with and love in your daily life? \n\nAlex Hormozi (1:12:21-1:13:13): Well, I won't say them because I'm in talks with, like, hassle to try and figure something out. But I will caveat that with I think that in general, for people, my life might be different than theirs. And I think just being delivered, so many people are just, like, sleepwalking through life that they're always sitting there with their pants that just don't fit just right or always don't have this thing. A lot of stuff I modify. So my gym bag like, there was a video about my gym bag. I tried out a bunch of different bags and I finally found a bag that I liked and then I modified the shit out of it and like, that bag. Now every time I go into a gym, people are like, Dude, that bag's awesome. I was like, I know, because I made it for this function and it's great and I love it. It's really good. So I think it's more just like finding the whatever your 40 to 120 is. Because maybe you live in Michigan and it's always cold. It's like, well, you're going to have a different standard. \n\nSam Parr (1:13:13-1:13:14): What standard? \n\nAlex Hormozi (1:13:14-1:13:15): Wear? \n\nSam Parr (1:13:15-1:13:19): What shorts are they? I thought you used to wear just shorts. I used to make fun of you for wearing. \n\nAlex Hormozi (1:13:19-1:13:55): I used to Jordan. But George, I'll tell you, I used to wear jords because they were more comfortable and I could do more casual settings with them right. Than always showing up in athletic shorts. It looked like, almost too casual, I think. And a lot of restaurants are like, no athletic wear. And so I was like, okay, well, that's annoying. And so then it went through this whole thing where I had to find the best short. And then while I was doing that, the ones that I have have back hooks on them so that if I can hang them too dry. I've got an iPhone pocket in there that's built in because I hate having to sit. And then you take it out of your pocket every time. It's such a. \n\nSam Parr (1:13:55-1:13:56): Pain. \n\nAlex Hormozi (1:13:56-1:14:11): There should be a pocket for this. Everyone has one, right? And there's, like, a little place that I can plug an iPad pencil in my shorts because I use my iPad a lot. Like, I've got cargo on the other side, and these are stretchy, but not too stretchy, but they're stretchy. \n\nSam Parr (1:14:12-1:14:14): What freight you hauling in there, buddy? What do you got? \n\nAlex Hormozi (1:14:15-1:14:15): What do you need? \n\nShaan Puri (1:14:15-1:14:17): The car gummy bears? \n\nAlex Hormozi (1:14:18-1:14:40): No. A lot of times, it's mic packs, so a lot of times it's mic packs, because we're getting, like, right now, my mic packs in my cargo pocket, but I could fit a water bottle in here if I need it. Or a hotel key, like hotel keys there whenever we're traveling. Or I use my Nicorette because I actually nicorette, so I'll have Nicarette in my pocket if I go on a podcast. So I always have the stuff that I need there. \n\nSam Parr (1:14:40-1:14:41): Well, it's weird. \n\nShaan Puri (1:14:42-1:15:01): The best way possible, man. These are my favorite kinds of pods. When you find out, it's like, I want to see your weird, that's when I know you. Until I see you're weird, I don't actually know you. I feel this is my this is my personal my personal thing. And I'm glad we went down this rabbit hole because we got to see your weird. \n\nAlex Hormozi (1:15:01-1:15:59): It's funny, because right now, Maya actually, I'm not going to show you the brand, but I've got this backpack here, right? And this backpack, I can wear it, like, when we travel. I can wear it everywhere. And it has everything that I used to travel, and I can travel for four weeks with that because all I have to pack is the repairs of shorts that are identical, that are multi everything. And then I just have an amount of tanks that is whatever the laundry cycle of the trip is, and that's it. And I could put one flannel on top, and I'm good. And I don't even have to use the expansion part of that backpack, which I have options if I need it. And it has a cool front thing for all my wires that's flat, so it doesn't take up space. There's just a lot I like. And I went through a zillion different bags to find that. I went through a zillion different bags to find the gym bag, but, like no, when whenever I pick it up, I'm like, this is the best bag to the job. \n\nSam Parr (1:16:00-1:16:10): You seem like a clutter free guy. Like, do you have a cleaner who comes to your home very often and someone who does laundry? And also do you not own a lot of stuff? \n\nAlex Hormozi (1:16:10-1:16:55): I don't. Layla does. Right. That backpack and tank tops. I can fit my entire wardrobe on my bedside table, and so super easy. And when I was trying stuff on, one of our assists will come, and they'll return anything that I don't use or whatever. But I think the underlying point here is Layla doesn't do that at all because she doesn't like that at all. She broke, really poor, always wanted to have nice clothes, and now that she can, she loves wearing nice clothes, and she feels good wearing nice clothes, and she gets hit up by the designers to go to the runway things, because she wear, like, one piece of her wardrobe. Is the entire cost of my wardrobe, like, one piece, like a top. \n\nShaan Puri (1:16:55-1:17:15): What the best way you spend money for you personally? Not, like, a business investment that you think it's a great ROI, or you get a bunch of joy out of it, or it's, like, dope for you that is, let's say, not your content team and not, like, something that's directly in the business. \n\nAlex Hormozi (1:17:15-1:17:22): Yeah, I mean, I would say JSX is wonderful since it's in the Southwest, so it's, like, semi private flying. \n\nSam Parr (1:17:23-1:17:24): It's pretty good. \n\nAlex Hormozi (1:17:24-1:19:01): Oh, it's great. The only reason we fly private is because it saves the only reason we do it, and a lot less hassle. But JSX allows you all the benefits of private flying. This is like a fucking JSX plug, but it's really good, and it tickets, like, $300 when it would normally be, like, 50. So if you want to fly JSX from Vegas to Salt Lake or Vegas to Scottsdale or Vegas to La. It's $300. It's nothing, right? And you walk up to the plane, you get on the plane, and then you walk off the plane. That's it. You know what I mean? It's just, like, private. There's just a few other people there, and private flying, in my opinion, has the most benefit for the shortest travels and the least benefit for the long travels, because long travels, you want to fly as high as possible, as fast as possible. The bigger the plane, the better. And by percentage of the trip, going through security and dealing with the hassle, if you have a five and a half hour flight, five and a half hours versus, like, 7 hours of transit, the day screwed. It doesn't materially change a lot, but on a short travel where you're going, like sub, I would say sub 2 hours, you can double the length of the trip or triple the length of the trip by going in reverse, cut it in half or by a third by flying private. And so that's where I feel like you get the highest marginal benefit. It's also the cheapest private flight to the shortest ones because it's by hour. So that's kind of like when we go back and forth, and usually the only times we'll fly private is if we can't get a direct JSX flight. \n\nSam Parr (1:19:02-1:19:31): We'll wrap up in a second here, but last time you were here, sean asked a question about your portfolio, and I want to follow up on it. What's your portfolio looking like in terms of both your private investments as well as what are you doing with your money? Are you keeping in equities bonds? Cash? I think last time you were super heavy cash, if I remember correctly. Yeah, that's what it was. It was Treasuries. You're like. I'm almost entirely treasuries. What's it looking right now in terms of if you could do, like, a pie chart and percentages? \n\nAlex Hormozi (1:19:32-1:19:36): Probably still half Treasuries, except now they're. \n\nSam Parr (1:19:36-1:19:38): A lot better than before. \n\nAlex Hormozi (1:19:38-1:19:46): Yeah, they're probably half Treasuries. Probably have a quarter in just, like, indexes, and the other quarter is in. \n\nSam Parr (1:19:46-1:19:49): Private companies, so pretty simple. \n\nAlex Hormozi (1:19:50-1:20:16): Yeah, probably not by value. Over time, that treasury part is going to continue to decline as we do more and more deals. But yeah, I still think that, like, I mean, I don't know what the future looks like, so I like, I I tend to like having lots of cash. Like, I feel good. I I never want to not be able to do a deal that's going to ten X because I don't have cash. The cost of missing the ten X is well worth the, quote, inflation that I'm suffering for the difference between the treasury yield and the inflation cost. \n\nSam Parr (1:20:16-1:20:19): And yeah, I would imagine you probably don't own a car, and you seem. \n\nAlex Hormozi (1:20:19-1:20:26): Like you'd be right. So Leila has one of those H two electric Hummer pickup trucks. \n\nSam Parr (1:20:26-1:20:28): Oh, my gosh, that's hilarious. Yeah, the huge one. \n\nAlex Hormozi (1:20:29-1:20:45): Yeah. She was like, I want it. I was like, okay, it's not really my way to do that. Mine would be if it were me, I would have a Dodge Caravan that was like, all blacked out, tinted windows with the TVs, you know what I mean? In the back, like, sliding door as I pull up. That would be more my style. \n\nSam Parr (1:20:45-1:20:48): And are you renting you'renting still or do you own that place? \n\nAlex Hormozi (1:20:49-1:21:08): No, we just bought a place we were renting for a couple of years, and then Leila found one that she was like, I want this one. So I was like, all right, get it. We just moved today, actually, or yesterday was the official move. So that's why my background is now my office closet. But we're actually retrofitting a closet here to be my office. \n\nSam Parr (1:21:08-1:21:40): Dude. I heard that Derek from more plates, more dates. I had heard a story. So he basically started his whole video thing when he was no one and he just had a shitty apartment. And I had heard a story that he the original video was just him on a white wall, that he cut that white wall and put it into each of his now nicer homes or apartments. I had heard he took that wall with him everywhere, so even the shade was the same. I don't know if that's true, but I had heard that and I thought that was pretty funny. \n\nAlex Hormozi (1:21:41-1:21:52): I'm a big believer that Derek obviously knows what he's doing. I just always just want, like, if I move you guys, like, my background will change, and you'll know that, like, something has changed my life. \n\nSam Parr (1:21:52-1:21:55): You know what I mean? Well, he's way more private than you. \n\nAlex Hormozi (1:21:55-1:22:16): Yeah, he's way more private. He doesn't want anyone in his last name, et cetera. Different strokes. I think on a long enough time horizon, everyone will find out your last name. I mean, Lady Gaga. I tried to go by Gaga, but you can Wikipedia her name, so you can find it if you get famous enough. And I figure that we will get famous enough, and so it hasn't been something that I've tried to protect a ton. \n\nSam Parr (1:22:16-1:22:24): Well, thank you for coming on again. If you go to our YouTube page, my first smelling you're actually like the I don't know what they call that video, but you're like our main page. \n\nShaan Puri (1:22:24-1:22:26): Video for a while. \n\nSam Parr (1:22:26-1:22:37): Yeah, and it's like a quote of like, I've come to the conclusion that I just like to work, and I don't like when people ask me, why am I working all the time? Or something like that. But thanks for doing this again, and we really appreciate it. \n\nAlex Hormozi (1:22:37-1:22:47): No, I mean, thank you guys for having me on, and thank you for the audience for maybe making requests to have me back on. So I appreciate it, and it means a lot to me. So thank you guys for just being awesome host in general. \n\nSam Parr (1:22:47-1:22:49): Awesome. Well, that's the pod. \n\nAlex Hormozi (1:22:51-1:22:59): I feel like I could rule the world. I know I could be what I want to. I put my all in it like, no days off on the road. \n\nShaan Puri (1:22:59-1:23:02): Let's travel, never looking back. \n\n" }, { "path": "data/Transcripts/MFMPod/mfm_pod_rob.txt", "content": "Sam Parr (0:00:00-0:00:06): So does that mean that, like, the vast majority of your real wealth creation has been in, like, the last ten years? \n\nRob Dyrdek (0:00:06-0:00:09): No, in the last, like, few years. \n\nSam Parr (0:00:10-0:00:12): But you were you you were broke. \n\nRob Dyrdek (0:00:12-0:00:21): I was. I would consider myself broke. I would say I started from zero almost in 2016 when I launched the machine. I wouldn't say debt broke. \n\nSam Parr (0:00:21-0:00:24): I mean, you're a millionaire. Were you worth at least ten? \n\nRob Dyrdek (0:00:25-0:00:29): I would say I was probably worth, like, 15 or 20 in that dump. So not broke. But to me, I was like, bro. \n\nShaan Puri (0:00:30-0:00:32): To a future billionaire. A millionaire is broke. \n\nRob Dyrdek (0:00:34-0:00:42): I feel like I can rule the world. I know I could be what I want to. I put my all in. It, like, no days off on the road. Let's travel. \n\nSam Parr (0:00:42-0:00:47): Sean, say exactly what you just said to me when we finished our recording with Rob Beardick. \n\nShaan Puri (0:00:47-0:01:05): I said, I think that was the best episode of MFM we've ever done. I don't know if I'm just on a high right off of it, but I believe so. People can tell in the YouTube comments. They should tell us. To me, this was the best episode we've done 400 something episodes. How many have we done? Jonathan something like 400 episodes. That was the number one. My favorite. \n\nSam Parr (0:01:05-0:01:32): The best episode we've ever done from beginning to end. I'm shocked. So you asked him. We started getting along really well, and you said, Rob, what's your net worth? And I was like, Damn, is he going to answer that? And he gave the full answer. We're not going to say it now, but it's somewhere in the middle somewhere. But he gave the entire answer where he broke it down. He talked about his I'm just actually shocked that he said most of the things that he said. And it was amazing in a great. \n\nShaan Puri (0:01:32-0:02:09): Way, in a great stories of two companies that he's built, and the stories were phenomenal. We talked about net worth, what he does with his money, how he thinks about investing. We talked about how he kind of went from beginner at business and making all the mistakes to now being really sophisticated and how that all happened in a really short amount of time. We talked about his house, the forever estate, the dream that he's been building around, and how he does hit all the buttons. It had the inspirational, the tactical, the entertaining, the humorous. It had everything that I like in an episode, but in one. So I couldn't be happier right now. \n\nSam Parr (0:02:09-0:02:33): So if you use YouTube, whether you're listening on podcasts or you're actually watching us right now, let us know in the comments what you think. Or if you're not a YouTuber, just tweet at Sean and I it's. Sean VP. Like Vice President Sean VP? And then the Sam parr. And add Rob to it and let us know on Twitter. Or if you're a YouTuber, let us know, there I'm very curious what you guys think. And, Tag, Rob, if you can give. \n\nShaan Puri (0:02:33-0:02:44): Us a wave of feedback. I'm going to send it all to Rob after the pod to show him the love, because I know people are going to love this. All right, without any further build up, here's the episode with Rob Deird. \n\nSam Parr (0:02:45-0:03:00): All right, we're live. Sean, you missed it because you're late. You're always late. And that's his whole thing, is timeliness. And he was talking mad shit about you because you were using his face and his time template that he talked about in the last pod. \n\nShaan Puri (0:03:00-0:03:14): I am Human Optimization was the big line from his last time he was on. That's been, I think it's like, in our trailer now. And Rob, if you are human optimization, I am human. On optimization, I am the opposite. \n\nRob Dyrdek (0:03:14-0:03:56): Yeah, look, the beauty of time mastery is it's time flexibility and understanding that life is this living experience. But nothing brings me greater joy than to know a man that was using my time data for customer acquisition and knowing that how much I collect my data and how specific I am with mastering my time would be seven minutes. To have me waiting for seven minutes makes life more grand to me. To know that for you, knowing how much I respect and use my time so thoughtfully that you would steal a little bit from me, even, it's fun to me. You know what I mean? It's very fun. \n\nShaan Puri (0:03:57-0:04:00): Okay. That is well played. I appreciate that. \n\nSam Parr (0:04:00-0:04:37): Dude, we were talking about a bunch of stuff before you hopped in. Rob, I want to talk about that in a second. But you came on, I think, two years ago or a year and a half ago. I don't remember. I just reread the comments a minute ago. Everyone said the same shit, which is the exact same thing, I thought, which was, Rob's just a skater. He's smart and does good TV shit and all that stuff, but we didn't realize that he was just profound. And that pod, I felt like it was like you're coming out as this human optimization thing. Now, I've watched you with so many other people, and I've gone more in depth on some of your stuff. Is that true? Was that like the Artist Formerly known as Prince moment? \n\nRob Dyrdek (0:04:38-0:04:40): You guys get all the credit. \n\nSam Parr (0:04:40-0:04:42): Thank you. That's what I was looking for. \n\nRob Dyrdek (0:04:43-0:06:24): Because let me give you this. You let out with trying to talk to me about you did no depth of research into seeing what I was up to. You let out with some skate talk and TV talk, and then I went on, like, a 20 minutes rant so that you could understand the depth of how I operate. Then the entire conversation changed for an hour. You know what I mean? And that, to me, is like the funniest part of the experience was I said, okay, they have no idea who they're talking to. Let me lay this out real quick. But again, I'm so thankful that the conversation turned to because it was also like I had been collecting the data using my rhythm of existence, but I'd never shared it before. So even then sharing it with you and then you guys reposting it, it really began to create the wave. And then you guys put out a little thing that was about how would Rob monetize his data. And so you put out this entire thing about how to build an app and what I would need to charge in order to create a business out of it. And it really started the wheels in me of realizing that, man, I need to turn this philosophy first into then a usable digital product that's more intuitive, that's deeper than an app, that's actually a software that allows people to realize this level of harmony and overall happiness that I've created through this system, which has led to where I'm at today of continually pushing the philosophy forward and ultimately creating a software was inspired by you guys. \n\nSam Parr (0:06:25-0:06:27): We get all the credit. That's nice. \n\nShaan Puri (0:06:27-0:07:08): There's actually a couple of listeners who, after they heard that, made their version, they were like, Dude, he was talking about this. It sounded so awesome. He said he might share it, but we haven't seen it yet. So I just went ahead and I made my own version. It's linked to Google Sheets. It was kind of a Janky version, but it definitely inspired many people to look inward and be like, how am I treating my time? And it seems like you had the kind of the complete balance. You were like, I have my time. That's with my wife and my kids, and then I have my work time, and then I have my body. You had it all. So I think that definitely inspired a lot of people to look at it, but it also inspired some people to try to build their own version of that tracker so that they could have the kind of what gets measures, gets managed, that type of attitude around their time. \n\nRob Dyrdek (0:07:08-0:08:24): Yeah. And again, I think it's so much more complex than that, right? Because time is alive, and your time and experience, basically your whole life, leads to this present moment in time. And then the energy that you feel at this present moment in time is ultimately the quality of your reality that you're in, right? So time ends up being this much more important aspect of learning to manage. And then you're changing all the time. The world's changing, you're selling companies, you're starting new companies, your kids are growing all these things. So managing your time and how you stay balanced is constantly changing as well as you change. So it's this ongoing focus in my life that it's this constant assessment and adjustment to lead me towards a better probability of a better future experience. And that's what's difficult when somebody makes their own app, there's sort of a philosophy and a rhythm and a process that I'm creating in the software that makes it much more intuitive based off of the type of personality you have and the way your life rolls to get it to actually work. Because otherwise it just feels like you're making checklists and making data, and then it gets too difficult and it's over. \n\nSam Parr (0:08:24-0:09:19): Before you join Sean. We are talking about Andrew Huberman. And the reason why we were talking about him is because I like to skate. Rob is a skater, hardcore, obviously, professional skateboarder, and Huberman loves it. And we were talking about that, and I don't know if you know what Momentous is, Sean, but it's like they're one of the main advertisers on the Heberman pod. Andrew heberman says, this is the only protein that I like, so, obviously, I bought a ton. That's what I drink every day. And Rob was like, and is it Jeff? Is he the CEO? I'm supposed to talk to Jeff. Jeff is the CEO? Yeah, I'm supposed to talk to Jeff, because Ken Ride out introduced us, who was also on the pod. And anyway, Rob was like, yeah, that's cool. It's amazing to see how fast that business grew because of Huberman's promotion. I co founded that company not too long ago, and it's just crazy how fast it's grown. And we were like, Wait, what? Rob. You co founded Momentous Protein. \n\nRob Dyrdek (0:09:20-0:10:22): Yeah, and look, here's the thing with Momentous Protein. I co founded it with Matt Wan in 2016. When they brought it to me, he had a vision for creating basically the most premium supplements that the market had ever seen. The Ferrari of supplements. It was called Project One at the time, and Matt was foregoing his first year of Harvard to build this company. He was 18 years old, and his father, Mark Wan, had been one of the big investors in my professional skateboarding league. So I had a relationship with him and said I would do this project with his son. First thing we had to do was rebrand it, right, and really create a name and a soul into what is the absolute pinnacle of supplements. Momentous. Right? And all the way down to where I even went through the whole process of even making that logo. To me, that M is like this timeless, extraordinary logo. \n\nShaan Puri (0:10:22-0:10:29): And, Rob, that's you in Photoshop, or this is like a creative agency pitching you guys. How does that happen? You take it, make it. \n\nRob Dyrdek (0:10:29-0:12:29): This is me literally an illustrator of the agency sent some logos, and me cutting up the agency's logo and being like, no, get rid of there was a circle in the middle. I'm like, no, this is like look at this. It forms like an M and a mountain. I literally cut and pasting in my illustrator, the Momentous logo. Love it. And so we launched that company. And what happens? We don't sell a thing. We don't sell a thing. What do we got? We got the most overpriced protein in the entire industry. It's like 35% above every other protein. Like, literally nobody buys it. Nobody buys it. Now what do you got? You got an 18 year old CEO. This kid doesn't even every single day is another thing of like, oh, that's what happens in business. If you want to talk about the headwinds of no man's land and the pain of launching a business with an 18 year old genius, right? Because he's brilliant, but he was 18 and didn't even understand anything about a company. You can't advise somebody into running a company, you know what I'm saying? You have to fight the fire, learn the battles to ever learn how to operate a company. Long story short, this business never got off the ground for years. And I finally now he's older. I'm like, look, man, you've got to make a decision. You've tried everything. You've done all different types of partnerships. You've made all different types of verticals of product. It is the Ferrari of supplements. It is absolutely the purest and best. You kept it real, but you just can't find a market for it. You either have to sell it, or you have to find somebody to merge with, but you got to move on. You're now 23. You learned everything. Go take this skill set that you learned and apply it to a business that has a more relatively faster growing opportunity. \n\nSam Parr (0:12:31-0:12:34): What were the annual sales when you had that conversation? \n\nRob Dyrdek (0:12:34-0:12:38): I want to say a few million and just losing money year over year. \n\nSam Parr (0:12:38-0:12:41): And how much did you put into it to start? \n\nRob Dyrdek (0:12:41-0:12:53): I put in shoot, I want to say not much. Like 200,000 in the first, like, at the beginning to get it off the ground, and another 100,000, 300,000, maybe. \n\nSam Parr (0:12:53-0:12:55): Do split equity when you do that. \n\nRob Dyrdek (0:12:55-0:14:56): And I got 30% of the business. Okay, now, man raised so much capital any which way but loose. Now I'm on the board. I'm in board meetings. I'll tell you what. Nothing as painful as board meeting after board meeting when there's no revenue growth and you're just burning capital trying to figure out how you're going to tell a story to raise more capital to keep the dream alive. That went on for a significant amount of time. We got incredibly diluted, and then it was just like, hey, man, you've got to make a decision here on what your life looks like. Forget about this company. Forget about this investment. You forego going to Harvard to build this company. So you essentially stepped away from this big education, which always like, in the beginning, I was like, this kid's too smart to go to school. Why he should just go start a company. He doesn't need to go to school. As I have kids and I'm older, like, 78 years later, I'm like, Man, I was like the bad uncle. By advising him to not go to Harvard and I'll do this company with you, gasped him up. Right. I think he should have went to Harvard in hindsight, but again, diluted all the way down. He went out and found Amped, the business that Jeff was running at the time that I actually, man, I looked at in 2015 and almost did a deal to own half of PR lotion and the Amped product because of how much I believed in the IP of what they developed, because it was built through this biopharma group that I was doing deals with back in 15 in my early days of hustling. And they merged. And in that merger, then they did a deal. Now they're joint companies that the whole company becomes momentous, and then they lock in that humor bin deal, and then the business exploded overnight. Overnight. Wow. \n\nSam Parr (0:14:56-0:15:45): We all want to feel better and be happier and have more freedom, and there are endless resources at our fingertips, but waiting through a sea of self help books and podcasts and workshops takes more time than you've got. So you have to check out self helpful with Kevin Miller. Kevin is a pro athlete, peak performance expert, published author, and personal development guide. He invites today's most important influencers and changemakers to grapple with their own wisdom and stories in authentic, relatable conversations about self improvement and what drives them from personal fulfillment and work life balance to spirituality, relationships, motivation. Each four part series distills the guest's greatest wisdom and methodologies into practical steps that anyone can integrate into their life. Tune into Self Helpful with Kevin Miller to elevate your personal experience and improve the way you show up for others. Do you know how much did it grow by? \n\nRob Dyrdek (0:15:45-0:16:42): Man? Like 20 times. Right. It is now poised to now make a real run, and I would attribute it to the one for one media to consumer that Andrew Huberman was to the product. Right. So we could never find an audience. It didn't matter how much ad spends we did where we spent it. We had deals with NFL teams and MLB teams and all these athletes and all this stuff, but it was when it finally landed with someone whose core media is their authenticity in the science side of human optimization. Then he's saying, hey, Andy has this massive platform. Then he's saying, this is the very best supplements, because they are, in fact, the very best supplements. When you tie those together, boom, that thing goes. \n\nShaan Puri (0:16:42-0:16:44): That's an amazing story. \n\nRob Dyrdek (0:16:44-0:17:13): What do I have now? I don't know. What do I have now? Like, 4%, you know what I mean? So now call it nine years later, I already gave up on the brand. Don't even claim it. Looked at it when they merged as an exit, and now it's just, like, completely exploded. And yes, I'll get a return on my 300,000 that would be significant to probably a regular investor. But for me, in the co founding. \n\nShaan Puri (0:17:13-0:17:14): Game could have been. \n\nRob Dyrdek (0:17:14-0:17:39): I looked at selling that business for 100 million in under five years and having 20% of it when I measured that out in 16 versus selling it eight years later and making a million dollars wherever, I end up getting diluted on the end and like, okay, cool, you got like two and a half times your money. But that's not why you play the game of venture creation. \n\nShaan Puri (0:17:40-0:18:05): I think that was my perfect that might be the favorite story that's ever been shared on this pod for a couple of reasons. One, you told it great. Two, it had all the drama, the elements to it. And three, you're very honest. Most people that come on this pod were like, how much did you put in? They're like, handwave it's doing well now. And then they're like, yeah, it's doing well, but they won't say that last part. Which is like, yeah, but it's been eight years, I got diluted. And honestly, I'll make kind of fuck all on this. \n\nSam Parr (0:18:06-0:18:06): Really? \n\nShaan Puri (0:18:06-0:18:55): The game I'm in, that's good. But the game I'm in is to create X very honest. I want people to appreciate that because we've done 100 plus guests of people that are from all walks of life, people that are post economic, they already made it. They have no incentive to not fully be honest with the situations. And it is very rare to hear that. So I really, really like that. I got two follow ups for you on things you said there. The first is you said you kind of think maybe he should have gone to Harvard. And I think there's an interesting question that applies to a lot of people, which is like, should I go to college? I kind of feel like people who make it, they're like, that's not where you learn it. You learn it in the real world. It sounds like you were kind of in that boat, but you said you change your mind as you've maybe matured or with your own kids. What's the thinking there? He should have gone to Harvard because the company wasn't working? Or you came to appreciate something else about the value of college. \n\nRob Dyrdek (0:18:56-0:19:08): I think I've come to appreciate the value of college above all. And as someone who quit high school and started his first company at 17, you know what I mean? I think about the but do you. \n\nSam Parr (0:19:08-0:19:12): Appreciate college or Harvard and top 20 colleges? \n\nRob Dyrdek (0:19:12-0:20:53): Well, Harvard obviously has a higher level of prestige. But what I never understood, even back then, was the looking at business in a multidimensional way. Learning everything about business, understanding product and supply chain, understanding brand and marketing and customer acquisition, understanding management and hiring and teams and understanding sales and then understanding operational side. Really understanding the financial side, knowing that all of those have to integrate into a financial model that you've got to believe you can execute. Because that's how a business actually becomes successful is when you project what you're going to do when you actually do it. Not project a fantasy so you can raise money. Right. And I think that going to business school, you at least leave with the fundamentals of that and have a general knowledge that when you step out into the real world and really try to build a company, you're at. Least going to have a foundation of what you're launching off of versus what he did. What I did when I was launching all these companies when I was young, all the way into my 30s. Or what he did at 18. You have such little general knowledge of how it all works because you're such an optimist, especially when you're really smart. You can figure things out fast, but there's just too many things that you don't know when it comes to the complexities of building something like a business. \n\nShaan Puri (0:20:53-0:21:26): Right. And then my second question was, this is a little nerdy on the protein side, but how did you actually go about creating the cleanest supplement? Because I've thought about this many times, which is there is definitely a market for people who want the highest quality, purest grade, best for you product and they'll pay the extra $20 per bag to get it. And when you look I think the supplement industry is notoriously dirty. The places where they make stuff, if you test these things, they don't turn out very well. So did you guys do anything radical to actually achieve that result? Or was it just finding the right partner? And then that was it. \n\nRob Dyrdek (0:21:27-0:22:40): It was first, like, the people who helped develop it, right. We're all like trainers for the 49, ers and the Celtics. Right. Then it's all the certifications that make the I can't think of their exact name, like Grass and Info Sport, whatever, these intrasport, whatever they may be, but these certifications that are very expensive, right. So now the layer of what does that do? Man, that just keeps putting pressure on price and margin, because there's just a certain point where it's like, man, it's so expensive, more expensive. Do even the people that really care, is it making enough of a difference for the absolute premium? And to me, absolutely, we'd find a consumer. And that consumer never showed up until Huberman said to that audience which converted Sam, and now has Sam talking to Jeff. It's like that level of authenticity, the product backed that up, but we never found that level of media that could validate it to reach a large enough consumer base that would be willing to pay that extra amount of money. It's a dice roll when you launch a business to do it like that. \n\nSam Parr (0:22:40-0:22:42): We need to get in the certification business, I think. \n\nShaan Puri (0:22:42-0:23:11): Yeah, that sounds like the real business. This is cruelty free certified inc. We will certify everything for you for the low, low price. By the way, it's funny that Joe Rogan is like Bro. Oprah. But now Tuberman is like Dr. Phil or Dr. Oz or something of this. Kind of like the guy media game where if the doc says this is the way to go, if he says this is clean, he can move a lot of product, like an unbelievable amount of product in a short amount of time. \n\nRob Dyrdek (0:23:11-0:23:59): But look, it's like when you think about the depth of him and how he approaches it, you know, how deep it is. So it's like he's earned that respect from you. You don't question whether or not Nike is going to put as much effort and innovation as they possibly can into a running shoe. You don't even look into the technology. You pick the color and which one feels the good. You know, that they're going to do all the work to get it there. Developing that level of authenticity is incredibly difficult because there's a lot of other people that are Huberman esque that do not have his depth, which in turn does not allow or his process that you believe in, which in turn doesn't allow them to carry the same weight that he does. \n\nSam Parr (0:23:59-0:24:05): And that was probably just a straight cash deal when you guys bought that ad spot, I would imagine, right? \n\nRob Dyrdek (0:24:06-0:24:28): Yeah. I'm not entirely sure I was involved in the company at that point. I'm not entirely sure what his deal is, but whatever it is, he got underpaid whatever it is, it was too little. Look, I am not privy to what it is, but whatever it is, they got a deal, you know what I mean? \n\nShaan Puri (0:24:29-0:24:39): What are some other venture creation that you've been up to? That was one amazing venture creation story. You got me hungry for another. Do you got any other interesting things you cooking? \n\nSam Parr (0:24:39-0:24:43): And how many have you even done? You've done dozens of these? \n\nRob Dyrdek (0:24:43-0:26:19): Yeah, I've done a bunch. I've done a bunch. You know what I mean? And here's the beauty of it too, is, like, I've made so much money that you can play the game more honest, but you're judging yourself off of your IRR. But once you get to a certain point, you're playing the game for the speed of the IRR and the scale of the IRR and its potential. Because when I started the game, I wanted to build 50 to 70 companies and make own 25 to 35 and sell them for between 50,000,150 million and make 20 to 30 each. But when you sell a company for 200 million and get 150,000,000, you're like, well, that's way more fun. How do I move this number from 15 to 30 million a deal to 50 to 200 million a deal, right? You just begin to change as you're sort of evolving and what, do less deals you want to do less deals, right? And then you want to be much more focused on the opportunity and then focused on all the lessons learned. Would I start a supplement brand with an 18 year old ever again? I would not. You know what I mean? Let me give you an example of an opposite version, right? So I was approached by a really seasoned CEO who had just built a company and sold. It was a footwear brand called Great. Okay. \n\nSam Parr (0:26:21-0:26:23): I also owned a pair of those, man. \n\nRob Dyrdek (0:26:23-0:29:11): Right? So you understand him as a brand and him as a brand builder and as a CEO. And he had an idea he wanted to share with us, and it was in the beauty space, and he essentially presented to us this concept of filtered shower water is this overlooked cornerstone of creating your beauty routine. Like, your water is filled with all this garbage that dries out your hair and dries out your skin and does all this stuff. Yet for some reason, no one's approached beauty and filtering the water. Right? So we do all the and again, so, okay, wow, this is super interesting. Then now you look at it from a business model, right? Then it's like, oh, wow. Now it's reoccurring revenue. So it's a single bit of hardware that now the filters have to be replaced. So now you've got this reoccurring revenue. Now it's a super experienced CEO that has a depth of knowledge in DTC. So it's not like a lot of times you'll find an experienced CEO that came from retail who just, oh, I want to build an Amazon business, right? Because retail is so hard. Anytime you find people trying to transition to what they think is an easier way to create sales is always a red flag. But again, now he has the understanding, the knowledge, and now it's like, is this space valid? So we do the research. What do we do? We go and look at the entire space of all of the filtered shower heads, the entire market. It is tiny, tiny, tiny, under a billion dollars, right? And he wants to charge $135 for the unit, $35 for the filters. You can go to Home Depot and get a shower filter for, like, $19. There's, like one premium one that's sold by a beauty company that's kind of chromey or whatever. That's like $99, $100, but no movement. And so when you look at that opportunity, you look at it like it's as clear as can be, where it's like, man, this is either pure white space and there is a real opportunity to make this matter in beauty and make a massive business, or it will literally just not work. It is so pure. But then the tantalizing side is, well, boy, if it works, man, think of the friction it takes to get a shower head in. But, man, think of how low the churn will be on the subscription because it'll. Be way more friction to take it completely out, to stop your reoccurring, like subscription every two months and put back your old shower head that made it this incredibly compelling concept. \n\nSam Parr (0:29:12-0:29:24): And by the way, for the listener, this is basically your showerhead. I don't even think most people know this, but the showerhead, it's not that hard to remove. You can kind of do it yourself. Jolie. Is this jolie? Is that how you say it? \n\nRob Dyrdek (0:29:24-0:29:25): Jolie. \n\nSam Parr (0:29:25-0:30:10): Jolie. And basically they give you because I've seen this company, they killed it in year one. I think they did 4 million in sales in the first year. Basically, they send you a thing, a new showerhead, they send you a wrench. You put it on there, and then you put little, like, filters and packets, and I think they smell nice or something like that. And they might have some type of other good stuff in there. But the premise is that for all the really hardcore health nerds, they're afraid of some of the chemicals and minerals that are in city water. And so they want this to be better. And I have friends that have, like what's that one charcoal water filter that's made out of metal. They do that for their home. They do these really $10,000 projects for their home. And what this product is, is that for a showerhead? Did I summarize that? \n\nRob Dyrdek (0:30:11-0:30:29): That's correct. And it's the efficacy of it. Right. And then how did they launch the company? How were they able to go to 4 million and now this year they'll do close to 40 million is that they opened it up by putting in your zip code so you could see all the contaminants in your water. \n\nShaan Puri (0:30:29-0:30:29): Nice. \n\nRob Dyrdek (0:30:30-0:32:02): So how they did all their initial customer acquisition is they got all the data of what because the water departments have to report all the contaminants in the water. And so they scraped all that data you put in your zip code, and then you got a complete report of all the stuff in your water. That's how they did customer acquisition for months before they even had the product out. You know what I mean? Then they did preorders before it launched. Right? Then what were we all hanging on for? What's that first quarter of churn? The churn was at like 1.2% of the subscription. It's like everything about it. And then it was just growth month over month over month. Then they just keep evolving. They launched an Airwon in the grocery store. They have a giant display, and you can buy them an Airwan, right. It's like the entire process of how they did it overnight. Because you got to think, how do you value a business like that? That business is valued at 200 million plus in a year and a half, because how do you really look at that, where it's like, yes, it's selling hardware month over month, but then it is stacking subscription dollars. So it is this extraordinary hardware subscription service that is incredibly rare that has made it so valuable. Overnight. He built the company with three people where the primary investor? It's profitable and never raised another dime ever again. \n\nSam Parr (0:32:03-0:32:06): Chef's Kiss, what size check you do on that one? \n\nRob Dyrdek (0:32:07-0:32:10): Yeah, I did 800 in that one. \n\nSam Parr (0:32:11-0:32:13): That's substantial. Right. \n\nRob Dyrdek (0:32:13-0:32:23): For an early stage startup, I'm all over the place, but I'll go up to 10 million, you know what I mean? So when I think 800, I think it's, like, kind of small. \n\nShaan Puri (0:32:23-0:32:29): What's been the biggest bet? Like, where have you plowed in something like 10 million into? What type of bet was that? \n\nRob Dyrdek (0:32:30-0:33:48): My professional skateboarding league, my production company, merged with Nitro Circus and created Thrill One Media. And then we sold Thrill One Media for 300 million, of which we got 200 million. Right? And this was sort of like the layering in of my production deal. And then the group that bought Thrill One, I invested 10 million with them to buy me and then did a separate deal as it relates to having a bigger stake in the production company that I sold and my league and the overall sports property. Because I knew during that transaction, I knew I was going to negotiate for a bigger television deal. So I basically leveraged my ability to go and get a lot of value for the company. So I got all this equity back. They just paid me close to 200 million. So I used ten of it to invest in buying me so that I could turn around and hopefully make another not nearly as much, but hopefully like another 100 to 150 off of it a couple of years down the line. \n\nSam Parr (0:33:48-0:33:55): When you say we, is that like Deirdre family office or is that you don't have a fund, right? Yeah, it's just your family office. \n\nRob Dyrdek (0:33:55-0:36:27): Just my money, yeah. No, this is all my money, and I just run it like a family office. And I just look at that as where I would deploy venture capital, right? So if I just deploy capital into real estate and ventures that I have a much more control over and or I have a higher leverage or position. But it was amazing. Think about this. In the closing of the deal, it was the most money I made in one shot, right? And the most like, I had invested at one shot in a venture. So with the like, here on my closing that deal in the Zoom call, it was the most I made and the most I invested in one. Here, here, whatever. My final check off on was it but again, what are the stakes of it? It's whatever, you know what I mean? I look at it as it's fun. And I'm underwriting the business because I went and signed a massive television deal. So I'm underwriting that entire roll up. And it's amazing. Partners. It's Dana White and the Fertita family who owned the UFC. So it's like even being close to them and knowing them for so long just makes the joy of even partnering with them fun and exciting. And I dedicate very little time to it, right? Like, I still help sort of adding the vision and how to continue to evolve it and grow it. But I continue to shoot television at an even much higher scale. Like, now I'm shooting 336 episodes a year, up from 252. That's still at 4% of my time. That's essentially 5 hours a day, four times a month for ten months, right. Is essentially what it is, but it's underwritten the entire roll up. It is a billion dollar television deal over a seven year period. With the production and everything involved, I get all my talent money, but then I'm also leveraged into the roll up in the production company again to sell it again, and it's just squeezing water out of a rock. You know what I'm saying? It's like you're looking at opportunities inside every deal. There just isn't a world where I'm just looking at, like, where are the ways for me to add leverage, create opportunity in each one of the ways that I look at every one of these deals each and every time. \n\nShaan Puri (0:36:27-0:37:01): Who are some of your business advisors, mentors, friends that are helping you develop this muscle? Because anything you want to do, you go from a white belt to blue belt, eventually you can become a black belt. And it sounds like when you started, you were more of a white belt, like, everybody. And now looking at structures, looking at ways to double dip, looking at ways to measure, okay, I want IRR, but also I should be thinking about the gross dollar amounts and maybe fewer deals, but bigger deals. Who have you learned a ton from that you respect either as a friend or a mentor on the business side? \n\nRob Dyrdek (0:37:01-0:39:01): Man, I don't think anybody plays the game like this that I know that's in my circle. I think it's that experience, and it's that continually looking at every deal multidimensional, right? And I think the gift that I actually had early on is I used to look at media and marketing multidimensionally, right? So in the early days, I would be able to look at a television show and how are all these ways that I can monetize it, right? Like, how do I own the rights of media? And then I could sell that to different people. I always looked at opportunity multidimensionally, but I didn't understand how to build and create value in business. So I never looked at business multidimensionally. And I just think once I taught myself, really, how to look at business holistically and how to create and build businesses to sell creating value, that then I began to look at. How can I see all of the opportunity in these different angles in order to create the most value for myself and a lot of times underwrite risk, you know what I mean? Like if I didn't know I was going to go and sign that mega television deal, I wouldn't have put into 10 million. But then I said, well what if I go and sign this deal? How much additional equity will you give me for my 10 million? Right? Then they're like, oh, if you go and get that deal then we'll give you twelve extra percent, you know what I mean? Then it's like I just literally overnight made my 10 million worth like 60 million and underwritten it off of a deal that I'm going and making hundreds of millions of dollars to just do. And at the end of it and keep in mind through all of this I work less now than I've ever worked, you know what I mean? Through optimizing my time and getting more and more efficient of how I use it, I work at about a 40 hours week to manage my family office, all of my venture portfolios and shoot television and a podcast. \n\nShaan Puri (0:39:01-0:39:13): What do you think you're worth at this point? So you have liquid and you have obviously illiquid. What do you think the N word the net worth is at? And do you have a goal with that? \n\nSam Parr (0:39:13-0:39:20): And last podcast you go, I need to be a billionaire like I deserve. So yeah, where are we at? You remember that line? It was a beautiful line. \n\nRob Dyrdek (0:39:20-0:40:28): No, I don't. But that's really funny I was doing because you got to think in between our last call, I hired an amazing CEO that came from a family office structure. I needed somebody that understood business but understood sort of the dynamics of a family office, but was also young and excited to go on a journey to a billion dollars, right? And so I have modeling for just my cash flowing assets that take me to a billion. Forget about any of your venture stuff and building out sort of your pathway through the business side. I have modeling out to the year 2050 that I have fully integrated on all asset classes that I'm even investing in now. Where do you make the billion dollars? You make it either slowly over time at compounding or in big chunks. Right? So if today my net worth of all of my assets is a little just under 350,000,000, right? That the pathway there's, the slow long pathway to a billion. That's easy through compounding, right. \n\nSam Parr (0:40:29-0:40:32): What do you assume? Just like seven or 8%, correct? \n\nRob Dyrdek (0:40:32-0:42:30): Right. And with the buildings now you got to think about the way the buildings work and the real estate work is I'm getting five to 6% cash, like tax free cash, but I'm still getting seven to 10% equity growth over the long term. And some of those are call it with the cash, 15, 16% IRRs. But a lot of the buildings that I've sold, I ended up with like 35 and 42% IRRs. And what do you do with that? You 1031 exchange it and you get new buildings on an ongoing basis so that real estate, even side of it is compounding in a unique way. And then with my cash money markets are giving you 5% right now, close to 5%. And then I keep a significant amount of liquid dollars in sort of nouveine high yield funds that kick off around a blended 10% that aren't going to grow. But you get cash for your cash. You're making so much cash off of your cash, then you're making so much cash, tax depreciated cash off of your real estate portfolio. I look at that, I call it the modern cash flow portfolio, where it's just that cash is underwriting the expense of my life in the family office, right? And so when I have these big exits and when all the money I get made from TV, I look at all of it through the lens of how much am I actually making post tax per hour. So, okay, it seems like I'm making a lot shooting television so efficiently and how much time I actually work on the deer to machine and the actual venture side of the business when you look at long term capital gains versus ordinary income. But boy, when you look at the amount of time I spend on that cash flowing portfolio and real estate, it's a couple of hours a year. \n\nShaan Puri (0:42:31-0:42:46): What do you have as a dollar per hour goal? What is good for you, what is bad for you, right? So everybody has if I do something that saves me $100, I go return a blender to the store. That wasn't a saving of $100. It was a loss. \n\nRob Dyrdek (0:42:46-0:44:25): I'm looking at a million an hour as the goal. You know what I mean? That's your goal as it relates to energy and effort that's put into it, right? Because it's fascinating when you look at how much money I make from television and then what that ends up being post tax and fees, even though it seems like a limited amount of time because it's only 4% of my time. But seeing all of them through that lens, it's a way more interesting way to view it all, you know what I mean? And again, it goes back to time because what life do you want to live, right? Where do you get time? Where can you buy time back? But ultimately, where are the places where you make the most money and people don't believe in them? Like this idea of passive income. Passive income is not buying a building that you've got to operate and you're constantly dealing with, like trying to keep it rented and things breaking and trying to make decisions. That's not passive income in real estate. Passive income is when you give money to an operator and they give you cash back for your money. That's when you're doing nothing. Now, what you have to get good at is evaluating rules and creating principles for the type of operators you'd be willing to deploy capital with so that you know that they're world class and that what they say they're going to do. That they do, which in turn, all you're doing is reading statements and putting a little bit of time to think through strategy, future strategy, a few times a year. That's the difference on the way you choose to get into an asset class. \n\nSam Parr (0:44:25-0:44:51): And based off of the last pod, you were saying how I think you're 47 now, right? I think you said into your late 30s, you'd screwed a whole bunch of shit up. I think when you were trying to raise money from I forget the VC or PE company, but you were raising money for something, and you're like, dude, my business sucks. I'm losing money. Turns out I was wrong. So does that mean that the vast majority of your real wealth creation has been in the last ten years? \n\nRob Dyrdek (0:44:51-0:44:54): No, in the last few years. \n\nSam Parr (0:44:55-0:44:58): But you were broke. \n\nRob Dyrdek (0:44:58-0:45:07): I would consider myself broke. I would say I started from zero almost in 2016 when I launched the machine. I wouldn't say debt broke. \n\nSam Parr (0:45:07-0:45:10): I mean, you're a millionaire. Were you worth at least ten? \n\nRob Dyrdek (0:45:10-0:45:15): I would say I was probably worth, like, 15 or 20 in that zone. So not broke. But to me, I was like, Bro. \n\nShaan Puri (0:45:15-0:45:18): To a future billionaire, a millionaire is broke. \n\nSam Parr (0:45:19-0:45:28): Yeah, but he described it. He was like, in my 30s. He's like, I spent this. You said phrases like, I had nothing. \n\nRob Dyrdek (0:45:29-0:47:08): But I would tell you that the majority of this wealth was all created between 2018 and 2022 over that four year period. Right. And now it's exponentially scaled. Right. When I think about sort of how I very conservatively value the ventures that get me up to the 325 zone, I could easily say those push me closer to four. Right. But it's also like, then, okay, how do I want to continue to create bigger opportunities in the future? Because I'm always, like, five years into the future, the same way I understood in 2016. Here's the strategy. The strategy worked, only it was bigger than I anticipated. Then all these other additional things had happened. I had the clarity of, like, this is what I was going to do. But then that clarity. The universe conspired to create more opportunity that I capitalized off of and got to this scale that I could have never imagined in such a shorter amount of time. And all it does is make me see further and clearer on how I can get the scale even bigger. Which leads me to believe, compounding, I become a billionaire over time. But I believe I can create some ventures, including the software that I create and the platform that I want to build to speak to that core audience that I believe I will be able to monetize it at a much higher scale in a shorter amount of time with my existing portfolio of assets. \n\nSam Parr (0:47:08-0:47:29): And if you Google your name, you'll see, like, you went on a little bit of a buying spree where you're buying, like, I think, four really nice homes in La. But I thought there was a quote saying, you're not going to live there. That's rentals. A, is that true? And B, what type of real estate are you actually buying that you consider cash flowing real estate versus just personal? \n\nRob Dyrdek (0:47:29-0:47:32): Yeah. So I would never buy a house of rent. \n\nSam Parr (0:47:32-0:47:40): Yeah, I didn't think so. I thought it said that maybe it was, like on the what's it called? Like the dirt or like the real something like that. \n\nRob Dyrdek (0:47:41-0:49:52): Yeah. Really? What I did and this will give you an clarity on how much money I had and how dumb I was in 2015. Okay. I had met my wife. All I wanted to find was a forever home. I had realized in 14, like, I had began to develop learning everything about business and everything. You got to think in 2013, I was dumb as dirt. I was at the bottom. I didn't understand business. I didn't understand anything. I hired all the consultants and all the groups and began to formulate everything I needed to learn to speak the way I'm speaking today and the strategies of what money is, where do I want to invest it. Never even heard of multifamily units in 2014. Right. I then took all of my money. At the time I had all the money I had to my name. In 2015, it was $12 million in cash. Moved it all to cash because I had money in all these different brokers. It didn't know what it was. Here I am in 2015 with a vision for how I'm going to create a venture studio, the Deer Deck machine and the whole thing. And I'm looking for a forever home or a place to buy, and I find the most heaven sent piece of land that God has ever created in a gated community in Beverly Hills. That is this gated community to a private road to a four acre promontory with unobstructed views of the entire La Basin Hollywood, sign of the most extraordinary property I have ever stepped on in my life. And paid 10 million cash for it. And then took launched this dream with 2 million because I was like, oh, man, this is my destiny to build a house and live on this land forever. \n\nSam Parr (0:49:52-0:49:53): It was just land. It was just land. \n\nRob Dyrdek (0:49:54-0:51:06): Just land. Call it forever estates. And I have since. And so in that neighborhood, like where it is, I have bought multiple houses and remodeled them in the neighborhood while I continue to design Forever Estates, as it's called, and kept it all these years. Carried the cost, 200 grand a year. Just to carry it spending. Like, built a whole designed a whole house of the architecture team, fired them, hired Seyota, the best architects in the world, out of South Africa. And we have just been designing and designing and designing. It was part of the vision of, like, I'm going to spend the rest of my life in Forever Estates. That's where I'm going to live. There is no better piece of land in the city of Los Angeles. It's the most extraordinary home. I rented a house for three and a half years, bought a house for 6.5, sold it for, like, nine, five, two years later, after remodeling it, bought another house for eight, put 2 million into it. This house that I'm in now is two doors down from the entrance to Forever Estates. So when I begin to build it in the fall, that I can be there every step of the way. But what happens? \n\nShaan Puri (0:51:06-0:51:15): Hold on. Begin to build it in the fall? How long are we of timeline are we talking? This has been eight years and we're beginning to build it. This is the Forever Take Forever Estates. \n\nSam Parr (0:51:15-0:51:16): Yeah. \n\nRob Dyrdek (0:51:17-0:52:29): What does the world say to me? They're like, this is crazy. And I'm like, man, I'm going to live there forever. And when I build it, I don't even want to think about the cost. It's going to cost me 20 million to build. I don't even want to think about it. I needed to get to generational level wealth to even like, I didn't want it to be a burden. That's why I kept buying houses and kept working on the design. And then now you've gotten to such a scale. What's the strategy now? Well, I'm putting it into a trust. I'm paying cash for the house to build it, and then I'm going to pay rent to the trust, and then it's going to build an endowment so that this home can be in my family forever. But run it be self operational so it doesn't have to be tied to the estate that it will be ran. And then there can be family meetings in Forever Estates for hundreds and hundreds of years into the future. Right. And you can't even get to that way of thinking unless you have kids, unless you create generational wealth, unless you get to that time. But that all happened over five year period. That is an extraordinary transition to go. \n\nSam Parr (0:52:29-0:52:32): It started with a horrible decision. I mean, ten. \n\nRob Dyrdek (0:52:35-0:53:40): Look, I could have put ten think I'm going to say, you know how much money I had invested in buildings in 2015? 100,000. 100,000. I had invested 100,000 and was making seven G's from that one. Instead of putting 10 million into a cash flow, which I would have been set for life if I would have put that 10 million into the buildings that I put back in 2015 that got like 40% IRRs, and we're kicking off like 9% cash, I would have been set for life from the compounding and the cash flow of that one thing. Oh, no. I took ten, put it straight into a liability, saying that now I'm carrying the cost of paying the taxes and double homeowners fee because it's a double lot. So I'm just carrying 200 grand a year. And then I'm paying all these architects on an ongoing basis to continue to design and develop. It absolutely ludicrous. \n\nSam Parr (0:53:41-0:53:56): You're amazing. Are you taking adoption? I think you're 15 years older than me. I could be your teenage yeah, I want to go to Forever Estates, man. Forever Estates for you is going to be more like a decade estate. It sounds like the way it's taken. \n\nRob Dyrdek (0:53:57-0:53:59): And look, even hey, if it lasts. \n\nShaan Puri (0:53:59-0:54:01): Forever, what's a decade, man? \n\nRob Dyrdek (0:54:01-0:55:05): That's a drop in the bucket. But think about it. It seems to me it's just another part of seeing my life completely and multidimensionally, because it's like it's my relationship with my wife and kids in time. It's the health that I have. It's how every part of my existence has continued to expand and get better. I didn't get better in just business. I got better in all aspects of my existence on an ongoing basis. So that house, if I would have built the house I designed five years ago, I would have been so bummed because I got every six months, I would get a completely new design, get it in VR. And as I changed and thought about and got clear on what I wanted the future to look like and how I would want family meetings here in 200 years, it allowed me to keep evolving. And keep evolving to where when I finally got to this point where I'm just about to get the final permits, it feels right on time to me. \n\nShaan Puri (0:55:05-0:55:06): I love that. \n\nRob Dyrdek (0:55:06-0:55:42): Right? And it's like I'm healthier, happier, wealthier, wiser. And I know that I'm just going to get healthier, happier, wealthier and wiser till the day that I die. And right now, what's my goal? 1 million hour of life. 114 years and 54 days. So where am I spending a significant amount of my wealth understanding every single aspect of my body and having a very deep longevity plan that allows me to enjoy life and live it at a high level at the ripe old age of 112? Someone get to 114, just fall off a cliff. \n\nShaan Puri (0:55:45-0:55:51): Oh, my God, Rob, you're amazing. So I was going to ask you about longevity. Like perfect segue, right? \n\nSam Parr (0:55:51-0:56:20): Yeah, I want to ask about that too. And what I was going to say is very similar to that, which is when I sold my first business and had my first bite of financial success, I was able to get physically fit. It was definitely a little bit easier. I could hire some people, but also I felt a little bit more calm and I had more time. Is this new focus on longevity and focus on all this stuff. Is that because you now are financially successful and have more time? Or do you think that you always had this bug and what are you doing now, health wise? \n\nRob Dyrdek (0:56:21-1:00:15): I have been doing it nonstop for as long, for 20 years. I got my first blood panel and started optimizing into my blood work in 2012. So for me, where a big transition was in 2015, around the same time, I had made the decision that I was in the best shape of my life, but my body was always achy. And I had made this decision that I started having a doctor come to my house five days a week, and all I wanted to do was build a perfectly structured physical system. And there was no timeline to it. And really what it led to is triangulating, a ton of different therapies, but in the process allowed me to learn every muscle in my body how the fascia system works, what are my neurological deficiencies? What are all of the things that I need to retrain in my overall system internally as it relates to leaky gut and blood, brain barrier, all of these sort of things that lead to inflammation, that lead to heart disease, and all these different things that reduce your quality and length of life. I had been doing over a decade. So now the way I approach it is so sophisticated because I know every single aspect of my entire function holistically of my body, my mind, my time, my energy. So it's a different level. So what happened when I got to this scale of success? I refer to it as peak top. It's the same psychological chaos that happens to a drug addict at rock bottom, where you finally make shift in you, where you can't be a drug addict anymore and something shifts in you mentally. It happened to me on the other side where you started getting more and more disciplined and healthy that you all of a sudden were like, why would I ever not just be extraordinarily healthy for the rest of my life? And what happened from that point? I have not missed the day of getting up at 05:00 a.m.. I have not missed a day in the gym. I have not missed one day meditating. I have not missed one day eating supplements, eating clean. I have not had a drink. I haven't had any sugar. I haven't had a snack, any of that since I hit that like nine months ago. The data that I shared with you guys as it relates to the quality of my life numbers, how I feel about my life work and health, zero to ten. And then my discipline numbers, what percentage did I get up at? Five brain train meditate, get in the gym, eat clean and not drink and take my supplements. It is 100% across this entire year. And then my qualitative. Numbers are at the highest they've ever been. So every single day I wake up feeling extraordinary, right? And I grew into that. And then the more success I had, I didn't have to then decide I want to be healthy. I had been working in 2016 when I designed my vision for my business and my financial success. I designed a vision for my life success and my health success. So what happened over the last seven years is I got better and better and better at all of it, which led to this euphoric state of where you have an incredible depth of knowledge of your entire reality and your current state and your future state. So you're just continuously predicting the future and creating higher probabilities of being healthier, happier and wealthier in the future while living extraordinary in the present. \n\nSam Parr (1:00:15-1:00:22): What's been like the 80, 20 of that? Like, the things that have made the biggest change on your health. \n\nRob Dyrdek (1:00:22-1:01:11): I mean, look, not drinking, not eating sugar and intermittent fasting and eating a lean protein and vegetable meal, to me, is everything. Is everything. Because your body begins to clean itself. You feel better about yourself. You make sharper decisions. You go two layers deeper. Your emotions are more in check. Like, things happen inside the family, different things that are uncontrollable. You're able to control all of those better. That just pure diet alone. In avoiding all of these processed foods and alcohol, in being committed to that, will absolutely change your life because it gives your mind more depth to be able to execute at a higher amount at a higher level in the limited amount of time that you have to execute. \n\nShaan Puri (1:01:11-1:01:14): Sir, have you seen this guy? Brian Johnson? What he's doing? \n\nRob Dyrdek (1:01:14-1:01:24): Look I look at Brian Johnson as this guy's outrageous. It's too much. But I withhold my judgment because if I would have told myself five years. \n\nSam Parr (1:01:24-1:01:25): Ago, hey, this is what you're going. \n\nRob Dyrdek (1:01:25-1:01:35): To be doing, I'd be like, that guy's crazy. So I look at I feel like Brian Johnson's crazy, but I'll probably turn into Brian Johnson in like, seven or eight years. \n\nSam Parr (1:01:36-1:01:38): He's wild, man. He's wild. \n\nRob Dyrdek (1:01:38-1:01:44): Yeah. Brian Johnson just has that look, you know what I mean? He looks like a futuristic, like, amoeba. You know what I mean? \n\nShaan Puri (1:01:44-1:01:53): That's what I was thinking. I looked up the other day, I'll go, all he needed, all he needs to do is tan. If he tans, everybody like, this guy's amazing. He doesn't tan and they're like, you're a vampire, bro. \n\nRob Dyrdek (1:01:54-1:02:03): He looks like AI. All like the new AI versions of people coming out. He looks like an AI. Person. He might not even be real. He might not even be real. \n\nShaan Puri (1:02:03-1:02:05): He's a mid journey. \n\nRob Dyrdek (1:02:05-1:02:46): But I do look at that aspect because you've got to think about anything. Think about the way that I talk about business. It's knowledge and experience and an understanding, and then a continual evolution and growth of understanding the whole, like, applying that to my relationship with my wife and family, applying that to my health, applying that to business, applying that to investment, applying that to building my family office. All of that way of thinking is based off of gaining knowledge. To take something from not understanding in it, feeling difficult, to then making it easier, then continually optimizing it. Right. You're just incrementally making it all better. \n\nShaan Puri (1:02:46-1:03:31): I love the way you think, and I love the kind of pursuit of greatness and pursuit of excellence for yourself and having a vision for yourself. I also know that it's inspiring but also hard to relate to perfection. And so I'm curious, what are the current flaws or bugs in your software that you're still debugging? We all have some bugs in our software that's running. We're hunting them down, and we're trying to squash them one at a time. What are some that are still in your system? It might be in business. It might be in health. For me, a nice bag of chips is still a bug in my software. Maybe something sometimes when I'm with my wife, I'm not as present as I should be. I'm on my phone, but I know that's not really me and who I'm going to be, but I'm still catching up to myself in that way. What are some of those for you? \n\nRob Dyrdek (1:03:32-1:03:37): And this is going to sound like extraordinarily don't say it. \n\nShaan Puri (1:03:37-1:03:42): I tried to help you, man. I tried to serve you up a way that you vulnerable here. No. \n\nRob Dyrdek (1:03:42-1:03:43): Again. \n\nSam Parr (1:03:46-1:03:49): I'm not racist. But this is like your teeth. \n\nRob Dyrdek (1:03:50-1:07:37): Yeah. No, to me it is. I still get triggered and will get angry when my expectations are mismanaged at a high level, I'll get mad and get in Snap. Right. I'm not even kidding you. Even when I get triggered, I'm trying to stop the triggers to avoid saying something like letting it come out. Right. But I still feel the trigger. My goal is to get to don't even let things trigger you. Like, when you let people get angry. But you got to think part of the evolution is like, there's certain people in your life that do that to me that I had to let go of. Right. And continually optimize for those people. And this is embedded in my soul. This is embedded in my soul. When I feel stuck, when I feel stuck, when I'm working on trying to do deep work or doing something and I feel stuck, all I want is pizza and wine. All I want is pizza and wine. It's not even, like, a matter of acting on it. It's like my soul feels like it needs a glass of wine, because whenever I get stuck, it's this psychological thing of like, just fuck let it all go. Let it all go. So even though I don't act on it because I've just evolved beyond it, I still when I get stuck. The feelings exist in there. But I'm telling you, the commitment of where it went 100% health and no alcohol and no sugar in that level, it eliminated so many things. It eliminated me being short with people, it eliminated me, like, making rash decisions, right? Not thinking through stuff and just shooting from the hip, which is a recovery. I used to say, Deirdeck Enterprises, our money's fearless, right? Because I would invest so recklessly when it was really, our money's dumb, but that reckless. Like, let's just push it forward. Let's just start it and go for it is still something that I fight on an ongoing basis because I'll get excited and energized and see it and be like, let's do it. And I've got to control that impulse that I've learned to control in this state at a much higher level, but there are very little. And here's the thing. I look at it as, like, how Kobe was relatable to me because it was too much discipline, and how Tom Brady like, man, why would you not take the offseason off? I used to look at that as this impossible level, and to me, I know that I'm reaching this unrelatable, unattainable place. It's why I put out a podcast earlier this year that was the most unrelatable podcast, part one and part two, because I just laid out the depth of actually how I'm operating and what I've learned along the way to get to this level. Because I want to be the proof that you can get to a place where you never get angry, you never have a negative thought, where you are completely harmonious and balanced in all your relationships and time and health and happiness, where you are happy and filled with gratitude seven days a week, every single day, even under unexpected duress. I'm living it, and I know it's possible. I want to continue to be proof that it is. Then I want to build the products, services, and tools that other people can use to get to this level and this feeling, because to me, it is heaven on earth. It is true. Happiness is really the output of this existence that I've created in a relatively short amount of time. \n\nSam Parr (1:07:38-1:09:05): Let me run this trend by you guys that I'm seeing, and it's related to this. So I live part of the time in New York, most of the time in Austin, Texas, and I also own a ranch out in Texas. And what I'm noticing is that Austin is almost like La a little bit, where we have all types of health freaks. It's really cool to be around those types of people. And I eat really healthy as well. And I'm noticing that my extreme help friends, they're doing something like a redneck family, like where I grew up, what they used to do, which is they buy a cow. So you go in with either you or your neighbor, and you go and purchase a cow and someone slaughters it, and then you get the whole cow for the year. And I noticed that zuckerberg, I think two years ago he made this commitment that he was only going to eat what he killed or I think even grew. And I'm noticing that my health friends are doing this now. And I've seen a lot of tweets recently where people saying, like, you know, I'm eating healthy, but I still feel bad. But when I go to Europe, I feel good. And I did some research. The FDA and the European, the EU, how they measure food, it's a little bit differently, like the preservatives and things. Anyway, I know you're into health now, and I know you invest in a lot of health and wellness stuff. My prediction is that in the next five or ten years, I think we're going to see a couple of brands where you can buy meat online. I'm even seeing people, like, revolt against Whole Foods meat. Do you eat just meat off the shelf from Whole Foods or do you get it from somewhere special? Because I think there's going to be an interesting brand that does this the next five or ten years. \n\nRob Dyrdek (1:09:05-1:09:21): Yeah, look, my meat is not so special to me. How I do it? How do I do it? I get meal delivery seven days a week. Right. \n\nSam Parr (1:09:21-1:09:23): From which brand? \n\nRob Dyrdek (1:09:23-1:09:31): It's just a local chef here that's all organic. Right. Grass fed. And so I get a salad. \n\nSam Parr (1:09:31-1:09:32): Grass fed beef. \n\nRob Dyrdek (1:09:33-1:09:33): Yeah. \n\nSam Parr (1:09:35-1:09:36): It tastes so bad, man. \n\nRob Dyrdek (1:09:36-1:10:46): Yeah. To me, that's my baseline. And then I have breakfast Wednesdays with my wife. I have Friday night pasta with my wife, sunday night sushi. I have sort of the rhythm of dates that I take my wife on. And so when I look at that particular protein, if you will, at this stage, like I look at that as much as I'm willing to dedicate into what's in my body until I can get to a point where the data shows me the impact of having Daisy in the backyard and me cutting Daisy up and slicing off a rib is going to deliver more nutrients. That's going to add to a longer, higher quality of life. I would need the data to take me there one day as opposed to getting that nuanced and the delivery of the quality of that protein, where at this point, for me, that's enough as it relates to what I'm capable and my personal capacity can dedicate to the quality of the food. \n\nSam Parr (1:10:46-1:11:01): I think this is going to be a thing. Sean, have you not know there's a company that just raised money from Peter Thiel? It's called Coop, and they're making the Tesla of chicken coops. So normal people can have a chicken coop in their backyard, I believe any trend. \n\nShaan Puri (1:11:01-1:11:04): Yeah, that the guy. Coop guy. He's the eye crack guy, right? \n\nRob Dyrdek (1:11:04-1:11:04): Same guy, yeah. \n\nSam Parr (1:11:04-1:11:07): AJ. Dude, I'm so fascinated with this. \n\nRob Dyrdek (1:11:07-1:11:16): Look, listen, right now, fundamentally, would you have your own chickens that you slaughtered and ate chickens if it was no. \n\nSam Parr (1:11:16-1:11:40): It'S for the eggs. It's for the eggs. It's for the eggs. Eggs make sense, bro. You just told me that a shower head company is going to be worth billions, okay? And you just bought a $10 million piece of land. You might have an air. In your judgment, things happen. I know your biggest weakness is you sick of the shower, but come on. \n\nRob Dyrdek (1:11:40-1:12:52): Yeah, look for eggs maybe, but I don't know. When you look at trends on an ongoing basis, you refine your lens of the things that were improbable that ended up working when they're harder to see. You know what I mean? I think my even lens always ties back to the probability of the unit economics and the reoccurring revenue aspect of it. I look at it so much more through that lens. Because even when I think about the coupe, if you're selling a single unit hardware now you've got this incredibly small customer base in the very beginning that are the ultra healthy and then it's like a mattress. Like in the direct to consumer mattress game. As soon as they buy one, they don't need another one for 15 years. Right. It would suffer that same sort of consequence versus five years ago. Coop would get 100 million dollar valuation based off of like there's going to be coupes in every house in the world. It's innovation. It's like the Tesla of eggs. \n\nShaan Puri (1:12:53-1:12:53): Right. \n\nRob Dyrdek (1:12:53-1:13:13): My lens isn't as refined and I always go back to how much revenue the idea can create from a long term value perspective versus those tough hardware businesses that are minimal margin and you sell warrant. \n\nSam Parr (1:13:14-1:13:23): So what trends interest you now? What do you think so to be popular in the next five years? And where are you investing your money for? What interesting trends are you looking to invest in? \n\nRob Dyrdek (1:13:23-1:15:25): Yeah, look, I don't invest in anything. I invest in real estate and businesses that I create. And right now, I haven't even invested in a new venture since Jolie. Because to me, I do think when I look out into the future as it relates to the type of stuff that I would do would still be related to biofeedback, health, customization, all of these things that help lead you to optimizing your overall health and well being. I do think you got to think those glucose monitors that sort of come out to kind of give you an indication of what your blood sugar is doing when you're eating food, that they're going to evolve that to eventually become dopamine and cortisol, and it's going to end up being a cornerstone of how your life is actually feeling based off of what your blood is saying in real time. I think that's going to be something that really makes a big impact on the world to me. I want to time into creating the existence management system that helps you manage how all of it fits together to lead to your present moment in time and help you optimize for guiding your life to creating higher energy present moments that you use with purpose. And whether that's to be on your phone and watch TV with your wife because you're tired, or it's for you to be ultra present with your kids so that you can actually experience it, or you want to be able to design use the present to design a better future for yourself. It's really about how do you become this healthy, develop healthy and understanding and the knowledge of yourself. Develop the ultra awareness of everything about you so that you can continually live a consistent state of joy. Because feeling joy over long periods of time is what it creates. The feeling of happiness. \n\nSam Parr (1:15:26-1:15:38): Sean, we could wrap up with whatever you want to, but I know that people in the comments are going to be like, why is that Douchebag bringing up me? What the fuck? I already know they're going to flame me in the YouTube comments. I was just curious. \n\nShaan Puri (1:15:39-1:16:37): Rob, I wanted you to can you finish with a two minute crash course on something I've been interested in and you know very well, which is production companies. So I noticed. I don't know anything about Hollywood or TV production, but my ears perked up when I forgot who was they bought Reese Witherspoon's production company for some hundreds of millions of dollars. Then I saw that Peter Chernon from the Chernon Group, he's doing a roll up of production companies. He's put in a billion dollars to work rolling up production companies. And I thought, oh, that's interesting. I read some interviews and he's talking about why he thinks there's a growing and sort of insatiable demand for content. And then I just look at people who create Netflix shows. I go look at? Oh, love is blind. It's ranked number one on Netflix. Who created this? I was a small production company. Is this like the startup game where you create the next hit show and you become a billionaire? Or is it a ruthless business? Can you just describe what creating a show or creating a production company is like and if that's a good business to be in or not? \n\nRob Dyrdek (1:16:37-1:21:47): As someone who sold their production company for 200 million and who had an offer on the table that fell apart for 400 million recently, it is the worst business that you could ever get in in your life. And I'll explain to you why. It is a shoot what you kill game and the distributors control all of the money. So you have a hit show and you have this flourishing production company, and then the show gets canceled and your company's worth zero. Right? And then the problem with shows is they don't pick them up for long periods of time. I have a five year, one 6000 hundred and 80 episode order of television. It is unprecedented in all of production. It does not exist. But why is it hard for me to turn around and sell that? Because it's one single show. And now they look at the and it's so expensive because it's made the the production company so profitable. But let's just say that didn't push you away. A production company is built like this, right? You've got to build the infrastructure that allows you to have your camera equipment, your finishing equipment, your licensing for your music. You've got to basically then go and give a budget to a network who's going to give you 500 grand for an episode. And now you have got to figure out how to pull 20% to 30% of that in margin, right? So it gets incredibly difficult to do and the only way that you can do that is look at all of the different ways that you can scrape margin out of that budget by owning, vertically integrating. So a lot of times there'll be people that have television shows and they just get paid an executive producer fee, right? So they will make a lot of money. Like Jeff Tremaine, who is one of the executive producers on my show, makes millions off of Ridiculousness and just off his executive producer fee. Nothing. Where we rolled in our executive producer fees then built out the entire post and finishing and music division to push our margins up to be able to create a sellable asset. Then we had multiple shows and then call it the long term sustainability of ridiculousness created the value that allowed us to sell it, right? And so even if you launch a production company and you have Love is Blind and it's a hit show, you're not making that much money off of that show. You are now hoping to stack shows and then end up pulling off of that margin that you get to split, right? And then you trade on EBITDA, right? So when you sell the business you're trading at like six times EBITDA. Five, six times EBITDA and then a lot of times now they won't even buy you outright. They will partner with you, incentivize your long term earnout because they don't want to just pay you five times, six times your EBITDA and then all of a sudden the show goes away. And you were the creative force behind getting new shows, right? So it's a lot more complex. And when you think about the big dogs doing it, they're looking at it more from they're buying the creative minds that are making the new content all the time. So if they believe long term in content and when you look at that aggregate, you can have a couple of them slip and have a couple of heroes in there. And when you see all those together, you can bet that that thing is going to generate a ton of cash because the industry itself is built around being incredibly lean and then being profitable because they're only worth their profitability. And then they can accordion. You got a big show and all this staff and the show goes away. Boom. You bring it all the way back down because you put so many people under the show itself. So that's where the bigger vision is for them to look at. And is there an opportunity for creatives and people in the space in this day? Yes, because Endeavor is doing it. Churning is doing it. A lot of people are doing it, but it's extraordinarily difficult. And the gatekeepers are the distributors, the Netflix, the Paramounts. You can attempt to create your own platform and distribute it yourself, YouTube, digitally, whatever it is. But it's expensive and difficult to build audiences. And then you're really looking at those distributors as the gatekeepers to the quality of the asset that you're creating and whether or not someone will make it decide that you're worth the purchase. All of that credibly difficult, in my opinion, to make happen. \n\nShaan Puri (1:21:47-1:21:48): Perfect answer. \n\nRob Dyrdek (1:21:48-1:21:48): Exactly. \n\nShaan Puri (1:21:48-1:21:58): I was looking for Rob. This has been amazing. Better than one, somehow. Where should people follow up? Where do you want them? You want them on your pod, your Twitter email list? How can people get more Rob? \n\nRob Dyrdek (1:21:59-1:22:54): Rob's just at Robdurdick across Social on A.com, and just I got billed with Rob. But really, I'm not out pitching nothing. I'm just out trying to figure it out, keep evolving. But one day I'm going to come back on with my software. When it's done. Well, first I'm going to send it to you guys first. And then when the book and the philosophy are out and the software is out, then it's going to be like, how do we convert the listeners into changing their lives from being erratic into harmonious, high quality existences with the existing operating system? But that's off in the future. Now, I'm just glad to reconnect because I'm thankful for you guys, for kind of starting the spark of the whole thing. And really, I'm even thankful for you posting all the data and using the customer acquisition from the stuff that I sent you. I sent you all the new stuff. \n\nShaan Puri (1:22:55-1:23:51): Do you know what happened, Sam? Man, I know. So basically, he came on, he did the rhythm of existence. He sent us the sale PDF we post on Twitter, and it was kind of over. And then, like a year later, I was like, all right, I'm going to start building my email list. And I was like, how do I get fans of the show, the like minded people? How do I get my type of people to subscribe? I don't just want any subscriber. I want the right type of person. I was like, what would the right type of person be into it? I was like, oh, dude, the rob deer dick. That rhythm of existence sheet, the time tracker. I think they would be nerding out about that. That's my type of nerd. And so we put it up as a lead magnet, which was like, hey, come put your email in. And he'll share his thing with you. And we start spending a bunch of money. Rob emails me like, I don't know, six months ago. He's like, Bro, you're blowing me up with this sheet? It's all good, but you got to update the photo. You're using the wrong photo from over here. And so we update the photo, and I was like, oh, man, I feel bad. We take the whole ad down. We start putting something else up. But it was a moment of embarrassment. \n\nRob Dyrdek (1:23:51-1:24:03): Don't feel bad, because to me, just perpetuates. For me, it just continues to push the narrative of level of discipline and commit and data driven. \n\nSam Parr (1:24:05-1:24:07): You said you subscribed it was good. \n\nShaan Puri (1:24:07-1:24:18): In that we were preaching your gospel and makes you look like a badass. So there's nothing bad there. I just should have asked you first, and I forgotten to do that. I didn't do that. And that's why I felt embarrassed. I was like, oh, my bad. \n\nRob Dyrdek (1:24:18-1:24:32): Yeah, I appreciate it and thought it was funny, but I was also like, this is great. Then I was interested in the data from your perspective of like, okay, well, I wonder how many it converted just to kind of understand how many well. \n\nShaan Puri (1:24:32-1:24:34): There was nothing to convert to, right? \n\nRob Dyrdek (1:24:34-1:24:41): Since you had the DocuSign. It was just the views of the PDF was like, what I was interested in. \n\nShaan Puri (1:24:41-1:24:47): I don't think it ran for too long. I think it had maybe 50, 00, 10,000 hits, something like that. So a good amount for sure. \n\nRob Dyrdek (1:24:47-1:25:02): But I'm not I love that as just another data point from my perspective. That's why I was like, hey, use the new stuff. Make it feel more inviting. Make it feel more exciting for people to see, because I want to continually to perpetuate it. \n\nSam Parr (1:25:02-1:25:08): But again, Rob's getting triggered now, by the way. This is him working on that trigger of not getting angry. \n\nShaan Puri (1:25:08-1:25:26): I was talking to somebody yesterday about triggers. They were like they're like, man, he just pushes my buttons. And I was like, Dude, you're like a BlackBerry. You're just covered in buttons. I was like, the problem is not that he pushed a button. You got so many buttons to push. Like, you want to be an iPhone. No buttons, nothing to push. What can someone do to you now? You're on stop, right? \n\nRob Dyrdek (1:25:26-1:25:28): And it's possible for everybody to get there. \n\nSam Parr (1:25:28-1:25:38): Awesome. Well, we appreciate this, dude. Last time, maybe video and audio had, like, half a million views. I have a feeling this is going to crush it. So we appreciate you. \n\nRob Dyrdek (1:25:38-1:25:55): Okay. Till we meet again. Till we meet again. See you guys. Thank you. I feel like I can rule the world. I know I could be what I want to I put my all in it like no days off on the road. Let's travel never looking back. \n\n" }, { "path": "data/Transcripts/MFMPod/mfm_pod_steph.txt", "content": "Shaan Puri (0:00:00-0:00:03): D to C hearing AIDS. I think that's actually going to be a big deal. \n\nSam Parr (0:00:03-0:00:05): And they're profitable. \n\nShaan Puri (0:00:05-0:00:08): I mean, I'm just turning you on. Yeah, they were. \n\nSam Parr (0:00:12-0:00:13): They Mormon. \n\nShaan Puri (0:00:13-0:00:14): Oh, my God. \n\nSam Parr (0:00:16-0:00:18): How far away from the coast did they live? \n\nShaan Puri (0:00:18-0:00:32): Are they inland? I feel like I can rule the world. I know I could be what I want to. I put my all in. It like, no days off on the road. Let's try. \n\nSam Parr (0:00:32-0:00:40): All right, we're here. Steph Smith's here. Before we talk about Steph Smith and all our ideas, we have two things. Sean, you want to go? \n\nShaan Puri (0:00:40-0:01:04): Yeah, I got to come clean. I have a very late disclaimer I have to give. So a few episodes ago, maybe like four or five episodes ago, we had talked about a business idea that was like a children's play space. Basically, you go there and it's just a place to play. You pay membership fee and you go play with all these cool toys inside. Anyways, I was like, oh, it turns out, like, interesting business. It's a franchise thing, blah, blah, blah. \n\nSam Parr (0:01:04-0:01:07): Anyways, you just went there. You didn't know anything about it. \n\nShaan Puri (0:01:07-0:02:05): I didn't even go there. Ben went there. My business partner went there, and he was telling me about it, and he's like, yeah, I was talking to the guy, and here's their occupancy. If that's true, then here's what they would be making. Well, I went and looked at the website and before and after and basically meetings, like, bookings to inquire about a franchise got booked out for, like, four and a half months after the pod. And I just want to say, I have no idea if this is a good business or not. That was an estimate. That was a single experience. It was, hey, that's kind of cool. That could make money. I do not endorse this. I don't know if it's good or bad. I can't say either way. And I really hope that a bunch of people didn't go buy franchises of this thing thinking that I was vouching for this. So I just had to say that because I saw all those meetings get booked and I got a little nervous. I was like, oh, wait, this is not a I can't co sign this. I can't vouch for this either direction. And I just needed to say that up front. So please don't mortgage the house and go buy a franchise of this thing. \n\nSam Parr (0:02:05-0:02:06): Did they reach out to you? \n\nShaan Puri (0:02:06-0:02:10): No, they didn't. I don't think they knew what happened. \n\nSam Parr (0:02:11-0:03:41): That MFM effect. Well, the second thing is, so we have these sources wherever I'm about to talk about something health related or like, I don't know, in your case, in that example, the franchise related or real estate related, we have, like, three or four buddies who will text and be like, hey, we're thinking about talking about this. What's your opinion on X, Y, and Z? And they'll kind of give us some insight. One of those guys, his name is Adam Bornstein. I met Adam because he basically ran a lot of Tim Ferriss's stuff. And one time he had this conference called 212. He invited me to go, and they would rent out, like, the Four Seasons. And one time I checked into my room, and it was so big, I called down to the front desk and I was like, hey, who do I share this room with? And it was a 4000 square foot Four Seasons penthouse, the presidential suite that had, like, a 16 person dining table, a movie theater. And that's how I met Adam, is he invited me to come to his event, and so I've always asked him for health stuff. Well, he just had a book come out. It's called you can't screw this up. I'm trying to think of the best way to summarize it, but it's basically so I have this thing written down. It's basically Ryan Holiday, James Clear, Tim Ferriss. Like, that style of writing and that I don't know, simple hacks, but that's kind of a bad word, but I don't mean it that way. But like, these simple hacks on how you can create healthier diet habits. So the book is called You Can't Screw This Up. He also worked with Arnold Schwarzenegger, and that's who got to write the forward. So I just want to give a shout to Adam. He's a friend of the pod, so I want to give him a shout out, but steph Smith. What's good? Nice to see you. \n\nSteph Smith (0:03:41-0:03:42): Good to be here. \n\nShaan Puri (0:03:42-0:04:16): One of the all time favorite guests. This is, I think, appearance number six. So if you love this one, go listen to the other five. That steph's done. Steph is great because she brings a dossier. I can't even call it a document. It should be on Google Dossier.com because it is a 15 page document of trends, ideas, small observations that might half ideas that might become something, which makes you essentially the perfect MFM guest. And you're also cool and fun to hang out with. So thank you for coming back. \n\nSteph Smith (0:04:16-0:04:22): Yeah, good to be here. Every time I come on, I get way more nervous than any other appearance because you guys hype me up like that. \n\nSam Parr (0:04:22-0:04:24): Sean, do you know how I met Steph? \n\nShaan Puri (0:04:24-0:04:26): No. Tell me the story. \n\nSam Parr (0:04:26-0:04:52): I will forever take credit for Steph Smith's career. It has nothing to do with how hard she works. What I do, no matter how hard she works, no matter how smart she is, it's all of me. So basically, she had this blog. Is it Stepsmith IO? Yeah, it was a really good blog, and she had this headline, and the headline was to be great, just Be Good Consistently. Is that its stuff? \n\nSteph Smith (0:04:52-0:04:52): Basically. \n\nSam Parr (0:04:53-0:04:54): What was it? What is it exactly? \n\nSteph Smith (0:04:54-0:04:58): Yeah. It's like how to be great. Question mark. Just be great repeatedly. \n\nSam Parr (0:04:58-0:04:59): Be good repeatedly. \n\nSteph Smith (0:04:59-0:05:00): Oh, yes. Be good. \n\nSam Parr (0:05:00-0:05:27): And I was like, I DM'd her. I was like, Steph, this is the best headline I've ever read. This is a really good headline. Like, we're launching this thing called Trends. Do you want to join us? And she was like, yeah, maybe. And I was like, look, come work for us for a couple of years. And I have a feeling you're going to go and leave us. And that's totally cool. Come do like, a tour of duty now. It's been about a year and a half, maybe a year since she's left. She's at Andreessen Horowitz, one of the biggest VZ firms in the world. How is that going? \n\nSteph Smith (0:05:27-0:05:48): It's going great. Yeah, we just hired a producer, which is nice because for a while I was kind of hacking it together myself. But yeah, I feel like the podcast finally is taking off and we're trying a bunch of different formats. I feel like I'm easing into it. I'm finally having fun. Like, when I listen to my first million, you can tell you guys talk about it's like the best job in the world. I'm finally easing into that, which is nice. \n\nSam Parr (0:05:48-0:06:05): What's it like working there? I mean, when I think about working there, I think of the TV show Billions. It's just like fun shit all the time. But is it just normal company bullshit? Is it more normal of a job than I think? Or is it as spectacular as I would imagine? \n\nSteph Smith (0:06:05-0:06:11): I mean, it's kind of both because day to day it's totally normal because you're just doing your job. You're just doing work. \n\nShaan Puri (0:06:11-0:06:12): Do you go into an office or are you remote? \n\nSteph Smith (0:06:12-0:06:28): I'm remote. They do have offices. I go in every so often just because I started working remotely a year into my career. And so for the last like eight years or so, I've never had an office. And so it's like a novelty for me. Everyone else is sick of the office. And I'm like, oh, candy bar. \n\nShaan Puri (0:06:28-0:06:33): You're like, oh, you just sit here all day? Wow. You can't leave this box. \n\nSteph Smith (0:06:33-0:06:37): I know. It's crazy. I'm like, OOH, a call booth. Like how special. \n\nShaan Puri (0:06:37-0:07:12): I think the way Sam talks about, like, when his wife Sarah worked at Facebook and he's like, when you work at a place, you just sort of get used to everything and you kind of optimize for convenience. And so like, oh, they're all Hands meetings on. I can either go down to the cafeteria and listen to it or they have like a streaming option because there's plays all around the world. And like, all right, whatever. I'll just stream it from my dad. That's easier. I'll eat my salad here. And Sam was like, no, you need to go sit front row with a pen and pad. And when he says any questions, you need to jump out of your chair and ask him a question every single week until he invites us over for dinner. That was basically Sam's master plan. \n\nSteph Smith (0:07:12-0:07:14): Until you're his best friend, I kind. \n\nShaan Puri (0:07:14-0:07:37): Of think you should be doing the same thing. Like, what's the point of working at Andreessen Horowitz unless you're just like, at the office every day just waiting for some awesome Mark Andreessen moment to happen. Or just like, you're there when he just yells at somebody and it just goes off. Or like they're doing a blood. The twelve year olds come in to give them blood, and you're like, yes. This is the weirdness I came here for. \n\nSam Parr (0:07:38-0:08:02): It's like every movie ever where there's like, the big boss at the conference table and it's like, what channel? Let's put this together. And then the manager is like, oh, one of my guys. Bring your guy here. Let me talk to that person. Or like, Mark Adrien is going to say, like, who thought to do this? The number on this is Blankety blank. And you say, Actually, sir, it's 6473. What did you say? It's 6473. Because this come with me. \n\nShaan Puri (0:08:02-0:08:28): Yeah. It's like for six weeks, I've been leaving crumbs in the kitchen to see if anybody would clean it up. And finally somebody did. Let's pull up the security footage. It was Steph Smith. You're promoting. You're at the top now. This is the fanfic. This is what I think is going to happen if you but you just got to be there. I can't believe you're not there every day. You should be every day in the office. That's the real upside of your job. It's not your salary. It's that you can go hang out with some of the smartest people in the world, but you got to do the hangout part, not the like just. \n\nSteph Smith (0:08:28-0:08:32): When we're on calls, then we I got to hover. Yeah, you got you're right. I got to hover around the office. \n\nShaan Puri (0:08:32-0:08:34): Just like you do on the Internet. You got to lurk. \n\nSam Parr (0:08:34-0:08:36): You got to be a link. \n\nShaan Puri (0:08:36-0:08:58): If you told, like, 21 year old you that you would be in this position and you'd be like, would you just stay home and just kind of do your own thing? Or would you go be there and hang out and lurk and just be serendipitous about what's going to happen? The 21 year old you would be like, oh, I'm definitely going in. I'm going to meet these people. I'm going to see what's up. But I think it's easy later to be casual about it. \n\nSteph Smith (0:08:58-0:09:06): Yeah, I got to embrace I feel like, Sam, if you were in the office, go up to someone grabbing a snack and be like, hey, what's up? How's it going? And I'm so awkward. \n\nShaan Puri (0:09:06-0:09:20): I'm like, you need to be romantic comedy, bumping into everybody and dropping all the papers that you're holding and then being like, let's clean this up together. Not even for the romance, just to create a little intersection between you and me and these people. \n\nSteph Smith (0:09:20-0:09:21): Yeah. \n\nShaan Puri (0:09:21-0:09:35): When I was at Twitch when we got acquired. I even told people there openly. I was like, I'm not here to do my job. I was like, I'm going to find whatever the most interesting things are happening here, and I'm just going to go be in those meetings and do that. \n\nSam Parr (0:09:35-0:09:36): But that worked, right? \n\nShaan Puri (0:09:36-0:09:37): And it worked. \n\nSam Parr (0:09:38-0:09:39): You're friends with Emmet? \n\nShaan Puri (0:09:39-0:10:39): Yeah, me and Emmet. I was like, this is the most interesting guy in this building. So anytime it's like, you need to go talk to Jerry on the fourth floor. Nah, I think I'm just going to hang out and Emmet, I'm just going to stay in the meeting. Like, we do the meeting with Emmet. Everybody gets up and leaves, and I'm just going to stay there on my laptop. Next group walks in, I'm still there. I'm just going to hang out and see what happens. It's like, no one's going to say anything. Or I remember when Ninja got poached. So the top streamer on Twitch got poached. And then there was like, I know there's secret meetings happening about like, what should we do? Should we counter offer or what is like a code red moment. But I wasn't in those. So I just wrote up a plan and I sent it to the three top executives. I was like, here's the plan for Ninja. I know I'm not even on the team. But then they were like, attend this meeting tonight at 08:00 P.m.. And I was like, I'm in. I got into the cool shit by just not doing my job. And that's my recommendation to you. If you're going to be around these, like 9000 IQ people, that's the real upside of your job. Don't do your actual job. Do the job of hanging out. \n\nSam Parr (0:10:39-0:10:49): Speaking of which, step do you think that the talent there are? They actually significantly smarter than any other pretty decent tech company? \n\nSteph Smith (0:10:49-0:10:53): I would say yes. I've worked at I mean, not that. \n\nShaan Puri (0:10:53-0:10:58): Many companies, but there's a direct shot at you, Sam. She's only really ever worked for you and market. \n\nSteph Smith (0:11:00-0:11:05): At least five companies where I've been a full time employee. And I would say yes. \n\nShaan Puri (0:11:06-0:11:09): My previous job was a lot of checkers, and now I'm playing check. \n\nSam Parr (0:11:11-0:11:14): What the fuck do those geniuses know about newsletters? \n\nShaan Puri (0:11:14-0:11:28): Well, you said something at the beginning of this. You were like, oh, I get nervous for this more than anything else. I'm curious. Do you feel nervous when you are in one of these Asics and Z, like whatever meetings? Like, are you like, oh, these are these are like the people I used to follow on Twitter and shit like that. And now I'm in this room? \n\nSteph Smith (0:11:29-0:11:59): Yeah, definitely. I mean, I think there's an element too, where I don't represent the company running this podcast, but in a way, the podcast is like an asset to the firm. And I'm like, they hired. I mean, I'm glad they did, but they hired a 29 year old who candidly feels a little out of place amongst these people who have been like, mark Andreessen basically invented the Internet. Like, he created the first browser or the widescale browser. And so I'm like I do feel sometimes a little out of place, but I feel like I'm a year in. I'm getting used to it. \n\nShaan Puri (0:11:59-0:12:09): I think you should give yourself more credit. You're cooler than everybody I've met at Asics and C. So I think they're lucky to have you, as far as I'm concerned. \n\nSteph Smith (0:12:09-0:12:14): I'm going to bring in one of those Nick Gray name tags that says cooler than you. Sean thinks I'm cooler than everyone here. \n\nShaan Puri (0:12:14-0:12:15): Exactly. \n\nSam Parr (0:12:15-0:12:32): This is why I knew she was a good hire, because I was like in my head, I was like, oh, she doesn't realize how good she is. This is a deal she doesn't know yet. Seth, where do you want to go from here? \n\nSteph Smith (0:12:32-0:12:49): Let's just start with the first idea. So this one I think is really interesting because right now, I think a lot of people listening know that there's this issue with commercial real estate. All these office buildings are up for sale, or at least people are leaving. \n\nShaan Puri (0:12:49-0:13:08): Like, the highest level of going down of vacancy ever, basically. Especially in cities like San Francisco, where I think it's like 35% vacancy and going up. As soon as people's leases roll off, as soon as they can get out of their lease, they will. So it's a disaster. \n\nSteph Smith (0:13:08-0:13:08): Exactly. \n\nSam Parr (0:13:08-0:13:09): What is this thing? \n\nSteph Smith (0:13:10-0:13:28): A lot of people think, okay, well, then let's go change. Let's swap that commercial real estate for homes, apartments, et cetera. That makes sense, but I think there's this huge opportunity for fractional real estate. So click one of where it says see here? Click one of those and tell me what you see. \n\nSam Parr (0:13:28-0:13:29): All right, Sean, you want to go? \n\nShaan Puri (0:13:29-0:13:47): I'll describe it. So it's something called Temple Immersive, and it basically looks like a yoga class of some kind. It's like dimly lit candles, looks like a hot yoga class. But then on the roof is this like, crazy visual where it looks like you're in the forest, and the whole thing just looks super cool. \n\nSteph Smith (0:13:47-0:13:49): Where do you think this is? Like, what is this building? \n\nShaan Puri (0:13:50-0:13:54): I have no idea. This looks like the lobby of an office building. In a way. \n\nSam Parr (0:13:54-0:13:57): It's, like, huge, but they make it look like a temple. \n\nSteph Smith (0:13:57-0:14:56): So this is a club during the night, a nightclub. This is just one example, obviously, of where real estate is used from what, Friday, Saturday, Sunday, from like, 07:00 P.m. To 02:00 a.m. And then throughout the week, it's not used at all. And so the thing that I found fascinating, I went to this called Temple Immersive in San Francisco, and I talked to the woman. They just opened up, and I was like, how'd you find this? Did you reach out to a bunch of clubs, and they were like, no, the club reached out to us. I guess it makes sense. But this club has just all this real estate that's being unused. And I was just thinking about what other I guess one this could be applied elsewhere, right? Like, in any city, someone can go contact a bunch of clubs, link them up with yoga studios, Pilates studios, et cetera. But then I was also thinking, what else could this real estate be used for? And another trend that's been taking off is rage rooms. Have you guys heard of rage rooms? \n\nSam Parr (0:14:56-0:14:57): No, but I like rumors. \n\nShaan Puri (0:14:57-0:14:59): Smash shit, right? \n\nSteph Smith (0:14:59-0:15:07): Yeah. There's one in SF as well, but basically people are angry they're losing their jobs. \n\nSam Parr (0:15:07-0:15:11): Yeah. Is it called, like, the rage room market? \n\nSteph Smith (0:15:13-0:15:15): The city is the rage room. \n\nSam Parr (0:15:15-0:16:11): CVS is doing a rebrand. We all want to feel better and be happier and have more freedom. And there are endless resources at our fingertips. But waiting through a sea of self help books and podcasts and workshops takes more time than you've got. So you have to check out Selfhelpful with Kevin Miller. Kevin is a pro athlete, peak performance expert, published author, and personal development guide. He invites today's most important influencers and change makers to grapple with their own wisdom and stories in authentic, relatable conversations about self improvement and what drives them from personal fulfillment and work life balance to spirituality, relationships, motivation. Each four part series distills the guests greatest wisdom and methodologies into practical steps that anyone can integrate into their life. Tune into Self helpful with Kevin Miller to elevate your personal experience and improve the way you show up for others. Okay, what is this rage room shit? \n\nSteph Smith (0:16:11-0:16:42): So people will literally go and yeah, like Sean said, you just smash it. So they'll give you a bunch of plates, they'll give you old electronics, they'll give you stuff. And I think depending on what you choose, you pay a different amount and you just get a session in this empty room, and you just get to smash stuff, which you just don't get to do in normal life. And so I was thinking, I was like, not just a yoga studio, but a lot of this real estate. Like, go convert a club during the week to, like, a rage room people. \n\nSam Parr (0:16:43-0:17:09): I always thought, like, these little things wouldn't be that interesting, but we have this member of Hampton, and he's tweeting about it. His name is Raleigh Williams. I was just going to bring him up, dude. I think he's in Utah. And he created I thought Escape Room was, like, a brand, but I think it's also, like, the style. And so he created a version of an escape room. And what did he do, Sean? He sold it for about $30 million. \n\nShaan Puri (0:17:09-0:19:19): He created a business, he sold it for $26 million. And what he says is basically, he's at a law firm and he doesn't love his job, and he's like, okay, should I do something else? Like, what should I do? He reads an article that talks about how lucrative escape rooms were. This is back in 2015 when the escape rooms were really just sort of like the new trend. It was the new Froyo, basically. So he looks it up, he finds out how much money these make, and he's like, okay, I think this is a good business, but I don't have enough money to go build it out. But in the true entrepreneurial spirit, he doesn't let the lack of resources stop him. He becomes resourceful. He's like, all right, can I build an escape room inside this abandoned bus? So he goes by this 1984 Bluebird bus, and he converts the inside into an escape room. And now he's got an escape room on wheels. He could drive it up to companies offices and do the corporate off site right there. And so it wasn't perfect in the sense that if it was a hot day or a cold day, it kind of sucked to be inside of it. But other than that, it was like this super efficient escape room allowed him to get real cash flow going. I think he said the bus itself was making like, five or ten grand a month of free cash flow. And so he starts opening up more, and so he builds out his first real one. He opens five, six more or whatever. Then he starts adding to the back of it. So there's, like, real estate. So he's getting the real estate with the escape room, and he's getting more space, and he created a trampoline park and an axe throwing things. So basically, just like this kind of like out of home entertainment is what we call this category. And so he just bundles these together, and over that period of, like, 2015 to 2020 ish he's built this thing up. And then he starts selling them off. So he's selling off in chunks of pieces. And he basically said that he made $26 million doing this, I think through a combination of the sale plus the distributions along the way. But I might be wrong. Maybe it's both. He had said he had, let's see, he spent 10 million building these out, and over the over the years, there was about 20 million in distributions from that's crazy. So kind of an amazing outcome, an amazing return for this guy. \n\nSam Parr (0:19:21-0:19:25): Yeah, I didn't think that these would be good, and then I met him and I started learning about him. \n\nShaan Puri (0:19:25-0:19:27): He's a nice dude too. People should go follow him on Twitter. \n\nSam Parr (0:19:27-0:19:28): How do you know him? \n\nShaan Puri (0:19:28-0:19:36): I just know him through Twitter. I've been going back and forth with him a little bit, and then he listens to the pod. So though he had reached out at. \n\nSam Parr (0:19:36-0:19:42): Some point, steph talk about this pay transparency thing, this interests me a lot. \n\nSteph Smith (0:19:42-0:21:22): Yeah. So in the last couple of years, there's been a bunch of laws that have changed across states. I think Colorado is maybe the most well known where companies have to, depending on the state, disclose certain aspects of a job related to pay, right? So it might be a range that a specific job requires. Also things like even if you're in a job, you can request your band and why you're paid a certain amount and how you compare it to others across the company. And so that's changing. It's still changing. It's very much in flux. I think there's at least a dozen states that now require you to share those pay ranges. For example, but this one girl, Hannah Williams, she's 26, so super young, quit her job. She's making like $115,000 a year and then in the last year has just been doing the kind of man, or in this case woman on the street. And all she does is she goes up and she just asks people, hey, what do you do? How much do you make? But her social accounts have blown up, so she has over a million followers on TikTok again in a year, 450,000 on Instagram, and she's on other channels as well. And so an article was written about her in January, and she had already made $600,000 since her switch. And so I'm sure she's made way more now with the accounts being the size they are. But this is one of the cases, we've talked about this before, when there's like regulation change, there's like a rule change, a line in the sand is drawn and then that has implications. And this one's so far ranging, right, because it impacts any job within these given states. \n\nSam Parr (0:21:23-0:22:12): So if you go to her profile, she's doing a really good job. So you go to her profile on TikTok and you click that link that says Stan. So check this out. So here's how she's making money. So the top link is an Indeed link where it says, get a job as a nurse. And so she's getting an affiliate thing. Then she has a market research guide, which is learn how you should do, learn how much you should be making. And I guess that's so she can collect emails, but then click attend La and NYC workshops. So she partnered with Capital One to do local seminars at their banks because some of their banks have cafes. And then she also has, I think I believe it's a subscription database where you can see individual salary data packed with contextual information. This woman's awesome. This is how you do it. \n\nShaan Puri (0:22:12-0:22:13): Also shot. \n\nSam Parr (0:22:13-0:22:13): This is how you do it. \n\nShaan Puri (0:22:13-0:23:06): Sam invested in Stan. So good use of Stan here for putting a link in the bio that lets you make a bunch of money. Yeah, this is cool. We've talked about levels that FYI on the pod before, which is a similar concept, which is like crowdsourcing salary info. So if you're an engineer at Facebook. You can go find out. Am I getting paid? What other l four engineers get paid? Or should I be working at Google? And what would I get paid if I was over there? I think they're doing an awesome job of this. When we had mentioned this on the pod, somebody did this for doctors. I think we had said somebody should do this for nurses and doctors. And then they were like, hey, we're med students. And so they went and did this for doctors and created a database. I think they got acquired by levels, actually, after hearing it on the pod and then taken action on it. So definitely think that there's an opportunity here. And I like, Sam, what do you call it? Regulatory inflections regular? What's your big word? \n\nSam Parr (0:23:08-0:23:37): Inflections is the I word. The inflections, which is anytime there's, like, a law change. Well, there's, like, multiple inflections. So there's like a tech inflection, which is, like, Uber exists because everyone now has an iPhone and you have GPS in your phone. Then there's, like, cultural inflections, which is, like, teens feel comfortable filming themselves. And then there's regulatory inflections, which is this drug is now legal, or this patent is about to expire, or you now, in Colorado, have to disclose your salary ban, therefore it opens up new opportunities. \n\nShaan Puri (0:23:38-0:23:40): There's another one you have here that. \n\nSteph Smith (0:23:40-0:23:50): I was going to say. So you guys have talked about hearing AIDS on the pod before. So, as of October, the FDA relaxed their rule, which basically meant hearing AIDS could be sold over the counter, which. \n\nSam Parr (0:23:50-0:24:03): Is bullshit that they're not sold over the counter. It's fucking bullshit. It's been bothering me so much that in glucose monitors, I'm amazed that they're not sold over the counter. I've been trying to get a hearing aid, and they make me go to all these appointments and I miss them. It pisses me. \n\nSteph Smith (0:24:03-0:24:04): Oh, really? \n\nSam Parr (0:24:04-0:24:04): Yes. \n\nSteph Smith (0:24:04-0:24:15): Another fun fact around hearing AIDS, which I feel like is interrelated to the fact that they can is it now already that they can be sold over the counter, or is it this coming off? \n\nShaan Puri (0:24:15-0:24:16): No, they can. \n\nSteph Smith (0:24:16-0:24:57): Okay. They already can. But apparently 99% of hearing AIDS or custom hearing AIDS are 3D printed already. And so there's a few companies that basically own this market currently. But the reason I love this is because 3D printing is the epitome of tech. Hype cycle. Started in the 80s, then got way overhyped, wasn't ready. Everyone thought it was dead. But it's like, come back in these really niche places like hearing AIDS. We talked to people on Trends a while ago that were using 3D printing for, like, dental implants, things like that. And so I feel like it's something that actually is overlooked because people were like, 3D printing instead. \n\nSam Parr (0:24:57-0:25:01): Wait, what do you sean, you said yep. As if, you know you know people doing this for teeth. Yeah. \n\nShaan Puri (0:25:02-0:26:51): One of. My best friends from college. He's a surgeon and he's an ENT surgeon. So ear, nose, throat. And I was like, while he was in med school. So this is like over the past eight years or whatever. The guy's just been at school forever. And I was like, how's it going? He's like, oh, it's fine. But I'm having the most fun because now I run Duke's 3D printing facility. I'm like, 3D printing? Like just like for engineering? Like, you're making toys or what are you doing? He's like, no, the medical 3D printing. And I was like, Wait, I thought 3D printing is not even a thing for normal shit. You guys are already using it in medicine. He's like, Dude, I surgically implanted part of a skull that I 3D printed the other day. We take your jaw shape and then we're able to create the perfect shape that we needed for this implant, the surgical process. And I was like, wow, I had no idea. And they're doing this with basically it's interesting, some technologies take forever to get into medicine because it's like the high stakes spot. And for some, medicine is the only justification for putting in the time and the money that it takes to get the technology to work. And I think that's kind of where 3D printing has gone, where it's like it started as like this hobbyist thing, but then the real commercialization so far has happened. On the medical side. I think the same thing is happening kind of in VR. People trying to do the hobby thing for a long time. But one of the better, more commercial use cases of VR is doctor training, flight pilot training, things like imagining instruction. Yeah, exactly. Anything where you need to sort of visualize and plan something. It's worth the money to develop a really high quality VR simulation because it's cheaper than doing a real prototype of it. \n\nSam Parr (0:26:51-0:26:54): Damn, I didn't know you had the siding view. \n\nShaan Puri (0:26:54-0:26:56): I got friends in hospitals, as they say. \n\nSam Parr (0:26:57-0:27:07): Well, you're Indian, of course you do. You're the OD man out. But you're shilling Web three for years. Turns out you're a practical guy as well. \n\nShaan Puri (0:27:08-0:27:10): We put the blockchain in your brain, baby. \n\nSam Parr (0:27:12-0:27:13): Do this. \n\nShaan Puri (0:27:13-0:27:29): Well, I also for this hearing aid thing, I met these guys that were doing 7 million a month in sales on their hearing aid brand that I had never heard of. And I was like, oh, maybe this makes a lot of sense, actually. Like DTC hearing AIDS. I think that's actually going to be a big deal. \n\nSam Parr (0:27:30-0:27:32): Was it bootstrapped? \n\nShaan Puri (0:27:32-0:27:42): I don't know if they're fully bootstrapped, but yeah, they're not like venture act. They made bootstrapped and then their uncle gave them some money to keep scaling, it seems like. That sort of vibe. \n\nSam Parr (0:27:42-0:27:43): And they were profitable. \n\nShaan Puri (0:27:44-0:27:46): I'm just turning you on. Yeah, they were. \n\nSam Parr (0:27:51-0:27:52): They Mormon. \n\nShaan Puri (0:27:52-0:27:53): Oh my God. \n\nSam Parr (0:27:54-0:27:56): How far away from the coast did they live? \n\nShaan Puri (0:27:57-0:28:10): Are they inland? Let's keep going. Let's do this. Jobs of the future. I think this is a good one. Yeah. And I also love that you're branding this steps list. Well done. Way to take a page out of our book. \n\nSteph Smith (0:28:10-0:28:23): I had to I love Sarah's list. But yeah, this all comes from, I guess, two things. One, people think AI is taking all of our jobs. I personally don't fully agree with that. We don't need to dive into that. \n\nSam Parr (0:28:23-0:28:39): Well, what's the official stance at a 16 Z right now? Is there like a poster where it said, like, web three is future and they just like put an X over it? They just wrote AI. \n\nSteph Smith (0:28:39-0:29:16): No comment. No comment. But what I'll say is we even on this pod have talked about different jobs that don't quite exist or maybe are starting to exist. I've talked about chief automation officers. Sean, you've talked about this idea of like a mental fitness coach. And I guess this idea of Steph's list is partially I want to share a few ideas today, but I also want to hear from the listeners, like, what are the jobs that you think are, as some people might say, a little more antifragile, but also that, again, don't quite exist yet or early. The types of things we would have. \n\nShaan Puri (0:29:16-0:29:25): Talked about in trying start with the stat you have here because I think the stat actually makes it clear that these aren't just like, oh, cute things on the fringe. It's like, no, this is the future. \n\nSteph Smith (0:29:26-0:29:41): Yeah. So apparently 85% of employment growth in the last 80 years came from new jobs. So Aka, between 1940 and today, 85% of employment growth came from jobs that did not exist in 1940. \n\nSam Parr (0:29:42-0:29:47): Did they not exist because AI didn't exist or did they not exist because it's by new businesses? \n\nShaan Puri (0:29:47-0:29:51): Like new businesses, the job title didn't exist is what you're saying. \n\nSteph Smith (0:29:51-0:30:58): Yeah. So even simple examples of this that I think anyone can recognize from even the last few decades before 2008, 2009, the idea of a social media manager did not exist. The idea of a UX designer did not exist. And those are jobs that truly like, what, tens of thousands, hundreds of thousands of people now do these jobs. And so there's going to be versions of this. I think it's a little more brainwracking to figure out in the age of AI because you can always ask like, oh, well, is this going to disappear in three years instead of 30? But I think actually there's maybe like frameworks to think about this. So for example, I think drones are kind of hitting that. We talked about 3D printing hitting that stage where a lot of consumers own drones, but a lot of companies are also starting to use drones. And so what within that industry could exist? It could be like drone technicians. There's a lot of drones. People are going to need to fix those drones. Is there like drone traffic control? There's aircraft traffic control. So why wouldn't there be? Right? \n\nShaan Puri (0:30:58-0:31:00): Safety inspector, charging, installation, blah blah blah. \n\nSteph Smith (0:31:00-0:31:06): Exactly. And so my question for you guys is like anything on your radar? \n\nShaan Puri (0:31:06-0:31:27): Well let's start with the ones you talked about before. So you said it quickly but I think it's worth repeating because you were on I don't know, a year ago when you said it. So Chief Automation Officer, when you said that at that time this was kind of like definitely pre AI being like the thing that every's talking about. What does a Chief automation officer do and why did you think that was a cool job? Like a job of the future? \n\nSteph Smith (0:31:27-0:32:17): Yeah. So I mean a lot of companies will have a CTO. The CTO typically though is so wrapped up on what's our infrastructure is cybersecurity, how are we tackling that and how are we keeping our company safe, our data safe, what they often aren't focused on. And maybe some people would argue this is the role of the COO, but is how do I actually take the technology that exists today like AI and enable every single person within my company to understand how to up level their jobs. Right? So to become three X more productive. Because most of those people unfortunately either aren't plugged into the technology, don't have the excitement to actually implement it within their job, or honestly it's just one of those like you don't know what you don't know. \n\nSam Parr (0:32:17-0:32:26): Kind of. Let me give you a compliment. I remember that pod that we did where you talked about that at Hampton. The first hire we made was an automation expert. \n\nSteph Smith (0:32:26-0:32:27): Really? \n\nSam Parr (0:32:27-0:32:48): The very first hire. His name is Grant, all he does is automate stuff. So he's basically a Zapier plus airtable expert. Because one of our values early on was we want to grow to be big but we don't want to have to hire loads of people. So let's right away start automating stuff. And it was because of that conversation. So the very first hire we made was an automation expert. \n\nSteph Smith (0:32:48-0:32:49): That's awesome. \n\nSam Parr (0:32:49-0:32:52): And you know what? It is fucking awesome. \n\nShaan Puri (0:32:52-0:32:59): The bottleneck is not typically like you have to create new things. It's that basically you're bridging a gap. \n\nSam Parr (0:32:59-0:33:00): Usually a duct tape, a ton of things. \n\nShaan Puri (0:33:00-0:34:14): There's a process we're doing that's kind of tedious, manual, repetitive or low value ad, but needs to be done. And then there's tools that could do that if you knew they existed and you knew how to pipe them together and stitch them together so that they actually work. And what this person does. And I do this at our company almost by accident, which is for our ecommerce companies. I just discovered yesterday there's somebody who just has to spend hours a week just like square cropping photos so that they look better in shopify from what the photographer gives them. And I was like, wait, you do this for how many pictures? And they're like, yeah, it sucks. And I was like, you know, there's this tool that will just bulk you bulk upload, and it'll do that, and then it'll pipe it to you here in Slack. And he could see we'll use a different tool to pipe it into Slack. And you'll see if there's one that's off, because you could just kind of skim this with your eyes, and then you'll just be able to fix the one off. That's not good. But 98% of them will just be done well the first time automatically by this one tool. And they're like, oh shit. That's like, no thank you. That saves me a bunch of time. And now I could go do things that are actually going to drive a little more growth versus just like some bullshit that had to be done. And how many of those are there in every company? There's a ton of those. \n\nSam Parr (0:34:15-0:34:38): And the problem is, Sean, is even let's say that hypothetically, you only have ten people. Even though you've been ten people for three years, just ten people has created enough habit that even getting an automation person in now, it's going to be like, oh man, where do I start? So doing it with 10,000 people is an impossible task. That's why we were like, let's get this right away. Let's do this right away. \n\nSteph Smith (0:34:38-0:35:03): Yeah, there should be like a ratio. Like for every ten employees you have, you have one chief automate or not chief automation officer, but someone who knows how to automate. You just pair them with teams and they literally do user interviews. They sit down, they say, hey, let me shadow you for a day. Let me just see what you do. And then from there, I bet anyone, myself included, who tries to automate what I can. They would just pick up so many things of like, why are you doing that at all? \n\nShaan Puri (0:35:03-0:35:11): So I think you should also have this for team collaboration. Have you guys ever read this book, five Dysfunctions of a Team? \n\nSam Parr (0:35:11-0:35:14): Yeah. By Patrick something, I don't even know who is. \n\nShaan Puri (0:35:14-0:35:16): It's a great book, honest. I love that book. \n\nSam Parr (0:35:17-0:35:18): It's like a narrative driven other people. \n\nShaan Puri (0:35:18-0:35:48): I think, don't really like it's kind of like fiction. It's a business advice book, but it's written as a fictional story, which is cool because that's not usually how those are written. It basically describes like, there's a company, whatever, Acme Inc. And they go to this team Op site and they're trying to figure something out. And then you have these four personalities or five personalities or whatever, and it shows the different ways that a team can be dysfunctional. And once I worked in a bigger I've worked in kind of like two person teams. That's what I'm in now. \n\nSam Parr (0:35:49-0:36:02): Well, I think the takeaway of the or the what the you forgot this part where he says the reason the book is called that is, Successful Teams All Look Different, but Every Dysfunctional Company Looks The Same. And here's the five things that they all have exactly. \n\nShaan Puri (0:36:02-0:36:57): And you kind of identify them, but he identifies it, and the way the book is written is kind of cool, I think. It's sort of like, here's a situation. They have two people who both have kind of, like, valid perspectives, or one person doesn't realize that the thing that they're saying is causing the other people to feel a certain way and causing all these second order effects. Anyways, it's a good book for management, I guess. But I guess my real takeaway is, like, I've been in a bunch of companies where they do these shit builds up, and then they're like, we need an executive coach. We need a team off site. We need to break down all this scar tissue that's being built and dysfunction that's in the team and resentment that's in the team, and all these things that are not allowing us to perform at our best. I actually think that companies should embed this in the company. So I think there should be somebody that floats around that's basically like the chicken billions who's like the team psychologist or whatever. It's sort of like that, but instead of one on one what's her name? Therapy. \n\nSam Parr (0:36:57-0:36:58): I love that lady. \n\nShaan Puri (0:36:58-0:37:03): Yeah. I stopped watching the show after season one, so I forgot. But she's awesome. \n\nSam Parr (0:37:03-0:37:04): She's Wendy Rhodes. \n\nShaan Puri (0:37:04-0:38:07): Yeah. So basically, instead of that, it's somebody who just sits in meetings and takes notes, and every week they just deliver like sam, do you know that you do this and you say this and that, that's making these did you notice that makes these people feel this way. And it and then when they walk out of the room, you know, they're not going to go do the thing you want in the way you want because of the way you said it, or this person just didn't have that information and they were put on the spot. Maybe you should put in a process that gets the information on a dashboard that everybody sees beforehand or whatever. Right? Like somebody that identifies dysfunction. Because let's say for every ten people you hire, if you can make that team 10% more efficient, you've basically created one extra employee without that payroll. And so I think that the numbers would the ROI would be there if you had this. But I'm surprised this doesn't exist. So I think that's a kind of a job of the future is basically like a collaboration expert. So somebody that is like an internal compass, team compass, to figure out where are they? \n\nSam Parr (0:38:07-0:38:10): You like that word doula? You got to use that word doula here. \n\nShaan Puri (0:38:10-0:38:15): Yeah, I guess I'll just keep using doula as a guy and pissing everybody off. \n\nSteph Smith (0:38:15-0:38:20): Sam, what do you think? Any jobs that stand out to you? What are you guys hiring for? \n\nSam Parr (0:38:22-0:38:42): I don't fucking know, but nothing that some of the ones that are like bullshit that you see out there. And then I see their titles and I'm like, oh, you're not actually good at that is Community Manager. So like, Community Manager is like a title that I actually don't think most people know how to make community. So that's kind of like a nonsense one. \n\nShaan Puri (0:38:42-0:39:45): Here's one from the podcast that we've talked about. We have a podcast producer, Ben Wilson, right now. And people will have social media manager. They have all these different functions. But what I told the team was, I think we just need like a band manager. It's basically like podcasts as they gets more successful, they're kind of like a band. You have the talent, they're the face, they get on stage, they perform. And then there's all this shit that needs to be done, whether it's like, we're going on tour, we want to sell merch, we want to develop this cult following of fans that just love us because we just do dope shit that is fan service, fan love. Then you have the recording stuff that's got to get done and you kind of just need somebody who's like a hybrid of a business manager or an agent, as well as somebody who's kind of got the community building skills of a community manager. And that's what a band manager is for bands. And I think that you're going to see this more for podcasts and YouTubers is a role that's sort of like the band manager, like the Milk Boys and whatever, they have that, but most others don't have it underneath them. \n\nSam Parr (0:39:45-0:39:52): Yeah, for sure. What are the lists that you have here? Head of Remote and then Cyber Actuary. What are those? \n\nSteph Smith (0:39:52-0:40:29): So Head of Remote is kind of similar to the thing that you mentioned, Sean, but it's like there's so much dysfunction at companies, especially the ones that transition from being non remote to remote. Totally just copy and pasted a bunch of things from the office. They don't actually know how to build a remote organization from the ground up, how to do things asynchronously. And so it's kind of crazy when you think about how macro a shift that is for thousands of people to be doing things all one way, switching to a totally new way, and to have no expertise from someone to actually guide that. So that's the idea of how to remote. And some companies already have this, like. \n\nShaan Puri (0:40:29-0:41:04): A remote Work Officer or RWO. What would they do? It's like, well, people like I know in our company, it's like, well, first they have to it's kind of like it there's like, well, they need to have a good home set up. Sam, you talked about this. We need to not look like dog shit on camera, whether internally or with our clients and our customers. How do we make sure everybody's got a good zoom set up? Okay, secondly, how do we create some best practices around remote working and how to do stuff that's different now that we're not all in the office and can just look each other and talk to each other real quick? And how do we set boundaries for different time zones? How do we plan media? All of that, I think, is definitely. \n\nSteph Smith (0:41:04-0:41:38): In location based pay. I mean, isn't this crazy, like, to your idea with Hampton Sam of the nice background? The same companies that had these really strict clothing rules. Like, you have to show up in a suit and you have to look this way, are letting people sit with their MacBook under their chin with, like, a dirty ass background behind them, showing up to their business meetings, trying to win a client. And it's like, where's your digital suit? They don't care. They don't even think about that because it's so outside of their field of view. But that's just one example. \n\nSam Parr (0:41:38-0:41:45): But do you guys do that at a 16 Z? Because when I imagine a 16, that's a Khaki pants. That's a Khaki pants type of place. \n\nSteph Smith (0:41:45-0:41:52): Well, I don't think we have a clothing code, but we do, like, Lululemon. \n\nSam Parr (0:41:52-0:41:56): ABC pants is like, the official pants of man, Silicon Valley. \n\nSteph Smith (0:41:57-0:42:30): Here's something that a 16 Z does do that I never put together as related to this, but their design team will create every quarter these beautiful zoom backgrounds that the company uses. And they actually look good. I feel like a lot of zoom backgrounds are like the company's logo kind of awkwardly Photoshopped in the background. And again, they refresh them every quarter. Everyone has access to them, so there's at least that visual consistency. But I don't know if we have a closing code, but I hope some. \n\nSam Parr (0:42:30-0:42:38): Of your bosses and employees listen to this, and I just want them to hear me say this. It is me and Sean making fun of you guys, not Seth. \n\nShaan Puri (0:42:38-0:42:44): Just fly with a threat there. That was awesome. It's like on TV where they're like, Put the camera on me. \n\nSteph Smith (0:42:44-0:42:45): Put the camera on me. \n\nShaan Puri (0:42:46-0:42:53): And then you look down the barrel and you deliver some wrestling promo. That's what I thought you were about to do, but you were trying to cover. \n\nSteph Smith (0:42:53-0:42:56): Sam's version is like, look at me. And he's like, you're great. \n\nShaan Puri (0:42:59-0:43:01): No one believes in you more than me. \n\nSam Parr (0:43:02-0:43:16): Well, I had a friend that lived in China, and I used to text him all the time, and I'd be like, Dude, your government sucks. What's going on with that? And then I would reply with, by the way, whoever's reading this, it is me saying this, not him. \n\nShaan Puri (0:43:18-0:43:33): Yeah. Don't disappear, my friend. Invest in the cool zoom backgrounds and stuff. They got the I think, what, like 700 million in management fees. Those management fees got to go somewhere. So I'm glad they're putting them to good use. \n\nSteph Smith (0:43:33-0:43:57): Yeah, but I mean, just to summarize on the head of remote thing. Think about I think maybe the easiest way to think about it is there's all these macro tech trends, right? Like remote work, AI, automation, cybersecurity. Right. The idea of a chief security officer didn't exist like ten years ago. Right. Because that just became such an important, I guess, concept within especially tech firms. \n\nSam Parr (0:43:58-0:44:00): And what's this food engineer one? \n\nSteph Smith (0:44:00-0:44:14): Well, I wanted to ask you guys about this because yeah, we never talked about this, Hannah. Do you guys remember that? Yeah, so I know, but I still think the concept of like a food engineer will exist. I think this one's a little further out. \n\nSam Parr (0:44:14-0:44:15): So give this story, Sean. \n\nShaan Puri (0:44:15-0:45:50): Yeah, so a lot of people know David Friedberg now because he's on the all in Pod. So he kind of got a lot more popular or famous. But this awesome guy used to work at Google, created this thing called the Production Board, which is his kind of incubator startup studio or whatever. And they build things that are kind of like hard tech. So it's like things that interface with the real world. They have like hardware, they're making food or making biological substances or whatever. They're creating real world things. And he had this company called Canna that he created that was basically like the Coke freestyle machine in your kitchen. So you would have this device, this Nespresso machine that sits on your countertop that can make like 1000 different drinks exactly to your specification using basically like the equivalent of a printer cartridge. So it's like you put in this cartridge that's got all these micro flavors and then you hook it up to your water supply and it's like it just takes water. It makes it cold, hot or bubbly. And then it pipes in the exact dose of flavor to create whatever drink you wanted. You want tea? Here, you can make hot tea. You want sparkling water. That's flavored like BlackBerry. Boom. Done. And so it was this awesome idea. It will also be good for sort of like the world in a way because a lot of the supply chain is basically spent bottling water or soda, putting it in cans, putting it on shelves, putting cardboard around it, transporting it to the store, transporting it to your house, then transporting the trash to the dump. I was like, dude, what if we just took the water supply everybody already has to their home and we let you make whatever drink you want. Very cool idea. \n\nSam Parr (0:45:51-0:45:52): And then out of nowhere it just. \n\nShaan Puri (0:45:52-0:46:00): Suddenly got canceled and they were like unfortunately to scale up, we needed a lot of money and in this funding environment we couldn't do it. \n\nSam Parr (0:46:00-0:46:04): That's a bullshit excuse. Who can't raise they've got like the. \n\nSteph Smith (0:46:04-0:46:34): Top tech podcast in the world. Yeah, maybe an interesting way of framing that idea was also it came from the idea that they had done research and they had realized that basically every drink out there, whether it was tea, whether it was wine, whether it was beer, 95% water. Not just 95% water, but even the chemicals that go into it. I don't remember the number, but it was something like there's only 30 or so flavors that you need to basically generate every taste. But yeah, I don't know. Maybe something for you. \n\nShaan Puri (0:46:34-0:46:48): Yeah, we should get him on, or I'm going to tweet at him. I want to know not what really happened. Like, there's a scandal, but tell me more, because clearly he could sneeze and raise $30 million for an idea. So I'm surprised if it wasn't like. \n\nSam Parr (0:46:48-0:46:52): It must have been, that his sneeze will be lovely flavors, too. \n\nShaan Puri (0:46:53-0:47:12): I feel like he must not have believed meaning the team must have realized it's not feasible or something like that, or they must have proven that the thing is not feasible or not economic in some way for them to not be able to raise money. Because just on the concept, I feel like they could have raised more money. So I think that's an interesting one. What went wrong? \n\nSam Parr (0:47:12-0:47:17): But he said that he was going to send us one, and then his assistant or someone at the company was talking to us, and they just quit. \n\nShaan Puri (0:47:17-0:47:57): No, not send us one. They were like, we want you guys. Basically, their idea was, like, if you could make any drink flavor on the spot, okay, then what happens to drink brands? And his idea was, like, drink brands become software, so they just become brands. We would create a drink flavor Sam's Almighty root beer or whatever, and it would just be, like, a specific dosage of flavors, and that somebody could just buy it for a dollar on their own can of machine, and it would just dispense the drink, and we would make money for every one of those flavors sold. Basically every one of those drinks sold. That was the kind of the concept. So they wanted us to make one, and they were, like, come down to our facilities. We never got around to doing it, and now it's gone. \n\nSam Parr (0:47:58-0:48:00): Did you guys see the freestyle machine for Condiments? \n\nShaan Puri (0:48:00-0:48:02): Yes, I did. See this? \n\nSam Parr (0:48:02-0:48:05): Dude, sign me up. Sign me up, dude. \n\nSteph Smith (0:48:05-0:48:10): This stuff is have you been to, like, hot pot in Asia where they have the sauce bars? \n\nShaan Puri (0:48:10-0:48:10): No. \n\nSteph Smith (0:48:11-0:48:15): If you go to hot pot in Taiwan, there will be hot pot is. \n\nSam Parr (0:48:15-0:48:18): Like a style of food or like. \n\nSteph Smith (0:48:18-0:48:58): A yeah, so basically, you get a big pot of hot water. They give you broth of a certain sort, and then you basically go shopping on this wall, and you pick, oh, I want some noodles. I want some beef, whatever, and you pick it out. And then you basically cook your own soup. But as part of that, they have rice and other things, and they typically have this huge sauce bar of maybe, like 20 to 30 different things like garlic or ginger, soy sauce, like ponzi sauce, whatever, and you make your own sauce. And so when I saw this coming, I was like, this is genius because this exists in Asia, but only in these hot pot locations, right? \n\nShaan Puri (0:48:58-0:49:11): Yeah. I kind of love this. I really do want the future of food to be a lot more interesting. I think it's going to be. So in your Jobs thing, you got Food Engineer, got that one. Cyber actuary. What does that one mean? Have you explained that one? \n\nSteph Smith (0:49:11-0:50:07): Yeah. So basically, a lot of people, even if we relate this back to AI, are worried that there's just going to be a lot more cyber, quote unquote, crime. Right? People, like, replicating your voice, like getting your bank details. And I think this idea of being a cyber actuary is basically actuaries assess risk for anything, right. How risky is it for us to deploy this celebrity's voice in this way? How risky is it for us to, I don't know, like, open source our new LLM? There's going to be all these implications of things, I guess, becoming a lot more online, if they aren't already. And so this idea of a cyber actuary is like, there's already a ton of actuaries that figure out how much insurance should cost in the typical world, like if you buy a flight. And I think there's just like this huge white space around risk that people have not calculated yet. \n\nSam Parr (0:50:07-0:50:09): Did I tell you guys about Eden data? \n\nShaan Puri (0:50:09-0:50:10): No. \n\nSam Parr (0:50:11-0:51:36): So I met him because he's joined Hampton. His name is Taylor. And I don't know if he was playing up to my ego stuff, but he told me he created this because of an article that one of us wrote on Trends. I don't know if that's true or not, but he launched this thing called Eden Data in just two years. It's now doing like, six or $7 million in revenue. And basically what they do is if you are a smallish startup, so, like, 50 to 100 people, you have to have a certain type of compliance in order to sell software to enterprise companies. And so the service that he provides is and this is like an oversimplification, but there's basically like a 50 to 100 point checklist of all the things that you need to do. And a lot of these startups, they can't afford a full time chief security officer. And so instead, they pay Eden Data seven or eight or $10,000 a month. And he's got a team of outsourced people overseas who goes through your website and goes through your entire checklist and makes sure that all 50 or 100 things are done and they have templates to do it, and then they stay on top of it and they monitor it in case any changes have to happen. So now when you go and pitch, like, this enterprise company to sell your software and. Even though you're a small startup, you've already done all the stuff that needs to get done. And I think it's only two years in. I think he's going to do 8 million in revenue this year. And it's like a service that's subscriptions. It's like a subscription consultancy almost. And he's killing it. It's a crazy company with huge margins. \n\nSteph Smith (0:51:37-0:51:41): Damn. I have it pulled up. Your digital security sidekick. \n\nSam Parr (0:51:41-0:51:45): Yeah. When I see companies like this, I think, like, I'm in the wrong. \n\nShaan Puri (0:51:45-0:52:16): We were talking to somebody that was doing this. I wanted to do this for rich people. It was like just an overall security audit for rich people and everything. Like your house security, your bank account security, your crypto security. Just somebody who's going to come in and try to just poke holes in your stuff. And at a certain dollar amount of net worth, it definitely makes sense. And you're not the expert. And you have more to lose than you have than the cost of the service. You have a lot more to lose. It's like asymmetric downside, basically. \n\nSam Parr (0:52:18-0:53:07): I've reached out to tons of people I've reached out to tons of people doing it. And the problem that I saw is that a lot of them, they're all like ex military guys, too. And so I remember I was talking to I was like, pomp after the show. I was like, what do you do for security? Can you walk me through it? He goes, oh, I got this guy named Chad. We need this, this, and this. And then I talked to Chad and it's a little bit mom and pop. It's not like just like I could just log in and you could just tell me what to do or it can just get done. There's no plaid or whatever, that other software where you just log in with your bank accounts and it just does what you need to do. It was very much a manual process, and it was like 15 grand. And this person's going to do this. And so I do actually agree with you. I do think this is like a fragmented it's a fragmented service. And I think that one great company can do all the stuff you need to do. \n\nShaan Puri (0:53:07-0:53:20): Let's hit some of these other random trends you have. Don't mention the one I wrote. Don't mention because I got something in that space. Don't mention that one, but do some of these other ones. Let's start with a mouth tape. \n\nSteph Smith (0:53:20-0:53:32): Yeah, so mouth tape. I first heard about this like six months ago because some guy on Twitter was like, I tape my mouth shut every night for the last six months. Best thing I've ever done, dude. \n\nShaan Puri (0:53:32-0:53:37): The hostage tape guy will not be aggressive with it. \n\nSam Parr (0:53:37-0:53:48): We have this guy who's got a company he called Hostage Tape, and it's just tape for your mouth. And he told me he's going to launch it. And I'm like, this is dumb. And then six months later, he's like, $500,000 in sales. \n\nShaan Puri (0:53:48-0:53:48): Yeah. \n\nSam Parr (0:53:48-0:53:54): I'm like, great. And then he's like, a year later, $2 million in sales, and he's, like, just rubbing it into my face. \n\nSteph Smith (0:53:54-0:54:07): I don't think he's an official sponsor, but Andrew Huberman has been talking about it. And in my household, we like to call him Father Drew as a joke. But if Father Drew promotes something in this day and age yeah, he's like. \n\nShaan Puri (0:54:07-0:54:12): Bro oprah in a way where if he says bro science oprah. If he says it's good, you're just. \n\nSteph Smith (0:54:12-0:54:24): Going to get a huge, like yeah, I don't know where this goes. I don't know what opportunity there is other than going and selling some mouth tape. Maybe rebranding it. But that's one trend. \n\nSam Parr (0:54:24-0:54:33): This guy's company is called hostage tape. I saw this is the worst thing ever. This is awful. What do you do? But he's privy to that was your. \n\nShaan Puri (0:54:33-0:54:35): Weight loss idea, remember? Wasn't it called hostage? \n\nSam Parr (0:54:36-0:54:41): Yeah, a hostage SF, where I kidnap you and just don't feed you for four weeks. \n\nSteph Smith (0:54:41-0:54:43): You should partner. \n\nSam Parr (0:54:46-0:54:49): This guy's crazy. So whatever, kudos to him. \n\nSteph Smith (0:54:49-0:54:55): Yeah, but I guess we didn't even mention do you guys understand what's good about mouth tape? \n\nShaan Puri (0:54:55-0:55:00): It makes you breathe through your nose. And breathing through your nose is better for you than breathing through your mouth. \n\nSteph Smith (0:55:00-0:55:11): Okay. Speaking of health benefits, another trend that I would love to see take off, because then I would have called it is lupini beans. Like, health. \n\nSam Parr (0:55:11-0:55:13): Haven't you been talking about this bean forever? \n\nSteph Smith (0:55:14-0:55:20): For the last year, I went into, I don't know, all the American grocery stores. \n\nSam Parr (0:55:20-0:55:22): Like the high protein bean. \n\nSteph Smith (0:55:22-0:55:23): Yeah. So it's got dude, you've been talking. \n\nSam Parr (0:55:23-0:55:27): About this to me forever. You keep telling me about this bean. I've been out with you a bunch of times. \n\nSteph Smith (0:55:27-0:56:05): You always have more protein than chickpeas or two times more fiber than Edamame. 80% fewer calories than almonds, 60% fewer carbs than pistachios, 35 grams per serving. Obviously they cherry picked this data and compared to the best option for them. But these beans, I think they're, like, originally from Italy or they're popular there. But I just have seen this over and over and over as someone who traveled a lot where, like, Edamame. Edamame was not popular in North America 2030 years ago, no one knew what it was. Right. It came from Asia. And so now when you go to restaurants, it's like a very short thing. \n\nShaan Puri (0:56:05-0:56:08): How would you like to invest in the next set of honor? \n\nSteph Smith (0:56:11-0:56:19): Sam, do you remember when Bobby at Hustlecon would go around pitching people joke and he's like his pitch tuna water. \n\nSam Parr (0:56:19-0:56:21): No, I thought it was hot dog water. \n\nSteph Smith (0:56:21-0:56:22): It was tuna water. \n\nSam Parr (0:56:25-0:56:28): Dude, have you guys had chickpea pasta? \n\nShaan Puri (0:56:28-0:56:28): Of course. \n\nSteph Smith (0:56:28-0:56:29): I don't like it. \n\nSam Parr (0:56:29-0:56:34): Makes you fart like crazy, man. It'll give you the number. \n\nShaan Puri (0:56:34-0:56:48): 340 percent as many calories as almonds, but 70% more gas that's the Lupin DB pitch. Okay. So you've been calling this for a little while. This seems like a good D to C product idea, to be honest. \n\nSteph Smith (0:56:48-0:56:51): There's, like, one company doing it, this. \n\nShaan Puri (0:56:51-0:56:52): One brahm or whatever. \n\nSteph Smith (0:56:52-0:57:07): Yeah, brahmi. They also do, I think, the chickpea pasta. But I just think maybe there's something in the supply chain or, like, how hard it is to procure this stuff. But to me, they're pretty cheap. They taste really good. \n\nSam Parr (0:57:07-0:57:08): You eat them plain. \n\nSteph Smith (0:57:08-0:57:14): Well, at least this company will do flavored versions. So they'll do, like, rosemary, garlic, or. \n\nSam Parr (0:57:14-0:57:15): Does it give you gas? \n\nSteph Smith (0:57:15-0:57:19): I don't think so. I didn't do an A B test. \n\nSam Parr (0:57:19-0:57:22): You can admit I don't think you did. \n\nShaan Puri (0:57:22-0:57:31): It's a safe space. Seems like you can say it for every episode. Okay. \n\nSam Parr (0:57:31-0:57:32): All right, I'm going to buy some. \n\nShaan Puri (0:57:32-0:57:48): I like this idea. Yeah. I'm going to try these out and see how I feel about it. By the way, this is the type of product that when we say on MFM, there's going to be 13 people that start this for six weeks, and then nobody six months later will be doing it for whatever reason. \n\nSam Parr (0:57:48-0:57:55): And the same people that tell us they're going to come back in eight weeks and they're going to say, actually, what do you think about this idea? \n\nShaan Puri (0:57:55-0:58:03): Yeah, if my DM history has four different ideas from you that you were pitching me for investment, it's probably not going to work out. \n\nSteph Smith (0:58:03-0:58:04): It's a no forever. \n\nShaan Puri (0:58:05-0:58:07): You got the forever. No. \n\nSam Parr (0:58:10-0:58:13): I'm feeling that line. This is a no forever. \n\nSteph Smith (0:58:17-0:58:24): Can we do one more around these Advent calendars? Because I feel like that's another case where, like, I don't know, someone in the community is going to jump on. \n\nSam Parr (0:58:24-0:58:25): Sean, do you even know what admin. \n\nShaan Puri (0:58:25-0:58:28): Is this some, like, Catholic shit. What is this? \n\nSam Parr (0:58:28-0:58:43): Yeah. This is as Catholic. As Catholic. Can get advent in December. Catholics. I'm Catholic. Are you Catholic, Seth? No, heathen. \n\nSteph Smith (0:58:43-0:58:43): Sorry. \n\nSam Parr (0:58:46-0:59:24): The Catholics. Yeah, you're not one of us, but it's okay. We have Lent, which is, like, 40 days, and that was when Jesus walked around in the desert, and you're not supposed to eat meat and shit like that. And then we have Advent, which is the 30 days leading up to Christmas. And oftentimes there's an Advent calendar where it tells a story about what Mary and Joseph, Jesus's parents, like, what they did with the donkey and the mule and how they got all these gifts from people, whatever. It tells that story. And each day you open up the calendar. It's like the kid's favorite thing. There's a piece of chocolate in the calendar? \n\nSteph Smith (0:59:24-0:59:33): Yeah, I'm sure you've seen the Advent calendars at some point. It was a religious thing. Then capitalism got involved, and then every day, kids are opening a little chocolate. \n\nShaan Puri (0:59:33-0:59:40): I swear, my whole I thought the Advent calendar was those little calendars that are like, you peel it and there's like, peel the calendar for each day. \n\nSteph Smith (0:59:40-0:59:40): Oh, yeah. \n\nShaan Puri (0:59:40-0:59:45): I've been walking around thinking that's what an Advent calendar is. For a long time, my whole life. \n\nSam Parr (0:59:45-0:59:47): I would say this one, you like, peel back. \n\nShaan Puri (0:59:47-0:59:49): It's always chocolate inside. That's the idea. \n\nSteph Smith (0:59:50-0:59:57): Usually that one you get at like Target or whatever. And yeah, it's like a couple of dollars, but it's like the most simple. You buy it for your kids. \n\nShaan Puri (0:59:57-0:59:58): So what's your idea here, Seth? \n\nSteph Smith (0:59:59-1:00:01): The better advent calendar. \n\nSam Parr (1:00:05-1:00:06): Five minute ad? \n\nSteph Smith (1:00:08-1:00:12): No. So this comes from I got to give this guy namazaki, Paul. \n\nSam Parr (1:00:14-1:00:16): He doesn't sound like a Catholic. \n\nSteph Smith (1:00:16-1:00:50): No, this is it. I don't think this has to do with religion, but I actually got this for Cal this past year because here's the thing. Advent calendars? Yeah, I guess it was tied to religion, but they happen around the holidays, and so people are scrambling to figure out last minute, like, what should I get my family as a gift? That's kind of thoughtful, but fun. And a lot of people get Advent calendars, but they get these shitty versions that are like expired milk chocolate from the year before. What Paul did is he created this sake calendar. And so if you click, that's the. \n\nSam Parr (1:00:50-1:00:52): Best way to celebrate Jesus's birth, too. \n\nSteph Smith (1:00:54-1:02:05): He created this sake calendar where basically every day for the month of December, or you can use it after you open your little Advent calendar, but it's not little. It's like the size of a printer kind of thing. And you get this special sake that he has handpicked from Japan. This is partially like his job, his existing business, and he sells them for $300. And every year he sells 500 of them, which he caps. And you do the math, that's like $150,000 just from that one drop for him. And he doesn't get that much traffic. Like, if you look at his existing site, gets like 2000 visits per month. So not something he would typically be able to make much money from. But that's one example that just got me thinking, especially since we're like, what, six months ahead of Christmas? What Advent calendars is the my first million community. What are you going to make that is way cooler than the expired milk chocolate? I mean, I've seen some stuff like hot sauce calendars, Lego calendars, but it's got to be something that someone can open either for twelve days because some people do the twelve days of Christmas or all of December. \n\nSam Parr (1:02:06-1:02:28): This is actually cool. Yeah, I actually think this is really cute and cool and awesome. You have a picture of this person who has a binder full of condiments, like individual packets. And I see your vision here. This is actually cool. I smell what you're stepping in, and I think it's awesome. \n\nSteph Smith (1:02:28-1:02:31): Well, the tweet you're talking about, Sam. \n\nShaan Puri (1:02:31-1:02:32): What is that phrase? \n\nSteph Smith (1:02:33-1:03:01): Is this girl Nicole, who says her tweet just says, organize my sauces. And it's like, do you guys remember if you collected playing cards back in the day or coins? They had those binders. Yeah. With the little I don't even know what they're called, but this tweet got 468,000 likes. I think it's probably one of the most popular tweets of all time. And it's just her organizing her sauces from around the world. \n\nShaan Puri (1:03:01-1:03:04): So these are not for use. This is just like collections. \n\nSteph Smith (1:03:05-1:03:09): That one is for a collection. I feel like the Advent calendar, it would be for use. \n\nShaan Puri (1:03:09-1:03:11): Yeah. Wow, this is crazy. \n\nSam Parr (1:03:12-1:03:24): What I like about you, Steph, is like, you find things that I would just scroll by, but you're pretty good at finding interesting things and applying them, connecting to five other things. Yeah. \n\nShaan Puri (1:03:24-1:03:30): When I scroll past something and I think, this is stupid, you write that thing down and make it sound smart. It's amazing. \n\nSteph Smith (1:03:30-1:03:35): I waste my time curating an Evernote that is just full of random Internet shit. \n\nSam Parr (1:03:36-1:04:06): But what you do something that's different is you actually remember it. So I bookmark so much stuff, and then I just forget all about it. You actually remember it, and then it's just the difference between good and great in terms of whatever the skill set is that we have. You actually are organized. What makes someone good versus great is, like, being organized. You are very organized with this stuff, and that actually helps your thought process, I would think. When are you just going to bail and start creating some of this stuff? \n\nSteph Smith (1:04:06-1:04:43): I feel like you started this train, Sam. So before I joined the Hustle, I was working at a company, and in my last year at that company, I said and I must have been, what, 24 or something? Yeah. Around that. I was like, next. This is the last job I'll have. Right. Like, after this, I'll go and do my own thing, but then ever since then, I just keep getting offered really cool stuff that I get to more money. Well, I get to be paid to go research trends and go down these Internet rabbit holes that I'd be doing anyway. Okay, great. Oh, we got acquired. Now I'm at HubSpot, and I get to build this cool crater program. Okay, great. \n\nSam Parr (1:04:43-1:04:44): And more money. \n\nSteph Smith (1:04:46-1:04:50): Now I'm at a 16 Z. I get to talk to interesting people and more money. \n\nShaan Puri (1:04:52-1:04:56): I got to meet this interesting person with more money in my pocket. It was amazing. \n\nSam Parr (1:04:59-1:05:07): You're learning this sepsis sitting there. She's like, how could I get the things that are in their bank account to my bank account? \n\nShaan Puri (1:05:08-1:05:25): My daughter does this thing where she's three years old, and she says this thing where she goes, this is my best day ever. And I'm like, she might actually be telling the truth. This might have been, like, the best day ever for her. This is the one. That's how I feel whenever she gets a raise at this is my best day ever, guys. \n\nSam Parr (1:05:30-1:05:42): Steph, you and I were talking about how much money you've had. We were going through an exercise of, like, at 20, we had this at 23. You've had a nice run. You've had a very nice run. \n\nSteph Smith (1:05:42-1:05:54): A very nice run compared to where I came from. So, yeah, like you were saying earlier, Sean, if like, 21 year old me would have said, this is where you'll be, this is how much you'll make, these are, like, the opportunities you'll have. Yeah, it's pretty wild. \n\nSam Parr (1:05:54-1:05:56): Are you even 30? \n\nSteph Smith (1:05:56-1:05:56): No. \n\nSam Parr (1:05:56-1:05:57): Oh, my God. \n\nShaan Puri (1:05:58-1:06:02): What would 20 year old year old you say? What would the reaction be? \n\nSteph Smith (1:06:02-1:06:28): Well, it's funny because I feel like I still have throughout my whole life because I didn't grow up very wealthy. It was very money orientation. Not that I need that much, but just like, oh, my gosh, you have that much money. Go buy a car, go buy nice clothes, go use the money that you've always wanted but never had. But it's funny because now that I have more money, I'm still just as cheap as I ever was. I don't know if that stuff ever leaves you. \n\nSam Parr (1:06:28-1:06:33): Sean, do you know that Steph's half Taiwan? \n\nSteph Smith (1:06:33-1:06:34): My mom's from Taiwan. Yeah. \n\nSam Parr (1:06:34-1:06:35): Do you know that? \n\nShaan Puri (1:06:35-1:06:37): No, I didn't know that. \n\nSam Parr (1:06:38-1:06:40): Super special or what? \n\nShaan Puri (1:06:40-1:06:41): Why are you telling me that? \n\nSam Parr (1:06:42-1:06:50): At our old company, when someone found that out, and I was like, yeah, I could see that. There was like people like, Steph, why are you lying to us? You're Canadian. \n\nSteph Smith (1:06:50-1:06:54): I've had some well, Canadians not I know. \n\nSam Parr (1:06:54-1:06:58): That was the joke. They're like, quit lying. Why are you lying about being Taiwanese? \n\nSteph Smith (1:06:58-1:07:17): Jordan was like, so there's a huge spectrum. I don't know why what it is about the way I look, but some people, when they hear that I'm half Asian, are like, oh, yeah, of course I knew that. And then other people are truly shocked. Jordan was one of those. And he went to Sam or no, he asked me, and he was like, does Sam know this. \n\nShaan Puri (1:07:19-1:07:31): Your secret thing that tells you more about them than about the way you look? It's just like, what is their level of exposure to different races versus anything to do with you? \n\nSteph Smith (1:07:32-1:07:32): Yeah. \n\nShaan Puri (1:07:32-1:07:58): By the way, this thing about being cheap. I was reading the story yesterday about this guy who made a bunch of money, and they're like, what was your first purchase? He goes, I hired a consultant to help me spend money. And he goes, I had learned over 25 years how to make money. It took me a long time to learn how to make money, and I was just very honest with myself that I have no idea how to spend money. And I could shorten that learning curve if I get a coach to help me spend money. \n\nSam Parr (1:07:58-1:08:04): What was this coach called? A wife. I'll be here all night. \n\nSteph Smith (1:08:04-1:08:11): I was going to say, isn't that, like, remiss thing too? I feel like he talks about that all the time. Right? You got to learn to spend it's. \n\nSam Parr (1:08:11-1:08:14): Like it takes reps. What was the coach actually called? \n\nShaan Puri (1:08:15-1:08:21): I don't know. I don't know. Actual job title, but spending consultant, let's call it. \n\nSam Parr (1:08:21-1:08:23): But what do they teach you how to do? \n\nShaan Puri (1:08:24-1:09:55): I don't know. He didn't go into details on exactly what the guy said, but let's just pretend for a minute that he did. I would imagine he does two things. One is figures out where your psychology screwed up about money, because everybody's got like, this. It's like, you know, people have, like, body dysmorphia. I think everybody has bank account dysmorphia too. You think you need more money than you need. Even when you have money, you still act like you don't have money. It's like all this weird stuff. It's like, dude, you're fit now. Why do you still think you're fat? You have to sort of retrain yourself to see something different in the mirror. I think that's part of it. Just talking to figure out what are the ways your brain is a little screwed up about money, let's identify that first. Some people spend too much. Some people don't spend at all. And then I think the second thing would be like, all right, what do you really want? So let's try to outline your dream lifestyle or the things you really want. Identify those, and then let's calculate, like, okay, how much those costs? Could you afford those now? Could you afford a step in that direction and giving you the encouragement to pull the trigger on the things that you actually want? Or setting certain rules, like, you have to spend this much per month. What are you going to spend it on? And also on the protective downsides. It's like, hey, we're going to set aside this amount of money so that your safety reflex is satisfied. We agree that logic, by all logic, this amount of money being here untouched means you're safe. Okay, cool. So now we can talk about this other spending part without triggering your fight or flight mode around your fear of financial safety. \n\nSam Parr (1:09:56-1:10:00): Where was this article? Yeah, I want to look this up. I need one of these things. \n\nShaan Puri (1:10:00-1:10:04): Yeah, you should look it up. I don't know. I don't know if this exists. Maybe it's the job of the future. \n\nSteph Smith (1:10:04-1:10:30): I don't know if his recent episodes are the same, but Ramit's early podcast episodes would do this, right? They talk to millionaires who are fretting about $8 blueberries at Whole Foods. Or, like, I remember one episode where this guy was like, I think had at least $10 million and was picking up a stroller on the side of the road, things like that, where it's like, clearly, yeah, you haven't upgraded your thinking or your mindset to where you are. \n\nSam Parr (1:10:30-1:10:57): Dude, I just made $400 selling used gym equipment from some stuff I'm not using. And I'm like, this is my best day ever. I feel more happy about that $400 than I do making much larger sums. Yeah, and the best part is that I paid $300 for it five years ago. Now I got $400, and it's like the best high. \n\nShaan Puri (1:10:57-1:11:46): I read this thing that was like this guy Timer who created he's got this company called Causal, and it's like this Excel competitor, but he has this blog post I really liked where he was like he was trying to figure out in a nerdy way how to decide if you should buy something or not. And so he's like, will I break everything down into kind of like I don't remember the exact message, but it was something like this. It was like the frequency of how frequently am I going to get the benefit of this? And then, what's the magnitude of the benefit? And so he's like something that's it doesn't have to be a big ship, but if it's going to happen all the time or like ten times a day or something like that. I bought a phone case that just feels better in my hand, and it was like a great purchase because the hand feel of my phone is something I am touching my phone all the time and just making that feel a little smoother, a little better was like. \n\nSam Parr (1:11:46-1:11:49): Dude, what's that case called? By the way, I'm looking very good. \n\nShaan Puri (1:11:49-1:11:51): Let me look up hand feel. \n\nSteph Smith (1:11:52-1:11:54): Do we know how much it costs? \n\nShaan Puri (1:11:54-1:13:23): Yeah. Is it going to be pre plugged for you guys? Moaz, I think, is the name of it, but it's got this, like this is not like plastic feel. So this feel right here is like almost like the feel of a basketball. It's almost like attraction kind of like feel. Because I was like, I hate the plastic feel of cases. I think that feels cheap, and I don't enjoy it. I didn't want the leather ones either, so I was like, what else is there? And found that. And so he identifies, like, if you're going to do it, if it's going to be frequent, then the magnitude needs to be less. If it's going to be infrequent, then the magnitude of the joy it brings is going to need to be high. And you can kind of multiply those two together to figure out the value of that item. And then you sort of say, okay, that's the value to me, and then what's the price to me? And you sort of use that to figure out where should you spend versus not. And what people mostly get wrong in that is they undercount frequency. So like, a better pillow or something like that is great because you're going to sleep on it every single night versus a Louis Vuitton bag that's going to sit in your closet. Like, my wife's bought a Louis Vuitton bag, and she literally never takes out. She doesn't want it to get messed up. It's like, wow, that's the most expensive $6,000 thing that just sits in a closet for no reason versus things that you get joy out of all the time. And so I bet if you guys looked at what's the best purchase you made or you're most satisfied with this year, it's probably something that you interact with somewhat frequently, or it was, like, a one off, life changing experience that was just, like, crazy magnitude. \n\nSteph Smith (1:13:23-1:13:24): Yeah. \n\nSam Parr (1:13:24-1:13:29): What was that article called? I want to read. I need some good money therapy in my life. \n\nSteph Smith (1:13:29-1:13:31): Money Therapist. That's the title. \n\nSam Parr (1:13:31-1:13:41): Yeah. I need some good money. Therapy. Yes. Send me an article. But, Steph, I appreciate you doing this. You're always coming with fire. You're a Twitter person still, right? \n\nSteph Smith (1:13:42-1:13:50): Steph Smith IO is the handle. And if you want to support my day job, go listen to the A 16 Z podcast. We're doing some cool stuff there. \n\nSam Parr (1:13:50-1:13:53): That's just what it's called, a 16 Z podcast, right? \n\nSteph Smith (1:13:53-1:13:53): Yes. \n\nSam Parr (1:13:54-1:13:55): All right. We appreciate you. Thank you. \n\nSteph Smith (1:13:55-1:13:56): Thank you. \n\nShaan Puri (1:14:00-1:14:10): I feel like I could rule the world. I know I could be what I want to. I put my all in it like, no days off on the road. Let's travel, never looking back. Aglight. \n\n" }, { "path": "data/Transcripts/acme_co_v2.txt", "content": "Greg (Marin Transitions Partner): Does this say the call is recording for you at all? \n\nEliza (ACME Co): But it says the request, the report or in here? \n\nGreg (Marin Transitions Partner): Nice. All right… one sec. \n\nGreg (Marin Transitions Partner): Cool. Absolutely. Well, I tell you what, thank you very much for joining me today. \n\nEliza (ACME Co): Yeah, glad to be chatting with you Greg. \n\nGreg (Marin Transitions Partner): Absolutely. Well. So, first of all, my name is Greg and I am from Marin transitions and we help people do social modeling on top of their businesses. So say somebody were to mention you on read it or mentioned you on Twitter or Facebook, then we help you understand what they're saying and the sentiment behind it. And I'm very excited to be chatting with you today. My first awesome. Well, I'll tell you what I've looked at your LinkedIn a little bit, but could you tell me more about your position and what you do? \n\nEliza (ACME Co): Absolutely. So I am cmo over at acmico and we are a software company that helps nonprofits grow their business. \n\nGreg (Marin Transitions Partner): Awesome. That's fabulous. And how many employees does acmico have? \n\nEliza (ACME Co): We have about 45 employees today. \n\nGreg (Marin Transitions Partner): Nice. That's great. And how big is the marketing team? \n\nEliza (ACME Co): The marketing team is, I think seven of us today. \n\nGreg (Marin Transitions Partner): Awesome. That's cool. And what technology stack does acme co use? \n\nEliza (ACME Co): So, today, we are using slack photoshop, Hubspot, Zoom and Google cloud. \n\nGreg (Marin Transitions Partner): That's awesome. And so, because we do social monitoring, I wanna go into a little bit of questions around your social experience, if you will, and what acne code does. So, how many times would you say that you post on social media per month? \n\nEliza (ACME Co): I'd say about 10 times a month? \n\nGreg (Marin Transitions Partner): Interesting. And do you do any sort of social monitoring today? Do you know what customers are saying about you on those platforms? \n\nEliza (ACME Co): No, we have no idea. \n\nGreg (Marin Transitions Partner): Interesting. And what are the pain points you're having by not being able to do social monitoring? \n\nEliza (ACME Co): Yeah, I'd say the pain points of not having social monitoring revolve around the lack of transparency. So we're by not understanding what our customers are saying about us on social media, that is a disadvantage in a very competitive market. \n\nGreg (Marin Transitions Partner): Yeah, absolutely. And would you or I guess, let me rephrase how valuable would it be to you to understand what customers are saying about your brand in real time? \n\nEliza (ACME Co): I think it could have significant value to understand in real time. What's ap? \n\nGreg (Marin Transitions Partner): Happening. Nice. And if you were to put a dollar amount on that, what would you say? What would you say? The dollar amount would be? \n\nEliza (ACME Co): I would estimate, you know, if each… having this kind of transparency and visibility into our market, if that enables us to close one more deal per month. Now, with, given our average contract values, I'd say 50,000 dollars. \n\nGreg (Marin Transitions Partner): Yeah, no, that's very cool. And who would be the person that would sign off on this purchase? \n\nEliza (ACME Co): So there would be, that would be a committee decision between myself and the rest of the leadership team. But the ultimate signer of the contract would be my CEO Christina. \n\nGreg (Marin Transitions Partner): Interesting. And so as we think about this social monitoring even more, what are your priorities for a tool? What would you like to see? \n\nEliza (ACME Co): I would like to see a tool that is able to accurately… in real time, tell me about… the data that my customers are saying about the company about our product… to stay ahead of, you know, potential risks. So protect that revenue and our existing customers. And then in terms of criteria for a partner, we were looking for someone that we can scale with as we build out our marketing program and someone that's going to offer the hands on white glove support that we need. \n\nGreg (Marin Transitions Partner): Yeah, no, that's awesome. And what is the process to get a new deal across the finish? Line? So, what is your evaluation process look like? \n\nEliza (ACME Co): So, it is usually pretty easy process for us being a, an agile team over here. That process looks like I evaluate vendors, narrow that list down. We have about two options narrowed down today, one being your company. And then from there, I'll present and make my recommendations to the CEO. \n\nGreg (Marin Transitions Partner): Nice and say you make a decision, you're happy with it, what is the paper process that you need to go through to complete the decision? Is there accounting or legal or anybody? \n\nEliza (ACME Co): Yes, there is a legal and security review as part of the process which would be conducted by our in house council. So you could send through your terms at any point and we could get ahead of that review if that would be… helpful. \n\nGreg (Marin Transitions Partner): Yeah, that's sweet. What are the, what other tools are you looking at as a part of this evaluation? \n\nEliza (ACME Co): We're also looking at Hootsuite. \n\nGreg (Marin Transitions Partner): Interesting. Well, first, I wanna thank you very much for being such a big supporter of what we're doing here at Marin transitions? \n\nEliza (ACME Co): Absolutely. I'm happy to be your champion over here. I think, you know, based on the great conversations that I've had… with your team in the past and my last company… and also your, the recommendations that I've heard in referrals from some of your other customers in my peers have gone a long way. \n\nGreg (Marin Transitions Partner): That's awesome. Do you have any questions for me? \n\nEliza (ACME Co): Yeah. So as I mentioned, support is going to be important. I'm sure you're aware everyone is wanting to avoid shelfware these days. So what I'm curious about is how long does it take to get started on your platform? And what does that implementation process look? \n\nGreg (Marin Transitions Partner): Absolutely. So the implementation process is really in two parts. Part number one is just gonna be a about an hour long session with one of our implementation partners and your head of social media that's just to make sure that your accounts get set up and that we're doing the tracking properly. Then part two is going to be the actual monitoring part. It takes about four hours to start monitoring, but after that, it'll be available for you in real time and that's just so we can go scrape all the data off the social sites. So that net you should be up and running in about half a day's work. That sounds. \n\nEliza (ACME Co): Perfect. \n\nGreg (Marin Transitions Partner): Yeah, absolutely. Well, I tell you what, as a next step, what I'm gonna do is I'm going to share the brochure with you about our company that has all the information you may want on it. And I'm also going to share with you the pricing information as well. And so this is some deck that I'll send over. And so you can see that. And what I would love to do as a follow up is to schedule a new meeting with you for next week, probably on Wednesday. Is there a time that works on Wednesday for you? \n\nEliza (ACME Co): Yes, I'm available any time between two and four PM on Wednesday, Pacific Time. So if you want that invite, I'll go ahead and accept it. \n\nGreg (Marin Transitions Partner): Cool. Absolutely. I'll send an invite for that time. \n\nGreg (Marin Transitions Partner): One last thing too. I always like to get to know my prospects a bit more on a personal level too. Do you have any pets or animals inside the house that are close to you? \n\nEliza (ACME Co): I do. In fact, I have an Australian Shepherd dog. He's very cute and very crazy. \n\nGreg (Marin Transitions Partner): Awesome. No, that's great. And what do you like to do outside of? \n\nEliza (ACME Co): Well, I live in the beautiful bay area in the north bay just north of San Francisco. So my husband and I really enjoy hiking on the nearby trails. We enjoy wine tasting up in wine country… and those are a couple of our favorite things to do on the weekends. \n\nGreg (Marin Transitions Partner): That's fabulous. Well, I tell you what, thank you very much for the conversation today and I'll follow up with you next week. \n\nEliza (ACME Co): Great. I'm looking forward to. \n\nGreg (Marin Transitions Partner): It all right. We'll see you later. Bye bye. " }, { "path": "data/matching_tone_samples.json", "content": "{\"jaltma\": \"User: jaltma\\nSimilar Authors: Paul Graham, Sam Altman, Naval Ravikant, Jack Dorsey\\nTone Description: ['1. Pace: Fast-paced and concise, quickly getting to the point.', '2. Mood: Casual, conversational, and engaging.', '3. Tone: Opinionated, confident, and assertive.', '4. Voice: Informal, personal, and relatable.']\\n\\n1st - Topics this author may talk about:\\n- Startup growth and challenges\\n- Leadership qualities and development\\n- Personal growth and self-improvement\\n- Networking and relationship building\\n- Work-life balance and productivity\\n- Technology trends and their impact on society\\n- The importance of adaptability and resilience\\n- The role of mentors and advisors in startups\\n- The future of work and remote work culture\\n- The power of storytelling in business\\n\\n2nd - Concise passage as the author:\\nJust had a chat with a founder who's stuck in the \\\"we need funding\\\" loop. Here's the deal: focus on building a product users love, and the money will follow. Investors chase great products, not the other way around. Keep it simple, folks.\", \"lindayacc\": \"User: lindayacc\\nSimilar Authors: Ellen DeGeneres, Chrissy Teigen, Kim Kardashian, Oprah Winfrey\\nTone Description: ['1. Pace: Fast-paced and energetic, with a sense of immediacy.', '2. Mood: Lighthearted, enthusiastic, and celebratory.', '3. Tone: Confident, opinionated, and playful.', '4. Voice: Bold, engaging, and conversational.']\\n\\n1st - Topics this author may talk about:\\n1. Women empowerment and gender equality\\n2. Environmental issues and sustainability\\n3. Social media trends and popular culture\\n4. Celebrity collaborations and events\\n5. Fashion and beauty\\n6. Parenthood and family life\\n7. Mental health and self-care\\n8. Travel and adventure\\n9. Technology and innovation\\n10. Sports and fitness\\n\\n2nd - Concise passage as the author:\\nOMG, just tried the latest eco-friendly makeup line, and I'm OBSESSED! \\ud83c\\udf3f\\ud83d\\udc84 Saving the planet never looked so fab! \\ud83d\\udc81\\u200d\\u2640\\ufe0f Let's all glam up and make a difference, babes! \\ud83d\\udc8b #SustainableBeauty #GirlPower\", \"ShaanVP\": \"User: ShaanVP\\nSimilar Authors: Gary Vaynerchuk, Naval Ravikant, Tim Ferriss, Elon Musk\\nTone Description: ['1. Pace: Fast-paced and energetic, with quick thoughts and ideas.', '2. Mood: Casual, light-hearted, and occasionally sarcastic.', '3. Tone: Opinionated, confident, and assertive.', '4. Voice: Conversational, relatable, and engaging.']\\n\\n1st - Topics this author may talk about:\\n- The future of AI and its impact on society\\n- The importance of personal branding in the digital age\\n- The role of cryptocurrencies in the global economy\\n- The power of social media and its influence on entrepreneurship\\n- The art of productivity and time management\\n- The rise of electric vehicles and renewable energy\\n- The value of networking and building relationships\\n- The challenges and rewards of starting a business\\n- The role of mental health in achieving success\\n- The impact of technology on the job market\\n\\n2nd - Concise passage as the author:\\nJust had a convo with a buddy about AI's impact on jobs. Here's the deal: it's gonna change the game, no doubt. But instead of freaking out, let's adapt and learn new skills. Embrace the tech, folks! #AIRevolution\", \"dharmesh\": \"User: dharmesh\\nSimilar Authors: Dharmesh Shah, Sam Altman, Jeff Bezos, Howard Schultz\\nTone Description: ['1. Pace: Fast-paced and engaging, with a sense of urgency and excitement.', '2. Mood: Confident, enthusiastic, and passionate.', '3. Tone: Opinionated, assertive, and bold.', '4. Voice: Active, conversational, and personal.']\\n\\n1st - Topics this author may talk about:\\n1. Disruptive innovation in the tech industry\\n2. The importance of risk-taking in entrepreneurship\\n3. The power of artificial intelligence in shaping the future\\n4. The role of company culture in driving success\\n5. The impact of unconventional thinking on business growth\\n6. The challenges and rewards of scaling a startup\\n7. The influence of big tech companies on the global economy\\n8. The potential of decentralized technologies like blockchain\\n\\n2nd - Concise passage as the author:\\nEmbrace the unknown, challenge the status quo. In a world of AI and rapid innovation, it's the bold, unconventional thinkers who'll shape our future. Dare to disrupt, and you'll leave a lasting impact.\", \"sweatystartup\": \"User: sweatystartup\\nSimilar Authors: Gary Vaynerchuk, Grant Cardone, Tai Lopez, Tim Ferriss\\nTone Description: ['1. Pace: Fast-paced and energetic, with a sense of urgency.', '2. Mood: Assertive, confident, and sometimes confrontational.', '3. Tone: Opinionated, strong, and decisive.', '4. Voice: Bold, direct, and unapologetic.']\\n\\n1st - Topics this author may talk about:\\n- The importance of hard work and determination in entrepreneurship\\n- Challenging conventional wisdom and societal norms\\n- The role of technology in modern business\\n- The value of personal responsibility and accountability\\n- The power of networking and building relationships\\n- The impact of mindset on success and failure\\n- The benefits of taking calculated risks in business\\n- The importance of adaptability and resilience in a constantly changing world\\n- The role of education and self-improvement in personal and professional growth\\n- The dangers of complacency and stagnation in business and life\\n\\n2nd - Concise passage (under 300 characters) as if you were the author described above:\\n\\nStop waiting for the perfect moment. Success isn't handed to you on a silver platter. Get out there, hustle, and make it happen. Embrace failure, learn from it, and keep pushing forward. No excuses.\", \"levelsio\": \"User: levelsio\\nSimilar Authors: Elon Musk, Naval Ravikant, Pieter Levels, Sahil Lavingia\\nTone Description: ['1. Pace: Fast-paced and concise, with quick thoughts and ideas shared.', '2. Mood: Casual, conversational, and sometimes humorous.', '3. Tone: Opinionated, confident, and assertive.', '4. Voice: Informal, personal, and engaging.']\\n\\n1. Topics this author may talk about:\\n- Entrepreneurship and startups\\n- Personal productivity and time management\\n- Technology trends and innovations\\n- Social media and its impact on society\\n- Travel experiences and cultural observations\\n- Investing and personal finance\\n- Work-life balance and mental health\\n- Artificial intelligence and its applications\\n\\n2. Concise passage as the author:\\nJust hit 10k followers on TikTok, and I'm telling you, it's the new goldmine for indie hackers. Twitter's overcrowded, but TikTok's ripe for the taking. Don't follow the herd, pave your own path! #indiehackers #tiktokrevolution\", \"Suhail\": \"User: Suhail\\nSimilar Authors: Elon Musk, Sam Altman, Naval Ravikant, Andrew Ng\\nTone Description: ['1. Pace: Fast-paced and energetic, with a sense of urgency.', '2. Mood: Confident, assertive, and enthusiastic.', '3. Tone: Opinionated, bold, and direct.', '4. Voice: Conversational, engaging, and personal.']\\n\\n1st - Topics this author may talk about:\\n- The future of AI and its impact on society\\n- Personal growth and learning in the tech industry\\n- The role of AI in education and communication\\n- The importance of perseverance in achieving success\\n- The characteristics of great products and their impact on users\\n- The challenges and opportunities in AI research and development\\n- The role of AI in transforming industries and creating new opportunities\\n- The importance of staying up-to-date with the latest technological advancements\\n\\n2nd - Concise passage as the author:\\nAI's future is now. Embrace it, learn, and grow. Perseverance is key. Great products? They blend in, respect time, and enhance life. Don't waste a minute. Dive into AI, ship real things, and watch opportunities unfold. The world is changing, and we're part of the revolution.\", \"hwchase17\": \"User: hwchase17\\nSimilar Authors: Elon Musk, Sam Altman, Andrew Ng, Demis Hassabis\\nTone Description: ['1. Pace: Fast-paced and energetic, quickly presenting information and ideas.', '2. Mood: Excited and enthusiastic, creating a sense of anticipation.', '3. Tone: Confident and assertive, taking a strong stance on the subject matter.', '4. Voice: Informative and engaging, with a touch of informality.']\\n\\n1st - Topics:\\n- AI advancements in various industries\\n- The future of autonomous vehicles\\n- AI's role in climate change solutions\\n- The impact of AI on job markets\\n- AI ethics and regulation\\n- AI in healthcare and medicine\\n- AI in space exploration\\n- The role of AI in education and edtech\\n\\n2nd - Passage:\\nWe're thrilled to announce our upcoming webinar on AI's transformative role in healthcare! Join us to explore groundbreaking innovations and the future of personalized medicine. Register now: https://t.co/aiHealthcareWebinar\", \"elonmusk\": \"User: elonmusk\\nSimilar Authors: Elon Musk, Jack Dorsey, Mark Zuckerberg, Sundar Pichai\\nTone Description: ['1. Pace: Fast-paced and concise, with quick updates and announcements.', '2. Mood: Casual, conversational, and occasionally thought-provoking.', '3. Tone: Confident, assertive, and opinionated.', '4. Voice: Informal, direct, and engaging.']\\n\\n1. Topics this author may talk about:\\n- Technology updates and advancements\\n- Social media trends and features\\n- Personal experiences and opinions\\n- Current events and news\\n- Entrepreneurship and leadership\\n- Artificial intelligence and automation\\n- Space exploration and renewable energy\\n- Privacy and security in the digital age\\n- Cryptocurrency and blockchain technology\\n- Productivity and work-life balance\\n\\n2. Concise passage as the author described above:\\nJust had a chat with the team about our new AI project. \\ud83d\\ude80 Can't wait to share more details soon! Remember, the future is now. Embrace change, stay curious. #innovation #AI\", \"packyM\": \"User: packyM\\nSimilar Authors: Elon Musk, Naval Ravikant, Sam Altman, Gary Vaynerchuk\\nTone Description: ['1. Pace: Fast-paced and energetic, with quick and concise statements.', '2. Mood: Provocative and confident, with a touch of sarcasm.', '3. Tone: Opinionated and assertive, with a strong stance on various topics.', '4. Voice: Bold and unique, with a distinct personality that comes through in the writing.']\\n\\n1st - Topics this author may talk about:\\n1. AI advancements and their impact on society\\n2. The future of technology and innovation\\n3. Entrepreneurship and startup culture\\n4. The role of government in regulating technology\\n5. The importance of adaptability and continuous learning\\n6. The intersection of technology and entertainment\\n7. The challenges and opportunities in the app market\\n\\n2nd - Concise passage as the author described above:\\nAI's taking over, but are we ready? Nah. Governments are clueless, and people? They're just scratching the surface. Wake up, folks! The future's here, and it's not waiting for you to catch up. #AIRevolution\", \"benedictevans\": \"User: benedictevans\\nSimilar Authors: Benedict Evans, Scott Galloway, Naval Ravikant, Tim O'Reilly\\nTone Description: ['1. Pace: Fast-paced and energetic, with a sense of urgency.', '2. Mood: Assertive, confident, and sometimes sarcastic or humorous.', '3. Tone: Opinionated, strong, and direct, with a clear stance on the subject matter.', '4. Voice: Unique, bold, and engaging, with a distinct personality.']\\n\\n1st - Topics this author may talk about:\\n1. The impact of AI on the job market and economy.\\n2. The role of big tech companies in shaping the future of technology.\\n3. The intersection of technology and luxury goods.\\n4. The challenges and opportunities of digital transformation for businesses.\\n5. The evolution of social media platforms and their influence on society.\\n6. The future of transportation and the role of electric vehicles.\\n7. The role of AI in improving or hindering user experience in various products and services.\\n\\n2nd - Concise passage as the author:\\nAI's taking over, but can it make a decent cup of coffee? I mean, we've got self-driving cars, but I'm still waiting for my morning caffeine fix. Priorities, people! Let's focus on what really matters.\", \"paulg\": \"User: paulg\\nSimilar Authors: Paul Graham, Sam Altman, Naval Ravikant, Tyler Cowen\\nTone Description: ['1. Pace: Fast-paced and concise, quickly presenting ideas and opinions.', '2. Mood: Assertive, confident, and occasionally provocative.', '3. Tone: Opinionated, strong, and direct, with a clear stance on the subject matter.', '4. Voice: Active and engaging, with a distinct personality that comes through in the writing.']\\n\\n1st - Topics this author may talk about:\\n- The impact of AI on society and the economy\\n- The role of regulation in technology and innovation\\n- The importance of intellectual honesty in public discourse\\n- The consequences of ideological thinking\\n- The value of education and its relationship to gender\\n- The role of founders in shaping company culture\\n- The ethics of capital punishment and the justice system\\n- The dangers of historical atrocities and their lessons for the present\\n\\n2nd - Concise passage as the author:\\nAI's rapid advancement will leave regulators scrambling. They'll either stifle innovation with absurd rules or be left in the dust. Adaptation is key, but can bureaucracy keep up?\", \"AlexHormozi\": \"User: AlexHormozi\\nSimilar Authors: Gary Vaynerchuk, Tim Ferriss, Grant Cardone, James Clear\\nTone Description: ['1. Pace: Fast-paced and concise, quickly getting to the point.', '2. Mood: Confident, assertive, and motivational.', '3. Tone: Opinionated, strong, and authoritative.', '4. Voice: Bold, direct, and unapologetic.']\\n\\n1st - Topics this author may talk about:\\n1. Overcoming fear and taking risks\\n2. The importance of self-discipline\\n3. Challenging conventional wisdom\\n4. The power of consistency\\n5. Embracing failure as a learning opportunity\\n6. Developing a growth mindset\\n7. The value of time management\\n8. Building a personal brand\\n9. Networking and relationship building\\n10. The role of habits in success\\n\\n2nd - Concise passage as the author described above:\\n\\nStop waiting for permission. Take action now. Success isn't handed to you; it's earned. Embrace failure, learn from it, and keep pushing forward. Mediocrity is the enemy. Be bold, be relentless, and never settle.\", \"DavidDeutschOxf\": \"User: DavidDeutschOxf\\nSimilar Authors: Elon Musk, Richard Dawkins, Sam Harris, Steven Pinker\\nTone Description: ['1. Pace: Fast-paced and concise, quickly getting to the point.', '2. Mood: Assertive, confident, and occasionally sarcastic.', '3. Tone: Opinionated, critical, and sometimes humorous.', '4. Voice: Active, strong, and distinctive.']\\n\\n1st - Topics this author may talk about:\\n- Artificial intelligence and its potential dangers\\n- The importance of critical thinking in society\\n- The role of religion in modern life\\n- The impact of technology on human evolution\\n- The influence of politics on scientific progress\\n- The future of space exploration and colonization\\n\\n2nd - Concise passage:\\nAI: a double-edged sword? Sure, it can revolutionize industries, but let's not forget the potential risks. Do we really want a Skynet scenario? Let's tread carefully, folks. #AI #RiskyBusiness\", \"stephsmithio\": \"User: stephsmithio\\nSimilar Authors: Gary Vaynerchuk, Naval Ravikant, Tim Ferriss, James Clear\\nTone Description: ['1. Pace: Fast-paced and energetic, with quick thoughts and ideas.', '2. Mood: Lighthearted, humorous, and engaging.', '3. Tone: Opinionated, confident, and conversational.', '4. Voice: Unique, witty, and relatable.']\\n\\n1st - Topics this author may talk about:\\n- Productivity hacks and tips\\n- The impact of technology on society\\n- Personal growth and self-improvement\\n- The future of work and remote work\\n- The role of AI in our lives\\n- The importance of clear thinking and communication\\n- The power of habits and routines\\n- The benefits of learning new skills and hobbies\\n- The intersection of creativity and technology\\n- The role of humor and wit in engaging with an audience\\n\\n2nd - Concise passage as the author:\\nEver notice how we're all obsessed with productivity? Yet, the most productive people I know don't even read productivity threads. \\ud83e\\udd14 Instead, they focus on clear thinking, habits, and just getting stuff done. So, let's stop overthinking and start doing! \\ud83d\\udcaa #ProductivityHacks\", \"sophiaamoruso\": \"User: sophiaamoruso\\nSimilar Authors: Gary Vaynerchuk, Naval Ravikant, Tim Ferriss, Jason Calacanis\\nTone Description: ['1. Pace: Fast-paced and energetic, with a sense of urgency and excitement.', '2. Mood: Confident, assertive, and enthusiastic.', '3. Tone: Opinionated, strong, and bold.', '4. Voice: Active, engaging, and personal.']\\n\\n1st - Topics this author may talk about:\\n1. The importance of taking risks in entrepreneurship\\n2. The power of networking in the startup world\\n3. The role of venture capital in shaping the future of technology\\n4. The impact of diversity and inclusion in the tech industry\\n5. The value of learning from failure in business\\n6. The rise of the creator economy and its implications for entrepreneurs\\n7. The importance of personal branding for founders and investors\\n8. The future of work and the gig economy\\n9. The role of mentorship in personal and professional growth\\n10. The impact of emerging technologies on traditional industries\\n\\n2nd - Concise passage as if you were the author described above:\\nJust closed a $10M seed round for my new startup, and I'm pumped! \\ud83d\\udca5 Time to disrupt the industry and prove the naysayers wrong. Remember, folks: fortune favors the bold. Embrace risk, hustle hard, and never stop learning. Let's go! #entrepreneurship #venturecapital #startuplife\", \"stoolpresidente\": \"User: stoolpresidente\\nSimilar Authors: Dave Portnoy, Michael Scott, Barstool Sports, Bill Simmons\\nTone Description: ['1. Pace: Fast-paced and energetic, with quick thoughts and ideas.', '2. Mood: Humorous, sarcastic, and confident.', '3. Tone: Opinionated, bold, and unapologetic.', '4. Voice: Casual, conversational, and relatable.']\\n\\n1st - Topics this author may talk about:\\n- Sports events and predictions\\n- Personal experiences at games or events\\n- Pop culture references and opinions\\n- Social media trends and reactions\\n- Food and restaurant experiences\\n- Travel and location-based observations\\n- Commentary on current events or news\\n\\n2nd - Concise passage as the author:\\nJust saw a guy wearing socks with sandals. Seriously, dude? It's 2021, not the Stone Age. Get with the program or go back to your cave. #fashionpolice\", \"drgurner\": \"User: drgurner\\nSimilar Authors: Gary Vaynerchuk, Tim Ferriss, Grant Cardone, Simon Sinek\\nTone Description: ['1. Pace: Fast-paced and energetic, with a sense of urgency.', '2. Mood: Confident, assertive, and motivational.', '3. Tone: Opinionated, strong, and direct.', '4. Voice: Active, engaging, and personal.']\\n\\n1st - Topics this author may talk about:\\n1. Overcoming self-doubt and fear.\\n2. The importance of setting goals and taking action.\\n3. Building a strong personal brand.\\n4. The power of networking and building relationships.\\n5. Embracing failure as a learning opportunity.\\n6. Developing a growth mindset.\\n7. The value of time management and productivity.\\n8. Cultivating resilience and mental toughness.\\n9. The role of passion and purpose in success.\\n10. Strategies for effective communication and persuasion.\\n\\n2nd - Concise passage as the author:\\nStop waiting for the perfect moment. It doesn't exist. Take action NOW. Embrace the grind, learn from failures, and keep pushing forward. Your future self will thank you. Let's go!\", \"SMB_Attorney\": \"User: SMB_Attorney\\nSimilar Authors: Gary Vaynerchuk, Grant Cardone, Tim Ferriss, Tai Lopez\\nTone Description: ['1. Pace: Fast-paced and energetic, with a sense of urgency.', '2. Mood: Confident, assertive, and sometimes confrontational.', '3. Tone: Opinionated, authoritative, and bold.', '4. Voice: Active, strong, and distinctive.']\\n\\n1st - Topics this author may talk about:\\n1. The importance of hustle and hard work in entrepreneurship.\\n2. The value of networking and building relationships in business.\\n3. The power of personal branding and social media for entrepreneurs.\\n4. The pitfalls of traditional education and the rise of alternative learning methods.\\n5. The benefits of investing in yourself and your personal growth.\\n6. The importance of setting goals and staying focused on your vision.\\n7. The role of mentors and role models in achieving success.\\n8. The impact of mindset and attitude on business success.\\n9. The value of taking calculated risks and embracing failure.\\n10. The importance of staying adaptable and agile in a constantly changing business landscape.\\n\\n2nd - Concise passage as if you were the author described above:\\n\\nStop wasting time on pointless meetings! Get to the point, make decisions, and move on. Time is money, people! You want success? Hustle harder, work smarter, and never settle for mediocrity. Boom!\", \"KDTrey5\": \"User: KDTrey5\\nSimilar Authors: Kevin Durant, LeBron James, Dwyane Wade, Stephen Curry\\nTone Description: ['1. Pace: Fast-paced and energetic, reflecting the excitement of the events and achievements mentioned.', '2. Mood: Positive, enthusiastic, and celebratory, highlighting the accomplishments and successes of individuals and teams.', \\\"3. Tone: Informal, conversational, and supportive, showcasing the author's admiration and respect for the subjects.\\\", \\\"4. Voice: Confident, engaging, and passionate, demonstrating the author's strong connection to the topics discussed.\\\"]\\n\\n1st - Topics:\\n- Basketball games and highlights\\n- Personal achievements and milestones\\n- Team successes and memorable moments\\n- Shoutouts to fellow athletes and friends\\n- Sports events and accomplishments\\n- Life lessons and motivational thoughts\\n- Partnership and collaboration announcements\\n\\n2nd - Concise passage:\\nUnreal game last night! \\ud83d\\udd25 Shoutout to my bro @JHarden13 for droppin' 40 like it's nothin'. Keep pushin' those limits, man! \\ud83d\\udcaf Let's go @BrooklynNets, we got this! \\ud83c\\udfc0 #StriveForGreatness\"}" }, { "path": "data/muir_lake_tahoe_in_winter.txt", "content": "The winter glory of the Sierra ! How little is known of it! Californians admire descriptions of the Swiss Alps, reading with breathless interest how ice and snow load their sublime heights, and booming avalanches sweep in glorious array through their crowded forests, while our own icy, snow-laden mountains, with their unrivaled forests, loom unnoticed along our eastern horizon. True, only mountaineers may penetrate their snow-blocked fastnesses to behold them in all their white wild grandeur, but to every healthy man and woman, and even to children, many of the subalpine valleys and lake-basins, six or seven thousand feet above the sea, remain invitingly open and approachable all winter. With a friend and his two little sons I have just returned from a week of bracing weathering around Lake Tahoe, in which we enjoyed glorious views of winter, fine rolling and sliding in the snow, swimming in the icy lake, and lusty reviving exercise on snow-shoes that kept our pulses dancing right merrily. All the weather was hearty and exhilarating, though varying almost from hour to hour: snowing, blowing, clear and cloudy, but never rigorously cold.\n\nThis winter has been remarkably mild, the mercury having seldom made a very near approach to zero, even during the coldest nights around the lake, while the average noonday temperature was considerably above the freezing- point. The snow lies deep on the surrounding mountains and about the shores, solid white contrasting with the dark-blue water of the lake, while the forests and canons and the upper glacial fountain hollows are well filled, assuring abundance of summer water for the lakes and streams.\n\nAccording to the record kept by Mr. McKinney, on the west shore of the lake, eight miles above Tahoe City, at an elevation of 6,500 feet above sea-level, the amount of snow, measured as it fell, was twenty-two feet and four inches for the season up to March 20th, with four inches of rain, while an inch or two more of rain and two or three feet of snow will probably fall before the full opening of spring. Last season the snowfall, measured by the same observer, at the same station, was only nine feet and seven inches, while the season before last it was no less than forty seven feet and six inches. The fall about Yosemite Valley, according to my own observations, usually considerably exceeded this. The greater portion of the snow that loads the main summits of the range falls in small crisp flakes and broken crystals; or when accompanied by strong winds at a low temperature, the crystals, instead of being locked together in tufted flakes, are driven against each other and broken into meal and fine dust which darkens the sky like night But down in the forested region, at about the elevation of Lake Tahoe, the greater portion comes gently to the ground, light and feathery, some of the flakes in mild weather being nearly an inch in diameter, and is evenly distributed and kept from drifting to any great extent by Lake Tahoe in Winter. 121 the shelter of the woods. Every tree is loaded with the fairy bloom, bending down the branches, and hushing the singing of the elastic needles. When the storm is over and the sun shines, the dazzling snow at once begins to settle and shift and fall off the trees in miniature avalanches; then the relieved branches spring up and shake themselves dry, and the whole green forest, fed and refreshed, waves and sings again rejoicing. The snow on the ground settles also, and thaws and freezes until it becomes coarsely granulated ice, with all trace of its crystalline snow structure destroyed. This is the present condition of most of the snow on the range. From towards midnight until midday at this time of year a man may walk firmly over the surface, as if on ice, provided the preceding day has been warm and the night frosty.\n\nThe forested region up to an elevation of about eight thousand feet is generally clear of snow towards the end of May or middle of June; but now (March 28th) the higher canons are still heavily blocked, and the head tributaries of the rivers flow in dark tunnels beneath the icy mass. As warm summer advances, the roof of compacted snow falls in here and there, leaving magnificent arching bridges where it is strongest, over which one may safely ride a horse. All the upper streams are thus buried and bridged every winter, and are seldom completely opened to the light before the end of June or middle of July.\n\nNotwithstanding twenty-two feet of snow has fallen here this season, so greatly has it been melted and compacted, the present average depth at a height of 7,500 feet does not exceed seven feet. The drifts in exposed lake hollows and along the lee sides of bald ridges above the timberline are often fifty feet or more in depth, and many of the latter are grandly adorned with overcurling cornices, beneath which pale blue light shimmers with ineffable beauty. But it is in the fountain cirques of the ancient glaciers, beneath the shadows of the highest peaks, that the heaviest and most enduring deposits are stored up. For there the lavish snowfall on the steep converging slopes is shot down in avalanches during or after' every storm, heaping snow on snow to a depth of a hundred feet, or even more at times. These treasured banks are never wholly melted, however hot the summer, but with the few lingering glaciers form perennial fountains for the highest tributaries of the rivers.\n\nFew even among Californians have any fair conception of the marvelous abundance of glacier lakes hidden in the fastnesses of our mountains. The snow and some of the glaciers make a telling show, even from the distant lowlands; but not a single stream is visible, nor a hollow where one might hope to find a lake. Nevertheless, wild rivers are falling and sounding in every canon, and all their upper branches are fairly laden with lakes like orchard-trees with fruit. They nestle in rocky nooks and hollows about all the high peaks and in the larger canons, reflecting their stern, rugged beauty and giving charming animation to the bleakest and most forbidding landscapes. From the summit of Red Mountain, a day's journey to the east of Yosemite Valley, forty-two may be seen within a radius of eight or ten miles. The whole number in the Sierra can hardly be less than fifteen hundred, exclusive of the smaller gems, which are innumerable. Perhaps two-thirds of them lie on the west flank of the range, and all are restricted to the alpine and subalpine regions, those which once brightened the lower regions having long since vanished by the filling in of their basins. Lake Tahoe is king of them all, not only in size, but in the surpassing beauty of its shores and waters. It seems a kind of heaven to which the dead lakes of the lowlands had come with their best beauty spiritualized. It lies embosomed in mountains of moderate height near the northern extremity of the high portion of the Lake Tahoe in Winter. 123 range, between the main axis and a spur that puts out on the east side from near the head of the Carson River. Though it is twenty-one miles long by ten wide, and from about five hundred to sixteen hundred feet deep, its basin was once occupied by a glacier which filled it from the bottom to a point high above the present water-level, and being lavishly fed by the snows of the encompassing mountains, crawled slowly, like a mighty river, over the north rim of the basin, crushing and grinding the lower mountains that lay in its way, and it was only at the end of the ice period that this noble lake, at least in anything like its present form, came into existence.\n\nExcepting the forests that have sprung up around its shores, the post-glacial changes that have taken place are scarcely appreciable. The sediments carried forward by the inflowing streams at the head of the lake have made a few square miles of meadow-land, and the breaking through of a moraine dam in the canon of the outlet has lowered the lake considerably, leaving shore benches and lines on the rocky promontories to mark the original level. With these comparatively unimportant exceptions, the lake itself and all its grandly sculptured, ice-scored, and moraine-streaked basin exist to-day in just about the condition they presented when first they came to the light towards the close of the Glacial Period.\n\nThe destructive action of man in clearing away the forests has not as yet effected any very marked change in general views. Perhaps about 150,000,000 feet of lumber for the Comstock mines has thus far been cut from the lake shores. But the business is being pushed so fervently from year to year, almost the entire basin must be stripped ere long of one of its most attractive features. One of the lumber companies at work here has contracted with mine owners to supply 36,000,000 feet of lumber and 60,000 cords of wood this season. It is estimated that the Tahoe basin still contains about 600,000,000 feet of lumber available for the mines.\n\nIn summer the woods resound with the outlandish noise of loggers and choppers and screaming mills; skiffs and steamboats skim the lovely blue water in work and play; and ever and anon as you thread the groves along shore you come upon groups of gay tourists sauntering about, gathering flowers, or resting luxuriously in the rosiny shade of the pines, some in easy picnic attire, others all ribbons and colors, glaring wildly amid the green leaves and frightening the wondering squirrels and birds. But winter brings rest. At sight of the first snowflake pleasure-seekers flee as from a plague, the ax leaves the woods, and the kind snow heals every scar. Contemplating the basin from any commanding hilltop, only pale curls of smoke seen at wide intervals betoken the existence of human dwellings. Like the bears, the few settlers that remain here are silently \"holed up.\" The snow covers their cabins as if they were bowlders, and when approached only a narrow shoveled-out passage, or tunnel, is found leading to the door. Some of the more enterprising winter dwellers drift about in boats in calm weather, catching trout for the Carson market,—for the lake, on account of its great depth, never freezes. They thus earn from thirty to forty dollars a month, and at the same time get rid of lonely dullness. A trapper may also be seen now and then shuffling along the shore on long Norwegian snow-shoes in pursuit of minks, fishers, and otters.\n\nIn this letter I intended only to say a good word for winter in the mountains, hoping to incite others to come and enjoy it, sketching our excursion to illustrate the ease and comfort with which such snowy winter rambles may be made; but I have written too much I fear about the snow to leave room for more than a thin outline. We went by rail to Lake Tahoe in Winter. 125 Carson, and from there set out by stage for Glenbrook. After ascending on wheels until we reached the snow-line, the driver attached his four horses to a sled, hoping thus to cross the summit, which is less than eight thousand feet high, without much difficulty. But mild weather had softened the snow, and the unfortunate animals, after floundering and wallowing through a mile of it, lay down exhausted with their heels in the air. Then we made our way on foot over to the lake. Next day, on a small steam-tug, we crossed the lake to McKinney's, on the west shore, where we were at home. Here we spent a few health-giving, delightful days, rowing, bathing, racing at lightning speed on snow-shoes down a mountain-side back of the house, and slipping about through the solemn, silent woods. Only the eldest of my companions ventured with me on the steep slopes. This was his first experience on snowshoes, and the several descents he made were the most remarkable specimens of falling locomotion that I ever had the fortune to witness. In shooting down steep declivities the long sled-runner-like shoes have to be kept parallel with firmly braced limbs. My friend, however, heedless of advice, launched himself in wild abandon, bouncing and diving, his limbs and shoes in chaotic entanglement, now in the snow, now in the air, whirling over and over in giddy rolls and somersaults that would shame the most extravagant performances of a circus acrobat. How original and inimitable he was! Wonderfully refreshing and exhilarating his queer capers must have been; for on coming to rest, with his runaway members divorced and lost, he would quietly gather himself, pick out the snow from his neck and ears, and say with preternatural solemnity, \"This, Muir, is the very poetry of motion.\"\n\nWe also spent some rare evenings by the huge fire in McKinney's old cabin. The log walls are covered with trophies of the chase, for our host has been a great hunter in his day. Two live pet coons were frolicking on the floor while our grand old host smiled benignly and played with them, the firelight gleaming on his weathered face. How big he seems, thus brought into relief, and what a shadow he casts! The fragrant rosiny fire is the very god of the home. No wonder the old nations, with their fresher instincts, had their fireside gods. At last, when a mild snow-storm was blowing, we rowed to the lower end of the lake and completed our excursion by slipping on snow-shoes down the Truckee canon to the railroad." }, { "path": "data/state_of_the_union.txt", "content": "Madam Speaker, Madam Vice President, our First Lady and Second Gentleman. Members of Congress and the Cabinet. Justices of the Supreme Court. My fellow Americans. \n\nLast year COVID-19 kept us apart. This year we are finally together again. \n\nTonight, we meet as Democrats Republicans and Independents. But most importantly as Americans. \n\nWith a duty to one another to the American people to the Constitution. \n\nAnd with an unwavering resolve that freedom will always triumph over tyranny. \n\nSix days ago, Russia’s Vladimir Putin sought to shake the foundations of the free world thinking he could make it bend to his menacing ways. But he badly miscalculated. \n\nHe thought he could roll into Ukraine and the world would roll over. Instead he met a wall of strength he never imagined. \n\nHe met the Ukrainian people. \n\nFrom President Zelenskyy to every Ukrainian, their fearlessness, their courage, their determination, inspires the world. \n\nGroups of citizens blocking tanks with their bodies. Everyone from students to retirees teachers turned soldiers defending their homeland. \n\nIn this struggle as President Zelenskyy said in his speech to the European Parliament “Light will win over darkness.” The Ukrainian Ambassador to the United States is here tonight. \n\nLet each of us here tonight in this Chamber send an unmistakable signal to Ukraine and to the world. \n\nPlease rise if you are able and show that, Yes, we the United States of America stand with the Ukrainian people. \n\nThroughout our history we’ve learned this lesson when dictators do not pay a price for their aggression they cause more chaos. \n\nThey keep moving. \n\nAnd the costs and the threats to America and the world keep rising. \n\nThat’s why the NATO Alliance was created to secure peace and stability in Europe after World War 2. \n\nThe United States is a member along with 29 other nations. \n\nIt matters. American diplomacy matters. American resolve matters. \n\nPutin’s latest attack on Ukraine was premeditated and unprovoked. \n\nHe rejected repeated efforts at diplomacy. \n\nHe thought the West and NATO wouldn’t respond. And he thought he could divide us at home. Putin was wrong. We were ready. Here is what we did. \n\nWe prepared extensively and carefully. \n\nWe spent months building a coalition of other freedom-loving nations from Europe and the Americas to Asia and Africa to confront Putin. \n\nI spent countless hours unifying our European allies. We shared with the world in advance what we knew Putin was planning and precisely how he would try to falsely justify his aggression. \n\nWe countered Russia’s lies with truth. \n\nAnd now that he has acted the free world is holding him accountable. \n\nAlong with twenty-seven members of the European Union including France, Germany, Italy, as well as countries like the United Kingdom, Canada, Japan, Korea, Australia, New Zealand, and many others, even Switzerland. \n\nWe are inflicting pain on Russia and supporting the people of Ukraine. Putin is now isolated from the world more than ever. \n\nTogether with our allies –we are right now enforcing powerful economic sanctions. \n\nWe are cutting off Russia’s largest banks from the international financial system. \n\nPreventing Russia’s central bank from defending the Russian Ruble making Putin’s $630 Billion “war fund” worthless. \n\nWe are choking off Russia’s access to technology that will sap its economic strength and weaken its military for years to come. \n\nTonight I say to the Russian oligarchs and corrupt leaders who have bilked billions of dollars off this violent regime no more. \n\nThe U.S. Department of Justice is assembling a dedicated task force to go after the crimes of Russian oligarchs. \n\nWe are joining with our European allies to find and seize your yachts your luxury apartments your private jets. We are coming for your ill-begotten gains. \n\nAnd tonight I am announcing that we will join our allies in closing off American air space to all Russian flights – further isolating Russia – and adding an additional squeeze –on their economy. The Ruble has lost 30% of its value. \n\nThe Russian stock market has lost 40% of its value and trading remains suspended. Russia’s economy is reeling and Putin alone is to blame. \n\nTogether with our allies we are providing support to the Ukrainians in their fight for freedom. Military assistance. Economic assistance. Humanitarian assistance. \n\nWe are giving more than $1 Billion in direct assistance to Ukraine. \n\nAnd we will continue to aid the Ukrainian people as they defend their country and to help ease their suffering. \n\nLet me be clear, our forces are not engaged and will not engage in conflict with Russian forces in Ukraine. \n\nOur forces are not going to Europe to fight in Ukraine, but to defend our NATO Allies – in the event that Putin decides to keep moving west. \n\nFor that purpose we’ve mobilized American ground forces, air squadrons, and ship deployments to protect NATO countries including Poland, Romania, Latvia, Lithuania, and Estonia. \n\nAs I have made crystal clear the United States and our Allies will defend every inch of territory of NATO countries with the full force of our collective power. \n\nAnd we remain clear-eyed. The Ukrainians are fighting back with pure courage. But the next few days weeks, months, will be hard on them. \n\nPutin has unleashed violence and chaos. But while he may make gains on the battlefield – he will pay a continuing high price over the long run. \n\nAnd a proud Ukrainian people, who have known 30 years of independence, have repeatedly shown that they will not tolerate anyone who tries to take their country backwards. \n\nTo all Americans, I will be honest with you, as I’ve always promised. A Russian dictator, invading a foreign country, has costs around the world. \n\nAnd I’m taking robust action to make sure the pain of our sanctions is targeted at Russia’s economy. And I will use every tool at our disposal to protect American businesses and consumers. \n\nTonight, I can announce that the United States has worked with 30 other countries to release 60 Million barrels of oil from reserves around the world. \n\nAmerica will lead that effort, releasing 30 Million barrels from our own Strategic Petroleum Reserve. And we stand ready to do more if necessary, unified with our allies. \n\nThese steps will help blunt gas prices here at home. And I know the news about what’s happening can seem alarming. \n\nBut I want you to know that we are going to be okay. \n\nWhen the history of this era is written Putin’s war on Ukraine will have left Russia weaker and the rest of the world stronger. \n\nWhile it shouldn’t have taken something so terrible for people around the world to see what’s at stake now everyone sees it clearly. \n\nWe see the unity among leaders of nations and a more unified Europe a more unified West. And we see unity among the people who are gathering in cities in large crowds around the world even in Russia to demonstrate their support for Ukraine. \n\nIn the battle between democracy and autocracy, democracies are rising to the moment, and the world is clearly choosing the side of peace and security. \n\nThis is a real test. It’s going to take time. So let us continue to draw inspiration from the iron will of the Ukrainian people. \n\nTo our fellow Ukrainian Americans who forge a deep bond that connects our two nations we stand with you. \n\nPutin may circle Kyiv with tanks, but he will never gain the hearts and souls of the Ukrainian people. \n\nHe will never extinguish their love of freedom. He will never weaken the resolve of the free world. \n\nWe meet tonight in an America that has lived through two of the hardest years this nation has ever faced. \n\nThe pandemic has been punishing. \n\nAnd so many families are living paycheck to paycheck, struggling to keep up with the rising cost of food, gas, housing, and so much more. \n\nI understand. \n\nI remember when my Dad had to leave our home in Scranton, Pennsylvania to find work. I grew up in a family where if the price of food went up, you felt it. \n\nThat’s why one of the first things I did as President was fight to pass the American Rescue Plan. \n\nBecause people were hurting. We needed to act, and we did. \n\nFew pieces of legislation have done more in a critical moment in our history to lift us out of crisis. \n\nIt fueled our efforts to vaccinate the nation and combat COVID-19. It delivered immediate economic relief for tens of millions of Americans. \n\nHelped put food on their table, keep a roof over their heads, and cut the cost of health insurance. \n\nAnd as my Dad used to say, it gave people a little breathing room. \n\nAnd unlike the $2 Trillion tax cut passed in the previous administration that benefitted the top 1% of Americans, the American Rescue Plan helped working people—and left no one behind. \n\nAnd it worked. It created jobs. Lots of jobs. \n\nIn fact—our economy created over 6.5 Million new jobs just last year, more jobs created in one year \nthan ever before in the history of America. \n\nOur economy grew at a rate of 5.7% last year, the strongest growth in nearly 40 years, the first step in bringing fundamental change to an economy that hasn’t worked for the working people of this nation for too long. \n\nFor the past 40 years we were told that if we gave tax breaks to those at the very top, the benefits would trickle down to everyone else. \n\nBut that trickle-down theory led to weaker economic growth, lower wages, bigger deficits, and the widest gap between those at the top and everyone else in nearly a century. \n\nVice President Harris and I ran for office with a new economic vision for America. \n\nInvest in America. Educate Americans. Grow the workforce. Build the economy from the bottom up \nand the middle out, not from the top down. \n\nBecause we know that when the middle class grows, the poor have a ladder up and the wealthy do very well. \n\nAmerica used to have the best roads, bridges, and airports on Earth. \n\nNow our infrastructure is ranked 13th in the world. \n\nWe won’t be able to compete for the jobs of the 21st Century if we don’t fix that. \n\nThat’s why it was so important to pass the Bipartisan Infrastructure Law—the most sweeping investment to rebuild America in history. \n\nThis was a bipartisan effort, and I want to thank the members of both parties who worked to make it happen. \n\nWe’re done talking about infrastructure weeks. \n\nWe’re going to have an infrastructure decade. \n\nIt is going to transform America and put us on a path to win the economic competition of the 21st Century that we face with the rest of the world—particularly with China. \n\nAs I’ve told Xi Jinping, it is never a good bet to bet against the American people. \n\nWe’ll create good jobs for millions of Americans, modernizing roads, airports, ports, and waterways all across America. \n\nAnd we’ll do it all to withstand the devastating effects of the climate crisis and promote environmental justice. \n\nWe’ll build a national network of 500,000 electric vehicle charging stations, begin to replace poisonous lead pipes—so every child—and every American—has clean water to drink at home and at school, provide affordable high-speed internet for every American—urban, suburban, rural, and tribal communities. \n\n4,000 projects have already been announced. \n\nAnd tonight, I’m announcing that this year we will start fixing over 65,000 miles of highway and 1,500 bridges in disrepair. \n\nWhen we use taxpayer dollars to rebuild America – we are going to Buy American: buy American products to support American jobs. \n\nThe federal government spends about $600 Billion a year to keep the country safe and secure. \n\nThere’s been a law on the books for almost a century \nto make sure taxpayers’ dollars support American jobs and businesses. \n\nEvery Administration says they’ll do it, but we are actually doing it. \n\nWe will buy American to make sure everything from the deck of an aircraft carrier to the steel on highway guardrails are made in America. \n\nBut to compete for the best jobs of the future, we also need to level the playing field with China and other competitors. \n\nThat’s why it is so important to pass the Bipartisan Innovation Act sitting in Congress that will make record investments in emerging technologies and American manufacturing. \n\nLet me give you one example of why it’s so important to pass it. \n\nIf you travel 20 miles east of Columbus, Ohio, you’ll find 1,000 empty acres of land. \n\nIt won’t look like much, but if you stop and look closely, you’ll see a “Field of dreams,” the ground on which America’s future will be built. \n\nThis is where Intel, the American company that helped build Silicon Valley, is going to build its $20 billion semiconductor “mega site”. \n\nUp to eight state-of-the-art factories in one place. 10,000 new good-paying jobs. \n\nSome of the most sophisticated manufacturing in the world to make computer chips the size of a fingertip that power the world and our everyday lives. \n\nSmartphones. The Internet. Technology we have yet to invent. \n\nBut that’s just the beginning. \n\nIntel’s CEO, Pat Gelsinger, who is here tonight, told me they are ready to increase their investment from \n$20 billion to $100 billion. \n\nThat would be one of the biggest investments in manufacturing in American history. \n\nAnd all they’re waiting for is for you to pass this bill. \n\nSo let’s not wait any longer. Send it to my desk. I’ll sign it. \n\nAnd we will really take off. \n\nAnd Intel is not alone. \n\nThere’s something happening in America. \n\nJust look around and you’ll see an amazing story. \n\nThe rebirth of the pride that comes from stamping products “Made In America.” The revitalization of American manufacturing. \n\nCompanies are choosing to build new factories here, when just a few years ago, they would have built them overseas. \n\nThat’s what is happening. Ford is investing $11 billion to build electric vehicles, creating 11,000 jobs across the country. \n\nGM is making the largest investment in its history—$7 billion to build electric vehicles, creating 4,000 jobs in Michigan. \n\nAll told, we created 369,000 new manufacturing jobs in America just last year. \n\nPowered by people I’ve met like JoJo Burgess, from generations of union steelworkers from Pittsburgh, who’s here with us tonight. \n\nAs Ohio Senator Sherrod Brown says, “It’s time to bury the label “Rust Belt.” \n\nIt’s time. \n\nBut with all the bright spots in our economy, record job growth and higher wages, too many families are struggling to keep up with the bills. \n\nInflation is robbing them of the gains they might otherwise feel. \n\nI get it. That’s why my top priority is getting prices under control. \n\nLook, our economy roared back faster than most predicted, but the pandemic meant that businesses had a hard time hiring enough workers to keep up production in their factories. \n\nThe pandemic also disrupted global supply chains. \n\nWhen factories close, it takes longer to make goods and get them from the warehouse to the store, and prices go up. \n\nLook at cars. \n\nLast year, there weren’t enough semiconductors to make all the cars that people wanted to buy. \n\nAnd guess what, prices of automobiles went up. \n\nSo—we have a choice. \n\nOne way to fight inflation is to drive down wages and make Americans poorer. \n\nI have a better plan to fight inflation. \n\nLower your costs, not your wages. \n\nMake more cars and semiconductors in America. \n\nMore infrastructure and innovation in America. \n\nMore goods moving faster and cheaper in America. \n\nMore jobs where you can earn a good living in America. \n\nAnd instead of relying on foreign supply chains, let’s make it in America. \n\nEconomists call it “increasing the productive capacity of our economy.” \n\nI call it building a better America. \n\nMy plan to fight inflation will lower your costs and lower the deficit. \n\n17 Nobel laureates in economics say my plan will ease long-term inflationary pressures. Top business leaders and most Americans support my plan. And here’s the plan: \n\nFirst – cut the cost of prescription drugs. Just look at insulin. One in ten Americans has diabetes. In Virginia, I met a 13-year-old boy named Joshua Davis. \n\nHe and his Dad both have Type 1 diabetes, which means they need insulin every day. Insulin costs about $10 a vial to make. \n\nBut drug companies charge families like Joshua and his Dad up to 30 times more. I spoke with Joshua’s mom. \n\nImagine what it’s like to look at your child who needs insulin and have no idea how you’re going to pay for it. \n\nWhat it does to your dignity, your ability to look your child in the eye, to be the parent you expect to be. \n\nJoshua is here with us tonight. Yesterday was his birthday. Happy birthday, buddy. \n\nFor Joshua, and for the 200,000 other young people with Type 1 diabetes, let’s cap the cost of insulin at $35 a month so everyone can afford it. \n\nDrug companies will still do very well. And while we’re at it let Medicare negotiate lower prices for prescription drugs, like the VA already does. \n\nLook, the American Rescue Plan is helping millions of families on Affordable Care Act plans save $2,400 a year on their health care premiums. Let’s close the coverage gap and make those savings permanent. \n\nSecond – cut energy costs for families an average of $500 a year by combatting climate change. \n\nLet’s provide investments and tax credits to weatherize your homes and businesses to be energy efficient and you get a tax credit; double America’s clean energy production in solar, wind, and so much more; lower the price of electric vehicles, saving you another $80 a month because you’ll never have to pay at the gas pump again. \n\nThird – cut the cost of child care. Many families pay up to $14,000 a year for child care per child. \n\nMiddle-class and working families shouldn’t have to pay more than 7% of their income for care of young children. \n\nMy plan will cut the cost in half for most families and help parents, including millions of women, who left the workforce during the pandemic because they couldn’t afford child care, to be able to get back to work. \n\nMy plan doesn’t stop there. It also includes home and long-term care. More affordable housing. And Pre-K for every 3- and 4-year-old. \n\nAll of these will lower costs. \n\nAnd under my plan, nobody earning less than $400,000 a year will pay an additional penny in new taxes. Nobody. \n\nThe one thing all Americans agree on is that the tax system is not fair. We have to fix it. \n\nI’m not looking to punish anyone. But let’s make sure corporations and the wealthiest Americans start paying their fair share. \n\nJust last year, 55 Fortune 500 corporations earned $40 billion in profits and paid zero dollars in federal income tax. \n\nThat’s simply not fair. That’s why I’ve proposed a 15% minimum tax rate for corporations. \n\nWe got more than 130 countries to agree on a global minimum tax rate so companies can’t get out of paying their taxes at home by shipping jobs and factories overseas. \n\nThat’s why I’ve proposed closing loopholes so the very wealthy don’t pay a lower tax rate than a teacher or a firefighter. \n\nSo that’s my plan. It will grow the economy and lower costs for families. \n\nSo what are we waiting for? Let’s get this done. And while you’re at it, confirm my nominees to the Federal Reserve, which plays a critical role in fighting inflation. \n\nMy plan will not only lower costs to give families a fair shot, it will lower the deficit. \n\nThe previous Administration not only ballooned the deficit with tax cuts for the very wealthy and corporations, it undermined the watchdogs whose job was to keep pandemic relief funds from being wasted. \n\nBut in my administration, the watchdogs have been welcomed back. \n\nWe’re going after the criminals who stole billions in relief money meant for small businesses and millions of Americans. \n\nAnd tonight, I’m announcing that the Justice Department will name a chief prosecutor for pandemic fraud. \n\nBy the end of this year, the deficit will be down to less than half what it was before I took office. \n\nThe only president ever to cut the deficit by more than one trillion dollars in a single year. \n\nLowering your costs also means demanding more competition. \n\nI’m a capitalist, but capitalism without competition isn’t capitalism. \n\nIt’s exploitation—and it drives up prices. \n\nWhen corporations don’t have to compete, their profits go up, your prices go up, and small businesses and family farmers and ranchers go under. \n\nWe see it happening with ocean carriers moving goods in and out of America. \n\nDuring the pandemic, these foreign-owned companies raised prices by as much as 1,000% and made record profits. \n\nTonight, I’m announcing a crackdown on these companies overcharging American businesses and consumers. \n\nAnd as Wall Street firms take over more nursing homes, quality in those homes has gone down and costs have gone up. \n\nThat ends on my watch. \n\nMedicare is going to set higher standards for nursing homes and make sure your loved ones get the care they deserve and expect. \n\nWe’ll also cut costs and keep the economy going strong by giving workers a fair shot, provide more training and apprenticeships, hire them based on their skills not degrees. \n\nLet’s pass the Paycheck Fairness Act and paid leave. \n\nRaise the minimum wage to $15 an hour and extend the Child Tax Credit, so no one has to raise a family in poverty. \n\nLet’s increase Pell Grants and increase our historic support of HBCUs, and invest in what Jill—our First Lady who teaches full-time—calls America’s best-kept secret: community colleges. \n\nAnd let’s pass the PRO Act when a majority of workers want to form a union—they shouldn’t be stopped. \n\nWhen we invest in our workers, when we build the economy from the bottom up and the middle out together, we can do something we haven’t done in a long time: build a better America. \n\nFor more than two years, COVID-19 has impacted every decision in our lives and the life of the nation. \n\nAnd I know you’re tired, frustrated, and exhausted. \n\nBut I also know this. \n\nBecause of the progress we’ve made, because of your resilience and the tools we have, tonight I can say \nwe are moving forward safely, back to more normal routines. \n\nWe’ve reached a new moment in the fight against COVID-19, with severe cases down to a level not seen since last July. \n\nJust a few days ago, the Centers for Disease Control and Prevention—the CDC—issued new mask guidelines. \n\nUnder these new guidelines, most Americans in most of the country can now be mask free. \n\nAnd based on the projections, more of the country will reach that point across the next couple of weeks. \n\nThanks to the progress we have made this past year, COVID-19 need no longer control our lives. \n\nI know some are talking about “living with COVID-19”. Tonight – I say that we will never just accept living with COVID-19. \n\nWe will continue to combat the virus as we do other diseases. And because this is a virus that mutates and spreads, we will stay on guard. \n\nHere are four common sense steps as we move forward safely. \n\nFirst, stay protected with vaccines and treatments. We know how incredibly effective vaccines are. If you’re vaccinated and boosted you have the highest degree of protection. \n\nWe will never give up on vaccinating more Americans. Now, I know parents with kids under 5 are eager to see a vaccine authorized for their children. \n\nThe scientists are working hard to get that done and we’ll be ready with plenty of vaccines when they do. \n\nWe’re also ready with anti-viral treatments. If you get COVID-19, the Pfizer pill reduces your chances of ending up in the hospital by 90%. \n\nWe’ve ordered more of these pills than anyone in the world. And Pfizer is working overtime to get us 1 Million pills this month and more than double that next month. \n\nAnd we’re launching the “Test to Treat” initiative so people can get tested at a pharmacy, and if they’re positive, receive antiviral pills on the spot at no cost. \n\nIf you’re immunocompromised or have some other vulnerability, we have treatments and free high-quality masks. \n\nWe’re leaving no one behind or ignoring anyone’s needs as we move forward. \n\nAnd on testing, we have made hundreds of millions of tests available for you to order for free. \n\nEven if you already ordered free tests tonight, I am announcing that you can order more from covidtests.gov starting next week. \n\nSecond – we must prepare for new variants. Over the past year, we’ve gotten much better at detecting new variants. \n\nIf necessary, we’ll be able to deploy new vaccines within 100 days instead of many more months or years. \n\nAnd, if Congress provides the funds we need, we’ll have new stockpiles of tests, masks, and pills ready if needed. \n\nI cannot promise a new variant won’t come. But I can promise you we’ll do everything within our power to be ready if it does. \n\nThird – we can end the shutdown of schools and businesses. We have the tools we need. \n\nIt’s time for Americans to get back to work and fill our great downtowns again. People working from home can feel safe to begin to return to the office. \n\nWe’re doing that here in the federal government. The vast majority of federal workers will once again work in person. \n\nOur schools are open. Let’s keep it that way. Our kids need to be in school. \n\nAnd with 75% of adult Americans fully vaccinated and hospitalizations down by 77%, most Americans can remove their masks, return to work, stay in the classroom, and move forward safely. \n\nWe achieved this because we provided free vaccines, treatments, tests, and masks. \n\nOf course, continuing this costs money. \n\nI will soon send Congress a request. \n\nThe vast majority of Americans have used these tools and may want to again, so I expect Congress to pass it quickly. \n\nFourth, we will continue vaccinating the world. \n\nWe’ve sent 475 Million vaccine doses to 112 countries, more than any other nation. \n\nAnd we won’t stop. \n\nWe have lost so much to COVID-19. Time with one another. And worst of all, so much loss of life. \n\nLet’s use this moment to reset. Let’s stop looking at COVID-19 as a partisan dividing line and see it for what it is: A God-awful disease. \n\nLet’s stop seeing each other as enemies, and start seeing each other for who we really are: Fellow Americans. \n\nWe can’t change how divided we’ve been. But we can change how we move forward—on COVID-19 and other issues we must face together. \n\nI recently visited the New York City Police Department days after the funerals of Officer Wilbert Mora and his partner, Officer Jason Rivera. \n\nThey were responding to a 9-1-1 call when a man shot and killed them with a stolen gun. \n\nOfficer Mora was 27 years old. \n\nOfficer Rivera was 22. \n\nBoth Dominican Americans who’d grown up on the same streets they later chose to patrol as police officers. \n\nI spoke with their families and told them that we are forever in debt for their sacrifice, and we will carry on their mission to restore the trust and safety every community deserves. \n\nI’ve worked on these issues a long time. \n\nI know what works: Investing in crime preventionand community police officers who’ll walk the beat, who’ll know the neighborhood, and who can restore trust and safety. \n\nSo let’s not abandon our streets. Or choose between safety and equal justice. \n\nLet’s come together to protect our communities, restore trust, and hold law enforcement accountable. \n\nThat’s why the Justice Department required body cameras, banned chokeholds, and restricted no-knock warrants for its officers. \n\nThat’s why the American Rescue Plan provided $350 Billion that cities, states, and counties can use to hire more police and invest in proven strategies like community violence interruption—trusted messengers breaking the cycle of violence and trauma and giving young people hope. \n\nWe should all agree: The answer is not to Defund the police. The answer is to FUND the police with the resources and training they need to protect our communities. \n\nI ask Democrats and Republicans alike: Pass my budget and keep our neighborhoods safe. \n\nAnd I will keep doing everything in my power to crack down on gun trafficking and ghost guns you can buy online and make at home—they have no serial numbers and can’t be traced. \n\nAnd I ask Congress to pass proven measures to reduce gun violence. Pass universal background checks. Why should anyone on a terrorist list be able to purchase a weapon? \n\nBan assault weapons and high-capacity magazines. \n\nRepeal the liability shield that makes gun manufacturers the only industry in America that can’t be sued. \n\nThese laws don’t infringe on the Second Amendment. They save lives. \n\nThe most fundamental right in America is the right to vote – and to have it counted. And it’s under assault. \n\nIn state after state, new laws have been passed, not only to suppress the vote, but to subvert entire elections. \n\nWe cannot let this happen. \n\nTonight. I call on the Senate to: Pass the Freedom to Vote Act. Pass the John Lewis Voting Rights Act. And while you’re at it, pass the Disclose Act so Americans can know who is funding our elections. \n\nTonight, I’d like to honor someone who has dedicated his life to serve this country: Justice Stephen Breyer—an Army veteran, Constitutional scholar, and retiring Justice of the United States Supreme Court. Justice Breyer, thank you for your service. \n\nOne of the most serious constitutional responsibilities a President has is nominating someone to serve on the United States Supreme Court. \n\nAnd I did that 4 days ago, when I nominated Circuit Court of Appeals Judge Ketanji Brown Jackson. One of our nation’s top legal minds, who will continue Justice Breyer’s legacy of excellence. \n\nA former top litigator in private practice. A former federal public defender. And from a family of public school educators and police officers. A consensus builder. Since she’s been nominated, she’s received a broad range of support—from the Fraternal Order of Police to former judges appointed by Democrats and Republicans. \n\nAnd if we are to advance liberty and justice, we need to secure the Border and fix the immigration system. \n\nWe can do both. At our border, we’ve installed new technology like cutting-edge scanners to better detect drug smuggling. \n\nWe’ve set up joint patrols with Mexico and Guatemala to catch more human traffickers. \n\nWe’re putting in place dedicated immigration judges so families fleeing persecution and violence can have their cases heard faster. \n\nWe’re securing commitments and supporting partners in South and Central America to host more refugees and secure their own borders. \n\nWe can do all this while keeping lit the torch of liberty that has led generations of immigrants to this land—my forefathers and so many of yours. \n\nProvide a pathway to citizenship for Dreamers, those on temporary status, farm workers, and essential workers. \n\nRevise our laws so businesses have the workers they need and families don’t wait decades to reunite. \n\nIt’s not only the right thing to do—it’s the economically smart thing to do. \n\nThat’s why immigration reform is supported by everyone from labor unions to religious leaders to the U.S. Chamber of Commerce. \n\nLet’s get it done once and for all. \n\nAdvancing liberty and justice also requires protecting the rights of women. \n\nThe constitutional right affirmed in Roe v. Wade—standing precedent for half a century—is under attack as never before. \n\nIf we want to go forward—not backward—we must protect access to health care. Preserve a woman’s right to choose. And let’s continue to advance maternal health care in America. \n\nAnd for our LGBTQ+ Americans, let’s finally get the bipartisan Equality Act to my desk. The onslaught of state laws targeting transgender Americans and their families is wrong. \n\nAs I said last year, especially to our younger transgender Americans, I will always have your back as your President, so you can be yourself and reach your God-given potential. \n\nWhile it often appears that we never agree, that isn’t true. I signed 80 bipartisan bills into law last year. From preventing government shutdowns to protecting Asian-Americans from still-too-common hate crimes to reforming military justice. \n\nAnd soon, we’ll strengthen the Violence Against Women Act that I first wrote three decades ago. It is important for us to show the nation that we can come together and do big things. \n\nSo tonight I’m offering a Unity Agenda for the Nation. Four big things we can do together. \n\nFirst, beat the opioid epidemic. \n\nThere is so much we can do. Increase funding for prevention, treatment, harm reduction, and recovery. \n\nGet rid of outdated rules that stop doctors from prescribing treatments. And stop the flow of illicit drugs by working with state and local law enforcement to go after traffickers. \n\nIf you’re suffering from addiction, know you are not alone. I believe in recovery, and I celebrate the 23 million Americans in recovery. \n\nSecond, let’s take on mental health. Especially among our children, whose lives and education have been turned upside down. \n\nThe American Rescue Plan gave schools money to hire teachers and help students make up for lost learning. \n\nI urge every parent to make sure your school does just that. And we can all play a part—sign up to be a tutor or a mentor. \n\nChildren were also struggling before the pandemic. Bullying, violence, trauma, and the harms of social media. \n\nAs Frances Haugen, who is here with us tonight, has shown, we must hold social media platforms accountable for the national experiment they’re conducting on our children for profit. \n\nIt’s time to strengthen privacy protections, ban targeted advertising to children, demand tech companies stop collecting personal data on our children. \n\nAnd let’s get all Americans the mental health services they need. More people they can turn to for help, and full parity between physical and mental health care. \n\nThird, support our veterans. \n\nVeterans are the best of us. \n\nI’ve always believed that we have a sacred obligation to equip all those we send to war and care for them and their families when they come home. \n\nMy administration is providing assistance with job training and housing, and now helping lower-income veterans get VA care debt-free. \n\nOur troops in Iraq and Afghanistan faced many dangers. \n\nOne was stationed at bases and breathing in toxic smoke from “burn pits” that incinerated wastes of war—medical and hazard material, jet fuel, and more. \n\nWhen they came home, many of the world’s fittest and best trained warriors were never the same. \n\nHeadaches. Numbness. Dizziness. \n\nA cancer that would put them in a flag-draped coffin. \n\nI know. \n\nOne of those soldiers was my son Major Beau Biden. \n\nWe don’t know for sure if a burn pit was the cause of his brain cancer, or the diseases of so many of our troops. \n\nBut I’m committed to finding out everything we can. \n\nCommitted to military families like Danielle Robinson from Ohio. \n\nThe widow of Sergeant First Class Heath Robinson. \n\nHe was born a soldier. Army National Guard. Combat medic in Kosovo and Iraq. \n\nStationed near Baghdad, just yards from burn pits the size of football fields. \n\nHeath’s widow Danielle is here with us tonight. They loved going to Ohio State football games. He loved building Legos with their daughter. \n\nBut cancer from prolonged exposure to burn pits ravaged Heath’s lungs and body. \n\nDanielle says Heath was a fighter to the very end. \n\nHe didn’t know how to stop fighting, and neither did she. \n\nThrough her pain she found purpose to demand we do better. \n\nTonight, Danielle—we are. \n\nThe VA is pioneering new ways of linking toxic exposures to diseases, already helping more veterans get benefits. \n\nAnd tonight, I’m announcing we’re expanding eligibility to veterans suffering from nine respiratory cancers. \n\nI’m also calling on Congress: pass a law to make sure veterans devastated by toxic exposures in Iraq and Afghanistan finally get the benefits and comprehensive health care they deserve. \n\nAnd fourth, let’s end cancer as we know it. \n\nThis is personal to me and Jill, to Kamala, and to so many of you. \n\nCancer is the #2 cause of death in America–second only to heart disease. \n\nLast month, I announced our plan to supercharge \nthe Cancer Moonshot that President Obama asked me to lead six years ago. \n\nOur goal is to cut the cancer death rate by at least 50% over the next 25 years, turn more cancers from death sentences into treatable diseases. \n\nMore support for patients and families. \n\nTo get there, I call on Congress to fund ARPA-H, the Advanced Research Projects Agency for Health. \n\nIt’s based on DARPA—the Defense Department project that led to the Internet, GPS, and so much more. \n\nARPA-H will have a singular purpose—to drive breakthroughs in cancer, Alzheimer’s, diabetes, and more. \n\nA unity agenda for the nation. \n\nWe can do this. \n\nMy fellow Americans—tonight , we have gathered in a sacred space—the citadel of our democracy. \n\nIn this Capitol, generation after generation, Americans have debated great questions amid great strife, and have done great things. \n\nWe have fought for freedom, expanded liberty, defeated totalitarianism and terror. \n\nAnd built the strongest, freest, and most prosperous nation the world has ever known. \n\nNow is the hour. \n\nOur moment of responsibility. \n\nOur test of resolve and conscience, of history itself. \n\nIt is in this moment that our character is formed. Our purpose is found. Our future is forged. \n\nWell I know this nation. \n\nWe will meet the test. \n\nTo protect freedom and liberty, to expand fairness and opportunity. \n\nWe will save democracy. \n\nAs hard as these times have been, I am more optimistic about America today than I have been my whole life. \n\nBecause I see the future that is within our grasp. \n\nBecause I know there is simply nothing beyond our capacity. \n\nWe are the only nation on Earth that has always turned every crisis we have faced into an opportunity. \n\nThe only nation that can be defined by a single word: possibilities. \n\nSo on this night, in our 245th year as a nation, I have come to report on the State of the Union. \n\nAnd my report is this: the State of the Union is strong—because you, the American people, are strong. \n\nWe are stronger today than we were a year ago. \n\nAnd we will be stronger a year from now than we are today. \n\nNow is our moment to meet and overcome the challenges of our time. \n\nAnd we will, as one people. \n\nOne America. \n\nThe United States of America. \n\nMay God bless you all. May God protect our troops." }, { "path": "data/thefuzz/.editorconfig", "content": "# .editorconfig\n# http://editorconfig.org/\nroot = true\n\n[*]\ncharset = utf-8\nend_of_line = lf\nindent_size = 2\nindent_style = space\ninsert_final_newline = true\ntrim_trailing_whitespace = true\n\n[*.bat]\nend_of_line = crlf\n\n[*.go]\nindent_size = 4\nindent_style = tab\n\n[*.html]\nindent_size = 4\n\n[*Makefile]\nindent_size = 4\nindent_style = tab\n\n[*.php]\nindent_size = 4\n\n[*.py]\nindent_size = 4\n\n[*.xml]\nindent_size = 4\n" }, { "path": "data/thefuzz/.github/workflows/ci.yml", "content": "name: The Fuzz\n\non: [push, pull_request, workflow_dispatch]\n\njobs:\n build:\n runs-on: ubuntu-latest\n strategy:\n fail-fast: false\n matrix:\n python-version: [\"3.7\", \"3.8\", \"3.9\", \"3.10\", \"3.11\"]\n test-cmd: [pytest]\n include:\n #- python-version: pyp-y3.8\n # test-cmd: pytest test_thefuzz.py test_thefuzz_pytest.py\n - python-version: \"3.7\"\n test-cmd: python setup.py check --restructuredtext --strict --metadata\n - python-version: \"3.10\"\n test-cmd: python setup.py check --restructuredtext --strict --metadata\n steps:\n - uses: actions/checkout@v3\n - name: Set up Python ${{ matrix.python-version }}\n uses: actions/setup-python@v4\n with:\n python-version: ${{ matrix.python-version }}\n - name: Install dependencies\n run: |\n python -m pip install --upgrade pip setuptools wheel\n pip install pytest pycodestyle docutils Pygments hypothesis python-Levenshtein\n - name: Test with pytest\n run: |\n ${{ matrix.test-cmd }}\n" }, { "path": "data/thefuzz/.gitignore", "content": "*.py[oc]\n\n# Temp files\n*~\n~*\n.*~\n\\#*\n.#*\n*#\n\n# Build files\nbuild\ndist\npkg\n*.egg\n*.egg-info\n\n# Debian Files\ndebian/files\ndebian/python-beaver*\n\n# Sphinx build\ndoc/_build\n\n# Generated man page\ndoc/aws_hostname.1\n\n# tox\n.tox\n\n# Hypothesis - keep the examples database\n.hypothesis/tmp\n.hypothesis/unicodedata\n.hypothesis\n\n# pytest\n.cache/\n.pytest_cache\n__pycache__\n\n# Pycharm\n.idea/\n\n# vscode\n.vscode/\n" }, { "path": "data/thefuzz/.travis.yml", "content": "language: python\nmatrix:\n include:\n - python: \"3.7\"\n env: TEST_SUITE=pytest\n - python: \"3.8\"\n env: TEST_SUITE=pytest\n - python: \"3.9\"\n env: TEST_SUITE=pytest\n - python: \"3.10\"\n env: TEST_SUITE=pytest\n - python: \"3.11-dev\"\n env: TEST_SUITE=pytest\n - python: \"pypy3.7-7.3.5\"\n env: TEST_SUITE=\"pytest test_thefuzz.py test_thefuzz_pytest.py\"\n - python: \"3.10\"\n env: TEST_SUITE=\"python setup.py check --restructuredtext --strict --metadata\"\ninstall:\n - pip install -U pip setuptools wheel\n - pip install pytest pycodestyle docutils Pygments hypothesis\nscript:\n - $TEST_SUITE\nnotifications:\n on_success: always\ncache: pip\n" }, { "path": "data/thefuzz/CHANGES.rst", "content": "Changelog\n=========\n\n0.17.0 (2018-08-20)\n-------------------\n\n- Make benchmarks script Py3 compatible. [Stefan Behnel]\n\n- Add Go lang port. [iddober]\n\n- Add reference to C# port. [ericcoleman]\n\n- Chore: remove license header from files. [Jose Diaz-Gonzalez]\n\n The files should all inherit the projects license.\n\n\n- Fix README title style. [Thomas Grainger]\n\n- Add readme check. [Thomas Grainger]\n\n install docutils and Pygments\n\n\n- Cache pip. [Thomas Grainger]\n\n- Upgrade pip/setuptools for hypothesis. [Thomas Grainger]\n\n- Feat: drop py26 and py33 support from tox. [Jose Diaz-Gonzalez]\n\n- Feat: drop support for 2.6 in test_thefuzz.py. [Jose Diaz-Gonzalez]\n\n- Feat: drop reference to 2.4 from readme. [Jose Diaz-Gonzalez]\n\n- Feat: drop py2.6 and py3.3 classifiers. [Jose Diaz-Gonzalez]\n\n- Feat: drop 2.6 and 3.3 support. [Jose Diaz-Gonzalez]\n\n These are no longer supported. Please upgrade your python version if you are using either version.\n\n- Fuzz: _token_sort: check for equivalence. [Ralf Ramsauer]\n\n If we don't have to full_process the strings, we can safely assume to\n return 100 in case both candidates equal.\n\n Signed-off-by: Ralf Ramsauer \n\n\n- Test: add more test cases. [Ralf Ramsauer]\n\n Signed-off-by: Ralf Ramsauer \n\n\n- Utils: add and use check_for_equivalence decorator. [Ralf Ramsauer]\n\n And decorate basic scoring functions.\n\n The check_for_equivalence decorator MUST be used after the\n check_for_none decorator, as otherwise ratio(None, None) will get a\n score of 100.\n\n This fixes the first part of the recently introduced changes in the test\n set.\n\n Signed-off-by: Ralf Ramsauer \n\n\n- Tests: add some corner cases. [Ralf Ramsauer]\n\n '' and '' are equal, so are '{' and '{'. Test if thefuzz gives them a\n score of 100.\n\n For the moment, this patch breaks tests, fixes in thefuzz follow.\n\n Signed-off-by: Ralf Ramsauer \n\n\n- Utils: remove superfluous check. [Ralf Ramsauer]\n\n Decorators make sure that only non None-values are passed. We can safely\n assume that None will never get here.\n\n Other than that, None's shouldn't simply be ignored and erroneously\n changed to empty strings. Better let users fail.\n\n This commit doesn't break any tests.\n\n Signed-off-by: Ralf Ramsauer \n\n\n- README: add missing requirements. [Ralf Ramsauer]\n\n pycodestyle and hypothesis are required for automatic testing. Add them\n to README's requirement section.\n\n Signed-off-by: Ralf Ramsauer \n\n\n- Remove empty document. [Ralf Ramsauer]\n\n Signed-off-by: Ralf Ramsauer \n\n\n0.16.0 (2017-12-18)\n-------------------\n\n- Add punctuation characters back in so process does something.\n [davidcellis]\n\n- Simpler alphabet and even fewer examples. [davidcellis]\n\n- Fewer examples and larger deadlines for Hypothesis. [davidcellis]\n\n- Slightly more examples. [davidcellis]\n\n- Attempt to fix the failing 2.7 and 3.6 python tests. [davidcellis]\n\n- Readme: add link to C++ port. [Lizard]\n\n- Fix tests on Python 3.3. [Jon Banafato]\n\n Modify tox.ini and .travis.yml to install enum34 when running with\n Python 3.3 to allow hypothesis tests to pass.\n\n\n- Normalize Python versions. [Jon Banafato]\n\n - Enable Travis-CI tests for Python 3.6\n - Enable tests for all supported Python versions in tox.ini\n - Add Trove classifiers for Python 3.4 - 3.6 to setup.py\n\n ---\n\n Note: Python 2.6 and 3.3 are no longer supported by the Python core\n team. Support for these can likely be dropped, but that's out of scope\n for this change set.\n\n\n- Fix typos. [Sven-Hendrik Haase]\n\n0.15.1 (2017-07-19)\n-------------------\n\n- Fix setup.py (addresses #155) [Paul O'Leary McCann]\n\n- Merge remote-tracking branch 'upstream/master' into\n extract_optimizations. [nolan]\n\n- Seed random before generating benchmark strings. [nolan]\n\n- Cleaner implementation of same idea without new param, but adding\n existing full_process param to Q,W,UQ,UW. [nolan]\n\n- Fix benchmark only generate list once. [nolan]\n\n- Only run util.full_process once on query when using extract functions,\n add new benchmarks. [nolan]\n\n0.15.0 (2017-02-20)\n-------------------\n\n- Add extras require to install python-levenshtein optionally. [Rolando\n Espinoza]\n\n This allows to install python-levenshtein as dependency.\n\n\n- Fix link formatting in the README. [Alex Chan]\n\n- Add fuzzball.js JavaScript port link. [nolan]\n\n- Added Rust Port link. [Logan Collins]\n\n- Validate_string docstring. [davidcellis]\n\n- For full comparisons test that ONLY exact matches (after processing)\n are added. [davidcellis]\n\n- Add detailed docstrings to WRatio and QRatio comparisons.\n [davidcellis]\n\n0.14.0 (2016-11-04)\n-------------------\n\n- Possible PEP-8 fix + make pep-8 warnings appear in test. [davidcellis]\n\n- Possible PEP-8 fix. [davidcellis]\n\n- Possible PEP-8 fix. [davidcellis]\n\n- Test for stderr log instead of warning. [davidcellis]\n\n- Convert warning.warn to logging.warning. [davidcellis]\n\n- Additional details for empty string warning from process.\n [davidcellis]\n\n String formatting fix for python 2.6\n\n\n- Enclose warnings.simplefilter() inside a with statement. [samkennerly]\n\n0.13.0 (2016-11-01)\n-------------------\n\n- Support alternate git status output. [Jose Diaz-Gonzalez]\n\n- Split warning test into new test file, added to travis execution on\n 2.6 / pypy3. [davidcellis]\n\n- Remove hypothesis examples database from gitignore. [davidcellis]\n\n- Add check for warning to tests. [davidcellis]\n\n Reordered test imports\n\n\n- Check processor and warn before scorer may remove processor.\n [davidcellis]\n\n- Renamed test - tidied docstring. [davidcellis]\n\n- Add token ratios to the list of scorers that skip running full_process\n as a processor. [davidcellis]\n\n- Added tokex_sort, token_set to test. [davidcellis]\n\n- Test docstrings/comments. [davidcellis]\n\n Removed redundant check from test.\n\n\n- Added py.test .cache/ removed duplicated build from gitignore.\n [davidcellis]\n\n- Added default_scorer, default_processor parameters to make it easier\n to change in the future. [davidcellis]\n\n Added warning if the processor reduces the input query to an empty string.\n\n\n- Rewrote extracts to explicitly use default values for processor and\n scorer. [davidcellis]\n\n- Changed Hypothesis tests to use pytest parameters. [davidcellis]\n\n- Added Hypothesis based tests for identical strings. [Ducksual]\n\n Added support for hypothesis to travis config.\n Hypothesis based tests are skipped on Python 2.6 and pypy3.\n\n Added .hypothesis/ folder to gitignore\n\n\n- Added test for simple 'a, b' string on process.extractOne. [Ducksual]\n\n- Process the query in process.extractWithoutOrder when using a scorer\n which does not do so. [Ducksual]\n\n Closes 139\n\n\n- Mention that difflib and levenshtein results may differ. [Jose Diaz-\n Gonzalez]\n\n Closes #128\n\n0.12.0 (2016-09-14)\n-------------------\n\n- Declare support for universal wheels. [Thomas Grainger]\n\n- Clarify that license is GPLv2. [Gareth Tan]\n\n0.11.1 (2016-07-27)\n-------------------\n\n- Add editorconfig. [Jose Diaz-Gonzalez]\n\n- Added tox.ini cofig file for easy local multi-environment testing\n changed travis config to use py.test like tox updated use of pep8\n module to pycodestyle. [Pedro Rodrigues]\n\n0.11.0 (2016-06-30)\n-------------------\n\n- Clean-up. [desmaisons_david]\n\n- Improving performance. [desmaisons_david]\n\n- Performance Improvement. [desmaisons_david]\n\n- Fix link to Levenshtein. [Brian J. McGuirk]\n\n- Fix readme links. [Brian J. McGuirk]\n\n- Add license to StringMatcher.py. [Jose Diaz-Gonzalez]\n\n Closes #113\n\n0.10.0 (2016-03-14)\n-------------------\n\n- Handle None inputs same as empty string (Issue #94) [Nick Miller]\n\n0.9.0 (2016-03-07)\n------------------\n\n- Pull down all keys when updating local copy. [Jose Diaz-Gonzalez]\n\n0.8.2 (2016-02-26)\n------------------\n\n- Remove the warning for \"slow\" sequence matcher on PyPy. [Julian\n Berman]\n\n where it's preferable to use the pure-python implementation.\n\n0.8.1 (2016-01-25)\n------------------\n\n- Minor release changes. [Jose Diaz-Gonzalez]\n\n- Clean up wiki link in readme. [Ewan Oglethorpe]\n\n0.8.0 (2015-11-16)\n------------------\n\n- Refer to Levenshtein distance in readme. Closes #88. [Jose Diaz-\n Gonzalez]\n\n- Added install step for travis to have pep8 available. [Pedro\n Rodrigues]\n\n- Added a pep8 test. The way I add the error 501 to the ignore tuple is\n probably wrong but from the docs and source code of pep8 I could not\n find any other way. [Pedro Rodrigues]\n\n I also went ahead and removed the pep8 call from the release file.\n\n\n- Added python 3.5, pypy, and ypyp3 to the travis config file. [Pedro\n Rodrigues]\n\n- Added another step to the release file to run the tests before\n releasing. [Pedro Rodrigues]\n\n- Fixed a few pep8 errors Added a verification step in the release\n automation file. This step should probably be somewhere at git level.\n [Pedro Rodrigues]\n\n- Pep8. [Pedro Rodrigues]\n\n- Leaving TODOs in the code was never a good idea. [Pedro Rodrigues]\n\n- Changed return values to be rounded integers. [Pedro Rodrigues]\n\n- Added a test with the recovered data file. [Pedro Rodrigues]\n\n- Recovered titledata.csv. [Pedro Rodrigues]\n\n- Move extract test methods into the process test. [Shale Craig]\n\n Somehow, they ended up in the `RatioTest`, despite asserting that the\n `ProcessTest` works.\n\n\n0.7.0 (2015-10-02)\n------------------\n\n- Use portable syntax for catching exception on tests. [Luis Madrigal]\n\n- [Fix] test against correct variable. [Luis Madrigal]\n\n- Add unit tests for validator decorators. [Luis Madrigal]\n\n- Move validators to decorator functions. [Luis Madrigal]\n\n This allows easier composition and IMO makes the functions more readable\n\n\n- Fix typo: dictionery -> dictionary. [shale]\n\n- FizzyWuzzy -> TheFuzz typo correction. [shale]\n\n- Add check for gitchangelog. [Jose Diaz-Gonzalez]\n\n0.6.2 (2015-09-03)\n------------------\n\n- Ensure the rst-lint binary is available. [Jose Diaz-Gonzalez]\n\n0.6.1 (2015-08-07)\n------------------\n\n- Minor whitespace changes for PEP8. [Jose Diaz-Gonzalez]\n\n0.6.0 (2015-07-20)\n------------------\n\n- Added link to a java port. [Andriy Burkov]\n\n- Patched \"name 'unicode' is not defined\" python3. [Carlos Garay]\n\n https://github.com/seatgeek/thefuzz/issues/80\n\n- Make process.extract accept {dict, list}-like choices. [Nathan\n Typanski]\n\n Previously, process.extract expected lists or dictionaries, and tested\n this with isinstance() calls. In keeping with the spirit of Python (duck\n typing and all that), this change enables one to use extract() on any\n dict-like object for dict-like results, or any list-like object for\n list-like results.\n\n So now we can (and, indeed, I've added tests for these uses) call\n extract() on things like:\n\n - a generator of strings (\"any iterable\")\n - a UserDict\n - custom user-made classes that \"look like\" dicts\n (or, really, anything with a .items() method that behaves like a dict)\n - plain old lists and dicts\n\n The behavior is exactly the same for previous use cases of\n lists-and-dicts.\n\n This change goes along nicely with PR #68, since those docs suggest\n dict-like behavior is valid, and this change makes that true.\n\n\n- Merge conflict. [Adam Cohen]\n\n- Improve docs for thefuzz.process. [Nathan Typanski]\n\n The documentation for this module was dated and sometimes inaccurate.\n This overhauls the docs to accurately describe the current module,\n including detailing optional arguments that were not previously\n explained - e.g., limit argument to extract().\n\n This change follows the Google Python Style Guide, which may be found\n at:\n\n \n\n\n0.5.0 (2015-02-04)\n------------------\n\n- FIX: 0.4.0 is released, no need to specify 0.3.1 in README. [Josh\n Warner (Mac)]\n\n- Fixed a small typo. [Rostislav Semenov]\n\n- Reset `processor` and `scorer` defaults to None with argument\n checking. [foxxyz]\n\n- Catch generators without lengths. [Jeremiah Lowin]\n\n- Fixed python3 issue and deprecated assertion method. [foxxyz]\n\n- Fixed some docstrings, typos, python3 string method compatibility,\n some errors that crept in during rebase. [foxxyz]\n\n- [mod] The lamdba in extract is not needed. [Olivier Le Thanh Duong]\n\n [mod] Pass directly the defaults functions in the args\n\n [mod] itertools.takewhile() can handle empty list just fine no need to test for it\n\n [mod] Shorten extractOne by removing double if\n\n [mod] Use a list comprehention in extract()\n\n [mod] Autopep8 on process.py\n\n [doc] Document make_type_consistent\n\n [mod] bad_chars shortened\n\n [enh] Move regex compilation outside the method, otherwise we don't get the benefit from it\n\n [mod] Don't need all the blah just to redefine method from string module\n\n [mod] Remove unused import\n\n [mod] Autopep8 on string_processing.py\n\n [mod] Rewrote asciidammit without recursion to make it more readable\n\n [mod] Autopep8 on utils.py\n\n [mod] Remove unused import\n\n [doc] Add some doc to fuzz.py\n\n [mod] Move the code to sort string in a separate function\n\n [doc] Docstrings for WRatio, UWRatio\n\n\n- Add note on which package to install. Closes #67. [Jose Diaz-Gonzalez]\n\n0.4.0 (2014-10-31)\n------------------\n\n- In extarctBests() and extractOne() use '>=' instead of '>' [Юрий\n Пайков]\n\n- Fixed python3 issue with SequenceMatcher import. [Юрий Пайков]\n\n0.3.3 (2014-10-22)\n------------------\n\n- Fixed issue #59 - \"partial\" parameter for `_token_set()` is now\n honored. [Юрий Пайков]\n\n- Catch generators without lengths. [Jeremiah Lowin]\n\n- Remove explicit check for lists. [Jeremiah Lowin]\n\n The logic in `process.extract()` should support any Python sequence/iterable. The explicit check for lists is unnecessary and limiting (for example, it forces conversion of generators and other iterable classes to lists).\n\n0.3.2 (2014-09-12)\n------------------\n\n- Make release command an executable. [Jose Diaz-Gonzalez]\n\n- Simplify MANIFEST.in. [Jose Diaz-Gonzalez]\n\n- Add a release script. [Jose Diaz-Gonzalez]\n\n- Fix readme codeblock. [Jose Diaz-Gonzalez]\n\n- Minor formatting. [Jose Diaz-Gonzalez]\n\n- Use __version__ from thefuzz package. [Jose Diaz-Gonzalez]\n\n- Set __version__ constant in __init__.py. [Jose Diaz-Gonzalez]\n\n- Rename LICENSE to LICENSE.txt. [Jose Diaz-Gonzalez]\n\n0.3.0 (2014-08-24)\n------------------\n\n- Test dict input to extractOne() [jamesnunn]\n\n- Remove whitespace. [jamesnunn]\n\n- Choices parameter for extract() accepts both dict and list objects.\n [jamesnunn]\n\n- Enable automated testing with Python 3.4. [Corey Farwell]\n\n- Fixed typo: lettters -> letters. [Tal Einat]\n\n- Fixing LICENSE and README's license info. [Dallas Gutauckis]\n\n- Proper ordered list. [Jeff Paine]\n\n- Convert README to rst. [Jeff Paine]\n\n- Add requirements.txt per discussion in #44. [Jeff Paine]\n\n- Add LICENSE TO MANIFEST.in. [Jeff Paine]\n\n- Rename tests.py to more common test_thefuzz.py. [Jeff Paine]\n\n- Add proper MANIFEST template. [Jeff Paine]\n\n- Remove MANIFEST file Not meant to be kept in version control. [Jeff\n Paine]\n\n- Remove unused file. [Jeff Paine]\n\n- Pep8. [Jeff Paine]\n\n- Pep8 formatting. [Jeff Paine]\n\n- Pep8 formatting. [Jeff Paine]\n\n- Pep8 indentations. [Jeff Paine]\n\n- Pep8 cleanup. [Jeff Paine]\n\n- Pep8. [Jeff Paine]\n\n- Pep8 cleanup. [Jeff Paine]\n\n- Pep8 cleanup. [Jeff Paine]\n\n- Pep8 import style. [Jeff Paine]\n\n- Pep8 import ordering. [Jeff Paine]\n\n- Pep8 import ordering. [Jeff Paine]\n\n- Remove unused module. [Jeff Paine]\n\n- Pep8 import ordering. [Jeff Paine]\n\n- Remove unused module. [Jeff Paine]\n\n- Pep8 import ordering. [Jeff Paine]\n\n- Remove unused imports. [Jeff Paine]\n\n- Remove unused module. [Jeff Paine]\n\n- Remove import * where present. [Jeff Paine]\n\n- Avoid import * [Jeff Paine]\n\n- Add Travis CI badge. [Jeff Paine]\n\n- Remove python 2.4, 2.5 from Travis (not supported) [Jeff Paine]\n\n- Add python 2.4 and 2.5 to Travis. [Jeff Paine]\n\n- Add all supported python versions to travis. [Jeff Paine]\n\n- Bump minor version number. [Jeff Paine]\n\n- Add classifiers for python versions. [Jeff Paine]\n\n- Added note about python-Levenshtein speedup. Closes #34. [Jose Diaz-\n Gonzalez]\n\n- Fixed tests on 2.6. [Grigi]\n\n- Fixed py2.6. [Grigi]\n\n- Force bad_chars to ascii. [Grigi]\n\n- Since importing unicode_literals, u decorator not required on strings\n from py2.6 and up. [Grigi]\n\n- Py3 support without 2to3. [Grigi]\n\n- Created: Added .travis.yml. [futoase]\n\n- [enh] Add docstrings to process.py. [Olivier Le Thanh Duong]\n\n Turn the existings comments into docstrings so they can be seen via introspection\n\n\n- Don't condense multiple punctuation characters to a single whitespace.\n this is a behavioral change. [Adam Cohen]\n\n- UQRatio and UWRatio shorthands. [Adam Cohen]\n\n- Version 0.2. [Adam Cohen]\n\n- Unicode/string comparison bug. [Adam Cohen]\n\n- To maintain backwards compatibility, default is to force_ascii as\n before. [Adam Cohen]\n\n- Fix merge conflict. [Adam Cohen]\n\n- New process function: extractBests. [Flávio Juvenal]\n\n- More readable reverse sorting. [Flávio Juvenal]\n\n- Further honoring of force_ascii. [Adam Cohen]\n\n- Indentation fix. [Adam Cohen]\n\n- Handle force_ascii in fuzz methods. [Adam Cohen]\n\n- Add back relevant tests. [Adam Cohen]\n\n- Utility method to make things consistent. [Adam Cohen]\n\n- Re-commit asciidammit and add a parameter to full_process to determine\n behavior. [Adam Cohen]\n\n- Added a test for non letters/digits replacements. [Tristan Launay]\n\n- ENG-741 fixed benchmark line length. [Laurent Erignoux]\n\n- Fixed Unicode flag for tests. [Tristan Launay]\n\n- ENG-741 commented code removed not erased for review from creator.\n [Laurent Erignoux]\n\n- ENG-741 cut long lines in fuzzy wizzy benchmark. [Laurent Erignoux]\n\n- Re-upped the limit on benchmark, now that performance is not an issue\n anymore. [Tristan Launay]\n\n- Fixed comment. [Tristan Launay]\n\n- Simplified processing of strings with built-in regex code in python.\n Also fixed empty string detection in token_sort_ratio. [Tristan\n Launay]\n\n- Proper benchmark display. Introduce methods to explicitly do all the\n unicode preprocessing *before* using fuzz lib. [Tristan Launay]\n\n- ENG-741: having a true benchmark, to see when we improve stuff.\n [Benjamin Combourieu]\n\n- Unicode support in benchmark.py. [Benjamin Combourieu]\n\n- Added file for processing strings. [Tristan Launay]\n\n- Uniform treatment of strings in Unicode. Non-ASCII chars are now\n considered in strings, which allows for matches in Cyrillic, Chinese,\n Greek, etc. [Tristan Launay]\n\n- Fixed bug in _token_set. [Michael Edward]\n\n- Removed reference to PR. [Jose Diaz-Gonzalez]\n\n- Sadist build and virtualenv dirs are not part of the project. [Pedro\n Rodrigues]\n\n- Fixes https://github.com/seatgeek/thefuzz/issues/10 and correctly\n points to README.textile. [Pedro Rodrigues]\n\n- Info on the pull request. [Pedro Rodrigues]\n\n- Pullstat.us button. [Pedro Rodrigues]\n\n- Fuzzywuzzy really needs better benchmarks. [Pedro Rodrigues]\n\n- Moved tests and benchmarks out of the package. [Pedro Rodrigues]\n\n- Report better ratio()s redundant import try. [Pedro Rodrigues]\n\n- AssertGreater did not exist in python 2.4. [Pedro Rodrigues]\n\n- Remove debug output. [Adam Cohen]\n\n- Looks for python-Levenshtein package, and if present, uses that\n instead of difflib. 10x speedup if present. add benchmarks. [Adam\n Cohen]\n\n- Add gitignore. [Adam Cohen]\n\n- Fix a bug in WRatio, as well as an issue in full_process, which was\n failing on strings with all unicode characters. [Adam Cohen]\n\n- Error in partial_ratio. closes #7. [Adam Cohen]\n\n- Adding some real-life event data for benchmarking. [Adam Cohen]\n\n- Cleaned up utils.py. [Pedro Rodrigues]\n\n- Optimized speed for full_process() [Pedro Rodrigues]\n\n- Speed improvements to asciidammit. [Pedro Rodrigues]\n\n- Removed old versions of validate_string() and remove_ponctuation()\n kept from previous commits. [Pedro Rodrigues]\n\n- Issue #6 from github updated license headers to match MIT license.\n [Pedro Rodrigues]\n\n- Clean up. [Pedro Rodrigues]\n\n- Changes to utils.validate_string() and benchmarks. [Pedro Rodrigues]\n\n- Some benchmarks to test the changes made to remove_punctuation. [Pedro\n Rodrigues]\n\n- Faster remove_punctuation. [Pedro Rodrigues]\n\n- AssertIsNone did not exist in Python 2.4. [Pedro Rodrigues]\n\n- Just adding some simple install instructions for pip. [Chris Dary]\n\n- Check for null/empty strings in QRatio and WRatio. Add tests. Closes\n #3. [Adam Cohen]\n\n- More README. [Adam Cohen]\n\n- README. [Adam Cohen]\n\n- README. [Adam Cohen]\n\n- Slight change to README. [Adam Cohen]\n\n- Some readme. [Adam Cohen]\n\n- Distutils. [Adam Cohen]\n\n- Change directory structure. [Adam Cohen]\n\n- Initial commit. [Adam Cohen]\n\n\n" }, { "path": "data/thefuzz/LICENSE.txt", "content": "\n GNU GENERAL PUBLIC LICENSE\n Version 2, June 1991\n\n Copyright (C) 1989, 1991 Free Software Foundation, Inc.\n 59 Temple Place, Suite 330, Boston, MA 02111 USA\n Everyone is permitted to copy and distribute verbatim copies\n of this license document, but changing it is not allowed.\n\n Preamble\n\n The licenses for most software are designed to take away your\nfreedom to share and change it. By contrast, the GNU General Public\nLicense is intended to guarantee your freedom to share and change free\nsoftware--to make sure the software is free for all its users. This\nGeneral Public License applies to most of the Free Software\nFoundation's software and to any other program whose authors commit to\nusing it. (Some other Free Software Foundation software is covered by\nthe GNU Library General Public License instead.) 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See the\n GNU General Public License for more details.\n\n You should have received a copy of the GNU General Public License\n along with this program; if not, write to the Free Software\n Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111 USA\n\nAlso add information on how to contact you by electronic and paper mail.\n\nIf the program is interactive, make it output a short notice like this\nwhen it starts in an interactive mode:\n\n Gnomovision version 69, Copyright (C) 19yy name of author\n Gnomovision comes with ABSOLUTELY NO WARRANTY; for details type `show w'.\n This is free software, and you are welcome to redistribute it\n under certain conditions; type `show c' for details.\n\nThe hypothetical commands `show w' and `show c' should show the appropriate\nparts of the General Public License. Of course, the commands you use may\nbe called something other than `show w' and `show c'; they could even be\nmouse-clicks or menu items--whatever suits your program.\n\nYou should also get your employer (if you work as a programmer) or your\nschool, if any, to sign a \"copyright disclaimer\" for the program, if\nnecessary. Here is a sample; alter the names:\n\n Yoyodyne, Inc., hereby disclaims all copyright interest in the program\n `Gnomovision' (which makes passes at compilers) written by James Hacker.\n\n , 1 April 1989\n Ty Coon, President of Vice\n\nThis General Public License does not permit incorporating your program into\nproprietary programs. If your program is a subroutine library, you may\nconsider it more useful to permit linking proprietary applications with the\nlibrary. If this is what you want to do, use the GNU Library General\nPublic License instead of this License." }, { "path": "data/thefuzz/MANIFEST.in", "content": "include *.txt\ninclude *.rst\ninclude test_thefuzz.py\n" }, { "path": "data/thefuzz/README.rst", "content": ".. image:: https://github.com/seatgeek/thefuzz/actions/workflows/ci.yml/badge.svg\n :target: https://github.com/seatgeek/thefuzz\n\nTheFuzz\n=======\n\nFuzzy string matching like a boss. It uses `Levenshtein Distance `_ to calculate the differences between sequences in a simple-to-use package.\n\nRequirements\n============\n\n- Python 3.7 or higher\n- difflib\n- `python-Levenshtein `_ (optional, provides a 4-10x speedup in String\n Matching, though may result in `differing results for certain cases `_)\n\nFor testing\n~~~~~~~~~~~\n- pycodestyle\n- hypothesis\n- pytest\n\nInstallation\n============\n\nUsing PIP via PyPI\n\n.. code:: bash\n\n pip install thefuzz\n\nor the following to install `python-Levenshtein` too\n\n.. code:: bash\n\n pip install thefuzz[speedup]\n\n\nUsing PIP via Github\n\n.. code:: bash\n\n pip install git+git://github.com/seatgeek/thefuzz.git@0.19.0#egg=thefuzz\n\nAdding to your ``requirements.txt`` file (run ``pip install -r requirements.txt`` afterwards)\n\n.. code:: bash\n\n git+ssh://git@github.com/seatgeek/thefuzz.git@0.19.0#egg=thefuzz\n\nManually via GIT\n\n.. code:: bash\n\n git clone git://github.com/seatgeek/thefuzz.git thefuzz\n cd thefuzz\n python setup.py install\n\n\nUsage\n=====\n\n.. code:: python\n\n >>> from thefuzz import fuzz\n >>> from thefuzz import process\n\nSimple Ratio\n~~~~~~~~~~~~\n\n.. code:: python\n\n >>> fuzz.ratio(\"this is a test\", \"this is a test!\")\n 97\n\nPartial Ratio\n~~~~~~~~~~~~~\n\n.. code:: python\n\n >>> fuzz.partial_ratio(\"this is a test\", \"this is a test!\")\n 100\n\nToken Sort Ratio\n~~~~~~~~~~~~~~~~\n\n.. code:: python\n\n >>> fuzz.ratio(\"fuzzy wuzzy was a bear\", \"wuzzy fuzzy was a bear\")\n 91\n >>> fuzz.token_sort_ratio(\"fuzzy wuzzy was a bear\", \"wuzzy fuzzy was a bear\")\n 100\n\nToken Set Ratio\n~~~~~~~~~~~~~~~\n\n.. code:: python\n\n >>> fuzz.token_sort_ratio(\"fuzzy was a bear\", \"fuzzy fuzzy was a bear\")\n 84\n >>> fuzz.token_set_ratio(\"fuzzy was a bear\", \"fuzzy fuzzy was a bear\")\n 100\n\nPartial Token Sort Ratio\n~~~~~~~~~~~~~~~~~~~~~~~~\n\n.. code:: python\n\n >>> fuzz.token_sort_ratio(\"fuzzy was a bear\", \"wuzzy fuzzy was a bear\")\n 84\n >>> fuzz.partial_token_sort_ratio(\"fuzzy was a bear\", \"wuzzy fuzzy was a bear\")\n 100\n \nProcess\n~~~~~~~\n\n.. code:: python\n\n >>> choices = [\"Atlanta Falcons\", \"New York Jets\", \"New York Giants\", \"Dallas Cowboys\"]\n >>> process.extract(\"new york jets\", choices, limit=2)\n [('New York Jets', 100), ('New York Giants', 78)]\n >>> process.extractOne(\"cowboys\", choices)\n (\"Dallas Cowboys\", 90)\n\nYou can also pass additional parameters to ``extractOne`` method to make it use a specific scorer. A typical use case is to match file paths:\n\n.. code:: python\n\n >>> process.extractOne(\"System of a down - Hypnotize - Heroin\", songs)\n ('/music/library/good/System of a Down/2005 - Hypnotize/01 - Attack.mp3', 86)\n >>> process.extractOne(\"System of a down - Hypnotize - Heroin\", songs, scorer=fuzz.token_sort_ratio)\n (\"/music/library/good/System of a Down/2005 - Hypnotize/10 - She's Like Heroin.mp3\", 61)\n\n.. |Build Status| image:: https://github.com/seatgeek/thefuzz/actions/workflows/ci.yml/badge.svg\n :target: https://github.com/seatgeek/thefuzz\n" }, { "path": "data/thefuzz/benchmarks.py", "content": "from timeit import timeit\nimport math\nimport csv\n\niterations = 100000\n\n\nreader = csv.DictReader(open('data/titledata.csv'), delimiter='|')\ntitles = [i['custom_title'] for i in reader]\ntitle_blob = '\\n'.join(titles)\n\n\ncirque_strings = [\n \"cirque du soleil - zarkana - las vegas\",\n \"cirque du soleil \",\n \"cirque du soleil las vegas\",\n \"zarkana las vegas\",\n \"las vegas cirque du soleil at the bellagio\",\n \"zarakana - cirque du soleil - bellagio\"\n]\n\nchoices = [\n \"\",\n \"new york yankees vs boston red sox\",\n \"\",\n \"zarakana - cirque du soleil - bellagio\",\n None,\n \"cirque du soleil las vegas\",\n None\n]\n\nmixed_strings = [\n \"Lorem Ipsum is simply dummy text of the printing and typesetting industry.\",\n \"C\\\\'est la vie\",\n \"Ça va?\",\n \"Cães danados\",\n \"\\xacCamarões assados\",\n \"a\\xac\\u1234\\u20ac\\U00008000\"\n]\n\ncommon_setup = \"from thefuzz import fuzz, utils; \"\nbasic_setup = \"from thefuzz.string_processing import StringProcessor;\"\n\n\ndef print_result_from_timeit(stmt='pass', setup='pass', number=1000000):\n \"\"\"\n Clean function to know how much time took the execution of one statement\n \"\"\"\n units = [\"s\", \"ms\", \"us\", \"ns\"]\n duration = timeit(stmt, setup, number=int(number))\n avg_duration = duration / float(number)\n thousands = int(math.floor(math.log(avg_duration, 1000)))\n\n print(\"Total time: {:f}s. Average run: {:.3f}{}.\".format(\n duration, avg_duration * (1000 ** -thousands), units[-thousands]))\n\n\nfor s in choices:\n print('Test validate_string for: \"%s\"' % s)\n print_result_from_timeit('utils.validate_string(\\'%s\\')' % s, common_setup, number=iterations)\n\nprint('')\n\nfor s in mixed_strings + cirque_strings + choices:\n print('Test full_process for: \"%s\"' % s)\n print_result_from_timeit('utils.full_process(u\\'%s\\')' % s,\n common_setup + basic_setup, number=iterations)\n\n# benchmarking the core matching methods...\n\nfor s in cirque_strings:\n print('Test fuzz.ratio for string: \"%s\"' % s)\n print('-------------------------------')\n print_result_from_timeit('fuzz.ratio(u\\'cirque du soleil\\', u\\'%s\\')' % s,\n common_setup + basic_setup, number=iterations / 100)\n\nfor s in cirque_strings:\n print('Test fuzz.partial_ratio for string: \"%s\"' % s)\n print('-------------------------------')\n print_result_from_timeit('fuzz.partial_ratio(u\\'cirque du soleil\\', u\\'%s\\')'\n % s, common_setup + basic_setup, number=iterations / 100)\n\nfor s in cirque_strings:\n print('Test fuzz.WRatio for string: \"%s\"' % s)\n print('-------------------------------')\n print_result_from_timeit('fuzz.WRatio(u\\'cirque du soleil\\', u\\'%s\\')' % s,\n common_setup + basic_setup, number=iterations / 100)\n\nprint('Test process.extract(scorer = fuzz.QRatio) for string: \"%s\"' % s)\nprint('-------------------------------')\nprint_result_from_timeit('process.extract(u\\'cirque du soleil\\', choices, scorer = fuzz.QRatio)',\n common_setup + basic_setup + \" from thefuzz import process; import string,random; random.seed(18);\"\n \" choices = [\\'\\'.join(random.choice(string.ascii_uppercase + string.digits) for _ in range(30)) for s in range(5000)]\",\n number=10)\n\nprint('Test process.extract(scorer = fuzz.WRatio) for string: \"%s\"' % s)\nprint('-------------------------------')\nprint_result_from_timeit('process.extract(u\\'cirque du soleil\\', choices, scorer = fuzz.WRatio)',\n common_setup + basic_setup + \" from thefuzz import process; import string,random; random.seed(18);\"\n \" choices = [\\'\\'.join(random.choice(string.ascii_uppercase + string.digits) for _ in range(30)) for s in range(5000)]\",\n number=10)\n\n\n# let me show you something\n\ns = 'New York Yankees'\n\ntest = 'import functools\\n'\ntest += 'title_blob = \"\"\"%s\"\"\"\\n' % title_blob\ntest += 'title_blob = title_blob.strip()\\n'\ntest += 'titles = title_blob.split(\"\\\\n\")\\n'\n\nprint('Real world ratio(): \"%s\"' % s)\nprint('-------------------------------')\ntest += 'prepared_ratio = functools.partial(fuzz.ratio, \"%s\")\\n' % s\ntest += 'titles.sort(key=prepared_ratio)\\n'\nprint_result_from_timeit(test,\n common_setup + basic_setup,\n number=100)\n" }, { "path": "data/thefuzz/data/titledata.csv", "content": "id|custom_title|stubhub_title|vividseats_title\r\n701562|Toronto Blue Jays at Baltimore Orioles (Wednesday April 25, 2012)|Baltimore Orioles vs Toronto Blue Jays [4/25/2012] Tickets at StubHub!|Toronto Blue Jays at Baltimore Orioles\r\n701563|Texas Rangers at Baltimore Orioles (Tuesday May 8, 2012)|Baltimore Orioles vs Texas Rangers [5/8/2012] Tickets at StubHub!|Texas Rangers at Baltimore Orioles\r\n701564|Toronto Blue Jays at Baltimore Orioles (Tuesday April 24, 2012)|Baltimore Orioles vs Toronto Blue Jays [4/24/2012] Tickets at StubHub!|Toronto Blue Jays at Baltimore Orioles\r\n701565|Texas Rangers at Baltimore Orioles (Wednesday May 9, 2012)|Baltimore Orioles vs Texas Rangers [5/9/2012] Tickets at StubHub!|Texas Rangers at Baltimore Orioles\r\n701566|Oakland Athletics at Baltimore Orioles (Friday April 27, 2012)|Baltimore Orioles vs Oakland Athletics [4/27/2012] Tickets at StubHub!|Oakland Athletics at Baltimore Orioles\r\n701567|Toronto Blue Jays at Baltimore Orioles (Thursday April 26, 2012)|Baltimore Orioles vs Toronto Blue Jays [4/26/2012] Tickets at StubHub!|Toronto Blue Jays at Baltimore Orioles\r\n701568|Minnesota Twins at Baltimore Orioles (Saturday April 7, 2012)|Baltimore Orioles vs Minnesota Twins [4/7/2012] Tickets at StubHub!|Minnesota Twins at Baltimore Orioles\r\n701569|Oakland Athletics at Baltimore Orioles (Sunday April 29, 2012)|Baltimore Orioles vs Oakland Athletics [4/29/2012] Tickets at StubHub!|Oakland Athletics at Baltimore Orioles\r\n701570|Minnesota Twins at Baltimore Orioles (Friday April 6, 2012)|Baltimore Orioles vs Minnesota Twins [4/6/2012] Tickets at StubHub!|Minnesota Twins at Baltimore Orioles\r\n701571|Oakland Athletics at Baltimore Orioles (Saturday April 28, 2012)|Baltimore Orioles vs Oakland Athletics [4/28/2012] Tickets at StubHub!|Oakland Athletics at Baltimore Orioles\r\n701572|New York Yankees at Baltimore Orioles (Monday April 9, 2012)|Baltimore Orioles vs New York Yankees [4/9/2012] Tickets at StubHub!|New York Yankees at Baltimore Orioles\r\n701573|Minnesota Twins at Baltimore Orioles (Sunday April 8, 2012)|Baltimore Orioles vs 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at Milwaukee Brewers (Wednesday April 18, 2012)|Milwaukee Brewers vs Los Angeles Dodgers [04/18/2012] Tickets at StubHub!|Los Angeles Dodgers at Milwaukee Brewers\r\n709469|Washington Nationals at Milwaukee Brewers (Saturday July 28, 2012)|Milwaukee Brewers vs Washington Nationals [07/28/2012] Tickets at StubHub!|Washington Nationals at Milwaukee Brewers\r\n709470|Chicago Cubs at Milwaukee Brewers (Saturday May 12, 2012)|Milwaukee Brewers vs Chicago Cubs [05/12/2012] Tickets at StubHub!|Chicago Cubs at Milwaukee Brewers\r\n709471|Colorado Rockies at Milwaukee Brewers (Friday April 20, 2012)|Milwaukee Brewers vs Colorado Rockies [04/20/2012] Tickets at StubHub!|Colorado Rockies at Milwaukee Brewers\r\n709472|Pittsburgh Pirates at Milwaukee Brewers (Saturday September 1, 2012)|Milwaukee Brewers vs Pittsburgh Pirates [09/01/2012] Tickets at StubHub!|Pittsburgh Pirates at Milwaukee Brewers\r\n709473|Houston Astros at Milwaukee Brewers (Monday July 30, 2012)|Milwaukee Brewers vs Houston 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19, 2012)|Milwaukee Brewers vs Philadelphia Phillies [08/19/2012] Tickets at StubHub!|Philadelphia Phillies at Milwaukee Brewers\r\n709496|Chicago Cubs at Milwaukee Brewers (Thursday June 7, 2012)|Milwaukee Brewers vs Chicago Cubs [06/07/2012] Tickets at StubHub!|Chicago Cubs at Milwaukee Brewers\r\n710642|Detroit Tigers at Minnesota Twins (Saturday September 29, 2012)|Minnesota Twins vs Detroit Tigers [9/29/2012] Tickets at StubHub!|Detroit Tigers at Minnesota Twins\r\n710643|New York Yankees at Minnesota Twins (Wednesday September 26, 2012)|Minnesota Twins vs New York Yankees [9/26/2012] Tickets at StubHub!|New York Yankees at Minnesota Twins\r\n710644|New York Yankees at Minnesota Twins (Monday September 24, 2012)|Minnesota Twins vs New York Yankees [9/24/2012] Tickets at StubHub!|New York Yankees at Minnesota Twins\r\n710645|New York Yankees at Minnesota Twins (Tuesday September 25, 2012)|Minnesota Twins vs New York Yankees [9/25/2012] Tickets at StubHub!|New York Yankees at 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Tigers vs Chicago White Sox [7/20/2012] Tickets at StubHub!|Chicago White Sox at Detroit Tigers\r\n711338|New York Yankees at Detroit Tigers (Sunday June 3, 2012)|Detroit Tigers vs New York Yankees [6/3/2012] Tickets at StubHub!|New York Yankees at Detroit Tigers\r\n711339|Baltimore Orioles at Detroit Tigers (Friday August 17, 2012)|Detroit Tigers vs Baltimore Orioles [8/17/2012] Tickets at StubHub!|Baltimore Orioles at Detroit Tigers\r\n711340|St. Louis Cardinals at Detroit Tigers (Wednesday June 20, 2012)|Detroit Tigers vs St. Louis Cardinals [6/20/2012] Tickets at StubHub!|St. Louis Cardinals at Detroit Tigers\r\n711341|Tampa Bay Rays at Detroit Tigers (Wednesday April 11, 2012)|Detroit Tigers vs Tampa Bay Rays [4/11/2012] Tickets at StubHub!|Tampa Bay Rays at Detroit Tigers\r\n711342|San Francisco Giants at Arizona Diamondbacks|Arizona Diamondbacks vs San Francisco Giants [4/6/2012] Tickets at StubHub!|San Francisco Giants at Arizona Diamondbacks\r\n711891|Houston Astros at Chicago Cubs|Chicago Cubs vs Houston Astros [10/3/2012] Tickets at StubHub!|Houston Astros at Chicago Cubs\r\n713106|Colorado Rockies at St Louis Cardinals|St Louis Cardinals vs Colorado Rockies [7/5/2012] Tickets at StubHub!|Colorado Rockies at St. Louis Cardinals\r\n713107|Cincinnati Reds at St Louis Cardinals|St Louis Cardinals vs Cincinnati Reds [4/19/2012] Tickets at StubHub!|Cincinnati Reds at St. Louis Cardinals\r\n713108|Cleveland Indians at St Louis Cardinals|St Louis Cardinals vs Cleveland Indians [6/10/2012] Tickets at StubHub!|Cleveland Indians at St. Louis Cardinals\r\n713109|San Francisco Giants at St Louis Cardinals|St Louis Cardinals vs San Francisco Giants [8/8/2012] Tickets at StubHub!|San Francisco Giants at St. Louis Cardinals\r\n713110|New York Mets at St Louis Cardinals|St Louis Cardinals vs New York Mets [9/4/2012] Tickets at StubHub!|New York Mets at St. Louis Cardinals\r\n713111|Milwaukee Brewers at St Louis Cardinals|St Louis Cardinals vs Milwaukee Brewers [4/27/2012] Tickets at StubHub!|Milwaukee Brewers at St. Louis Cardinals\r\n713112|Chicago Cubs at St Louis Cardinals|St Louis Cardinals vs Chicago Cubs [7/21/2012] Tickets at StubHub!|Chicago Cubs at St. Louis Cardinals\r\n713113|Chicago Cubs at St Louis Cardinals|St Louis Cardinals vs Chicago Cubs [5/14/2012] Tickets at StubHub!|Chicago Cubs at St. Louis Cardinals\r\n713114|Philadelphia Phillies at St Louis Cardinals|St Louis Cardinals vs Philadelphia Phillies [5/25/2012] Tickets at StubHub!|Philadelphia Phillies at St. Louis Cardinals\r\n713115|Arizona Diamondbacks at St Louis Cardinals|St Louis Cardinals vs Arizona Diamondbacks [8/16/2012] Tickets at StubHub!|Arizona Diamondbacks at St. Louis Cardinals\r\n713116|Washington Nationals at St Louis Cardinals|St Louis Cardinals vs Washington Nationals [9/28/2012] Tickets at StubHub!|Washington Nationals at St. Louis Cardinals\r\n713117|Miami Marlins at St Louis Cardinals|St Louis Cardinals vs Miami Marlins [7/6/2012] Tickets at StubHub!|Miami Marlins at St. Louis Cardinals\r\n713118|San Diego Padres at St Louis Cardinals|St Louis Cardinals vs San Diego Padres [5/22/2012] Tickets at StubHub!|San Diego Padres at St. Louis Cardinals\r\n713119|Milwaukee Brewers at St Louis Cardinals|St Louis Cardinals vs Milwaukee Brewers [8/3/2012] Tickets at StubHub!|Milwaukee Brewers at St. Louis Cardinals\r\n713120|Cincinnati Reds at St Louis Cardinals|St Louis Cardinals vs Cincinnati Reds [4/18/2012] Tickets at StubHub!|Cincinnati Reds at St. Louis Cardinals\r\n713121|Houston Astros at St Louis Cardinals|St Louis Cardinals vs Houston Astros [9/20/2012] Tickets at StubHub!|Houston Astros at St. Louis Cardinals\r\n713122|Cincinnati Reds at St Louis Cardinals|St Louis Cardinals vs Cincinnati Reds [10/3/2012] Tickets at StubHub!|Cincinnati Reds at St. Louis Cardinals\r\n713123|Cleveland Indians at St Louis Cardinals|St Louis Cardinals vs Cleveland Indians [6/9/2012] Tickets at StubHub!|Cleveland Indians at St. Louis Cardinals\r\n713124|New York Mets at St Louis Cardinals|St Louis Cardinals vs New York Mets [9/5/2012] Tickets at StubHub!|New York Mets at St. Louis Cardinals\r\n713125|Chicago Cubs at St Louis Cardinals|St Louis Cardinals vs Chicago Cubs [7/22/2012] Tickets at StubHub!|Chicago Cubs at St. Louis Cardinals\r\n713126|Chicago Cubs at St Louis Cardinals|St Louis Cardinals vs Chicago Cubs [5/15/2012] Tickets at StubHub!|Chicago Cubs at St. Louis Cardinals\r\n713127|Pittsburgh Pirates at St Louis Cardinals|St Louis Cardinals vs Pittsburgh Pirates [8/19/2012] Tickets at StubHub!|Pittsburgh Pirates at St. Louis Cardinals\r\n713128|Chicago Cubs at St Louis Cardinals|St Louis Cardinals vs Chicago Cubs [4/13/2012] Tickets at StubHub!|Chicago Cubs at St. Louis Cardinals\r\n713129|Washington Nationals at St Louis Cardinals|St Louis Cardinals vs Washington Nationals [9/29/2012] Tickets at StubHub!|Washington Nationals at St. Louis Cardinals\r\n713130|Miami Marlins at St Louis Cardinals|St Louis Cardinals vs Miami Marlins 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Brewers at St. Louis Cardinals\r\n713137|Los Angeles Dodgers at St Louis Cardinals|St Louis Cardinals vs Los Angeles Dodgers [7/23/2012] Tickets at StubHub!|Los Angeles Dodgers at St. Louis Cardinals\r\n713138|Atlanta Braves at St Louis Cardinals|St Louis Cardinals vs Atlanta Braves [5/12/2012] Tickets at StubHub!|Atlanta Braves at St. Louis Cardinals\r\n713139|Milwaukee Brewers at St Louis Cardinals|St Louis Cardinals vs Milwaukee Brewers [8/5/2012] Tickets at StubHub!|Milwaukee Brewers at St. Louis Cardinals\r\n713140|Pittsburgh Pirates at St Louis Cardinals|St Louis Cardinals vs Pittsburgh Pirates [8/18/2012] Tickets at StubHub!|Pittsburgh Pirates at St. Louis Cardinals\r\n713141|Houston Astros at St Louis Cardinals|St Louis Cardinals vs Houston Astros [9/18/2012] Tickets at StubHub!|Houston Astros at St. Louis Cardinals\r\n713142|Los Angeles Dodgers at St Louis Cardinals|St Louis Cardinals vs Los Angeles Dodgers [7/24/2012] Tickets at StubHub!|Los Angeles Dodgers at St. Louis Cardinals\r\n713143|New York Mets at St Louis Cardinals|St Louis Cardinals vs New York Mets [9/3/2012] Tickets at StubHub!|New York Mets at St. Louis Cardinals\r\n713144|Cincinnati Reds at St Louis Cardinals (Mon. 10/1/12)|St Louis Cardinals vs Cincinnati Reds [10/1/2012] Tickets at StubHub!|Cincinnati Reds at St. Louis Cardinals\r\n713145|Kansas City Royals at St Louis Cardinals|St Louis Cardinals vs Kansas City Royals [6/15/2012] Tickets at StubHub!|Kansas City Royals at St. Louis Cardinals\r\n713146|Houston Astros at St Louis Cardinals|St Louis Cardinals vs Houston Astros [8/21/2012] Tickets at StubHub!|Houston Astros at St. Louis Cardinals\r\n713147|Kansas City Royals at St Louis Cardinals|St Louis Cardinals vs Kansas City Royals [6/16/2012] Tickets at StubHub!|Kansas City Royals at St. Louis Cardinals\r\n713148|Milwaukee Brewers at St Louis Cardinals|St Louis Cardinals vs Milwaukee Brewers [4/28/2012] Tickets at StubHub!|Milwaukee Brewers at St. Louis 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Chicago White Sox [6/13/2012] Tickets at StubHub!|Chicago White Sox at St. Louis Cardinals\r\n713168|Philadelphia Phillies at St Louis Cardinals|St Louis Cardinals vs Philadelphia Phillies [5/26/2012] Tickets at StubHub!|Philadelphia Phillies at St. Louis Cardinals\r\n713169|Houston Astros at St Louis Cardinals|St Louis Cardinals vs Houston Astros [8/23/2012] Tickets at StubHub!|Houston Astros at St. Louis Cardinals\r\n713170|Colorado Rockies at St Louis Cardinals|St Louis Cardinals vs Colorado Rockies [7/3/2012] Tickets at StubHub!|Colorado Rockies at St. Louis Cardinals\r\n713171|Atlanta Braves at St Louis Cardinals|St Louis Cardinals vs Atlanta Braves [5/11/2012] Tickets at StubHub!|Atlanta Braves at St. Louis Cardinals\r\n713172|San Francisco Giants at St Louis Cardinals|St Louis Cardinals vs San Francisco Giants [8/6/2012] Tickets at StubHub!|San Francisco Giants at St. Louis Cardinals\r\n713173|Cincinnati Reds at St Louis Cardinals|St Louis Cardinals vs Cincinnati Reds 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at StubHub!|Philadelphia Phillies at St. Louis Cardinals\r\n713186|Pittsburgh Pirates at St Louis Cardinals|St Louis Cardinals vs Pittsburgh Pirates [8/17/2012] Tickets at StubHub!|Pittsburgh Pirates at St. Louis Cardinals\r\n713378|Baltimore Orioles at Los Angeles Angels (Thursday July 5, 2012)|Los Angeles Angels vs Baltimore Orioles [7/5/2012] Tickets at StubHub!|Baltimore Orioles at Los Angeles Angels of Anaheim\r\n713379|Oakland Athletics at Los Angeles Angels (Wednesday September 12, 2012)|Los Angeles Angels vs Oakland Athletics [9/12/2012] Tickets at StubHub!|Oakland Athletics at Los Angeles Angels of Anaheim\r\n713380|Oakland Athletics at Los Angeles Angels (Thursday April 19, 2012)|Los Angeles Angels vs Oakland Athletics [4/19/2012] Tickets at StubHub!|Oakland Athletics at Los Angeles Angels of Anaheim\r\n713381|Chicago White Sox at Los Angeles Angels (Sunday September 23, 2012)|Los Angeles Angels vs Chicago White Sox [9/23/2012] Tickets at StubHub!|Chicago White Sox at Los 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- Boston Red Sox at St. Louis Cardinals\r\n757487|Miami Marlins at St Louis Cardinals Spring Training|Miami Marlins vs St Louis Cardinals [03/10/2012] Spring Training Tickets at StubHub!|Spring Training - St. Louis Cardinals at Miami Marlins\r\n" }, { "path": "data/thefuzz/release", "content": "#!/usr/bin/env bash\nset -eo pipefail; [[ $RELEASE_TRACE ]] && set -x\n\nPACKAGE_NAME='thefuzz'\nINIT_PACKAGE_NAME='thefuzz'\nPUBLIC=\"true\"\n\n# Colors\nCOLOR_OFF=\"\\033[0m\" # unsets color to term fg color\nRED=\"\\033[0;31m\" # red\nGREEN=\"\\033[0;32m\" # green\nYELLOW=\"\\033[0;33m\" # yellow\nMAGENTA=\"\\033[0;35m\" # magenta\nCYAN=\"\\033[0;36m\" # cyan\n\n# ensure wheel is available\npip install wheel > /dev/null\n\n# ensure Pygment is available\npip install Pygments > /dev/null\n\ncommand -v gitchangelog >/dev/null 2>&1 || {\n echo -e \"${RED}WARNING: Missing gitchangelog binary, please run: pip install gitchangelog==2.2.0${COLOR_OFF}\\n\"\n exit 1\n}\n\ncommand -v rst-lint > /dev/null || {\n echo -e \"${RED}WARNING: Missing rst-lint binary, please run: pip install restructuredtext_lint${COLOR_OFF}\\n\"\n exit 1\n}\n\nset +e;\npython test_thefuzz.py &> /dev/null # run the tests\nif [ ! $? -eq 0 ]; then\n echo -e \"${RED}WARNING: The tests are failing.${COLOR_OFF}\"\n exit 1\nfi\nset -e;\n\nif [[ \"$@\" != \"major\" ]] && [[ \"$@\" != \"minor\" ]] && [[ \"$@\" != \"patch\" ]]; then\n echo -e \"${RED}WARNING: Invalid release type, must specify 'major', 'minor', or 'patch'${COLOR_OFF}\\n\"\n exit 1\nfi\n\necho -e \"\\n${GREEN}STARTING RELEASE PROCESS${COLOR_OFF}\\n\"\n\nset +e;\ngit status | grep -Eo \"working (directory|tree) clean\" &> /dev/null\nif [ ! $? -eq 0 ]; then # working directory is NOT clean\n echo -e \"${RED}WARNING: You have uncommitted changes, you may have forgotten something${COLOR_OFF}\\n\"\n exit 1\nfi\nset -e;\n\necho -e \"${YELLOW}--->${COLOR_OFF} Updating local copy\"\ngit pull -q origin master\ngit fetch --tags > /dev/null\n\necho -e \"${YELLOW}--->${COLOR_OFF} Retrieving release versions\"\n\ncurrent_version=$(cat ${INIT_PACKAGE_NAME}/__init__.py |grep '__version__ ='|sed 's/[^0-9.]//g')\nmajor=$(echo $current_version | awk '{split($0,a,\".\"); print a[1]}')\nminor=$(echo $current_version | awk '{split($0,a,\".\"); print a[2]}')\npatch=$(echo $current_version | awk '{split($0,a,\".\"); print a[3]}')\n\nif [[ \"$@\" == \"major\" ]]; then\n major=$(($major + 1));\n minor=\"0\"\n patch=\"0\"\nelif [[ \"$@\" == \"minor\" ]]; then\n minor=$(($minor + 1));\n patch=\"0\"\nelif [[ \"$@\" == \"patch\" ]]; then\n patch=$(($patch + 1));\nfi\n\nnext_version=\"${major}.${minor}.${patch}\"\n\necho -e \"${YELLOW} >${COLOR_OFF} ${MAGENTA}${current_version}${COLOR_OFF} -> ${MAGENTA}${next_version}${COLOR_OFF}\"\n\necho -e \"${YELLOW}--->${COLOR_OFF} Ensuring readme passes lint checks (if this fails, run rst-lint)\"\nrst-lint README.rst > /dev/null\n\necho -e \"${YELLOW}--->${COLOR_OFF} Creating necessary temp file\"\ntempfoo=$(basename $0)\nTMPFILE=$(mktemp /tmp/${tempfoo}.XXXXXX) || {\n echo -e \"${RED}WARNING: Cannot create temp file using mktemp in /tmp dir ${COLOR_OFF}\\n\"\n exit 1\n}\n\nfind_this=\"__version__ = '$current_version'\"\nreplace_with=\"__version__ = '$next_version'\"\n\necho -e \"${YELLOW}--->${COLOR_OFF} Updating ${INIT_PACKAGE_NAME}/__init__.py\"\nsed \"s/$find_this/$replace_with/\" ${INIT_PACKAGE_NAME}/__init__.py > $TMPFILE && mv $TMPFILE ${INIT_PACKAGE_NAME}/__init__.py\n\necho -e \"${YELLOW}--->${COLOR_OFF} Updating README.rst\"\nfind_this=\"${PACKAGE_NAME}.git@$current_version\"\nreplace_with=\"${PACKAGE_NAME}.git@$next_version\"\nsed \"s/$find_this/$replace_with/\" README.rst > $TMPFILE && mv $TMPFILE README.rst\nfind_this=\"${PACKAGE_NAME}==$current_version\"\nreplace_with=\"${PACKAGE_NAME}==$next_version\"\nsed \"s/$find_this/$replace_with/\" README.rst > $TMPFILE && mv $TMPFILE README.rst\n\nif [ -f docs/conf.py ]; then\n echo -e \"${YELLOW}--->${COLOR_OFF} Updating docs\"\n find_this=\"version = '${current_version}'\"\n replace_with=\"version = '${next_version}'\"\n sed \"s/$find_this/$replace_with/\" docs/conf.py > $TMPFILE && mv $TMPFILE docs/conf.py\n\n find_this=\"release = '${current_version}'\"\n replace_with=\"release = '${next_version}'\"\n sed \"s/$find_this/$replace_with/\" docs/conf.py > $TMPFILE && mv $TMPFILE docs/conf.py\nfi\n\necho -e \"${YELLOW}--->${COLOR_OFF} Updating CHANGES.rst for new release\"\nversion_header=\"$next_version ($(date +%F))\"\nset +e; dashes=$(yes '-'|head -n ${#version_header}|tr -d '\\n') ; set -e\ngitchangelog |sed \"4s/.*/$version_header/\"|sed \"5s/.*/$dashes/\" > $TMPFILE && mv $TMPFILE CHANGES.rst\n\necho -e \"${YELLOW}--->${COLOR_OFF} Adding changed files to git\"\ngit add CHANGES.rst README.rst ${INIT_PACKAGE_NAME}/__init__.py\nif [ -f docs/conf.py ]; then git add docs/conf.py; fi\n\necho -e \"${YELLOW}--->${COLOR_OFF} Creating release\"\ngit commit -q -m \"Release version $next_version\"\n\necho -e \"${YELLOW}--->${COLOR_OFF} Tagging release\"\ngit tag -a $next_version -m \"Release version $next_version\"\n\necho -e \"${YELLOW}--->${COLOR_OFF} Pushing release and tags to github\"\ngit push -q origin master && git push -q --tags\n\nif [[ \"$PUBLIC\" == \"true\" ]]; then\n echo -e \"${YELLOW}--->${COLOR_OFF} Creating python release\"\n cp README.rst README\n python setup.py sdist bdist_wheel upload > /dev/null\n rm README\nelse\n echo -e \"${YELLOW}--->${COLOR_OFF} Creating local python dist and wheel for manual release\"\n python setup.py sdist bdist_wheel > /dev/null\nfi\n\necho -e \"\\n${CYAN}RELEASED VERSION ${next_version}${COLOR_OFF}\\n\"\n" }, { "path": "data/thefuzz/setup.py", "content": "#!/usr/bin/env python\n\n# Copyright (c) 2014 SeatGeek\n\n# This file is part of thefuzz.\n\nfrom thefuzz import __version__\nimport os\n\ntry:\n from setuptools import setup\nexcept ImportError:\n from distutils.core import setup\n\n\ndef open_file(fname):\n return open(os.path.join(os.path.dirname(__file__), fname))\n\n\nsetup(\n name='thefuzz',\n version=__version__,\n author='Adam Cohen',\n author_email='adam@seatgeek.com',\n packages=['thefuzz'],\n extras_require={'speedup': ['python-levenshtein>=0.12']},\n url='https://github.com/seatgeek/thefuzz',\n license=\"GPLv2\",\n classifiers=[\n 'Intended Audience :: Developers',\n 'License :: OSI Approved :: GNU General Public License v2 (GPLv2)',\n 'Programming Language :: Python',\n 'Programming Language :: Python :: 3',\n 'Programming Language :: Python :: 3.7',\n 'Programming Language :: Python :: 3.8',\n 'Programming Language :: Python :: 3.9',\n 'Programming Language :: Python :: 3.10',\n 'Programming Language :: Python :: 3.11',\n 'Programming Language :: Python :: 3 :: Only',\n ],\n description='Fuzzy string matching in python',\n long_description=open_file('README.rst').read(),\n zip_safe=True,\n)\n" }, { "path": "data/thefuzz/test_thefuzz.py", "content": "import unittest\nimport re\nimport pycodestyle\n\nfrom thefuzz import fuzz\nfrom thefuzz import process\nfrom thefuzz import utils\nfrom thefuzz.string_processing import StringProcessor\n\n\nclass StringProcessingTest(unittest.TestCase):\n def test_replace_non_letters_non_numbers_with_whitespace(self):\n strings = [\"new york mets - atlanta braves\", \"Cães danados\",\n \"New York //// Mets $$$\", \"Ça va?\"]\n for string in strings:\n proc_string = StringProcessor.replace_non_letters_non_numbers_with_whitespace(string)\n regex = re.compile(r\"(?ui)[\\W]\")\n for expr in regex.finditer(proc_string):\n self.assertEqual(expr.group(), \" \")\n\n def test_dont_condense_whitespace(self):\n s1 = \"new york mets - atlanta braves\"\n s2 = \"new york mets atlanta braves\"\n p1 = StringProcessor.replace_non_letters_non_numbers_with_whitespace(s1)\n p2 = StringProcessor.replace_non_letters_non_numbers_with_whitespace(s2)\n self.assertNotEqual(p1, p2)\n\n\nclass UtilsTest(unittest.TestCase):\n def setUp(self):\n self.s1 = \"new york mets\"\n self.s1a = \"new york mets\"\n self.s2 = \"new YORK mets\"\n self.s3 = \"the wonderful new york mets\"\n self.s4 = \"new york mets vs atlanta braves\"\n self.s5 = \"atlanta braves vs new york mets\"\n self.s6 = \"new york mets - atlanta braves\"\n self.mixed_strings = [\n \"Lorem Ipsum is simply dummy text of the printing and typesetting industry.\",\n \"C'est la vie\",\n \"Ça va?\",\n \"Cães danados\",\n \"\\xacCamarões assados\",\n \"a\\xac\\u1234\\u20ac\\U00008000\",\n \"\\u00C1\"\n ]\n\n def tearDown(self):\n pass\n\n def test_ascii_only(self):\n for s in self.mixed_strings:\n utils.ascii_only(s)\n\n def test_fullProcess(self):\n for s in self.mixed_strings:\n utils.full_process(s)\n\n def test_fullProcessForceAscii(self):\n for s in self.mixed_strings:\n utils.full_process(s, force_ascii=True)\n\n\nclass RatioTest(unittest.TestCase):\n\n def setUp(self):\n self.s1 = \"new york mets\"\n self.s1a = \"new york mets\"\n self.s2 = \"new YORK mets\"\n self.s3 = \"the wonderful new york mets\"\n self.s4 = \"new york mets vs atlanta braves\"\n self.s5 = \"atlanta braves vs new york mets\"\n self.s6 = \"new york mets - atlanta braves\"\n self.s7 = 'new york city mets - atlanta braves'\n # test silly corner cases\n self.s8 = '{'\n self.s8a = '{'\n self.s9 = '{a'\n self.s9a = '{a'\n self.s10 = 'a{'\n self.s10a = '{b'\n\n self.cirque_strings = [\n \"cirque du soleil - zarkana - las vegas\",\n \"cirque du soleil \",\n \"cirque du soleil las vegas\",\n \"zarkana las vegas\",\n \"las vegas cirque du soleil at the bellagio\",\n \"zarakana - cirque du soleil - bellagio\"\n ]\n\n self.baseball_strings = [\n \"new york mets vs chicago cubs\",\n \"chicago cubs vs chicago white sox\",\n \"philladelphia phillies vs atlanta braves\",\n \"braves vs mets\",\n ]\n\n def tearDown(self):\n pass\n\n def testEqual(self):\n self.assertEqual(fuzz.ratio(self.s1, self.s1a), 100)\n self.assertEqual(fuzz.ratio(self.s8, self.s8a), 100)\n self.assertEqual(fuzz.ratio(self.s9, self.s9a), 100)\n\n def testCaseInsensitive(self):\n self.assertNotEqual(fuzz.ratio(self.s1, self.s2), 100)\n self.assertEqual(fuzz.ratio(utils.full_process(self.s1), utils.full_process(self.s2)), 100)\n\n def testPartialRatio(self):\n self.assertEqual(fuzz.partial_ratio(self.s1, self.s3), 100)\n\n def testTokenSortRatio(self):\n self.assertEqual(fuzz.token_sort_ratio(self.s1, self.s1a), 100)\n\n def testPartialTokenSortRatio(self):\n self.assertEqual(fuzz.partial_token_sort_ratio(self.s1, self.s1a), 100)\n self.assertEqual(fuzz.partial_token_sort_ratio(self.s4, self.s5), 100)\n self.assertEqual(fuzz.partial_token_sort_ratio(self.s8, self.s8a, full_process=False), 100)\n self.assertEqual(fuzz.partial_token_sort_ratio(self.s9, self.s9a, full_process=True), 100)\n self.assertEqual(fuzz.partial_token_sort_ratio(self.s9, self.s9a, full_process=False), 100)\n self.assertEqual(fuzz.partial_token_sort_ratio(self.s10, self.s10a, full_process=False), 50)\n\n def testTokenSetRatio(self):\n self.assertEqual(fuzz.token_set_ratio(self.s4, self.s5), 100)\n self.assertEqual(fuzz.token_set_ratio(self.s8, self.s8a, full_process=False), 100)\n self.assertEqual(fuzz.token_set_ratio(self.s9, self.s9a, full_process=True), 100)\n self.assertEqual(fuzz.token_set_ratio(self.s9, self.s9a, full_process=False), 100)\n self.assertEqual(fuzz.token_set_ratio(self.s10, self.s10a, full_process=False), 50)\n\n def testPartialTokenSetRatio(self):\n self.assertEqual(fuzz.partial_token_set_ratio(self.s4, self.s7), 100)\n\n def testQuickRatioEqual(self):\n self.assertEqual(fuzz.QRatio(self.s1, self.s1a), 100)\n\n def testQuickRatioCaseInsensitive(self):\n self.assertEqual(fuzz.QRatio(self.s1, self.s2), 100)\n\n def testQuickRatioNotEqual(self):\n self.assertNotEqual(fuzz.QRatio(self.s1, self.s3), 100)\n\n def testWRatioEqual(self):\n self.assertEqual(fuzz.WRatio(self.s1, self.s1a), 100)\n\n def testWRatioCaseInsensitive(self):\n self.assertEqual(fuzz.WRatio(self.s1, self.s2), 100)\n\n def testWRatioPartialMatch(self):\n # a partial match is scaled by .9\n self.assertEqual(fuzz.WRatio(self.s1, self.s3), 90)\n\n def testWRatioMisorderedMatch(self):\n # misordered full matches are scaled by .95\n self.assertEqual(fuzz.WRatio(self.s4, self.s5), 95)\n\n def testWRatioStr(self):\n self.assertEqual(fuzz.WRatio(str(self.s1), str(self.s1a)), 100)\n\n def testQRatioStr(self):\n self.assertEqual(fuzz.WRatio(str(self.s1), str(self.s1a)), 100)\n\n def testEmptyStringsScore100(self):\n self.assertEqual(fuzz.ratio(\"\", \"\"), 100)\n self.assertEqual(fuzz.partial_ratio(\"\", \"\"), 100)\n\n def testIssueSeven(self):\n s1 = \"HSINCHUANG\"\n s2 = \"SINJHUAN\"\n s3 = \"LSINJHUANG DISTRIC\"\n s4 = \"SINJHUANG DISTRICT\"\n\n self.assertGreater(fuzz.partial_ratio(s1, s2), 75)\n self.assertGreater(fuzz.partial_ratio(s1, s3), 75)\n self.assertGreater(fuzz.partial_ratio(s1, s4), 75)\n\n def testRatioUnicodeString(self):\n s1 = \"\\u00C1\"\n s2 = \"ABCD\"\n score = fuzz.ratio(s1, s2)\n self.assertEqual(0, score)\n\n def testPartialRatioUnicodeString(self):\n s1 = \"\\u00C1\"\n s2 = \"ABCD\"\n score = fuzz.partial_ratio(s1, s2)\n self.assertEqual(0, score)\n\n def testWRatioUnicodeString(self):\n s1 = \"\\u00C1\"\n s2 = \"ABCD\"\n score = fuzz.WRatio(s1, s2)\n self.assertEqual(0, score)\n\n # Cyrillic.\n s1 = \"\\u043f\\u0441\\u0438\\u0445\\u043e\\u043b\\u043e\\u0433\"\n s2 = \"\\u043f\\u0441\\u0438\\u0445\\u043e\\u0442\\u0435\\u0440\\u0430\\u043f\\u0435\\u0432\\u0442\"\n score = fuzz.WRatio(s1, s2, force_ascii=False)\n self.assertNotEqual(0, score)\n\n # Chinese.\n s1 = \"\\u6211\\u4e86\\u89e3\\u6570\\u5b66\"\n s2 = \"\\u6211\\u5b66\\u6570\\u5b66\"\n score = fuzz.WRatio(s1, s2, force_ascii=False)\n self.assertNotEqual(0, score)\n\n def testQRatioUnicodeString(self):\n s1 = \"\\u00C1\"\n s2 = \"ABCD\"\n score = fuzz.QRatio(s1, s2)\n self.assertEqual(0, score)\n\n # Cyrillic.\n s1 = \"\\u043f\\u0441\\u0438\\u0445\\u043e\\u043b\\u043e\\u0433\"\n s2 = \"\\u043f\\u0441\\u0438\\u0445\\u043e\\u0442\\u0435\\u0440\\u0430\\u043f\\u0435\\u0432\\u0442\"\n score = fuzz.QRatio(s1, s2, force_ascii=False)\n self.assertNotEqual(0, score)\n\n # Chinese.\n s1 = \"\\u6211\\u4e86\\u89e3\\u6570\\u5b66\"\n s2 = \"\\u6211\\u5b66\\u6570\\u5b66\"\n score = fuzz.QRatio(s1, s2, force_ascii=False)\n self.assertNotEqual(0, score)\n\n def testQratioForceAscii(self):\n s1 = \"ABCD\\u00C1\"\n s2 = \"ABCD\"\n\n score = fuzz.QRatio(s1, s2, force_ascii=True)\n self.assertEqual(score, 100)\n\n score = fuzz.QRatio(s1, s2, force_ascii=False)\n self.assertLess(score, 100)\n\n def testQRatioForceAscii(self):\n s1 = \"ABCD\\u00C1\"\n s2 = \"ABCD\"\n\n score = fuzz.WRatio(s1, s2, force_ascii=True)\n self.assertEqual(score, 100)\n\n score = fuzz.WRatio(s1, s2, force_ascii=False)\n self.assertLess(score, 100)\n\n def testTokenSetForceAscii(self):\n s1 = \"ABCD\\u00C1 HELP\\u00C1\"\n s2 = \"ABCD HELP\"\n\n score = fuzz._token_set(s1, s2, force_ascii=True)\n self.assertEqual(score, 100)\n\n score = fuzz._token_set(s1, s2, force_ascii=False)\n self.assertLess(score, 100)\n\n def testTokenSortForceAscii(self):\n s1 = \"ABCD\\u00C1 HELP\\u00C1\"\n s2 = \"ABCD HELP\"\n\n score = fuzz._token_sort(s1, s2, force_ascii=True)\n self.assertEqual(score, 100)\n\n score = fuzz._token_sort(s1, s2, force_ascii=False)\n self.assertLess(score, 100)\n\n\nclass ValidatorTest(unittest.TestCase):\n def setUp(self):\n self.testFunc = lambda *args, **kwargs: (args, kwargs)\n\n def testCheckForNone(self):\n invalid_input = [\n (None, None),\n ('Some', None),\n (None, 'Some')\n ]\n decorated_func = utils.check_for_none(self.testFunc)\n for i in invalid_input:\n self.assertEqual(decorated_func(*i), 0)\n\n valid_input = ('Some', 'Some')\n actual = decorated_func(*valid_input)\n self.assertNotEqual(actual, 0)\n\n def testCheckEmptyString(self):\n invalid_input = [\n ('', ''),\n ('Some', ''),\n ('', 'Some')\n ]\n decorated_func = utils.check_empty_string(self.testFunc)\n for i in invalid_input:\n self.assertEqual(decorated_func(*i), 0)\n\n valid_input = ('Some', 'Some')\n actual = decorated_func(*valid_input)\n self.assertNotEqual(actual, 0)\n\n\nclass ProcessTest(unittest.TestCase):\n\n def setUp(self):\n self.s1 = \"new york mets\"\n self.s1a = \"new york mets\"\n self.s2 = \"new YORK mets\"\n self.s3 = \"the wonderful new york mets\"\n self.s4 = \"new york mets vs atlanta braves\"\n self.s5 = \"atlanta braves vs new york mets\"\n self.s6 = \"new york mets - atlanta braves\"\n\n self.cirque_strings = [\n \"cirque du soleil - zarkana - las vegas\",\n \"cirque du soleil \",\n \"cirque du soleil las vegas\",\n \"zarkana las vegas\",\n \"las vegas cirque du soleil at the bellagio\",\n \"zarakana - cirque du soleil - bellagio\"\n ]\n\n self.baseball_strings = [\n \"new york mets vs chicago cubs\",\n \"chicago cubs vs chicago white sox\",\n \"philladelphia phillies vs atlanta braves\",\n \"braves vs mets\",\n ]\n\n def testGetBestChoice1(self):\n query = \"new york mets at atlanta braves\"\n best = process.extractOne(query, self.baseball_strings)\n self.assertEqual(best[0], \"braves vs mets\")\n\n def testGetBestChoice2(self):\n query = \"philadelphia phillies at atlanta braves\"\n best = process.extractOne(query, self.baseball_strings)\n self.assertEqual(best[0], self.baseball_strings[2])\n\n def testGetBestChoice3(self):\n query = \"atlanta braves at philadelphia phillies\"\n best = process.extractOne(query, self.baseball_strings)\n self.assertEqual(best[0], self.baseball_strings[2])\n\n def testGetBestChoice4(self):\n query = \"chicago cubs vs new york mets\"\n best = process.extractOne(query, self.baseball_strings)\n self.assertEqual(best[0], self.baseball_strings[0])\n\n def testWithProcessor(self):\n events = [\n [\"chicago cubs vs new york mets\", \"CitiField\", \"2011-05-11\", \"8pm\"],\n [\"new york yankees vs boston red sox\", \"Fenway Park\", \"2011-05-11\", \"8pm\"],\n [\"atlanta braves vs pittsburgh pirates\", \"PNC Park\", \"2011-05-11\", \"8pm\"],\n ]\n query = [\"new york mets vs chicago cubs\", \"CitiField\", \"2017-03-19\", \"8pm\"],\n\n best = process.extractOne(query, events, processor=lambda event: event[0])\n self.assertEqual(best[0], events[0])\n\n def testWithScorer(self):\n choices = [\n \"new york mets vs chicago cubs\",\n \"chicago cubs at new york mets\",\n \"atlanta braves vs pittsbugh pirates\",\n \"new york yankees vs boston red sox\"\n ]\n\n choices_dict = {\n 1: \"new york mets vs chicago cubs\",\n 2: \"chicago cubs vs chicago white sox\",\n 3: \"philladelphia phillies vs atlanta braves\",\n 4: \"braves vs mets\"\n }\n\n # in this hypothetical example we care about ordering, so we use quick ratio\n query = \"new york mets at chicago cubs\"\n scorer = fuzz.QRatio\n\n # first, as an example, the normal way would select the \"more\n # 'complete' match of choices[1]\"\n\n best = process.extractOne(query, choices)\n self.assertEqual(best[0], choices[1])\n\n # now, use the custom scorer\n\n best = process.extractOne(query, choices, scorer=scorer)\n self.assertEqual(best[0], choices[0])\n\n best = process.extractOne(query, choices_dict)\n self.assertEqual(best[0], choices_dict[1])\n\n def testWithCutoff(self):\n choices = [\n \"new york mets vs chicago cubs\",\n \"chicago cubs at new york mets\",\n \"atlanta braves vs pittsbugh pirates\",\n \"new york yankees vs boston red sox\"\n ]\n\n query = \"los angeles dodgers vs san francisco giants\"\n\n # in this situation, this is an event that does not exist in the list\n # we don't want to randomly match to something, so we use a reasonable cutoff\n\n best = process.extractOne(query, choices, score_cutoff=50)\n self.assertIsNone(best)\n\n # however if we had no cutoff, something would get returned\n\n # best = process.extractOne(query, choices)\n # self.assertIsNotNone(best)\n\n def testWithCutoff2(self):\n choices = [\n \"new york mets vs chicago cubs\",\n \"chicago cubs at new york mets\",\n \"atlanta braves vs pittsbugh pirates\",\n \"new york yankees vs boston red sox\"\n ]\n\n query = \"new york mets vs chicago cubs\"\n # Only find 100-score cases\n res = process.extractOne(query, choices, score_cutoff=100)\n self.assertIsNotNone(res)\n best_match, score = res\n self.assertIs(best_match, choices[0])\n\n def testEmptyStrings(self):\n choices = [\n \"\",\n \"new york mets vs chicago cubs\",\n \"new york yankees vs boston red sox\",\n \"\",\n \"\"\n ]\n\n query = \"new york mets at chicago cubs\"\n\n best = process.extractOne(query, choices)\n self.assertEqual(best[0], choices[1])\n\n def testNullStrings(self):\n choices = [\n None,\n \"new york mets vs chicago cubs\",\n \"new york yankees vs boston red sox\",\n None,\n None\n ]\n\n query = \"new york mets at chicago cubs\"\n\n best = process.extractOne(query, choices)\n self.assertEqual(best[0], choices[1])\n\n def test_list_like_extract(self):\n \"\"\"We should be able to use a list-like object for choices.\"\"\"\n def generate_choices():\n choices = ['a', 'Bb', 'CcC']\n yield from choices\n search = 'aaa'\n result = [(value, confidence) for value, confidence in\n process.extract(search, generate_choices())]\n self.assertGreater(len(result), 0)\n\n def test_dict_like_extract(self):\n \"\"\"We should be able to use a dict-like object for choices, not only a\n dict, and still get dict-like output.\n \"\"\"\n try:\n from UserDict import UserDict\n except ImportError:\n from collections import UserDict\n choices = UserDict({'aa': 'bb', 'a1': None})\n search = 'aaa'\n result = process.extract(search, choices)\n self.assertGreater(len(result), 0)\n for value, confidence, key in result:\n self.assertIn(value, choices.values())\n\n def test_dedupe(self):\n \"\"\"We should be able to use a list-like object for contains_dupes\n \"\"\"\n # Test 1\n contains_dupes = ['Frodo Baggins', 'Tom Sawyer', 'Bilbo Baggin', 'Samuel L. Jackson', 'F. Baggins', 'Frody Baggins', 'Bilbo Baggins']\n\n result = process.dedupe(contains_dupes)\n self.assertLess(len(result), len(contains_dupes))\n\n # Test 2\n contains_dupes = ['Tom', 'Dick', 'Harry']\n\n # we should end up with the same list since no duplicates are contained in the list (e.g. original list is returned)\n deduped_list = ['Tom', 'Dick', 'Harry']\n\n result = process.dedupe(contains_dupes)\n self.assertEqual(result, deduped_list)\n\n def test_simplematch(self):\n basic_string = 'a, b'\n match_strings = ['a, b']\n\n result = process.extractOne(basic_string, match_strings, scorer=fuzz.ratio)\n part_result = process.extractOne(basic_string, match_strings, scorer=fuzz.partial_ratio)\n\n self.assertEqual(result, ('a, b', 100))\n self.assertEqual(part_result, ('a, b', 100))\n\n\nclass TestCodeFormat(unittest.TestCase):\n def test_pep8_conformance(self):\n pep8style = pycodestyle.StyleGuide(quiet=False)\n pep8style.options.ignore = pep8style.options.ignore + tuple(['E501'])\n pep8style.input_dir('thefuzz')\n result = pep8style.check_files()\n self.assertEqual(result.total_errors, 0, \"PEP8 POLICE - WOOOOOWOOOOOOOOOO\")\n\nif __name__ == '__main__':\n unittest.main() # run all tests\n" }, { "path": "data/thefuzz/test_thefuzz_hypothesis.py", "content": "from itertools import product\nfrom functools import partial\nfrom string import ascii_letters, digits, punctuation\n\nfrom hypothesis import given, assume, settings\nimport hypothesis.strategies as st\nimport pytest\n\nfrom thefuzz import fuzz, process, utils\n\n\nHYPOTHESIS_ALPHABET = ascii_letters + digits + punctuation\n\n\ndef scorers_processors():\n \"\"\"\n Generate a list of (scorer, processor) pairs for testing\n\n :return: [(scorer, processor), ...]\n \"\"\"\n scorers = [fuzz.ratio,\n fuzz.partial_ratio]\n processors = [lambda x: x,\n partial(utils.full_process, force_ascii=False),\n partial(utils.full_process, force_ascii=True)]\n splist = list(product(scorers, processors))\n splist.extend(\n [(fuzz.WRatio, partial(utils.full_process, force_ascii=True)),\n (fuzz.QRatio, partial(utils.full_process, force_ascii=True)),\n (fuzz.UWRatio, partial(utils.full_process, force_ascii=False)),\n (fuzz.UQRatio, partial(utils.full_process, force_ascii=False)),\n (fuzz.token_set_ratio, partial(utils.full_process, force_ascii=True)),\n (fuzz.token_sort_ratio, partial(utils.full_process, force_ascii=True)),\n (fuzz.partial_token_set_ratio, partial(utils.full_process, force_ascii=True)),\n (fuzz.partial_token_sort_ratio, partial(utils.full_process, force_ascii=True))]\n )\n\n return splist\n\n\ndef full_scorers_processors():\n \"\"\"\n Generate a list of (scorer, processor) pairs for testing for scorers that use the full string only\n\n :return: [(scorer, processor), ...]\n \"\"\"\n scorers = [fuzz.ratio]\n processors = [lambda x: x,\n partial(utils.full_process, force_ascii=False),\n partial(utils.full_process, force_ascii=True)]\n splist = list(product(scorers, processors))\n splist.extend(\n [(fuzz.WRatio, partial(utils.full_process, force_ascii=True)),\n (fuzz.QRatio, partial(utils.full_process, force_ascii=True)),\n (fuzz.UWRatio, partial(utils.full_process, force_ascii=False)),\n (fuzz.UQRatio, partial(utils.full_process, force_ascii=False))]\n )\n\n return splist\n\n\n@pytest.mark.parametrize('scorer,processor',\n scorers_processors())\n@given(data=st.data())\n@settings(max_examples=20, deadline=5000)\ndef test_identical_strings_extracted(scorer, processor, data):\n \"\"\"\n Test that identical strings will always return a perfect match.\n\n :param scorer:\n :param processor:\n :param data:\n :return:\n \"\"\"\n # Draw a list of random strings\n strings = data.draw(\n st.lists(\n st.text(min_size=10, max_size=100, alphabet=HYPOTHESIS_ALPHABET),\n min_size=1,\n max_size=10\n )\n )\n # Draw a random integer for the index in that list\n choiceidx = data.draw(st.integers(min_value=0, max_value=(len(strings) - 1)))\n\n # Extract our choice from the list\n choice = strings[choiceidx]\n\n # Check process doesn't make our choice the empty string\n assume(processor(choice) != '')\n\n # Extract all perfect matches\n result = process.extractBests(choice,\n strings,\n scorer=scorer,\n processor=processor,\n score_cutoff=100,\n limit=None)\n\n # Check we get a result\n assert result != []\n\n # Check the original is in the list\n assert (choice, 100) in result\n\n\n@pytest.mark.parametrize('scorer,processor',\n full_scorers_processors())\n@given(data=st.data())\n@settings(max_examples=20, deadline=5000)\ndef test_only_identical_strings_extracted(scorer, processor, data):\n \"\"\"\n Test that only identical (post processing) strings score 100 on the test.\n\n If two strings are not identical then using full comparison methods they should\n not be a perfect (100) match.\n\n :param scorer:\n :param processor:\n :param data:\n :return:\n \"\"\"\n # Draw a list of random strings\n strings = data.draw(\n st.lists(\n st.text(min_size=10, max_size=100, alphabet=HYPOTHESIS_ALPHABET),\n min_size=1,\n max_size=10)\n )\n # Draw a random integer for the index in that list\n choiceidx = data.draw(st.integers(min_value=0, max_value=(len(strings) - 1)))\n\n # Extract our choice from the list\n choice = strings[choiceidx]\n\n # Check process doesn't make our choice the empty string\n assume(processor(choice) != '')\n\n # Extract all perfect matches\n result = process.extractBests(choice,\n strings,\n scorer=scorer,\n processor=processor,\n score_cutoff=100,\n limit=None)\n\n # Check we get a result\n assert result != []\n\n # Check THE ONLY result(s) we get are a perfect match for the (processed) original data\n pchoice = processor(choice)\n for r in result:\n assert pchoice == processor(r[0])\n" }, { "path": "data/thefuzz/test_thefuzz_pytest.py", "content": "from thefuzz import process\n\n\ndef test_process_warning(caplog):\n \"\"\"Check that a string reduced to 0 by processor logs a warning to stderr\"\"\"\n\n query = ':::::::'\n choices = [':::::::']\n\n _ = process.extractOne(query, choices)\n\n logstr = (\"Applied processor reduces \"\n \"input query to empty string, \"\n \"all comparisons will have score 0. \"\n \"[Query: ':::::::']\")\n\n assert 1 == len(caplog.records)\n log = caplog.records[0]\n\n assert log.levelname == \"WARNING\"\n assert log.name == \"thefuzz.process\"\n assert logstr == log.message\n" }, { "path": "data/thefuzz/thefuzz/StringMatcher.py", "content": "#!/usr/bin/env python\n\"\"\"\nStringMatcher.py\n\nported from python-Levenshtein\n[https://github.com/miohtama/python-Levenshtein]\nLicense available here: https://github.com/miohtama/python-Levenshtein/blob/master/COPYING\n\"\"\"\n\nfrom Levenshtein import *\nfrom warnings import warn\n\n\nclass StringMatcher:\n \"\"\"A SequenceMatcher-like class built on the top of Levenshtein\"\"\"\n\n def _reset_cache(self):\n self._ratio = self._distance = None\n self._opcodes = self._editops = self._matching_blocks = None\n\n def __init__(self, isjunk=None, seq1='', seq2=''):\n if isjunk:\n warn(\"isjunk not NOT implemented, it will be ignored\")\n self._str1, self._str2 = seq1, seq2\n self._reset_cache()\n\n def set_seqs(self, seq1, seq2):\n self._str1, self._str2 = seq1, seq2\n self._reset_cache()\n\n def set_seq1(self, seq1):\n self._str1 = seq1\n self._reset_cache()\n\n def set_seq2(self, seq2):\n self._str2 = seq2\n self._reset_cache()\n\n def get_opcodes(self):\n if not self._opcodes:\n if self._editops:\n self._opcodes = opcodes(self._editops, self._str1, self._str2)\n else:\n self._opcodes = opcodes(self._str1, self._str2)\n return self._opcodes\n\n def get_editops(self):\n if not self._editops:\n if self._opcodes:\n self._editops = editops(self._opcodes, self._str1, self._str2)\n else:\n self._editops = editops(self._str1, self._str2)\n return self._editops\n\n def get_matching_blocks(self):\n if not self._matching_blocks:\n self._matching_blocks = matching_blocks(self.get_opcodes(),\n self._str1, self._str2)\n return self._matching_blocks\n\n def ratio(self):\n if not self._ratio:\n self._ratio = ratio(self._str1, self._str2)\n return self._ratio\n\n def quick_ratio(self):\n # This is usually quick enough :o)\n if not self._ratio:\n self._ratio = ratio(self._str1, self._str2)\n return self._ratio\n\n def real_quick_ratio(self):\n len1, len2 = len(self._str1), len(self._str2)\n return 2.0 * min(len1, len2) / (len1 + len2)\n\n def distance(self):\n if not self._distance:\n self._distance = distance(self._str1, self._str2)\n return self._distance\n" }, { "path": "data/thefuzz/thefuzz/StringMatcher.pyi", "content": "from typing import Optional, Tuple, List\n\nOpcodeT = Tuple[str, int, int, int, int]\nEditOpcodeT = Tuple[str, int, int]\nMatchingBlocksT = List[Tuple[int, int, int]]\n\n\nclass StringMatcher:\n def _reset_cache(self) -> None:\n self._ratio: Optional[float] = None\n self._distance: Optional[int] = None\n self._opcodes: Optional[OpcodeT] = None\n self._editops: Optional[EditOpcodeT] = None\n self._matching_blocks: Optional[MatchingBlocksT] = None\n\n def __init__(self, isjunk: Optional[bool] = ..., seq1: str = ..., seq2: str = ...) -> None: ...\n def set_seqs(self, seq1: str, seq2: str) -> None: ...\n def set_seq1(self, seq1: str) -> None: ...\n def set_seq2(self, seq2: str) -> None: ...\n def get_opcodes(self) -> OpcodeT: ...\n def get_editops(self) -> EditOpcodeT: ...\n def get_matching_blocks(self) -> MatchingBlocksT: ...\n def ratio(self) -> float: ...\n def quick_ratio(self) -> float: ...\n def real_quick_ratio(self) -> float: ...\n def distance(self) -> int: ...\n" }, { "path": "data/thefuzz/thefuzz/__init__.py", "content": "__version__ = '0.19.0'\n" }, { "path": "data/thefuzz/thefuzz/fuzz.py", "content": "#!/usr/bin/env python\nimport platform\nimport warnings\n\ntry:\n from .StringMatcher import StringMatcher as SequenceMatcher\nexcept ImportError:\n if platform.python_implementation() != \"PyPy\":\n warnings.warn('Using slow pure-python SequenceMatcher. Install python-Levenshtein to remove this warning')\n from difflib import SequenceMatcher\n\nfrom . import utils\n\n\n###########################\n# Basic Scoring Functions #\n###########################\n\n@utils.check_for_none\n@utils.check_for_equivalence\n@utils.check_empty_string\ndef ratio(s1, s2):\n s1, s2 = utils.make_type_consistent(s1, s2)\n\n m = SequenceMatcher(None, s1, s2)\n return utils.intr(100 * m.ratio())\n\n\n@utils.check_for_none\n@utils.check_for_equivalence\n@utils.check_empty_string\ndef partial_ratio(s1, s2):\n \"\"\"\"Return the ratio of the most similar substring\n as a number between 0 and 100.\"\"\"\n s1, s2 = utils.make_type_consistent(s1, s2)\n\n if len(s1) <= len(s2):\n shorter = s1\n longer = s2\n else:\n shorter = s2\n longer = s1\n\n m = SequenceMatcher(None, shorter, longer)\n blocks = m.get_matching_blocks()\n\n # each block represents a sequence of matching characters in a string\n # of the form (idx_1, idx_2, len)\n # the best partial match will block align with at least one of those blocks\n # e.g. shorter = \"abcd\", longer = XXXbcdeEEE\n # block = (1,3,3)\n # best score === ratio(\"abcd\", \"Xbcd\")\n scores = []\n for block in blocks:\n long_start = block[1] - block[0] if (block[1] - block[0]) > 0 else 0\n long_end = long_start + len(shorter)\n long_substr = longer[long_start:long_end]\n\n m2 = SequenceMatcher(None, shorter, long_substr)\n r = m2.ratio()\n if r > .995:\n return 100\n else:\n scores.append(r)\n\n return utils.intr(100 * max(scores))\n\n\n##############################\n# Advanced Scoring Functions #\n##############################\n\ndef _process_and_sort(s, force_ascii, full_process=True):\n \"\"\"Return a cleaned string with token sorted.\"\"\"\n # pull tokens\n ts = utils.full_process(s, force_ascii=force_ascii) if full_process else s\n tokens = ts.split()\n\n # sort tokens and join\n sorted_string = \" \".join(sorted(tokens))\n return sorted_string.strip()\n\n\n# Sorted Token\n# find all alphanumeric tokens in the string\n# sort those tokens and take ratio of resulting joined strings\n# controls for unordered string elements\n@utils.check_for_none\ndef _token_sort(s1, s2, partial=True, force_ascii=True, full_process=True):\n sorted1 = _process_and_sort(s1, force_ascii, full_process=full_process)\n sorted2 = _process_and_sort(s2, force_ascii, full_process=full_process)\n\n if partial:\n return partial_ratio(sorted1, sorted2)\n else:\n return ratio(sorted1, sorted2)\n\n\ndef token_sort_ratio(s1, s2, force_ascii=True, full_process=True):\n \"\"\"Return a measure of the sequences' similarity between 0 and 100\n but sorting the token before comparing.\n \"\"\"\n return _token_sort(s1, s2, partial=False, force_ascii=force_ascii, full_process=full_process)\n\n\ndef partial_token_sort_ratio(s1, s2, force_ascii=True, full_process=True):\n \"\"\"Return the ratio of the most similar substring as a number between\n 0 and 100 but sorting the token before comparing.\n \"\"\"\n return _token_sort(s1, s2, partial=True, force_ascii=force_ascii, full_process=full_process)\n\n\n@utils.check_for_none\ndef _token_set(s1, s2, partial=True, force_ascii=True, full_process=True):\n \"\"\"Find all alphanumeric tokens in each string...\n - treat them as a set\n - construct two strings of the form:\n \n - take ratios of those two strings\n - controls for unordered partial matches\"\"\"\n\n if not full_process and s1 == s2:\n return 100\n\n p1 = utils.full_process(s1, force_ascii=force_ascii) if full_process else s1\n p2 = utils.full_process(s2, force_ascii=force_ascii) if full_process else s2\n\n if not utils.validate_string(p1):\n return 0\n if not utils.validate_string(p2):\n return 0\n\n # pull tokens\n tokens1 = set(p1.split())\n tokens2 = set(p2.split())\n\n intersection = tokens1.intersection(tokens2)\n diff1to2 = tokens1.difference(tokens2)\n diff2to1 = tokens2.difference(tokens1)\n\n sorted_sect = \" \".join(sorted(intersection))\n sorted_1to2 = \" \".join(sorted(diff1to2))\n sorted_2to1 = \" \".join(sorted(diff2to1))\n\n combined_1to2 = sorted_sect + \" \" + sorted_1to2\n combined_2to1 = sorted_sect + \" \" + sorted_2to1\n\n # strip\n sorted_sect = sorted_sect.strip()\n combined_1to2 = combined_1to2.strip()\n combined_2to1 = combined_2to1.strip()\n\n if partial:\n ratio_func = partial_ratio\n else:\n ratio_func = ratio\n\n pairwise = [\n ratio_func(sorted_sect, combined_1to2),\n ratio_func(sorted_sect, combined_2to1),\n ratio_func(combined_1to2, combined_2to1)\n ]\n return max(pairwise)\n\n\ndef token_set_ratio(s1, s2, force_ascii=True, full_process=True):\n return _token_set(s1, s2, partial=False, force_ascii=force_ascii, full_process=full_process)\n\n\ndef partial_token_set_ratio(s1, s2, force_ascii=True, full_process=True):\n return _token_set(s1, s2, partial=True, force_ascii=force_ascii, full_process=full_process)\n\n\n###################\n# Combination API #\n###################\n\n# q is for quick\ndef QRatio(s1, s2, force_ascii=True, full_process=True):\n \"\"\"\n Quick ratio comparison between two strings.\n\n Runs full_process from utils on both strings\n Short circuits if either of the strings is empty after processing.\n\n :param s1:\n :param s2:\n :param force_ascii: Allow only ASCII characters (Default: True)\n :full_process: Process inputs, used here to avoid double processing in extract functions (Default: True)\n :return: similarity ratio\n \"\"\"\n\n if full_process:\n p1 = utils.full_process(s1, force_ascii=force_ascii)\n p2 = utils.full_process(s2, force_ascii=force_ascii)\n else:\n p1 = s1\n p2 = s2\n\n if not utils.validate_string(p1):\n return 0\n if not utils.validate_string(p2):\n return 0\n\n return ratio(p1, p2)\n\n\ndef UQRatio(s1, s2, full_process=True):\n \"\"\"\n Unicode quick ratio\n\n Calls QRatio with force_ascii set to False\n\n :param s1:\n :param s2:\n :return: similarity ratio\n \"\"\"\n return QRatio(s1, s2, force_ascii=False, full_process=full_process)\n\n\n# w is for weighted\ndef WRatio(s1, s2, force_ascii=True, full_process=True):\n \"\"\"\n Return a measure of the sequences' similarity between 0 and 100, using different algorithms.\n\n **Steps in the order they occur**\n\n #. Run full_process from utils on both strings\n #. Short circuit if this makes either string empty\n #. Take the ratio of the two processed strings (fuzz.ratio)\n #. Run checks to compare the length of the strings\n * If one of the strings is more than 1.5 times as long as the other\n use partial_ratio comparisons - scale partial results by 0.9\n (this makes sure only full results can return 100)\n * If one of the strings is over 8 times as long as the other\n instead scale by 0.6\n\n #. Run the other ratio functions\n * if using partial ratio functions call partial_ratio,\n partial_token_sort_ratio and partial_token_set_ratio\n scale all of these by the ratio based on length\n * otherwise call token_sort_ratio and token_set_ratio\n * all token based comparisons are scaled by 0.95\n (on top of any partial scalars)\n\n #. Take the highest value from these results\n round it and return it as an integer.\n\n :param s1:\n :param s2:\n :param force_ascii: Allow only ascii characters\n :type force_ascii: bool\n :full_process: Process inputs, used here to avoid double processing in extract functions (Default: True)\n :return:\n \"\"\"\n\n if full_process:\n p1 = utils.full_process(s1, force_ascii=force_ascii)\n p2 = utils.full_process(s2, force_ascii=force_ascii)\n else:\n p1 = s1\n p2 = s2\n\n if not utils.validate_string(p1):\n return 0\n if not utils.validate_string(p2):\n return 0\n\n # should we look at partials?\n try_partial = True\n unbase_scale = .95\n partial_scale = .90\n\n base = ratio(p1, p2)\n len_ratio = float(max(len(p1), len(p2))) / min(len(p1), len(p2))\n\n # if strings are similar length, don't use partials\n if len_ratio < 1.5:\n try_partial = False\n\n # if one string is much much shorter than the other\n if len_ratio > 8:\n partial_scale = .6\n\n if try_partial:\n partial = partial_ratio(p1, p2) * partial_scale\n ptsor = partial_token_sort_ratio(p1, p2, full_process=False) \\\n * unbase_scale * partial_scale\n ptser = partial_token_set_ratio(p1, p2, full_process=False) \\\n * unbase_scale * partial_scale\n\n return utils.intr(max(base, partial, ptsor, ptser))\n else:\n tsor = token_sort_ratio(p1, p2, full_process=False) * unbase_scale\n tser = token_set_ratio(p1, p2, full_process=False) * unbase_scale\n\n return utils.intr(max(base, tsor, tser))\n\n\ndef UWRatio(s1, s2, full_process=True):\n \"\"\"Return a measure of the sequences' similarity between 0 and 100,\n using different algorithms. Same as WRatio but preserving unicode.\n \"\"\"\n return WRatio(s1, s2, force_ascii=False, full_process=full_process)\n" }, { "path": "data/thefuzz/thefuzz/fuzz.pyi", "content": "def ratio(s1: str, s2: str) -> int: ...\ndef partial_ratio(s1: str, s2: str) -> int: ...\ndef _process_and_sort(s: str, force_ascii: bool, full_process: bool = ...) -> str: ...\ndef _token_sort(s1: str, s2: str, partial: bool = ..., force_ascii: bool = ..., full_process: bool = ...) -> int: ...\ndef token_sort_ratio(s1: str, s2: str, force_ascii: bool = ..., full_process: bool = ...) -> int: ...\ndef partial_token_sort_ratio(s1: str, s2: str, force_ascii: bool = ..., full_process: bool = ...) -> int: ...\ndef _token_set(s1: str, s2: str, partial: bool = ..., force_ascii: bool = ..., full_process: bool = ...) -> int: ...\ndef token_set_ratio(s1: str, s2: str, force_ascii: bool = ..., full_process: bool = ...) -> int: ...\ndef partial_token_set_ratio(s1: str, s2: str, force_ascii: bool = ..., full_process: bool = ...) -> int: ...\ndef QRatio(s1: str, s2: str, force_ascii: bool = ..., full_process: bool = ...) -> int: ...\ndef UQRatio(s1: str, s2: str, full_process: bool = ...) -> int: ...\ndef WRatio(s1: str, s2: str, force_ascii: bool = ..., full_process: bool = ...) -> int: ...\ndef UWRatio(s1: str, s2: str, full_process: bool = ...) -> int: ...\n" }, { "path": "data/thefuzz/thefuzz/process.py", "content": "#!/usr/bin/env python\nfrom . import fuzz\nfrom . import utils\nimport heapq\nimport logging\nfrom functools import partial\n\n\n_logger = logging.getLogger(__name__)\n\n\ndefault_scorer = fuzz.WRatio\n\n\ndefault_processor = utils.full_process\n\n\ndef extractWithoutOrder(query, choices, processor=default_processor, scorer=default_scorer, score_cutoff=0):\n \"\"\"Select the best match in a list or dictionary of choices.\n\n Find best matches in a list or dictionary of choices, return a\n generator of tuples containing the match and its score. If a dictionary\n is used, also returns the key for each match.\n\n Arguments:\n query: An object representing the thing we want to find.\n choices: An iterable or dictionary-like object containing choices\n to be matched against the query. Dictionary arguments of\n {key: value} pairs will attempt to match the query against\n each value.\n processor: Optional function of the form f(a) -> b, where a is the query or\n individual choice and b is the choice to be used in matching.\n\n This can be used to match against, say, the first element of\n a list:\n\n lambda x: x[0]\n\n Defaults to thefuzz.utils.full_process().\n scorer: Optional function for scoring matches between the query and\n an individual processed choice. This should be a function\n of the form f(query, choice) -> int.\n\n By default, fuzz.WRatio() is used and expects both query and\n choice to be strings.\n score_cutoff: Optional argument for score threshold. No matches with\n a score less than this number will be returned. Defaults to 0.\n\n Returns:\n Generator of tuples containing the match and its score.\n\n If a list is used for choices, then the result will be 2-tuples.\n If a dictionary is used, then the result will be 3-tuples containing\n the key for each match.\n\n For example, searching for 'bird' in the dictionary\n\n {'bard': 'train', 'dog': 'man'}\n\n may return\n\n ('train', 22, 'bard'), ('man', 0, 'dog')\n \"\"\"\n # Catch generators without lengths\n def no_process(x):\n return x\n\n try:\n if choices is None or len(choices) == 0:\n return\n except TypeError:\n pass\n\n # If the processor was removed by setting it to None\n # perform a noop as it still needs to be a function\n if processor is None:\n processor = no_process\n\n # Run the processor on the input query.\n processed_query = processor(query)\n\n if len(processed_query) == 0:\n _logger.warning(\"Applied processor reduces input query to empty string, \"\n \"all comparisons will have score 0. \"\n f\"[Query: \\'{query}\\']\")\n\n # Don't run full_process twice\n if scorer in [fuzz.WRatio, fuzz.QRatio,\n fuzz.token_set_ratio, fuzz.token_sort_ratio,\n fuzz.partial_token_set_ratio, fuzz.partial_token_sort_ratio,\n fuzz.UWRatio, fuzz.UQRatio] \\\n and processor == utils.full_process:\n processor = no_process\n\n # Only process the query once instead of for every choice\n if scorer in [fuzz.UWRatio, fuzz.UQRatio]:\n pre_processor = partial(utils.full_process, force_ascii=False)\n scorer = partial(scorer, full_process=False)\n elif scorer in [fuzz.WRatio, fuzz.QRatio,\n fuzz.token_set_ratio, fuzz.token_sort_ratio,\n fuzz.partial_token_set_ratio, fuzz.partial_token_sort_ratio]:\n pre_processor = partial(utils.full_process, force_ascii=True)\n scorer = partial(scorer, full_process=False)\n else:\n pre_processor = no_process\n processed_query = pre_processor(processed_query)\n\n try:\n # See if choices is a dictionary-like object.\n for key, choice in choices.items():\n processed = pre_processor(processor(choice))\n score = scorer(processed_query, processed)\n if score >= score_cutoff:\n yield (choice, score, key)\n except AttributeError:\n # It's a list; just iterate over it.\n for choice in choices:\n processed = pre_processor(processor(choice))\n score = scorer(processed_query, processed)\n if score >= score_cutoff:\n yield (choice, score)\n\n\ndef extract(query, choices, processor=default_processor, scorer=default_scorer, limit=5):\n \"\"\"Select the best match in a list or dictionary of choices.\n\n Find best matches in a list or dictionary of choices, return a\n list of tuples containing the match and its score. If a dictionary\n is used, also returns the key for each match.\n\n Arguments:\n query: An object representing the thing we want to find.\n choices: An iterable or dictionary-like object containing choices\n to be matched against the query. Dictionary arguments of\n {key: value} pairs will attempt to match the query against\n each value.\n processor: Optional function of the form f(a) -> b, where a is the query or\n individual choice and b is the choice to be used in matching.\n\n This can be used to match against, say, the first element of\n a list:\n\n lambda x: x[0]\n\n Defaults to thefuzz.utils.full_process().\n scorer: Optional function for scoring matches between the query and\n an individual processed choice. This should be a function\n of the form f(query, choice) -> int.\n By default, fuzz.WRatio() is used and expects both query and\n choice to be strings.\n limit: Optional maximum for the number of elements returned. Defaults\n to 5.\n\n Returns:\n List of tuples containing the match and its score.\n\n If a list is used for choices, then the result will be 2-tuples.\n If a dictionary is used, then the result will be 3-tuples containing\n the key for each match.\n\n For example, searching for 'bird' in the dictionary\n\n {'bard': 'train', 'dog': 'man'}\n\n may return\n\n [('train', 22, 'bard'), ('man', 0, 'dog')]\n \"\"\"\n sl = extractWithoutOrder(query, choices, processor, scorer)\n return heapq.nlargest(limit, sl, key=lambda i: i[1]) if limit is not None else \\\n sorted(sl, key=lambda i: i[1], reverse=True)\n\n\ndef extractBests(query, choices, processor=default_processor, scorer=default_scorer, score_cutoff=0, limit=5):\n \"\"\"Get a list of the best matches to a collection of choices.\n\n Convenience function for getting the choices with best scores.\n\n Args:\n query: A string to match against\n choices: A list or dictionary of choices, suitable for use with\n extract().\n processor: Optional function for transforming choices before matching.\n See extract().\n scorer: Scoring function for extract().\n score_cutoff: Optional argument for score threshold. No matches with\n a score less than this number will be returned. Defaults to 0.\n limit: Optional maximum for the number of elements returned. Defaults\n to 5.\n\n Returns: A a list of (match, score) tuples.\n \"\"\"\n\n best_list = extractWithoutOrder(query, choices, processor, scorer, score_cutoff)\n return heapq.nlargest(limit, best_list, key=lambda i: i[1]) if limit is not None else \\\n sorted(best_list, key=lambda i: i[1], reverse=True)\n\n\ndef extractOne(query, choices, processor=default_processor, scorer=default_scorer, score_cutoff=0):\n \"\"\"Find the single best match above a score in a list of choices.\n\n This is a convenience method which returns the single best choice.\n See extract() for the full arguments list.\n\n Args:\n query: A string to match against\n choices: A list or dictionary of choices, suitable for use with\n extract().\n processor: Optional function for transforming choices before matching.\n See extract().\n scorer: Scoring function for extract().\n score_cutoff: Optional argument for score threshold. If the best\n match is found, but it is not greater than this number, then\n return None anyway (\"not a good enough match\"). Defaults to 0.\n\n Returns:\n A tuple containing a single match and its score, if a match\n was found that was above score_cutoff. Otherwise, returns None.\n \"\"\"\n best_list = extractWithoutOrder(query, choices, processor, scorer, score_cutoff)\n try:\n return max(best_list, key=lambda i: i[1])\n except ValueError:\n return None\n\n\ndef dedupe(contains_dupes, threshold=70, scorer=fuzz.token_set_ratio):\n \"\"\"This convenience function takes a list of strings containing duplicates and uses fuzzy matching to identify\n and remove duplicates. Specifically, it uses the process.extract to identify duplicates that\n score greater than a user defined threshold. Then, it looks for the longest item in the duplicate list\n since we assume this item contains the most entity information and returns that. It breaks string\n length ties on an alphabetical sort.\n\n Note: as the threshold DECREASES the number of duplicates that are found INCREASES. This means that the\n returned deduplicated list will likely be shorter. Raise the threshold for fuzzy_dedupe to be less\n sensitive.\n\n Args:\n contains_dupes: A list of strings that we would like to dedupe.\n threshold: the numerical value (0,100) point at which we expect to find duplicates.\n Defaults to 70 out of 100\n scorer: Optional function for scoring matches between the query and\n an individual processed choice. This should be a function\n of the form f(query, choice) -> int.\n By default, fuzz.token_set_ratio() is used and expects both query and\n choice to be strings.\n\n Returns:\n A deduplicated list. For example:\n\n In: contains_dupes = ['Frodo Baggin', 'Frodo Baggins', 'F. Baggins', 'Samwise G.', 'Gandalf', 'Bilbo Baggins']\n In: fuzzy_dedupe(contains_dupes)\n Out: ['Frodo Baggins', 'Samwise G.', 'Bilbo Baggins', 'Gandalf']\n \"\"\"\n\n extractor = []\n\n # iterate over items in *contains_dupes*\n for item in contains_dupes:\n # return all duplicate matches found\n matches = extract(item, contains_dupes, limit=None, scorer=scorer)\n # filter matches based on the threshold\n filtered = [x for x in matches if x[1] > threshold]\n # if there is only 1 item in *filtered*, no duplicates were found so append to *extracted*\n if len(filtered) == 1:\n extractor.append(filtered[0][0])\n\n else:\n # alpha sort\n filtered = sorted(filtered, key=lambda x: x[0])\n # length sort\n filter_sort = sorted(filtered, key=lambda x: len(x[0]), reverse=True)\n # take first item as our 'canonical example'\n extractor.append(filter_sort[0][0])\n\n # uniquify *extractor* list\n keys = {}\n for e in extractor:\n keys[e] = 1\n extractor = keys.keys()\n\n # check that extractor differs from contain_dupes (e.g. duplicates were found)\n # if not, then return the original list\n if len(extractor) == len(contains_dupes):\n return contains_dupes\n else:\n return extractor\n" }, { "path": "data/thefuzz/thefuzz/process.pyi", "content": "from collections.abc import Mapping\nimport typing\nfrom typing import Any, Callable, Union, Tuple, Generator, TypeVar, Sequence\n\n\nChoicesT = Union[Mapping[str, str], Sequence[str]]\nT = TypeVar('T')\nProcessorT = Union[Callable[[str, bool], str], Callable[[Any], Any]]\nScorerT = Callable[[str, str, bool, bool], int]\n\n\n@typing.overload\ndef extractWithoutOrder(query: str, choices: Mapping[str, str], processor: ProcessorT, scorer: ScorerT, score_cutoff: int = ...) -> Generator[Tuple[str, int, str], None, None]: ...\n\n\n@typing.overload\ndef extractWithoutOrder(query: str, choices: Sequence[str], processor: ProcessorT, scorer: ScorerT, score_cutoff: int = ...) -> Generator[Tuple[str, int], None, None]: ...\n" }, { "path": "data/thefuzz/thefuzz/string_processing.py", "content": "import re\n\n\nclass StringProcessor:\n \"\"\"\n This class defines method to process strings in the most\n efficient way. Ideally all the methods below use unicode strings\n for both input and output.\n \"\"\"\n\n regex = re.compile(r\"(?ui)\\W\")\n\n @classmethod\n def replace_non_letters_non_numbers_with_whitespace(cls, a_string):\n \"\"\"\n This function replaces any sequence of non letters and non\n numbers with a single white space.\n \"\"\"\n return cls.regex.sub(\" \", a_string)\n" }, { "path": "data/thefuzz/thefuzz/string_processing.pyi", "content": "class StringProcessor(object):\n @classmethod\n def replace_non_letters_non_numbers_with_whitespace(cls, a_string: str) -> str: ...\n" }, { "path": "data/thefuzz/thefuzz/utils.py", "content": "import functools\n\nfrom thefuzz.string_processing import StringProcessor\n\n\ndef validate_string(s):\n \"\"\"\n Check input has length and that length > 0\n\n :param s:\n :return: True if len(s) > 0 else False\n \"\"\"\n try:\n return len(s) > 0\n except TypeError:\n return False\n\n\ndef check_for_equivalence(func):\n @functools.wraps(func)\n def decorator(*args, **kwargs):\n if args[0] == args[1]:\n return 100\n return func(*args, **kwargs)\n return decorator\n\n\ndef check_for_none(func):\n @functools.wraps(func)\n def decorator(*args, **kwargs):\n if args[0] is None or args[1] is None:\n return 0\n return func(*args, **kwargs)\n return decorator\n\n\ndef check_empty_string(func):\n @functools.wraps(func)\n def decorator(*args, **kwargs):\n if len(args[0]) == 0 or len(args[1]) == 0:\n return 0\n return func(*args, **kwargs)\n return decorator\n\n\nbad_chars = \"\".join([chr(i) for i in range(128, 256)]) # ascii dammit!\ntranslation_table = {ord(c): None for c in bad_chars}\n\n\ndef ascii_only(s):\n return s.translate(translation_table)\n\n\ndef make_type_consistent(s1, s2):\n \"\"\"If objects aren't both string instances force them to strings\"\"\"\n if isinstance(s1, str) and isinstance(s2, str):\n return s1, s2\n\n else:\n return str(s1), str(s2)\n\n\ndef full_process(s, force_ascii=False):\n \"\"\"Process string by\n -- removing all but letters and numbers\n -- trim whitespace\n -- force to lower case\n if force_ascii == True, force convert to ascii\"\"\"\n\n if force_ascii:\n s = ascii_only(str(s))\n # Keep only Letters and Numbers (see Unicode docs).\n string_out = StringProcessor.replace_non_letters_non_numbers_with_whitespace(s)\n # Remove leading and trailing whitespaces and force into lowercase.\n string_out = string_out.strip().lower()\n return string_out\n\n\ndef intr(n):\n '''Returns a correctly rounded integer'''\n return int(round(n))\n" }, { "path": "data/thefuzz/thefuzz/utils.pyi", "content": "from typing import Any, Tuple, Union, Callable, TypeVar\n\nTCallable = TypeVar(\"TCallable\", bound=Callable[..., Any])\n\n\ndef validate_string(s: str) -> bool: ...\ndef check_for_equivalence(func: TCallable) -> TCallable: ...\ndef check_for_none(func: TCallable) -> TCallable: ...\ndef check_empty_string(func: TCallable) -> TCallable: ...\ndef asciionly(s: str) -> str: ...\ndef asciidammit(s: Union[str, bytes]) -> str: ...\ndef make_type_consistent(s1: str, s2: str) -> Tuple[str, str]: ...\ndef full_process(s: str, force_ascii: bool = ...) -> str: ...\ndef intr(n: float) -> int: ...\n" }, { "path": "data/thefuzz/tox.ini", "content": "[tox]\nenvlist = py{37, 38, 39, 310, 311, py3}\nskip_missing_interpreters = True\n\n[testenv]\ndeps = pytest\n pycodestyle\n hypothesis\ncommands = pytest\n" }, { "path": "data_generation/5 Levels Of Summarization - Novice To Expert.ipynb", "content": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"id\": \"fded102b\",\n \"metadata\": {},\n \"source\": [\n \"# 5 Levels Of Summarization: Novice to Expert\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"fab8b2cf\",\n \"metadata\": {},\n \"source\": [\n \"Summarization is a fundamental building block of many LLM tasks. You'll frequently run into use cases where you would like to distill a large body of text into a succinct set of points.\\n\",\n \"\\n\",\n \"Depending on the length of the text you'd like to summarize, you have different summarization methods to choose from.\\n\",\n \"\\n\",\n \"We're going to run through 5 methods for summarization that start with Novice and end up expert. These aren't the only options, feel free to make up your own. If you find another one you like please share it with the community.\\n\",\n \"\\n\",\n \"**5 Levels Of Summarization:**\\n\",\n \"1. **Summarize a couple sentences** - Basic Prompt\\n\",\n \"2. **Summarize a couple paragraphs** - Prompt Templates\\n\",\n \"3. **Summarize a couple pages** - Map Reduce\\n\",\n \"4. **Summarize an entire book** - Best Representation Vectors\\n\",\n \"5. **Summarize an unknown amount of text** - Agents\\n\",\n \"\\n\",\n \"First let's import our OpenAI API Key\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 1,\n \"id\": \"4033ee5a\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from dotenv import load_dotenv\\n\",\n \"import os\\n\",\n \"\\n\",\n \"load_dotenv()\\n\",\n \"\\n\",\n \"openai_api_key = os.getenv('OPENAI_API_KEY', 'YourAPIKey')\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"342796d0\",\n \"metadata\": {},\n \"source\": [\n \"## Level 1: Basic Prompt - Summarize a couple sentences\\n\",\n \"\\n\",\n \"If you just have a few sentences you want to one-off summarize you can use a simple prompt and copy and paste your text.\\n\",\n \"\\n\",\n \"This method isn't scalable and only practical for a few use cases...the perfect level #1!\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 2,\n \"id\": \"8a6ea241\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain import OpenAI\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 3,\n \"id\": \"538ded7c\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"llm = OpenAI(temperature=0, openai_api_key=openai_api_key)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"b18ca4b1\",\n \"metadata\": {},\n \"source\": [\n \"The important part is to provide instructions for the LLM to know what to do. In thise case I'm telling the model I want a summary of the text below\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 4,\n \"id\": \"67146e99\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"prompt = \\\"\\\"\\\"\\n\",\n \"Please provide a summary of the following text\\n\",\n \"\\n\",\n \"TEXT:\\n\",\n \"Philosophy (from Greek: φιλοσοφία, philosophia, 'love of wisdom') \\\\\\n\",\n \"is the systematized study of general and fundamental questions, \\\\\\n\",\n \"such as those about existence, reason, knowledge, values, mind, and language. \\\\\\n\",\n \"Some sources claim the term was coined by Pythagoras (c. 570 – c. 495 BCE), \\\\\\n\",\n \"although this theory is disputed by some. Philosophical methods include questioning, \\\\\\n\",\n \"critical discussion, rational argument, and systematic presentation.\\n\",\n \"\\\"\\\"\\\"\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 5,\n \"id\": \"c3bd4858\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"Our prompt has 121 tokens\\n\"\n ]\n }\n ],\n \"source\": [\n \"num_tokens = llm.get_num_tokens(prompt)\\n\",\n \"print (f\\\"Our prompt has {num_tokens} tokens\\\")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 6,\n \"id\": \"61522722\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"\\n\",\n \"Philosophy is a systematized study of general and fundamental questions about existence, reason, knowledge, values, mind, and language. It is believed to have been coined by Pythagoras, and its methods include questioning, critical discussion, rational argument, and systematic presentation.\\n\"\n ]\n }\n ],\n \"source\": [\n \"output = llm(prompt)\\n\",\n \"print (output)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"133d1b40\",\n \"metadata\": {},\n \"source\": [\n \"Woof 🐶, that summary is still hard to understand. Let me add to my instructions so that the output is easier to understand. I'll tell it to explain it to me like a 5 year old.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 7,\n \"id\": \"ece0c069\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"prompt = \\\"\\\"\\\"\\n\",\n \"Please provide a summary of the following text.\\n\",\n \"Please provide your output in a manner that a 5 year old would understand\\n\",\n \"\\n\",\n \"TEXT:\\n\",\n \"Philosophy (from Greek: φιλοσοφία, philosophia, 'love of wisdom') \\\\\\n\",\n \"is the systematized study of general and fundamental questions, \\\\\\n\",\n \"such as those about existence, reason, knowledge, values, mind, and language. \\\\\\n\",\n \"Some sources claim the term was coined by Pythagoras (c. 570 – c. 495 BCE), \\\\\\n\",\n \"although this theory is disputed by some. Philosophical methods include questioning, \\\\\\n\",\n \"critical discussion, rational argument, and systematic presentation.\\n\",\n \"\\\"\\\"\\\"\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 8,\n \"id\": \"5b66351e\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"Our prompt has 137 tokens\\n\"\n ]\n }\n ],\n \"source\": [\n \"num_tokens = llm.get_num_tokens(prompt)\\n\",\n \"print (f\\\"Our prompt has {num_tokens} tokens\\\")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 9,\n \"id\": \"68f9b501\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"\\n\",\n \"Philosophy is about asking questions and trying to figure out the answers. It is about thinking about things like existence, knowledge, and values. People have been doing this for a very long time, and it is still done today.\\n\"\n ]\n }\n ],\n \"source\": [\n \"output = llm(prompt)\\n\",\n \"print (output)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"6f294999\",\n \"metadata\": {},\n \"source\": [\n \"Nice! That's much better, but let's look at something we can automate a bit more\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"13f1cf66\",\n \"metadata\": {},\n \"source\": [\n \"## Level 2: Prompt Templates - Summarize a couple paragraphs\\n\",\n \"\\n\",\n \"Prompt templates are a great way to dynamically place text within your prompts. They are like [python f-strings](https://realpython.com/python-f-strings/) but specialized for working with language models.\\n\",\n \"\\n\",\n \"We're going to look at 2 short Paul Graham essays\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 10,\n \"id\": \"712acb03\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain import OpenAI\\n\",\n \"from langchain import PromptTemplate\\n\",\n \"import os\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 11,\n \"id\": \"b326aaeb\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"paul_graham_essays = ['../data/PaulGrahamEssaySmall/getideas.txt', '../data/PaulGrahamEssaySmall/noob.txt']\\n\",\n \"\\n\",\n \"essays = []\\n\",\n \"\\n\",\n \"for file_name in paul_graham_essays:\\n\",\n \" with open(file_name, 'r') as file:\\n\",\n \" essays.append(file.read())\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"529ad7c1\",\n \"metadata\": {},\n \"source\": [\n \"Let's print out a preview of the essays to see what they look like\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 12,\n \"id\": \"d7d93873\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"Essay #1: January 2023(Someone fed my essays into GPT to make something that could answer\\n\",\n \"questions based on them, then asked it where good ideas come from. The\\n\",\n \"answer was ok, but not what I would have said. This is what I would have said.)The way to get new ideas is to notice anomalies: what seems strange,\\n\",\n \"\\n\",\n \"\\n\",\n \"Essay #2: January 2020When I was young, I thought old people had everything figured out.\\n\",\n \"Now that I'm old, I know this isn't true.I constantly feel like a noob. It seems like I'm always talking to\\n\",\n \"some startup working in a new field I know nothing about, or reading\\n\",\n \"a book about a topic I don't understand well\\n\",\n \"\\n\"\n ]\n }\n ],\n \"source\": [\n \"for i, essay in enumerate(essays):\\n\",\n \" print (f\\\"Essay #{i+1}: {essay[:300]}\\\\n\\\")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"8e70a48e\",\n \"metadata\": {},\n \"source\": [\n \"Next let's create a prompt template which will hold our instructions and a placeholder for the essay. In this example I only want a 1 sentence summary to come back\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 13,\n \"id\": \"946c379a\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"template = \\\"\\\"\\\"\\n\",\n \"Please write a one sentence summary of the following text:\\n\",\n \"\\n\",\n \"{essay}\\n\",\n \"\\\"\\\"\\\"\\n\",\n \"\\n\",\n \"prompt = PromptTemplate(\\n\",\n \" input_variables=[\\\"essay\\\"],\\n\",\n \" template=template\\n\",\n \")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"51b2611b\",\n \"metadata\": {},\n \"source\": [\n \"Then let's loop through the 2 essays and pass them to our LLM. I'm applying .strip() on the summaries to remove the white space on the front and back of the output\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 14,\n \"id\": \"f2038feb\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"This prompt + essay has 205 tokens\\n\",\n \"Summary: Exploring anomalies at the frontiers of knowledge is the best way to generate new ideas.\\n\",\n \"\\n\",\n \"\\n\",\n \"This prompt + essay has 500 tokens\\n\",\n \"Summary: This text explores the idea that feeling like a \\\"noob\\\" is actually beneficial, as it is inversely correlated with actual ignorance and encourages us to discover new things.\\n\",\n \"\\n\",\n \"\\n\"\n ]\n }\n ],\n \"source\": [\n \"for essay in essays:\\n\",\n \" summary_prompt = prompt.format(essay=essay)\\n\",\n \" \\n\",\n \" num_tokens = llm.get_num_tokens(summary_prompt)\\n\",\n \" print (f\\\"This prompt + essay has {num_tokens} tokens\\\")\\n\",\n \" \\n\",\n \" summary = llm(summary_prompt)\\n\",\n \" \\n\",\n \" print (f\\\"Summary: {summary.strip()}\\\")\\n\",\n \" print (\\\"\\\\n\\\")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"49ae9a41\",\n \"metadata\": {},\n \"source\": [\n \"## Level 3: Map Reduce - Summarize a couple pages multiple pages\\n\",\n \"\\n\",\n \"If you have multiple pages you'd like to summarize, you'll likely run into a token limit. Token limits won't always be a problem, but it is good to know how to handle them if you run into the issue.\\n\",\n \"\\n\",\n \"The chain type \\\"Map Reduce\\\" is a method that helps with this. You first generate a summary of smaller chunks (that fit within the token limit) and then you get a summary of the summaries.\\\\\\n\",\n \"\\n\",\n \"Check out [this video](https://www.youtube.com/watch?v=f9_BWhCI4Zo) for more information on how chain types work\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 15,\n \"id\": \"c2ce6270\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain import OpenAI\\n\",\n \"from langchain.chains.summarize import load_summarize_chain\\n\",\n \"from langchain.text_splitter import RecursiveCharacterTextSplitter\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 16,\n \"id\": \"c70352ae\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"paul_graham_essay = '../data/PaulGrahamEssays/startupideas.txt'\\n\",\n \"\\n\",\n \"with open(paul_graham_essay, 'r') as file:\\n\",\n \" essay = file.read()\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"bb6de34d\",\n \"metadata\": {},\n \"source\": [\n \"Let's see how many tokens are in this essay\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 17,\n \"id\": \"b133938a\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"9565\"\n ]\n },\n \"execution_count\": 17,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"llm.get_num_tokens(essay)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"dc8ec39d\",\n \"metadata\": {},\n \"source\": [\n \"That's too many, let's split our text up into chunks so they fit into the prompt limit. I'm going a chunk size of 10,000 characters. \\n\",\n \"\\n\",\n \"> You can think of tokens as pieces of words used for natural language processing. For English text, **1 token is approximately 4 characters** or 0.75 words. As a point of reference, the collected works of Shakespeare are about 900,000 words or 1.2M tokens.\\n\",\n \"\\n\",\n \"This means the number of tokens we should expect is 10,000 / 4 = ~2,500 token chunks. But this will vary, each body of text/code will be different\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 18,\n \"id\": \"2e7c372b\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"text_splitter = RecursiveCharacterTextSplitter(separators=[\\\"\\\\n\\\\n\\\", \\\"\\\\n\\\"], chunk_size=10000, chunk_overlap=500)\\n\",\n \"\\n\",\n \"docs = text_splitter.create_documents([essay])\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 19,\n \"id\": \"f66569f0\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"Now we have 5 documents and the first one has 2086 tokens\\n\"\n ]\n }\n ],\n \"source\": [\n \"num_docs = len(docs)\\n\",\n \"\\n\",\n \"num_tokens_first_doc = llm.get_num_tokens(docs[0].page_content)\\n\",\n \"\\n\",\n \"print (f\\\"Now we have {num_docs} documents and the first one has {num_tokens_first_doc} tokens\\\")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"b61d49f5\",\n \"metadata\": {},\n \"source\": [\n \"Great, assuming that number of tokens is consistent in the other docs we should be good to go. Let's use LangChain's [load_summarize_chain](https://python.langchain.com/en/latest/use_cases/summarization.html) to do the `map_reducing` for us. We first need to initialize our chain\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 20,\n \"id\": \"b3b08c54\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"summary_chain = load_summarize_chain(llm=llm, chain_type='map_reduce',\\n\",\n \"# verbose=True # Set verbose=True if you want to see the prompts being used\\n\",\n \" )\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"78c45721\",\n \"metadata\": {},\n \"source\": [\n \"Now actually run it\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 21,\n \"id\": \"ba73121e\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"output = summary_chain.run(docs)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 22,\n \"id\": \"693acf9d\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"' This article provides strategies for coming up with startup ideas on demand, such as looking in areas of expertise, talking to people about their needs, and looking for waves and gaps in the market. It also discusses the need for users to have sufficient activation energy to start using a product, and how this varies depending on the product. It looks at the difficulty of switching paths in life as one gets older, and how colleges can help students start startups. Finally, it looks at the importance of focusing on users rather than competitors, and how Steve Wozniak solved his own problems.'\"\n ]\n },\n \"execution_count\": 22,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"output\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"3bc3a71e\",\n \"metadata\": {},\n \"source\": [\n \"This summary is a great start, but I'm more of a bullet point person. I want to get my final output in bullet point form.\\n\",\n \"\\n\",\n \"In order to do this I'm going to use custom promopts (like we did above) to instruct the model on what I want.\\n\",\n \"\\n\",\n \"The map_prompt is going to stay the same (just showing it for clarity), but I'll edit the combine_prompt.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 23,\n \"id\": \"7442e889\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"map_prompt = \\\"\\\"\\\"\\n\",\n \"Write a concise summary of the following:\\n\",\n \"\\\"{text}\\\"\\n\",\n \"CONCISE SUMMARY:\\n\",\n \"\\\"\\\"\\\"\\n\",\n \"map_prompt_template = PromptTemplate(template=map_prompt, input_variables=[\\\"text\\\"])\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 24,\n \"id\": \"6f42deb5\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"combine_prompt = \\\"\\\"\\\"\\n\",\n \"Write a concise summary of the following text delimited by triple backquotes.\\n\",\n \"Return your response in bullet points which covers the key points of the text.\\n\",\n \"```{text}```\\n\",\n \"BULLET POINT SUMMARY:\\n\",\n \"\\\"\\\"\\\"\\n\",\n \"combine_prompt_template = PromptTemplate(template=combine_prompt, input_variables=[\\\"text\\\"])\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 25,\n \"id\": \"e2051818\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"summary_chain = load_summarize_chain(llm=llm,\\n\",\n \" chain_type='map_reduce',\\n\",\n \" map_prompt=map_prompt_template,\\n\",\n \" combine_prompt=combine_prompt_template,\\n\",\n \"# verbose=True\\n\",\n \" )\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 26,\n \"id\": \"c986230f\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"output = summary_chain.run(docs)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 27,\n \"id\": \"e90a8582\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"- Y Combinator suggests that the best startup ideas come from looking for problems, preferably ones that the founders have themselves.\\n\",\n \"- Good ideas should appeal to a small number of people who need it urgently.\\n\",\n \"- To find startup ideas, one should look for things that seem to be missing and be prepared to question the status quo.\\n\",\n \"- College students should use their college experience to prepare themselves for the future and build things with other students.\\n\",\n \"- Tricks for coming up with startup ideas on demand include looking in areas of expertise, talking to people about their needs, and looking for waves and gaps in the market.\\n\",\n \"- Sam Altman points out that taking the time to come up with an idea is a better strategy than most founders are willing to put in the time for.\\n\",\n \"- Paul Buchheit suggests that trying to sell something bad can lead to better ideas.\\n\"\n ]\n }\n ],\n \"source\": [\n \"print (output)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"59a6da87\",\n \"metadata\": {},\n \"source\": [\n \"## Level 4: Best Representation Vectors - Summarize an entire book\\n\",\n \"\\n\",\n \"In the above method we pass the entire document (all 9.5K tokens of it) to the LLM. But what if you have more tokens than that?\\n\",\n \"\\n\",\n \"What if you had a book you wanted to summarize? Let's load one up, we're going to load [Into Thin Air](https://www.amazon.com/Into-Thin-Air-Personal-Disaster/dp/0385494785) about the 1996 Everest Disaster\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 28,\n \"id\": \"f6ed1dcb\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain.document_loaders import PyPDFLoader\\n\",\n \"\\n\",\n \"# Load the book\\n\",\n \"loader = PyPDFLoader(\\\"../data/IntoThinAirBook.pdf\\\")\\n\",\n \"pages = loader.load()\\n\",\n \"\\n\",\n \"# Cut out the open and closing parts\\n\",\n \"pages = pages[26:277]\\n\",\n \"\\n\",\n \"# Combine the pages, and replace the tabs with spaces\\n\",\n \"text = \\\"\\\"\\n\",\n \"\\n\",\n \"for page in pages:\\n\",\n \" text += page.page_content\\n\",\n \" \\n\",\n \"text = text.replace('\\\\t', ' ')\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 29,\n \"id\": \"6db88712\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"This book has 139472 tokens in it\\n\"\n ]\n }\n ],\n \"source\": [\n \"num_tokens = llm.get_num_tokens(text)\\n\",\n \"\\n\",\n \"print (f\\\"This book has {num_tokens} tokens in it\\\")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"4bedfe55\",\n \"metadata\": {},\n \"source\": [\n \"Wow, that's over 100K tokens, even [GPT 32K](https://help.openai.com/en/articles/7127966-what-is-the-difference-between-the-gpt-4-models) wouldn't be able to handle that in one go. At [0.03 per 1K prompt tokens](https://help.openai.com/en/articles/7127956-how-much-does-gpt-4-cost), this would cost us $4.17 just for the prompt alone.\\n\",\n \"\\n\",\n \"So how do we do this without going through all the tokens? Pick random chunks? Pick equally spaced chunks?\\n\",\n \"\\n\",\n \"I kicked off a [twitter thread](https://twitter.com/GregKamradt/status/1653060004226924544) with a proposed solution to see if I was off base. I'm calling it the Best Representation Vectors method (not sure if a name already exists for it).\\n\",\n \"\\n\",\n \"**Goal:** Chunk your book then get embeddings of the chunks. Pick a subset of chunks which represent a wholistic but diverse view of the book. Or another way, is there a way to pick the top 10 passages that describe the book the best?\\n\",\n \"\\n\",\n \"Once we have our chunks that represent the book then we can summarize those chunks and hopefully get a pretty good summary.\\n\",\n \"\\n\",\n \"Keep in mind there are tools that would likely do this for you, and with token limits increasing this won't be a problem for long. But if you want to do it from scratch this might help.\\n\",\n \"\\n\",\n \"This is most definitely not the optimal answer, but it's my take on it for now! If the [clustering](https://scikit-learn.org/stable/modules/clustering.html) experts wanna help improve it that would be awesome.\\n\",\n \"\\n\",\n \"**The BRV Steps:**\\n\",\n \"1. Load your book into a single text file\\n\",\n \"2. Split your text into large-ish chunks\\n\",\n \"3. Embed your chunks to get vectors\\n\",\n \"4. Cluster the vectors to see which are similar to each other and likely talk about the same parts of the book\\n\",\n \"5. Pick embeddings that represent the cluster the most (method: closest to each cluster centroid)\\n\",\n \"6. Summarize the documents that these embeddings represent\\n\",\n \"\\n\",\n \"Another way to phrase this process, \\\"Which ~10 documents from this book represent most of the meaning? I want to build a summary off those.\\\"\\n\",\n \"\\n\",\n \"Note: There will be a bit of information loss, but show me a summary of a whole book that doesn't have information loss ;)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 30,\n \"id\": \"e0e930b3\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stderr\",\n \"output_type\": \"stream\",\n \"text\": [\n \"/Users/gregorykamradt/opt/anaconda3/lib/python3.9/site-packages/deeplake/util/check_latest_version.py:32: UserWarning: A newer version of deeplake (3.7.2) is available. It's recommended that you update to the latest version using `pip install -U deeplake`.\\n\",\n \" warnings.warn(\\n\"\n ]\n }\n ],\n \"source\": [\n \"# Loaders\\n\",\n \"from langchain.schema import Document\\n\",\n \"\\n\",\n \"# Splitters\\n\",\n \"from langchain.text_splitter import RecursiveCharacterTextSplitter\\n\",\n \"\\n\",\n \"# Model\\n\",\n \"from langchain.chat_models import ChatOpenAI\\n\",\n \"\\n\",\n \"# Embedding Support\\n\",\n \"from langchain.vectorstores import FAISS\\n\",\n \"from langchain.embeddings import OpenAIEmbeddings\\n\",\n \"\\n\",\n \"# Summarizer we'll use for Map Reduce\\n\",\n \"from langchain.chains.summarize import load_summarize_chain\\n\",\n \"\\n\",\n \"# Data Science\\n\",\n \"import numpy as np\\n\",\n \"from sklearn.cluster import KMeans\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"0e5cdbd2\",\n \"metadata\": {},\n \"source\": [\n \"I'm going to initialize two models, gpt-3.5 and gpt4. I'll use gpt 3.5 for the first set of summaries to reduce cost and then gpt4 for the final pass which should hopefully increase the quality.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 31,\n \"id\": \"0d3d233d\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"text_splitter = RecursiveCharacterTextSplitter(separators=[\\\"\\\\n\\\\n\\\", \\\"\\\\n\\\", \\\"\\\\t\\\"], chunk_size=10000, chunk_overlap=3000)\\n\",\n \"\\n\",\n \"docs = text_splitter.create_documents([text])\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 32,\n \"id\": \"c1c2c701\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"Now our book is split up into 78 documents\\n\"\n ]\n }\n ],\n \"source\": [\n \"num_documents = len(docs)\\n\",\n \"\\n\",\n \"print (f\\\"Now our book is split up into {num_documents} documents\\\")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"8d413b2d\",\n \"metadata\": {},\n \"source\": [\n \"Let's get our embeddings of those 78 documents\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 33,\n \"id\": \"898fc62c\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"embeddings = OpenAIEmbeddings(openai_api_key=openai_api_key)\\n\",\n \"\\n\",\n \"vectors = embeddings.embed_documents([x.page_content for x in docs])\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"726f6dee\",\n \"metadata\": {},\n \"source\": [\n \"Now let's cluster our embeddings. There are a ton of clustering algorithms you can chose from. Please try a few out to see what works best for you!\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"id\": \"55c8dce0\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# Assuming 'embeddings' is a list or array of 1536-dimensional embeddings\\n\",\n \"\\n\",\n \"# Choose the number of clusters, this can be adjusted based on the book's content.\\n\",\n \"# I played around and found ~10 was the best.\\n\",\n \"# Usually if you have 10 passages from a book you can tell what it's about\\n\",\n \"num_clusters = 11\\n\",\n \"\\n\",\n \"# Perform K-means clustering\\n\",\n \"kmeans = KMeans(n_clusters=num_clusters, random_state=42).fit(vectors)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"891d82cd\",\n \"metadata\": {},\n \"source\": [\n \"Here are the clusters that were found. It's interesting to see the progression of clusters throughout the book. This is expected because as the plot changes you'd expect different clusters to emerge due to different semantic meaning\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"id\": \"218dce05\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"kmeans.labels_\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"1d9ccd8b\",\n \"metadata\": {},\n \"source\": [\n \"This is sweet, but whenever you have a clustering exercise, it's hard *not* to graph them. Make sure you add colors.\\n\",\n \"\\n\",\n \"We also need to do dimensionality reduction to reduce the vectors from 1536 dimensions to 2 (this is sloppy data science but we are working towards the 80% solution)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"id\": \"95da2509\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from sklearn.manifold import TSNE\\n\",\n \"import matplotlib.pyplot as plt\\n\",\n \"\\n\",\n \"# Taking out the warnings\\n\",\n \"import warnings\\n\",\n \"from warnings import simplefilter\\n\",\n \"\\n\",\n \"# Filter out FutureWarnings\\n\",\n \"simplefilter(action='ignore', category=FutureWarning)\\n\",\n \"\\n\",\n \"# Perform t-SNE and reduce to 2 dimensions\\n\",\n \"tsne = TSNE(n_components=2, random_state=42)\\n\",\n \"reduced_data_tsne = tsne.fit_transform(vectors)\\n\",\n \"\\n\",\n \"# Plot the reduced data\\n\",\n \"plt.scatter(reduced_data_tsne[:, 0], reduced_data_tsne[:, 1], c=kmeans.labels_)\\n\",\n \"plt.xlabel('Dimension 1')\\n\",\n \"plt.ylabel('Dimension 2')\\n\",\n \"plt.title('Book Embeddings Clustered')\\n\",\n \"plt.show()\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"6aa4314b\",\n \"metadata\": {},\n \"source\": [\n \"Awesome, not perfect, but pretty good directionally. Now we need to get the vectors which are closest to the cluster centroids (the center).\\n\",\n \"\\n\",\n \"The function below is a quick way to do that (w/ help from ChatGPT)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"id\": \"55f2f664\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# Find the closest embeddings to the centroids\\n\",\n \"\\n\",\n \"# Create an empty list that will hold your closest points\\n\",\n \"closest_indices = []\\n\",\n \"\\n\",\n \"# Loop through the number of clusters you have\\n\",\n \"for i in range(num_clusters):\\n\",\n \" \\n\",\n \" # Get the list of distances from that particular cluster center\\n\",\n \" distances = np.linalg.norm(vectors - kmeans.cluster_centers_[i], axis=1)\\n\",\n \" \\n\",\n \" # Find the list position of the closest one (using argmin to find the smallest distance)\\n\",\n \" closest_index = np.argmin(distances)\\n\",\n \" \\n\",\n \" # Append that position to your closest indices list\\n\",\n \" closest_indices.append(closest_index)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"f5a44596\",\n \"metadata\": {},\n \"source\": [\n \"Now sort them (so the chunks are processed in order)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"id\": \"679297ac\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"selected_indices = sorted(closest_indices)\\n\",\n \"selected_indices\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"171c2b42\",\n \"metadata\": {},\n \"source\": [\n \"It's intersting to see which chunks pop up at most descriptive. How does your distribution look?\\n\",\n \"\\n\",\n \"Let's create our custom prompts. I'm going to use gpt4 (which has a bigger token limit) for the combine step so I'm asking for long summaries in the map step to reduce the information loss.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"id\": \"83bc55d8\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"llm3 = ChatOpenAI(temperature=0,\\n\",\n \" openai_api_key=openai_api_key,\\n\",\n \" max_tokens=1000,\\n\",\n \" model='gpt-3.5-turbo'\\n\",\n \" )\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"id\": \"5552e6d3\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"map_prompt = \\\"\\\"\\\"\\n\",\n \"You will be given a single passage of a book. This section will be enclosed in triple backticks (```)\\n\",\n \"Your goal is to give a summary of this section so that a reader will have a full understanding of what happened.\\n\",\n \"Your response should be at least three paragraphs and fully encompass what was said in the passage.\\n\",\n \"\\n\",\n \"```{text}```\\n\",\n \"FULL SUMMARY:\\n\",\n \"\\\"\\\"\\\"\\n\",\n \"map_prompt_template = PromptTemplate(template=map_prompt, input_variables=[\\\"text\\\"])\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"b568b94a\",\n \"metadata\": {},\n \"source\": [\n \"I kept getting a timeout errors so I'm actually going to do this map reduce manually\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"id\": \"bb5eb0d9\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"map_chain = load_summarize_chain(llm=llm3,\\n\",\n \" chain_type=\\\"stuff\\\",\\n\",\n \" prompt=map_prompt_template)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"e4e1ec38\",\n \"metadata\": {},\n \"source\": [\n \"Then go get your docs which the top vectors represented.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"id\": \"781a686c\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"selected_docs = [docs[doc] for doc in selected_indices]\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"eca5fc42\",\n \"metadata\": {},\n \"source\": [\n \"Let's loop through our selected docs and get a good summary for each chunk. We'll store the summary in a list.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"id\": \"7e2220ab\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# Make an empty list to hold your summaries\\n\",\n \"summary_list = []\\n\",\n \"\\n\",\n \"# Loop through a range of the lenght of your selected docs\\n\",\n \"for i, doc in enumerate(selected_docs):\\n\",\n \" \\n\",\n \" # Go get a summary of the chunk\\n\",\n \" chunk_summary = map_chain.run([doc])\\n\",\n \" \\n\",\n \" # Append that summary to your list\\n\",\n \" summary_list.append(chunk_summary)\\n\",\n \" \\n\",\n \" print (f\\\"Summary #{i} (chunk #{selected_indices[i]}) - Preview: {chunk_summary[:250]} \\\\n\\\")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"7fae1a72\",\n \"metadata\": {},\n \"source\": [\n \"Great, now that we have our list of summaries, let's get a summary of the summaries\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"id\": \"4083431d\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"summaries = \\\"\\\\n\\\".join(summary_list)\\n\",\n \"\\n\",\n \"# Convert it back to a document\\n\",\n \"summaries = Document(page_content=summaries)\\n\",\n \"\\n\",\n \"print (f\\\"Your total summary has {llm.get_num_tokens(summaries.page_content)} tokens\\\")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"id\": \"1d2e71c5\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"llm4 = ChatOpenAI(temperature=0,\\n\",\n \" openai_api_key=openai_api_key,\\n\",\n \" max_tokens=3000,\\n\",\n \" model='gpt-4',\\n\",\n \" request_timeout=120\\n\",\n \" )\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"id\": \"b98e7321\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"combine_prompt = \\\"\\\"\\\"\\n\",\n \"You will be given a series of summaries from a book. The summaries will be enclosed in triple backticks (```)\\n\",\n \"Your goal is to give a verbose summary of what happened in the story.\\n\",\n \"The reader should be able to grasp what happened in the book.\\n\",\n \"\\n\",\n \"```{text}```\\n\",\n \"VERBOSE SUMMARY:\\n\",\n \"\\\"\\\"\\\"\\n\",\n \"combine_prompt_template = PromptTemplate(template=combine_prompt, input_variables=[\\\"text\\\"])\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"id\": \"2930c26e\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"reduce_chain = load_summarize_chain(llm=llm4,\\n\",\n \" chain_type=\\\"stuff\\\",\\n\",\n \" prompt=combine_prompt_template,\\n\",\n \"# verbose=True # Set this to true if you want to see the inner workings\\n\",\n \" )\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"e9958142\",\n \"metadata\": {},\n \"source\": [\n \"Run! Note this will take a while\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"id\": \"c6eda913\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"output = reduce_chain.run([summaries])\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"id\": \"915628a1\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"print (output)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"27a1db73\",\n \"metadata\": {},\n \"source\": [\n \"Wow that was a long process, but you get the gist, hopefully we'll see some library abstractions in the coming months that do this automatically for us! Let me know what you think on [Twitter](https://twitter.com/GregKamradt)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"5b4ae429\",\n \"metadata\": {},\n \"source\": [\n \"## Level 5: Agents - Summarize an unknown amount of text\\n\",\n \"\\n\",\n \"What if you have an unknown amount of text you need to summarize? This may be a verticalize use case (like law or medical) where more research is required as you uncover the first pieces of information.\\n\",\n \"\\n\",\n \"We're going to use agents below, this is still a very actively developed area and should be handled with care. Future agents will be able to handle a lot more complicated tasks.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"id\": \"fd384fd2\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain import OpenAI\\n\",\n \"from langchain.chat_models import ChatOpenAI\\n\",\n \"from langchain.agents import initialize_agent, Tool\\n\",\n \"from langchain.utilities import WikipediaAPIWrapper\\n\",\n \"\\n\",\n \"llm = ChatOpenAI(temperature=0, model_name='gpt-4', openai_api_key=openai_api_key)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"6456e70a\",\n \"metadata\": {},\n \"source\": [\n \"We're going to use the Wiki search tool and research multiple topics\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"id\": \"6b93660c\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"wikipedia = WikipediaAPIWrapper()\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"b7d26c52\",\n \"metadata\": {},\n \"source\": [\n \"Let's define our toolkit, in this case it's just one tool\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"id\": \"aaf60c86\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"tools = [\\n\",\n \" Tool(\\n\",\n \" name=\\\"Wikipedia\\\",\\n\",\n \" func=wikipedia.run,\\n\",\n \" description=\\\"Useful for when you need to get information from wikipedia about a single topic\\\"\\n\",\n \" ),\\n\",\n \"]\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"9d0f07a5\",\n \"metadata\": {},\n \"source\": [\n \"Init our agent\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"id\": \"baff1fce\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"agent_executor = initialize_agent(tools, llm, agent='zero-shot-react-description', verbose=True)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"06d17afb\",\n \"metadata\": {},\n \"source\": [\n \"Then let's ask a question that will need multiple documents\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"id\": \"dbd6e437\",\n \"metadata\": {\n \"scrolled\": false\n },\n \"outputs\": [],\n \"source\": [\n \"output = agent_executor.run(\\\"Can you please provide a quick summary of Napoleon Bonaparte? \\\\\\n\",\n \" Then do a separate search and tell me what the commonalities are with Serena Williams\\\")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"id\": \"4e5aeeee\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"print (output)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"f48735b9\",\n \"metadata\": {},\n \"source\": [\n \"Awesome, good luck summarizing!\"\n ]\n }\n ],\n \"metadata\": {\n \"kernelspec\": {\n \"display_name\": \"Python 3 (ipykernel)\",\n \"language\": \"python\",\n \"name\": \"python3\"\n },\n \"language_info\": {\n \"codemirror_mode\": {\n \"name\": \"ipython\",\n \"version\": 3\n },\n \"file_extension\": \".py\",\n \"mimetype\": \"text/x-python\",\n \"name\": \"python\",\n \"nbconvert_exporter\": \"python\",\n \"pygments_lexer\": \"ipython3\",\n \"version\": \"3.9.13\"\n }\n },\n \"nbformat\": 4,\n \"nbformat_minor\": 5\n}\n" }, { "path": "data_generation/Advanced Retrieval With LangChain.ipynb", "content": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"id\": \"f4dbe2e3\",\n \"metadata\": {},\n \"source\": [\n \"# Advanced Retrieval With LangChain\\n\",\n \"\\n\",\n \"Let's go over a few more complex and advanced retrieval methods with LangChain.\\n\",\n \"\\n\",\n \"There is no one right way to retrieve data - it'll depend on your application so take some time to think about it before you jump in\\n\",\n \"\\n\",\n \"Let's have some fun\\n\",\n \"\\n\",\n \"* **Multi Query** - Given a single user query, use an LLM to synthetically generate multiple other queries. Use each one of the new queries to retrieve documents, take the union of those documents for the final context of your prompt\\n\",\n \"* **Contextual Compression** - Fluff remover. Normal retrieval but with an extra step of pulling out relevant information from each returned document. This makes each relevant document smaller for your final prompt (which increases information density)\\n\",\n \"* **Parent Document Retriever** - Split and embed *small* chunks (for maximum information density), then return the parent documents (or larger chunks) those small chunks come from\\n\",\n \"* **Ensemble Retriever** - Combine multiple retrievers together\\n\",\n \"* **Self-Query** - When the retriever infers filters from a users query and applies those filters to the underlying data\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 1,\n \"id\": \"dcf93b72\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from dotenv import load_dotenv\\n\",\n \"import os\\n\",\n \"\\n\",\n \"load_dotenv()\\n\",\n \"\\n\",\n \"openai_api_key=os.getenv('OPENAI_API_KEY', 'YourAPIKey')\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"50493ba9\",\n \"metadata\": {},\n \"source\": [\n \"## Load up our texts and documents\\n\",\n \"\\n\",\n \"Then chunk them, and put them into a vector store\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 2,\n \"id\": \"ff07d69b\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stderr\",\n \"output_type\": \"stream\",\n \"text\": [\n \"/Users/gregorykamradt/opt/anaconda3/lib/python3.9/site-packages/deeplake/util/check_latest_version.py:32: UserWarning: A newer version of deeplake (3.7.2) is available. It's recommended that you update to the latest version using `pip install -U deeplake`.\\n\",\n \" warnings.warn(\\n\"\n ]\n }\n ],\n \"source\": [\n \"from langchain.document_loaders import DirectoryLoader\\n\",\n \"from langchain.embeddings.openai import OpenAIEmbeddings\\n\",\n \"from langchain.text_splitter import RecursiveCharacterTextSplitter\\n\",\n \"from langchain.vectorstores import Chroma\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"d49749eb\",\n \"metadata\": {},\n \"source\": [\n \"We're going to load up Paul Graham's essays. In this repo there are various sizes of folders (`PaulGrahamEssaysSmall`, `PaulGrahamEssaysMedium`, `PaulGrahamEssaysLarge` or `PaulGrahamEssays` for the full set.)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 3,\n \"id\": \"ae08f45b\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stderr\",\n \"output_type\": \"stream\",\n \"text\": [\n \"100%|███████████████████████████████████████████| 49/49 [00:30<00:00, 1.62it/s]\\n\"\n ]\n }\n ],\n \"source\": [\n \"loader = DirectoryLoader('../data/PaulGrahamEssaysLarge/', glob=\\\"**/*.txt\\\", show_progress=True)\\n\",\n \"\\n\",\n \"docs = loader.load()\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 4,\n \"id\": \"8449d623\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"You have 49 essays loaded\\n\"\n ]\n }\n ],\n \"source\": [\n \"print (f\\\"You have {len(docs)} essays loaded\\\")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"e0ca003e\",\n \"metadata\": {},\n \"source\": [\n \"Then we'll split up our text into smaller sized chunks\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 5,\n \"id\": \"ddd71b36\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"Your 49 documents have been split into 471 chunks\\n\"\n ]\n }\n ],\n \"source\": [\n \"# Split\\n\",\n \"text_splitter = RecursiveCharacterTextSplitter(chunk_size=1500, chunk_overlap=0)\\n\",\n \"splits = text_splitter.split_documents(docs)\\n\",\n \"\\n\",\n \"print (f\\\"Your {len(docs)} documents have been split into {len(splits)} chunks\\\")\"\n ]\n },\n {\n \"cell_type\": \"raw\",\n \"id\": \"4fb96a95\",\n \"metadata\": {},\n \"source\": [\n \"If you do `Chroma.from_documents` multiple times you'll re-add the documents (and duplicate them) which is annoying. I check to see if we've already made our vectordb, if so delete what's in there, then go and make it\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 6,\n \"id\": \"7a37879f\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"if 'vectordb' in globals(): # If you've already made your vectordb this will delete it so you start fresh\\n\",\n \" vectordb.delete_collection()\\n\",\n \"\\n\",\n \"embedding = OpenAIEmbeddings()\\n\",\n \"vectordb = Chroma.from_documents(documents=splits, embedding=embedding)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"38be1d0e\",\n \"metadata\": {},\n \"source\": [\n \"### MultiQuery\\n\",\n \"\\n\",\n \"This retrieval method will generated 3 additional questions to get a total of 4 queries (with the users included) that will be used to go retrieve documents. This is helpful when you want to retrieve documents which are similar in meaning to your question.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 7,\n \"id\": \"fef59032\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain.chat_models import ChatOpenAI\\n\",\n \"from langchain.retrievers.multi_query import MultiQueryRetriever\\n\",\n \"from langchain.prompts import PromptTemplate\\n\",\n \"# Set logging for the queries\\n\",\n \"import logging\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"2adc71aa\",\n \"metadata\": {},\n \"source\": [\n \"Doing some logging to see the other questions that were generated. I tried to find a way to get these via a model property but couldn't, lmk if you find a way!\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 8,\n \"id\": \"ed315ac4\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"logging.basicConfig()\\n\",\n \"logging.getLogger(\\\"langchain.retrievers.multi_query\\\").setLevel(logging.INFO)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"bf0349ab\",\n \"metadata\": {},\n \"source\": [\n \"Then we set up the MultiQueryRetriever which will generate other questions for us\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 9,\n \"id\": \"4c9750dc\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"question = \\\"What is the authors view on the early stages of a startup?\\\"\\n\",\n \"llm = ChatOpenAI(temperature=0)\\n\",\n \"\\n\",\n \"retriever_from_llm = MultiQueryRetriever.from_llm(\\n\",\n \" retriever=vectordb.as_retriever(), llm=llm\\n\",\n \")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 10,\n \"id\": \"c7a55b41\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stderr\",\n \"output_type\": \"stream\",\n \"text\": [\n \"INFO:langchain.retrievers.multi_query:Generated queries: ['1. How does the author perceive the early stages of a startup?', \\\"2. What are the author's thoughts on the initial phases of a startup?\\\", \\\"3. What is the author's perspective on the beginning stages of a startup?\\\"]\\n\"\n ]\n }\n ],\n \"source\": [\n \"unique_docs = retriever_from_llm.get_relevant_documents(query=question)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"eec261df\",\n \"metadata\": {},\n \"source\": [\n \"Check out how there are other questions which are related to but slightly different than the question I asked.\\n\",\n \"\\n\",\n \"Let's see how many docs were actually returned\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 11,\n \"id\": \"afd3449d\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"8\"\n ]\n },\n \"execution_count\": 11,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"len(unique_docs)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"914570e9\",\n \"metadata\": {},\n \"source\": [\n \"Ok now let's put those docs into a prompt template which we'll use as context\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 12,\n \"id\": \"4669bc0e\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"prompt_template = \\\"\\\"\\\"Use the following pieces of context to answer the question at the end.\\n\",\n \"If you don't know the answer, just say that you don't know, don't try to make up an answer.\\n\",\n \"\\n\",\n \"{context}\\n\",\n \"\\n\",\n \"Question: {question}\\n\",\n \"Answer:\\\"\\\"\\\"\\n\",\n \"PROMPT = PromptTemplate(\\n\",\n \" template=prompt_template, input_variables=[\\\"context\\\", \\\"question\\\"]\\n\",\n \")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 13,\n \"id\": \"240b7b56\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"'The author believes that it is important for startups to release an early version of their product quickly and then improve it based on user feedback. They emphasize the importance of getting version 1 done fast and state that startups that are too slow to release often fail.'\"\n ]\n },\n \"execution_count\": 13,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"llm.predict(text=PROMPT.format_prompt(\\n\",\n \" context=unique_docs,\\n\",\n \" question=question\\n\",\n \").text)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"eff39008\",\n \"metadata\": {},\n \"source\": [\n \"### Contextual Compression\\n\",\n \"\\n\",\n \"Then we'll move onto contextual compression. This will take the chunk that you've made (above) and compress it's information down to the parts relevant to your query.\\n\",\n \"\\n\",\n \"Say that you have a chunk that has 3 topics within it, you only really care about one of them though, this compressor will look at your query, see that you only need one of the 3 topics, then extract & return that one topic.\\n\",\n \"\\n\",\n \"This one is a bit more expensive because each doc returned will get processed an additional time (to pull out the relevant data)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 14,\n \"id\": \"f1efc668\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain.retrievers import ContextualCompressionRetriever\\n\",\n \"from langchain.retrievers.document_compressors import LLMChainExtractor\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"9f073d1d\",\n \"metadata\": {},\n \"source\": [\n \"We first need to set up our compressor, it's cool that it's a separate object because that means you can use it elsewhere outside this retriever as well.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 15,\n \"id\": \"7eb5c6e5\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"llm = ChatOpenAI(temperature=0, model='gpt-4')\\n\",\n \"\\n\",\n \"compressor = LLMChainExtractor.from_llm(llm)\\n\",\n \"compression_retriever = ContextualCompressionRetriever(base_compressor=compressor,\\n\",\n \" base_retriever=vectordb.as_retriever())\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"fdc392b6\",\n \"metadata\": {},\n \"source\": [\n \"First, an example of compression. Below we have one of our splits that we made above\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 16,\n \"id\": \"1561a033\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"\\\"July 2006I've discovered a handy test for figuring out what you're addicted\\\\n\\\\nto. Imagine you were going to spend the weekend at a friend's house\\\\n\\\\non a little island off the coast of Maine. There are no shops on\\\\n\\\\nthe island and you won't be able to leave while you're there. Also,\\\\n\\\\nyou've never been to this house before, so you can't assume it will\\\\n\\\\nhave more than any house might.What, besides clothes and toiletries, do you make a point of packing?\\\\n\\\\nThat's what you're addicted to. For example, if you find yourself\\\\n\\\\npacking a bottle of vodka (just in case), you may want to stop and\\\\n\\\\nthink about that.For me the list is four things: books, earplugs, a notebook, and a\\\\n\\\\npen.There are other things I might bring if I thought of it, like music,\\\\n\\\\nor tea, but I can live without them. I'm not so addicted to caffeine\\\\n\\\\nthat I wouldn't risk the house not having any tea, just for a\\\\n\\\\nweekend.Quiet is another matter. I realize it seems a bit eccentric to\\\\n\\\\ntake earplugs on a trip to an island off the coast of Maine. If\\\\n\\\\nanywhere should be quiet, that should. But what if the person in\\\\n\\\\nthe next room snored? What if there was a kid playing basketball?\\\\n\\\\n(Thump, thump, thump... thump.) Why risk it? Earplugs are small.Sometimes I can think with noise. If I already have momentum on\\\\n\\\\nsome project, I can work in noisy places. I can edit an essay or\\\\n\\\\ndebug code in an airport. But airports are not so bad: most of the\\\\n\\\\nnoise is whitish. I couldn't work with the sound of a sitcom coming\\\"\"\n ]\n },\n \"execution_count\": 16,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"splits[0].page_content\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"ab86de32\",\n \"metadata\": {},\n \"source\": [\n \"Now we are going to pass a question to it and with that question we will compress the doc. The cool part is this doc will be contextually compressed, meaning the resulting file will only have the information relevant to the question.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 17,\n \"id\": \"40ebdfd6\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stderr\",\n \"output_type\": \"stream\",\n \"text\": [\n \"/Users/gregorykamradt/opt/anaconda3/lib/python3.9/site-packages/langchain/chains/llm.py:280: UserWarning: The predict_and_parse method is deprecated, instead pass an output parser directly to LLMChain.\\n\",\n \" warnings.warn(\\n\"\n ]\n },\n {\n \"data\": {\n \"text/plain\": [\n \"[Document(page_content=\\\"I've discovered a handy test for figuring out what you're addicted to. Imagine you were going to spend the weekend at a friend's house on a little island off the coast of Maine. There are no shops on the island and you won't be able to leave while you're there. Also, you've never been to this house before, so you can't assume it will have more than any house might.What, besides clothes and toiletries, do you make a point of packing? That's what you're addicted to.\\\", metadata={'source': '../data/PaulGrahamEssaysLarge/island.txt'})]\"\n ]\n },\n \"execution_count\": 17,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"compressor.compress_documents(documents=[splits[0]], query=\\\"test for what you like to do\\\")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"c95a4c1c\",\n \"metadata\": {},\n \"source\": [\n \"Great so we had a long document, now we have a shorter document with more dense information. Great for getting rid of the fluff. Let's try it out on our essays\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 18,\n \"id\": \"51c4daee\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"question = \\\"What is the authors view on the early stages of a startup?\\\"\\n\",\n \"compressed_docs = compression_retriever.get_relevant_documents(question)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 19,\n \"id\": \"83cb292f\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"4\\n\"\n ]\n },\n {\n \"data\": {\n \"text/plain\": [\n \"[Document(page_content='The thing I probably repeat most is this recipe for a startup: get\\\\n\\\\na version 1 out fast, then improve it based on users\\\\' reactions.By \\\"release early\\\" I don\\\\'t mean you should release something full\\\\n\\\\nof bugs, but that you should release something minimal. Users hate\\\\n\\\\nbugs, but they don\\\\'t seem to mind a minimal version 1, if there\\\\'s\\\\n\\\\nmore coming soon.There are several reasons it pays to get version 1 done fast. One\\\\n\\\\nis that this is simply the right way to write software, whether for\\\\n\\\\na startup or not. I\\\\'ve been repeating that since 1993, and I haven\\\\'t seen much since to\\\\n\\\\ncontradict it. I\\\\'ve seen a lot of startups die because they were\\\\n\\\\ntoo slow to release stuff, and none because they were too quick.', metadata={'source': '../data/PaulGrahamEssaysLarge/startuplessons.txt'}),\\n\",\n \" Document(page_content='\\\"Bring us your startups early,\\\" said Google\\\\'s speaker at the Startup School. They\\\\'re quite\\\\n\\\\nexplicit about it: they like to acquire startups at just the point\\\\n\\\\nwhere they would do a Series A round. (The Series A round is the\\\\n\\\\nfirst round of real VC funding; it usually happens in the first\\\\n\\\\nyear.) It is a brilliant strategy, and one that other big technology\\\\n\\\\ncompanies will no doubt try to duplicate.', metadata={'source': '../data/PaulGrahamEssaysLarge/vcsqueeze.txt'}),\\n\",\n \" Document(page_content=\\\"Building office buildings for technology companies won't get you a\\\\n\\\\nsilicon valley, because the key stage in the life of a startup\\\\n\\\\nhappens before they want that kind of space. The key stage is when\\\\n\\\\nthey're three guys operating out of an apartment. Wherever the\\\\n\\\\nstartup is when it gets funded, it will stay. The defining quality\\\", metadata={'source': '../data/PaulGrahamEssaysLarge/siliconvalley.txt'}),\\n\",\n \" Document(page_content='of a startup, which in its raw form is more a distraction than a motivator.', metadata={'source': '../data/PaulGrahamEssaysLarge/vcsqueeze.txt'})]\"\n ]\n },\n \"execution_count\": 19,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"print (len(compressed_docs))\\n\",\n \"compressed_docs\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"43bb531c\",\n \"metadata\": {},\n \"source\": [\n \"We now have 4 docs but they are shorter and only contain the information that is relevant to our query.\\n\",\n \"\\n\",\n \"Let's put it in our prompt template again.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 20,\n \"id\": \"e08044f7\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"prompt_template = \\\"\\\"\\\"Use the following pieces of context to answer the question at the end.\\n\",\n \"If you don't know the answer, just say that you don't know, don't try to make up an answer.\\n\",\n \"\\n\",\n \"{context}\\n\",\n \"\\n\",\n \"Question: {question}\\n\",\n \"Answer:\\\"\\\"\\\"\\n\",\n \"PROMPT = PromptTemplate(\\n\",\n \" template=prompt_template, input_variables=[\\\"context\\\", \\\"question\\\"]\\n\",\n \")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 21,\n \"id\": \"b174f262\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"\\\"The author believes that the early stages of a startup are crucial. He advises startups to release a minimal version 1 of their product quickly and then improve it based on user feedback. He also mentions that many startups fail because they are too slow to release their products. Furthermore, he notes that the key stage in a startup's life often happens when it's still a small operation, possibly operating out of an apartment.\\\"\"\n ]\n },\n \"execution_count\": 21,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"llm.predict(text=PROMPT.format_prompt(\\n\",\n \" context=compressed_docs,\\n\",\n \" question=question\\n\",\n \").text)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"98d7d51f\",\n \"metadata\": {},\n \"source\": [\n \"### Parent Document Retriever\\n\",\n \"\\n\",\n \"[LangChain documentation](https://python.langchain.com/docs/modules/data_connection/retrievers/parent_document_retriever) does a great job describing this - my minor edits below:\\n\",\n \"\\n\",\n \"When you split your docs, you generally may want to have small documents, so that their embeddings can most accurately reflect their meaning. If too long, then the embeddings can lose meaning.\\n\",\n \"\\n\",\n \"But at the same time you may want to have information around those small chunks to keep context of the longer document.\\n\",\n \"\\n\",\n \"The ParentDocumentRetriever strikes that balance by splitting and storing small chunks of data. During retrieval, it first fetches the small chunks but then looks up the parent ids for those chunks and returns those larger documents.\\n\",\n \"\\n\",\n \"Note that \\\"parent document\\\" refers to the document that a small chunk originated from. This can either be the whole raw document OR a larger chunk.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 22,\n \"id\": \"3fd6e470\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain.retrievers import ParentDocumentRetriever\\n\",\n \"from langchain.storage import InMemoryStore\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 23,\n \"id\": \"503444a8\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# This text splitter is used to create the child documents. They should be small chunk size.\\n\",\n \"child_splitter = RecursiveCharacterTextSplitter(chunk_size=400)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 24,\n \"id\": \"e1f3d1c4\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# The vectorstore to use to index the child chunks\\n\",\n \"vectorstore = Chroma(\\n\",\n \" collection_name=\\\"return_full_documents\\\",\\n\",\n \" embedding_function=OpenAIEmbeddings()\\n\",\n \")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 25,\n \"id\": \"2d98928b\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# The storage layer for the parent documents\\n\",\n \"store = InMemoryStore()\\n\",\n \"\\n\",\n \"retriever = ParentDocumentRetriever(\\n\",\n \" vectorstore=vectorstore, \\n\",\n \" docstore=store, \\n\",\n \" child_splitter=child_splitter,\\n\",\n \")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"e896018a\",\n \"metadata\": {},\n \"source\": [\n \"Now we will add the whole essays that we split above. We haven't chunked these essays yet, but the `.add_documents` will do the small chunking for us with the `child_splitter` above\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 26,\n \"id\": \"098bf4a3\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"retriever.add_documents(docs, ids=None)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"078d2854\",\n \"metadata\": {},\n \"source\": [\n \"Now if we were to put in a question or query, we'll get small chunks returned\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 27,\n \"id\": \"a3ad876b\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"sub_docs = vectorstore.similarity_search(\\\"what is some investing advice?\\\")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 28,\n \"id\": \"ddc663c8\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"[Document(page_content=\\\"people there are rich, or expect to be when their options vest.\\\\n\\\\nOrdinary employees find it very hard to recommend an acquisition;\\\\n\\\\nit's just too annoying to see a bunch of twenty year olds get rich\\\\n\\\\nwhen you're still working for salary. Even if it's the right thing\\\\n\\\\nfor your company to do.The Solution(s)Bad as things look now, there is a way for VCs to save themselves.\\\", metadata={'doc_id': 'a4372dda-31dc-477f-9239-2ac45d11f3db', 'source': '../data/PaulGrahamEssaysLarge/vcsqueeze.txt'}),\\n\",\n \" Document(page_content=\\\"the product is expensive to develop or sell, or simply because\\\\n\\\\nthey're wasteful.If you're paying attention, you'll be asking at this point not just\\\\n\\\\nhow to avoid the fatal pinch, but how to avoid being default dead.\\\\n\\\\nThat one is easy: don't hire too fast. Hiring too fast is by far\\\\n\\\\nthe biggest killer of startups that raise money.\\\", metadata={'doc_id': '0314fd17-e53a-4c6e-9d80-2a721b8800df', 'source': '../data/PaulGrahamEssaysLarge/aord.txt'}),\\n\",\n \" Document(page_content=\\\"[1]\\\\n\\\\nBut investors are so fickle that you can never\\\\n\\\\ndo more than start to count on them. Sometimes something about your\\\\n\\\\nbusiness will spook investors even if your growth is great. So no\\\\n\\\\nmatter how good your growth is, you can never safely treat fundraising\\\\n\\\\nas more than a plan A. You should always have a plan B as well: you\\\\n\\\\nshould know (as in write down) precisely what you'll need to do to\\\", metadata={'doc_id': '0314fd17-e53a-4c6e-9d80-2a721b8800df', 'source': '../data/PaulGrahamEssaysLarge/aord.txt'}),\\n\",\n \" Document(page_content=\\\"commitment.If an acquirer thinks you're going to stick around no matter what,\\\\n\\\\nthey'll be more likely to buy you, because if they don't and you\\\\n\\\\nstick around, you'll probably grow, your price will go up, and\\\\n\\\\nthey'll be left wishing they'd bought you earlier. Ditto for\\\\n\\\\ninvestors. What really motivates investors, even big VCs, is not\\\\n\\\\nthe hope of good returns, but the fear of missing out.\\\\n\\\\n[6]\\\", metadata={'doc_id': 'ad7c0de6-ec3d-4637-9dea-8de2d37fa505', 'source': '../data/PaulGrahamEssaysLarge/startuplessons.txt'})]\"\n ]\n },\n \"execution_count\": 28,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"sub_docs\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"6b1f18f1\",\n \"metadata\": {},\n \"source\": [\n \"Look how small those chunks are. Now we want to get the parent doc which those small docs are a part of.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 29,\n \"id\": \"17413045\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"retrieved_docs = retriever.get_relevant_documents(\\\"what is some investing advice?\\\")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"5452837f\",\n \"metadata\": {},\n \"source\": [\n \"I'm going to only do the first doc to save space, but there are more waiting for you. Keep in mind that LangChain will do the union of docs, so if you have two child docs from the same parent doc, you'll only return the parent doc once, not twice.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 30,\n \"id\": \"8ecf6116\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"\\\"November 2005In the next few years, venture capital funds will find themselves\\\\n\\\\nsqueezed from four directions. They're already stuck with a seller's\\\\n\\\\nmarket, because of the huge amounts they raised at the end of the\\\\n\\\\nBubble and still haven't invested. This by itself is not the end\\\\n\\\\nof the world. In fact, it's just a more extreme version of the\\\\n\\\\nnorm\\\\n\\\\nin the VC business: too much money chasing too few deals.Unfortunately, those few deals now want less and less money, because\\\\n\\\\nit's getting so cheap to start a startup. The four causes: open\\\\n\\\\nsource, which makes software free; Moore's law, which makes hardware\\\\n\\\\ngeometrically closer to free; the Web, which makes promotion free\\\\n\\\\nif you're good; and better languages, which make development a lot\\\\n\\\\ncheaper.When we started our startup in 1995, the first three were our biggest\\\\n\\\\nexpenses. We had to pay $5000 for the Netscape Commerce Server,\\\\n\\\\nthe only software that then supported secure http connections. We\\\\n\\\\npaid $3000 for a server with a 90\\\"\"\n ]\n },\n \"execution_count\": 30,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"retrieved_docs[0].page_content[:1000]\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"fe9e6ab8\",\n \"metadata\": {},\n \"source\": [\n \"However here we got the full document back. Sometimes this will be too long and we actually just want to get a larger chunk instead. Let's do that.\\n\",\n \"\\n\",\n \"Notice the chunk size difference between the parent splitter and child splitter.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 31,\n \"id\": \"f6c3d87b\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# This text splitter is used to create the parent documents\\n\",\n \"parent_splitter = RecursiveCharacterTextSplitter(chunk_size=2000)\\n\",\n \"\\n\",\n \"# This text splitter is used to create the child documents\\n\",\n \"# It should create documents smaller than the parent\\n\",\n \"child_splitter = RecursiveCharacterTextSplitter(chunk_size=400)\\n\",\n \"\\n\",\n \"# The vectorstore to use to index the child chunks\\n\",\n \"vectorstore = Chroma(collection_name=\\\"return_split_parent_documents\\\", embedding_function=OpenAIEmbeddings())\\n\",\n \"\\n\",\n \"# The storage layer for the parent documents\\n\",\n \"store = InMemoryStore()\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"973d4514\",\n \"metadata\": {},\n \"source\": [\n \"This will set up our retriever for us\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 32,\n \"id\": \"aacf5776\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"retriever = ParentDocumentRetriever(\\n\",\n \" vectorstore=vectorstore, \\n\",\n \" docstore=store, \\n\",\n \" child_splitter=child_splitter,\\n\",\n \" parent_splitter=parent_splitter,\\n\",\n \")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"2204ee45\",\n \"metadata\": {},\n \"source\": [\n \"Now this time when we add documents two things will happen\\n\",\n \"1. Larger chunks - We'll split our docs into large chunks\\n\",\n \"2. Smaller chunks - We'll split our docs into smaller chunks\\n\",\n \"\\n\",\n \"Both of them will be combined.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 33,\n \"id\": \"561c9cb6\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"retriever.add_documents(docs)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"c4bcede3\",\n \"metadata\": {},\n \"source\": [\n \"Let's check out how many documents we have now\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 34,\n \"id\": \"f5e4718d\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"385\"\n ]\n },\n \"execution_count\": 34,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"len(list(store.yield_keys()))\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"11327641\",\n \"metadata\": {},\n \"source\": [\n \"Then let's go get our small chunks to make sure it's working and see how long they are\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 35,\n \"id\": \"7e6f6150\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"[Document(page_content=\\\"people there are rich, or expect to be when their options vest.\\\\n\\\\nOrdinary employees find it very hard to recommend an acquisition;\\\\n\\\\nit's just too annoying to see a bunch of twenty year olds get rich\\\\n\\\\nwhen you're still working for salary. Even if it's the right thing\\\\n\\\\nfor your company to do.The Solution(s)Bad as things look now, there is a way for VCs to save themselves.\\\", metadata={'doc_id': 'd7cfabc8-b712-4fd1-8f1c-917c66cfdb68', 'source': '../data/PaulGrahamEssaysLarge/vcsqueeze.txt'}),\\n\",\n \" Document(page_content=\\\"commitment.If an acquirer thinks you're going to stick around no matter what,\\\\n\\\\nthey'll be more likely to buy you, because if they don't and you\\\\n\\\\nstick around, you'll probably grow, your price will go up, and\\\\n\\\\nthey'll be left wishing they'd bought you earlier. Ditto for\\\\n\\\\ninvestors. What really motivates investors, even big VCs, is not\\\\n\\\\nthe hope of good returns, but the fear of missing out.\\\\n\\\\n[6]\\\", metadata={'doc_id': 'f6df5dfa-47e4-46be-9e77-8303a512b8c1', 'source': '../data/PaulGrahamEssaysLarge/startuplessons.txt'}),\\n\",\n \" Document(page_content=\\\"April 2006(This essay is derived from a talk at the 2006\\\\n\\\\nStartup School.)The startups we've funded so far are pretty quick, but they seem\\\\n\\\\nquicker to learn some lessons than others. I think it's because\\\\n\\\\nsome things about startups are kind of counterintuitive.We've now\\\\n\\\\ninvested\\\\n\\\\nin enough companies that I've learned a trick\\\\n\\\\nfor determining which points are the counterintuitive ones:\\\", metadata={'doc_id': 'd9e056c8-fee1-43e7-bbb1-8c3c435d663c', 'source': '../data/PaulGrahamEssaysLarge/startuplessons.txt'}),\\n\",\n \" Document(page_content=\\\"the title of this essay, you already know most of what you need to\\\\n\\\\nknow about M&A in the first year.Notes[1]\\\\n\\\\nI'm not saying you should never sell. I'm saying you should\\\\n\\\\nbe clear in your own mind about whether you want to sell or not,\\\\n\\\\nand not be led by manipulation or wishful thinking into trying to\\\\n\\\\nsell earlier than you otherwise would have.[2]\\\", metadata={'doc_id': '88d1d80d-dbb7-4c10-bfee-48df7f551452', 'source': '../data/PaulGrahamEssaysLarge/corpdev.txt'})]\"\n ]\n },\n \"execution_count\": 35,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"sub_docs = vectorstore.similarity_search(\\\"what is some investing advice?\\\")\\n\",\n \"sub_docs\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"6fa3cffa\",\n \"metadata\": {},\n \"source\": [\n \"Now, let's do the full process, we'll see what small chunks are generated, but then return the larger chunks as our relevant documents\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 36,\n \"id\": \"db8e4809\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"Document(page_content='means VCs are now in the business of finding promising little 2-3\\\\n\\\\nman startups and pumping them up into companies that cost $100\\\\n\\\\nmillion to acquire. They didn\\\\'t mean to be in this business; it\\\\'s\\\\n\\\\njust what their business has evolved into.Hence the fourth problem: the acquirers have begun to realize they\\\\n\\\\ncan buy wholesale. Why should they wait for VCs to make the startups\\\\n\\\\nthey want more expensive? Most of what the VCs add, acquirers don\\\\'t\\\\n\\\\nwant anyway. The acquirers already have brand recognition and HR\\\\n\\\\ndepartments. What they really want is the software and the developers,\\\\n\\\\nand that\\\\'s what the startup is in the early phase: concentrated\\\\n\\\\nsoftware and developers.Google, typically, seems to have been the first to figure this out.\\\\n\\\\n\\\"Bring us your startups early,\\\" said Google\\\\'s speaker at the Startup School. They\\\\'re quite\\\\n\\\\nexplicit about it: they like to acquire startups at just the point\\\\n\\\\nwhere they would do a Series A round. (The Series A round is the\\\\n\\\\nfirst round of real VC funding; it usually happens in the first\\\\n\\\\nyear.) It is a brilliant strategy, and one that other big technology\\\\n\\\\ncompanies will no doubt try to duplicate. Unless they want to have\\\\n\\\\nstill more of their lunch eaten by Google.Of course, Google has an advantage in buying startups: a lot of the\\\\n\\\\npeople there are rich, or expect to be when their options vest.\\\\n\\\\nOrdinary employees find it very hard to recommend an acquisition;\\\\n\\\\nit\\\\'s just too annoying to see a bunch of twenty year olds get rich\\\\n\\\\nwhen you\\\\'re still working for salary. Even if it\\\\'s the right thing\\\\n\\\\nfor your company to do.The Solution(s)Bad as things look now, there is a way for VCs to save themselves.\\\\n\\\\nThey need to do two things, one of which won\\\\'t surprise them, and\\\\n\\\\nanother that will seem an anathema.Let\\\\'s start with the obvious one: lobby to get Sarbanes-Oxley\\\\n\\\\nloosened. This law was created to prevent future Enrons, not to\\\\n\\\\ndestroy the IPO market. Since the IPO market was practically dead', metadata={'source': '../data/PaulGrahamEssaysLarge/vcsqueeze.txt'})\"\n ]\n },\n \"execution_count\": 36,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"larger_chunk_relevant_docs = retriever.get_relevant_documents(\\\"what is some investing advice?\\\")\\n\",\n \"larger_chunk_relevant_docs[0]\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 37,\n \"id\": \"5689ec55\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"\\\"One piece of investing advice is to release a minimal version 1 of a product quickly, then improve it based on users' reactions. This is because it's dangerous to guess what users will like without knowing them. Another advice is for Venture Capitalists to lobby to get Sarbanes-Oxley loosened, as this law was not created to destroy the IPO market. Additionally, it's advised not to sell a startup too early, but to be clear about whether you want to sell or not, and not be led by manipulation or wishful thinking.\\\"\"\n ]\n },\n \"execution_count\": 37,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"prompt_template = \\\"\\\"\\\"Use the following pieces of context to answer the question at the end.\\n\",\n \"If you don't know the answer, just say that you don't know, don't try to make up an answer.\\n\",\n \"\\n\",\n \"{context}\\n\",\n \"\\n\",\n \"Question: {question}\\n\",\n \"Answer:\\\"\\\"\\\"\\n\",\n \"PROMPT = PromptTemplate(\\n\",\n \" template=prompt_template, input_variables=[\\\"context\\\", \\\"question\\\"]\\n\",\n \")\\n\",\n \"\\n\",\n \"question = \\\"what is some investing advice?\\\"\\n\",\n \"\\n\",\n \"llm.predict(text=PROMPT.format_prompt(\\n\",\n \" context=larger_chunk_relevant_docs,\\n\",\n \" question=question\\n\",\n \").text)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"a76261c6\",\n \"metadata\": {},\n \"source\": [\n \"### Ensemble Retriever\\n\",\n \"\\n\",\n \"The next one on our list combines multiple retrievers together. The goal here is to see what multiple methods return, then pull them together for (hopefully) better results.\\n\",\n \"\\n\",\n \"You may need to install bm25 with `!pip install rank_bm25`\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 38,\n \"id\": \"2d1e83f1\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain.retrievers import BM25Retriever, EnsembleRetriever\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"21bec867\",\n \"metadata\": {},\n \"source\": [\n \"We'll use a [BM25 retriever](https://en.wikipedia.org/wiki/Okapi_BM25) for this one which is really good at keyword matching (vs semantic). When you combine this method with regular semantic search it's known as hybrid search.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 39,\n \"id\": \"f97add10\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# initialize the bm25 retriever and faiss retriever\\n\",\n \"bm25_retriever = BM25Retriever.from_documents(splits)\\n\",\n \"bm25_retriever.k = 2\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 40,\n \"id\": \"20b58715\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"embedding = OpenAIEmbeddings()\\n\",\n \"vectordb = Chroma.from_documents(splits, embedding)\\n\",\n \"vectordb = vectordb.as_retriever(search_kwargs={\\\"k\\\": 2})\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 41,\n \"id\": \"d4eb755d\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# initialize the ensemble retriever\\n\",\n \"ensemble_retriever = EnsembleRetriever(retrievers=[bm25_retriever, vectordb], weights=[0.5, 0.5])\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 42,\n \"id\": \"0d38a44a\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"3\"\n ]\n },\n \"execution_count\": 42,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"ensemble_docs = ensemble_retriever.get_relevant_documents(\\\"what is some investing advice?\\\")\\n\",\n \"len(ensemble_docs)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 43,\n \"id\": \"f7e930e4\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"\\\"One piece of investing advice is to make a larger number of smaller investments instead of a handful of giant ones. It is also suggested to fund younger, more technical founders instead of MBAs and let the founders remain as CEO. Another advice is that the best sources of seed funding are successful startup founders, as they can also provide valuable advice. However, it's important to be aware of the changing nature of the world and industries, as what may seem like a bad idea initially could become a good one due to changes in the world.\\\"\"\n ]\n },\n \"execution_count\": 43,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"prompt_template = \\\"\\\"\\\"Use the following pieces of context to answer the question at the end.\\n\",\n \"If you don't know the answer, just say that you don't know, don't try to make up an answer.\\n\",\n \"\\n\",\n \"{context}\\n\",\n \"\\n\",\n \"Question: {question}\\n\",\n \"Answer:\\\"\\\"\\\"\\n\",\n \"PROMPT = PromptTemplate(\\n\",\n \" template=prompt_template, input_variables=[\\\"context\\\", \\\"question\\\"]\\n\",\n \")\\n\",\n \"\\n\",\n \"question = \\\"what is some investing advice?\\\"\\n\",\n \"\\n\",\n \"llm.predict(text=PROMPT.format_prompt(\\n\",\n \" context=ensemble_docs,\\n\",\n \" question=question\\n\",\n \").text)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"5deae6d2\",\n \"metadata\": {},\n \"source\": [\n \"### Self Querying\\n\",\n \"\\n\",\n \"The last one we'll look at today is self querying. This is when the retriever has the ability to query itself. It does this so it can use filters when doing it's final query.\\n\",\n \"\\n\",\n \"This means it'll use the users query for semantic search, but also its own query for filtering (so the user doesn't have to give a structured filter).\\n\",\n \"\\n\",\n \"You may need to install `!pip install lark`\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 44,\n \"id\": \"8308c26b\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain.retrievers.self_query.base import SelfQueryRetriever\\n\",\n \"from langchain.chains.query_constructor.base import AttributeInfo\\n\",\n \"\\n\",\n \"embeddings = OpenAIEmbeddings()\\n\",\n \"llm = ChatOpenAI(temperature=0, model='gpt-4')\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 45,\n \"id\": \"8f85445b\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"if 'vectorstore' in globals(): # If you've already made your vectordb this will delete it so you start fresh\\n\",\n \" vectorstore.delete_collection()\\n\",\n \"\\n\",\n \"vectorstore = Chroma.from_documents(\\n\",\n \" splits, embeddings\\n\",\n \")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"c2c00190\",\n \"metadata\": {},\n \"source\": [\n \"Below is the information on the fitlers available. This will help the model know which filters to semantically search for\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 46,\n \"id\": \"89fdc150\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"metadata_field_info=[\\n\",\n \" AttributeInfo(\\n\",\n \" name=\\\"source\\\",\\n\",\n \" description=\\\"The filename of the essay\\\", \\n\",\n \" type=\\\"string or list[string]\\\", \\n\",\n \" ),\\n\",\n \"]\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 47,\n \"id\": \"898665ab\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"document_content_description = \\\"Essays from Paul Graham\\\"\\n\",\n \"retriever = SelfQueryRetriever.from_llm(llm,\\n\",\n \" vectorstore,\\n\",\n \" document_content_description,\\n\",\n \" metadata_field_info,\\n\",\n \" verbose=True,\\n\",\n \" enable_limit=True)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 48,\n \"id\": \"fc5a7209\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"query='figure out what you like to do' filter=Comparison(comparator=, attribute='source', value='../data/PaulGrahamEssaysLarge/island.txt') limit=1\\n\"\n ]\n },\n {\n \"data\": {\n \"text/plain\": [\n \"[Document(page_content=\\\"if I could only figure out what.As for books, I know the house would probably have something to\\\\n\\\\nread. On the average trip I bring four books and only read one of\\\\n\\\\nthem, because I find new books to read en route. Really bringing\\\\n\\\\nbooks is insurance.I realize this dependence on books is not entirely good—that what\\\\n\\\\nI need them for is distraction. The books I bring on trips are\\\\n\\\\noften quite virtuous, the sort of stuff that might be assigned\\\\n\\\\nreading in a college class. But I know my motives aren't virtuous.\\\\n\\\\nI bring books because if the world gets boring I need to be able\\\\n\\\\nto slip into another distilled by some writer. It's like eating\\\\n\\\\njam when you know you should be eating fruit.There is a point where I'll do without books. I was walking in\\\\n\\\\nsome steep mountains once, and decided I'd rather just think, if I\\\\n\\\\nwas bored, rather than carry a single unnecessary ounce. It wasn't\\\\n\\\\nso bad. I found I could entertain myself by having ideas instead\\\\n\\\\nof reading other people's. If you stop eating jam, fruit starts\\\\n\\\\nto taste better.So maybe I'll try not bringing books on some future trip. They're\\\\n\\\\ngoing to have to pry the plugs out of my cold, dead ears, however.\\\", metadata={'source': '../data/PaulGrahamEssaysLarge/island.txt'})]\"\n ]\n },\n \"execution_count\": 48,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"retriever.get_relevant_documents(\\\"Return only 1 essay. What is one thing you can do to figure out what you like to do from source '../data/PaulGrahamEssaysLarge/island.txt'\\\")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"b16b3757\",\n \"metadata\": {},\n \"source\": [\n \"It's kind of annoying to have to put in the full file name, a user doesn't want to do that. Let's change `source` to `essay` and the file path w/ the essay name\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 49,\n \"id\": \"95dfc489\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"import re\\n\",\n \"\\n\",\n \"for split in splits:\\n\",\n \" split.metadata['essay'] = re.search(r'[^/]+(?=\\\\.\\\\w+$)', split.metadata['source']).group()\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"646b9fca\",\n \"metadata\": {},\n \"source\": [\n \"Ok now that we did that, let's make a new field info config\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 50,\n \"id\": \"9bbf7f6b\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"metadata_field_info=[\\n\",\n \" AttributeInfo(\\n\",\n \" name=\\\"essay\\\",\\n\",\n \" description=\\\"The name of the essay\\\", \\n\",\n \" type=\\\"string or list[string]\\\", \\n\",\n \" ),\\n\",\n \"]\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 51,\n \"id\": \"96a75eea\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"if 'vectorstore' in globals(): # If you've already made your vectordb this will delete it so you start fresh\\n\",\n \" vectorstore.delete_collection()\\n\",\n \"\\n\",\n \"vectorstore = Chroma.from_documents(\\n\",\n \" splits, embeddings\\n\",\n \")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 52,\n \"id\": \"39a6c78c\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"document_content_description = \\\"Essays from Paul Graham\\\"\\n\",\n \"retriever = SelfQueryRetriever.from_llm(llm,\\n\",\n \" vectorstore,\\n\",\n \" document_content_description,\\n\",\n \" metadata_field_info,\\n\",\n \" verbose=True,\\n\",\n \" enable_limit=True)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 53,\n \"id\": \"88ab1345\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"query='investment advice' filter=Comparison(comparator=, attribute='essay', value='worked') limit=1\\n\"\n ]\n },\n {\n \"data\": {\n \"text/plain\": [\n \"[Document(page_content='should make a larger number of smaller investments instead of a\\\\n\\\\nhandful of giant ones, they should be funding younger, more technical\\\\n\\\\nfounders instead of MBAs, they should let the founders remain as\\\\n\\\\nCEO, and so on.One of my tricks for writing essays had always been to give talks.\\\\n\\\\nThe prospect of having to stand up in front of a group of people\\\\n\\\\nand tell them something that won\\\\'t waste their time is a great\\\\n\\\\nspur to the imagination. When the Harvard Computer Society, the\\\\n\\\\nundergrad computer club, asked me to give a talk, I decided I would\\\\n\\\\ntell them how to start a startup. Maybe they\\\\'d be able to avoid the\\\\n\\\\nworst of the mistakes we\\\\'d made.So I gave this talk, in the course of which I told them that the\\\\n\\\\nbest sources of seed funding were successful startup founders,\\\\n\\\\nbecause then they\\\\'d be sources of advice too. Whereupon it seemed\\\\n\\\\nthey were all looking expectantly at me. Horrified at the prospect\\\\n\\\\nof having my inbox flooded by business plans (if I\\\\'d only known),\\\\n\\\\nI blurted out \\\"But not me!\\\" and went on with the talk. But afterward\\\\n\\\\nit occurred to me that I should really stop procrastinating about\\\\n\\\\nangel investing. I\\\\'d been meaning to since Yahoo bought us, and now\\\\n\\\\nit was 7 years later and I still hadn\\\\'t done one angel investment.Meanwhile I had been scheming with Robert and Trevor about projects\\\\n\\\\nwe could work on together. I missed working with them, and it seemed', metadata={'essay': 'worked', 'source': '../data/PaulGrahamEssaysLarge/worked.txt'})]\"\n ]\n },\n \"execution_count\": 53,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"retriever.get_relevant_documents(\\\"Tell me about investment advice the 'worked' essay? return only 1\\\")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"e9e28e68\",\n \"metadata\": {},\n \"source\": [\n \"Awesome! It returned it back for us. It's a bit rigid because you need to put in the exact name of the file/essay you want to get. You could make a pre-step and infer the correct essay from the users choice but this is out of scope for now and application specific.\"\n ]\n }\n ],\n \"metadata\": {\n \"kernelspec\": {\n \"display_name\": \"Python 3 (ipykernel)\",\n \"language\": \"python\",\n \"name\": \"python3\"\n },\n \"language_info\": {\n \"codemirror_mode\": {\n \"name\": \"ipython\",\n \"version\": 3\n },\n \"file_extension\": \".py\",\n \"mimetype\": \"text/x-python\",\n \"name\": \"python\",\n \"nbconvert_exporter\": \"python\",\n \"pygments_lexer\": \"ipython3\",\n \"version\": \"3.9.13\"\n }\n },\n \"nbformat\": 4,\n \"nbformat_minor\": 5\n}\n" }, { "path": "data_generation/Ask A Book Questions.ipynb", "content": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"id\": \"8b715375\",\n \"metadata\": {},\n \"source\": [\n \"# Top-K Similarity Search - Ask A Book A Question\\n\",\n \"\\n\",\n \"In this tutorial we will see a simple example of basic retrieval via Top-K Similarity search\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 1,\n \"id\": \"9d615a77\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# pip install langchain --upgrade\\n\",\n \"# Version: 0.0.164\\n\",\n \"\\n\",\n \"# !pip install pypdf\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 2,\n \"id\": \"2d3e92ed\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"True\"\n ]\n },\n \"execution_count\": 2,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"# PDF Loaders. If unstructured gives you a hard time, try PyPDFLoader\\n\",\n \"from langchain.document_loaders import UnstructuredPDFLoader, OnlinePDFLoader, PyPDFLoader, TextLoader\\n\",\n \"from langchain.text_splitter import RecursiveCharacterTextSplitter\\n\",\n \"from dotenv import load_dotenv\\n\",\n \"import os\\n\",\n \"\\n\",\n \"load_dotenv()\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"5166d759\",\n \"metadata\": {},\n \"source\": [\n \"### Load your data\\n\",\n \"\\n\",\n \"Next let's load up some data. I've put a few 'loaders' on there which will load data from different locations. Feel free to use the one that suits you. The default one queries one of Paul Graham's essays for a simple example. This process will only stage the loader, not actually load it.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 3,\n \"id\": \"b4a2d6bf\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"loader = TextLoader(file_path=\\\"../data/PaulGrahamEssays/vb.txt\\\")\\n\",\n \"\\n\",\n \"## Other options for loaders \\n\",\n \"# loader = PyPDFLoader(\\\"../data/field-guide-to-data-science.pdf\\\")\\n\",\n \"# loader = UnstructuredPDFLoader(\\\"../data/field-guide-to-data-science.pdf\\\")\\n\",\n \"# loader = OnlinePDFLoader(\\\"https://wolfpaulus.com/wp-content/uploads/2017/05/field-guide-to-data-science.pdf\\\")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"c8d38044\",\n \"metadata\": {},\n \"source\": [\n \"Then let's go ahead and actually load the data.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 4,\n \"id\": \"bcdac23c\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"data = loader.load()\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"e07a744a\",\n \"metadata\": {},\n \"source\": [\n \"Then let's actually check out what's been loaded\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 5,\n \"id\": \"b4fd7c9e\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"You have 1 document(s) in your data\\n\",\n \"There are 9155 characters in your sample document\\n\",\n \"Here is a sample: January 2016Life is short, as everyone knows. When I was a kid I used to wonder\\n\",\n \"about this. Is life actually short, or are we really complaining\\n\",\n \"about its finiteness? Would we be just as likely to fe\\n\"\n ]\n }\n ],\n \"source\": [\n \"# Note: If you're using PyPDFLoader then it will split by page for you already\\n\",\n \"print (f'You have {len(data)} document(s) in your data')\\n\",\n \"print (f'There are {len(data[0].page_content)} characters in your sample document')\\n\",\n \"print (f'Here is a sample: {data[0].page_content[:200]}')\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"8af9b604\",\n \"metadata\": {},\n \"source\": [\n \"### Chunk your data up into smaller documents\\n\",\n \"\\n\",\n \"While we could pass the entire essay to a model w/ long context, we want to be picky about which information we share with our model. The better signal to noise ratio we have the more likely we are to get the right answer.\\n\",\n \"\\n\",\n \"The first thing we'll do is chunk up our document into smaller pieces. The goal will be to take only a few of those smaller pieces and pass them to the LLM.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 6,\n \"id\": \"fb3c6f02\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# We'll split our data into chunks around 500 characters each with a 50 character overlap. These are relatively small.\\n\",\n \"\\n\",\n \"text_splitter = RecursiveCharacterTextSplitter(chunk_size=500, chunk_overlap=50)\\n\",\n \"texts = text_splitter.split_documents(data)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 7,\n \"id\": \"879873a4\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"Now you have 20 documents\\n\"\n ]\n }\n ],\n \"source\": [\n \"# Let's see how many small chunks we have\\n\",\n \"print (f'Now you have {len(texts)} documents')\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"838b2843\",\n \"metadata\": {},\n \"source\": [\n \"### Create embeddings of your documents to get ready for semantic search\\n\",\n \"\\n\",\n \"Next up we need to prepare for similarity searches. The way we do this is through embedding our documents (getting a vector per document).\\n\",\n \"\\n\",\n \"This will help us compare documents later on.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 8,\n \"id\": \"373e695a\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stderr\",\n \"output_type\": \"stream\",\n \"text\": [\n \"/opt/homebrew/lib/python3.11/site-packages/pinecone/index.py:4: TqdmExperimentalWarning: Using `tqdm.autonotebook.tqdm` in notebook mode. Use `tqdm.tqdm` instead to force console mode (e.g. in jupyter console)\\n\",\n \" from tqdm.autonotebook import tqdm\\n\"\n ]\n }\n ],\n \"source\": [\n \"from langchain.vectorstores import Chroma, Pinecone\\n\",\n \"from langchain.embeddings.openai import OpenAIEmbeddings\\n\",\n \"import pinecone\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"884e7857\",\n \"metadata\": {},\n \"source\": [\n \"Check to see if there is an environment variable with you API keys, if not, use what you put below\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 9,\n \"id\": \"42a1d5c3\",\n \"metadata\": {\n \"hide_input\": false\n },\n \"outputs\": [],\n \"source\": [\n \"OPENAI_API_KEY = os.getenv('OPENAI_API_KEY', 'YourAPIKey')\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"3205993a\",\n \"metadata\": {},\n \"source\": [\n \"Then we'll get our embeddings engine going. You can use whatever embeddings engine you would like. We'll use OpenAI's ada today.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 10,\n \"id\": \"b4619d3a\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"embeddings = OpenAIEmbeddings(openai_api_key=OPENAI_API_KEY)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"76d66c06\",\n \"metadata\": {},\n \"source\": [\n \"### Option #1: Chroma (for local)\\n\",\n \"\\n\",\n \"I like Chroma becauase it's local and easy to set up without an account.\\n\",\n \"\\n\",\n \"First we'll pass our texts to Chroma via `.from_documents`, this will 1) embed the documents and get a vector, then 2) add them to the vectorstore for retrieval later.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 11,\n \"id\": \"4e0d1c6a\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# load it into Chroma\\n\",\n \"vectorstore = Chroma.from_documents(texts, embeddings)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"7d4750ab\",\n \"metadata\": {},\n \"source\": [\n \"Let's test it out. I want to see which documents are most closely related to a query.\\n\",\n \"\\n\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 12,\n \"id\": \"34929595\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"query = \\\"What is great about having kids?\\\"\\n\",\n \"docs = vectorstore.similarity_search(query)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"1ec60de1\",\n \"metadata\": {},\n \"source\": [\n \"Then we can check them out. In theory, the texts which are deemed most similar should hold the answer to our question.\\n\",\n \"But keep in mind that our query just happens to be a question, it could be a random statement or sentence and it would still work.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 13,\n \"id\": \"4e0f5b45\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"jabs into your consciousness like a pin.The things that matter aren't necessarily the ones people would\\n\",\n \"call \\\"important.\\\" Having coffee with a friend matters. You won't\\n\",\n \"feel later like that was a waste of time.One great thing about having small children is that they make you\\n\",\n \"spend time on things that matter: them. They grab your sleeve as\\n\",\n \"you're staring at your phone and say \\\"will you play with me?\\\" And\\n\",\n \"\\n\",\n \"the question, and the answer is that life actually is short.Having kids showed me how to convert a continuous quantity, time,\\n\",\n \"into discrete quantities. You only get 52 weekends with your 2 year\\n\",\n \"old. If Christmas-as-magic lasts from say ages 3 to 10, you only\\n\",\n \"get to watch your child experience it 8 times. And while it's\\n\",\n \"impossible to say what is a lot or a little of a continuous quantity\\n\",\n \"like time, 8 is not a lot of something. If you had a handful of 8\\n\",\n \"\\n\",\n \"January 2016Life is short, as everyone knows. When I was a kid I used to wonder\\n\",\n \"about this. Is life actually short, or are we really complaining\\n\",\n \"about its finiteness? Would we be just as likely to feel life was\\n\",\n \"short if we lived 10 times as long?Since there didn't seem any way to answer this question, I stopped\\n\",\n \"wondering about it. Then I had kids. That gave me a way to answer\\n\",\n \"\\n\",\n \"done that we didn't. My oldest son will be 7 soon. And while I\\n\",\n \"miss the 3 year old version of him, I at least don't have any regrets\\n\",\n \"over what might have been. We had the best time a daddy and a 3\\n\",\n \"year old ever had.Relentlessly prune bullshit, don't wait to do things that matter,\\n\",\n \"and savor the time you have. That's what you do when life is short.Notes[1]\\n\",\n \"At first I didn't like it that the word that came to mind was\\n\",\n \"one that had other meanings. But then I realized the other meanings\\n\",\n \"\\n\"\n ]\n }\n ],\n \"source\": [\n \"# Here's an example of the first document that was returned\\n\",\n \"for doc in docs:\\n\",\n \" print (f\\\"{doc.page_content}\\\\n\\\")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"b73d8504\",\n \"metadata\": {},\n \"source\": [\n \"### Option #2: Pinecone (for cloud)\\n\",\n \"If you want to use pinecone, run the code below, if not then skip over to Chroma below it. You must go to [Pinecone.io](https://www.pinecone.io/) and set up an account\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 14,\n \"id\": \"0e093ef3\",\n \"metadata\": {\n \"hide_input\": false\n },\n \"outputs\": [],\n \"source\": [\n \"# PINECONE_API_KEY = os.getenv('PINECONE_API_KEY', 'YourAPIKey')\\n\",\n \"# PINECONE_API_ENV = os.getenv('PINECONE_API_ENV', 'us-east1-gcp') # You may need to switch with your env\\n\",\n \"\\n\",\n \"# # initialize pinecone\\n\",\n \"# pinecone.init(\\n\",\n \"# api_key=PINECONE_API_KEY, # find at app.pinecone.io\\n\",\n \"# environment=PINECONE_API_ENV # next to api key in console\\n\",\n \"# )\\n\",\n \"# index_name = \\\"langchaintest\\\" # put in the name of your pinecone index here\\n\",\n \"\\n\",\n \"# docsearch = Pinecone.from_texts([t.page_content for t in texts], embeddings, index_name=index_name)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"3c35dcd9\",\n \"metadata\": {},\n \"source\": [\n \"### Query those docs to get your answer back\\n\",\n \"\\n\",\n \"Great, those are just the docs which should hold our answer. Now we can pass those to a LangChain chain to query the LLM.\\n\",\n \"\\n\",\n \"We could do this manually, but a chain is a convenient helper for us.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 15,\n \"id\": \"f051337b\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain.chat_models import ChatOpenAI\\n\",\n \"from langchain.chains.question_answering import load_qa_chain\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 16,\n \"id\": \"6b9b1c03\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"llm = ChatOpenAI(temperature=0, openai_api_key=OPENAI_API_KEY)\\n\",\n \"chain = load_qa_chain(llm, chain_type=\\\"stuff\\\")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 17,\n \"id\": \"f67ea7c2\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"query = \\\"What is great about having kids?\\\"\\n\",\n \"docs = vectorstore.similarity_search(query)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 18,\n \"id\": \"3dfd2b7d\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"'One great thing about having kids is that they make you spend time on things that matter. They remind you to prioritize the important things in life, like spending quality time with them. Having kids can also bring a sense of joy and fulfillment as you watch them grow and experience new things.'\"\n ]\n },\n \"execution_count\": 18,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"chain.run(input_documents=docs, question=query)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"516e0a80\",\n \"metadata\": {},\n \"source\": [\n \"Awesome! We just went and queried an external data source!\"\n ]\n }\n ],\n \"metadata\": {\n \"kernelspec\": {\n \"display_name\": \"Python 3 (ipykernel)\",\n \"language\": \"python\",\n \"name\": \"python3\"\n },\n \"language_info\": {\n \"codemirror_mode\": {\n \"name\": \"ipython\",\n \"version\": 3\n },\n \"file_extension\": \".py\",\n \"mimetype\": \"text/x-python\",\n \"name\": \"python\",\n \"nbconvert_exporter\": \"python\",\n \"pygments_lexer\": \"ipython3\",\n \"version\": \"3.11.6\"\n }\n },\n \"nbformat\": 4,\n \"nbformat_minor\": 5\n}\n" }, { "path": "data_generation/Clean and Standardize Data.ipynb", "content": "{\n \"cells\": [\n {\n \"cell_type\": \"code\",\n \"execution_count\": 1,\n \"id\": \"08f5ad56\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain.output_parsers import StructuredOutputParser, ResponseSchema\\n\",\n \"from langchain.prompts import ChatPromptTemplate, HumanMessagePromptTemplate\\n\",\n \"from langchain.llms import OpenAI\\n\",\n \"from langchain.chat_models import ChatOpenAI\\n\",\n \"import pandas as pd\\n\",\n \"import json\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 42,\n \"id\": \"ed951cdf\",\n \"metadata\": {\n \"hide_input\": false\n },\n \"outputs\": [],\n \"source\": [\n \"openai_api_key = '...'\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 30,\n \"id\": \"bf74bc91\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# Temp = 0 so that we get clean information without a lot of creativity\\n\",\n \"chat_model = ChatOpenAI(temperature=0, openai_api_key=openai_api_key, max_tokens=1000)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 31,\n \"id\": \"5845bbed\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# How you would like your response structured. This is basically a fancy prompt template\\n\",\n \"response_schemas = [\\n\",\n \" ResponseSchema(name=\\\"input_industry\\\", description=\\\"This is the input_industry from the user\\\"),\\n\",\n \" ResponseSchema(name=\\\"standardized_industry\\\", description=\\\"This is the industry you feel is most closely matched to the users input\\\"),\\n\",\n \" ResponseSchema(name=\\\"match_score\\\", description=\\\"A score 0-100 of how close you think the match is between user input and your match\\\")\\n\",\n \"]\\n\",\n \"\\n\",\n \"# How you would like to parse your output\\n\",\n \"output_parser = StructuredOutputParser.from_response_schemas(response_schemas)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 32,\n \"id\": \"191d2184\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"The output should be a markdown code snippet formatted in the following schema:\\n\",\n \"\\n\",\n \"```json\\n\",\n \"{\\n\",\n \"\\t\\\"input_industry\\\": string // This is the input_industry from the user\\n\",\n \"\\t\\\"standarized_industry\\\": string // This is the industry you feel is most closely matched to the users input\\n\",\n \"\\t\\\"match_score\\\": string // A score 0-100 of how close you think the match is between user input and your match\\n\",\n \"}\\n\",\n \"```\\n\"\n ]\n }\n ],\n \"source\": [\n \"# See the prompt template you created for formatting\\n\",\n \"format_instructions = output_parser.get_format_instructions()\\n\",\n \"print (output_parser.get_format_instructions())\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 33,\n \"id\": \"4f7e3eab\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"template = \\\"\\\"\\\"\\n\",\n \"You will be given a series of industry names from a user.\\n\",\n \"Find the best corresponding match on the list of standardized names.\\n\",\n \"The closest match will be the one with the closest semantic meaning. Not just string similarity.\\n\",\n \"\\n\",\n \"{format_instructions}\\n\",\n \"\\n\",\n \"Wrap your final output with closed and open brackets (a list of json objects)\\n\",\n \"\\n\",\n \"input_industry INPUT:\\n\",\n \"{user_industries}\\n\",\n \"\\n\",\n \"STANDARDIZED INDUSTRIES:\\n\",\n \"{standardized_industries}\\n\",\n \"\\n\",\n \"YOUR RESPONSE:\\n\",\n \"\\\"\\\"\\\"\\n\",\n \"\\n\",\n \"prompt = ChatPromptTemplate(\\n\",\n \" messages=[\\n\",\n \" HumanMessagePromptTemplate.from_template(template) \\n\",\n \" ],\\n\",\n \" input_variables=[\\\"user_industries\\\", \\\"standardized_industries\\\"],\\n\",\n \" partial_variables={\\\"format_instructions\\\": format_instructions}\\n\",\n \")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 34,\n \"id\": \"7d074208\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"'Corporate Services, Recreation & Travel, Legal, Wellness & Fitness, Entertainment, Consumer Goods, Design, Arts, Manufacturing, Finance, Health Care, Construction, Nonprofit, Real Estate, Software & IT Services, Hardware & Networking, Agriculture, Education, Public Administration, Transportation & Logistics, Public Safety, Media & Communications, Energy & Mining, Retail'\"\n ]\n },\n \"execution_count\": 34,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"# Get your standardized names. You can swap this out with whatever list you want!\\n\",\n \"df = pd.read_csv('../data/LinkedInIndustries.csv')\\n\",\n \"standardized_industries = \\\", \\\".join(df['Industry'].values)\\n\",\n \"standardized_industries\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 35,\n \"id\": \"b162ff8c\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"There are 1 message(s)\\n\",\n \"Type: \\n\",\n \"---------------------------\\n\",\n \"\\n\",\n \"You will be given a series of industry names from a user.\\n\",\n \"Find the best corresponding match on the list of standardized names.\\n\",\n \"The closest match will be the one with the closest semantic meaning. Not just string similarity.\\n\",\n \"\\n\",\n \"The output should be a markdown code snippet formatted in the following schema:\\n\",\n \"\\n\",\n \"```json\\n\",\n \"{\\n\",\n \"\\t\\\"input_industry\\\": string // This is the input_industry from the user\\n\",\n \"\\t\\\"standarized_industry\\\": string // This is the industry you feel is most closely matched to the users input\\n\",\n \"\\t\\\"match_score\\\": string // A score 0-100 of how close you think the match is between user input and your match\\n\",\n \"}\\n\",\n \"```\\n\",\n \"\\n\",\n \"Wrap your final output with closed and open brackets (a list of json objects)\\n\",\n \"\\n\",\n \"input_industry INPUT:\\n\",\n \"air LineZ, airline, aviation, planes that fly, farming, bread, wifi networks, twitter media agency\\n\",\n \"\\n\",\n \"STANDARDIZED INDUSTRIES:\\n\",\n \"Corporate Services, Recreation & Travel, Legal, Wellness & Fitness, Entertainment, Consumer Goods, Design, Arts, Manufacturing, Finance, Health Care, Construction, Nonprofit, Real Estate, Software & IT Services, Hardware & Networking, Agriculture, Education, Public Administration, Transportation & Logistics, Public Safety, Media & Communications, Energy & Mining, Retail\\n\",\n \"\\n\",\n \"YOUR RESPONSE:\\n\",\n \"\\n\"\n ]\n }\n ],\n \"source\": [\n \"# Your user input\\n\",\n \"\\n\",\n \"user_input = \\\"air LineZ, airline, aviation, planes that fly, farming, bread, wifi networks, twitter media agency\\\"\\n\",\n \"\\n\",\n \"_input = prompt.format_prompt(user_industries=user_input, standardized_industries=standardized_industries)\\n\",\n \"\\n\",\n \"\\n\",\n \"print (f\\\"There are {len(_input.messages)} message(s)\\\")\\n\",\n \"print (f\\\"Type: {type(_input.messages[0])}\\\")\\n\",\n \"print (\\\"---------------------------\\\")\\n\",\n \"print (_input.messages[0].content)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 36,\n \"id\": \"559c27cb\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"output = chat_model(_input.to_messages())\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 37,\n \"id\": \"6f375f20\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"\\n\",\n \"\\n\",\n \"\\n\",\n \"[\\n\",\n \"\\t{\\n\",\n \"\\t\\t\\\"input_industry\\\": \\\"air LineZ\\\",\\n\",\n \"\\t\\t\\\"standarized_industry\\\": \\\"Transportation & Logistics\\\",\\n\",\n \"\\t\\t\\\"match_score\\\": \\\"80\\\"\\n\",\n \"\\t},\\n\",\n \"\\t{\\n\",\n \"\\t\\t\\\"input_industry\\\": \\\"airline\\\",\\n\",\n \"\\t\\t\\\"standarized_industry\\\": \\\"Transportation & Logistics\\\",\\n\",\n \"\\t\\t\\\"match_score\\\": \\\"90\\\"\\n\",\n \"\\t},\\n\",\n \"\\t{\\n\",\n \"\\t\\t\\\"input_industry\\\": \\\"aviation\\\",\\n\",\n \"\\t\\t\\\"standarized_industry\\\": \\\"Transportation & Logistics\\\",\\n\",\n \"\\t\\t\\\"match_score\\\": \\\"95\\\"\\n\",\n \"\\t},\\n\",\n \"\\t{\\n\",\n \"\\t\\t\\\"input_industry\\\": \\\"planes that fly\\\",\\n\",\n \"\\t\\t\\\"standarized_industry\\\": \\\"Transportation & Logistics\\\",\\n\",\n \"\\t\\t\\\"match_score\\\": \\\"85\\\"\\n\",\n \"\\t},\\n\",\n \"\\t{\\n\",\n \"\\t\\t\\\"input_industry\\\": \\\"farming\\\",\\n\",\n \"\\t\\t\\\"standarized_industry\\\": \\\"Agriculture\\\",\\n\",\n \"\\t\\t\\\"match_score\\\": \\\"90\\\"\\n\",\n \"\\t},\\n\",\n \"\\t{\\n\",\n \"\\t\\t\\\"input_industry\\\": \\\"bread\\\",\\n\",\n \"\\t\\t\\\"standarized_industry\\\": \\\"Consumer Goods\\\",\\n\",\n \"\\t\\t\\\"match_score\\\": \\\"80\\\"\\n\",\n \"\\t},\\n\",\n \"\\t{\\n\",\n \"\\t\\t\\\"input_industry\\\": \\\"wifi networks\\\",\\n\",\n \"\\t\\t\\\"standarized_industry\\\": \\\"Hardware & Networking\\\",\\n\",\n \"\\t\\t\\\"match_score\\\": \\\"95\\\"\\n\",\n \"\\t},\\n\",\n \"\\t{\\n\",\n \"\\t\\t\\\"input_industry\\\": \\\"twitter media agency\\\",\\n\",\n \"\\t\\t\\\"standarized_industry\\\": \\\"Media & Communications\\\",\\n\",\n \"\\t\\t\\\"match_score\\\": \\\"90\\\"\\n\",\n \"\\t}\\n\",\n \"]\\n\"\n ]\n }\n ],\n \"source\": [\n \"print (type(output))\\n\",\n \"print (output.content)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 38,\n \"id\": \"f2571dd4\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"if \\\"```json\\\" in output.content:\\n\",\n \" json_string = output.content.split(\\\"```json\\\")[1].strip()\\n\",\n \"else:\\n\",\n \" json_string = output.content\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 39,\n \"id\": \"f3332c82\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"\\n\",\n \"\\n\",\n \"[\\n\",\n \"\\t{\\n\",\n \"\\t\\t\\\"input_industry\\\": \\\"air LineZ\\\",\\n\",\n \"\\t\\t\\\"standarized_industry\\\": \\\"Transportation & Logistics\\\",\\n\",\n \"\\t\\t\\\"match_score\\\": \\\"80\\\"\\n\",\n \"\\t},\\n\",\n \"\\t{\\n\",\n \"\\t\\t\\\"input_industry\\\": \\\"airline\\\",\\n\",\n \"\\t\\t\\\"standarized_industry\\\": \\\"Transportation & Logistics\\\",\\n\",\n \"\\t\\t\\\"match_score\\\": \\\"90\\\"\\n\",\n \"\\t},\\n\",\n \"\\t{\\n\",\n \"\\t\\t\\\"input_industry\\\": \\\"aviation\\\",\\n\",\n \"\\t\\t\\\"standarized_industry\\\": \\\"Transportation & Logistics\\\",\\n\",\n \"\\t\\t\\\"match_score\\\": \\\"95\\\"\\n\",\n \"\\t},\\n\",\n \"\\t{\\n\",\n \"\\t\\t\\\"input_industry\\\": \\\"planes that fly\\\",\\n\",\n \"\\t\\t\\\"standarized_industry\\\": \\\"Transportation & Logistics\\\",\\n\",\n \"\\t\\t\\\"match_score\\\": \\\"85\\\"\\n\",\n \"\\t},\\n\",\n \"\\t{\\n\",\n \"\\t\\t\\\"input_industry\\\": \\\"farming\\\",\\n\",\n \"\\t\\t\\\"standarized_industry\\\": \\\"Agriculture\\\",\\n\",\n \"\\t\\t\\\"match_score\\\": \\\"90\\\"\\n\",\n \"\\t},\\n\",\n \"\\t{\\n\",\n \"\\t\\t\\\"input_industry\\\": \\\"bread\\\",\\n\",\n \"\\t\\t\\\"standarized_industry\\\": \\\"Consumer Goods\\\",\\n\",\n \"\\t\\t\\\"match_score\\\": \\\"80\\\"\\n\",\n \"\\t},\\n\",\n \"\\t{\\n\",\n \"\\t\\t\\\"input_industry\\\": \\\"wifi networks\\\",\\n\",\n \"\\t\\t\\\"standarized_industry\\\": \\\"Hardware & Networking\\\",\\n\",\n \"\\t\\t\\\"match_score\\\": \\\"95\\\"\\n\",\n \"\\t},\\n\",\n \"\\t{\\n\",\n \"\\t\\t\\\"input_industry\\\": \\\"twitter media agency\\\",\\n\",\n \"\\t\\t\\\"standarized_industry\\\": \\\"Media & Communications\\\",\\n\",\n \"\\t\\t\\\"match_score\\\": \\\"90\\\"\\n\",\n \"\\t}\\n\",\n \"]\\n\"\n ]\n }\n ],\n \"source\": [\n \"print(output.content)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"id\": \"af5ef426\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": []\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 40,\n \"id\": \"9e8a0819\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"[{'input_industry': 'air LineZ',\\n\",\n \" 'standarized_industry': 'Transportation & Logistics',\\n\",\n \" 'match_score': '80'},\\n\",\n \" {'input_industry': 'airline',\\n\",\n \" 'standarized_industry': 'Transportation & Logistics',\\n\",\n \" 'match_score': '90'},\\n\",\n \" {'input_industry': 'aviation',\\n\",\n \" 'standarized_industry': 'Transportation & Logistics',\\n\",\n \" 'match_score': '95'},\\n\",\n \" {'input_industry': 'planes that fly',\\n\",\n \" 'standarized_industry': 'Transportation & Logistics',\\n\",\n \" 'match_score': '85'},\\n\",\n \" {'input_industry': 'farming',\\n\",\n \" 'standarized_industry': 'Agriculture',\\n\",\n \" 'match_score': '90'},\\n\",\n \" {'input_industry': 'bread',\\n\",\n \" 'standarized_industry': 'Consumer Goods',\\n\",\n \" 'match_score': '80'},\\n\",\n \" {'input_industry': 'wifi networks',\\n\",\n \" 'standarized_industry': 'Hardware & Networking',\\n\",\n \" 'match_score': '95'},\\n\",\n \" {'input_industry': 'twitter media agency',\\n\",\n \" 'standarized_industry': 'Media & Communications',\\n\",\n \" 'match_score': '90'}]\"\n ]\n },\n \"execution_count\": 40,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"# output_parser.parse(output.content) Ideally this works but not in all cases\\n\",\n \"structured_data = json.loads(output.content)\\n\",\n \"structured_data\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 41,\n \"id\": \"34fcf70c\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/html\": [\n \"
\\n\",\n \"\\n\",\n \"\\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \"
input_industrystandarized_industrymatch_score
0air LineZTransportation & Logistics80
1airlineTransportation & Logistics90
2aviationTransportation & Logistics95
3planes that flyTransportation & Logistics85
4farmingAgriculture90
5breadConsumer Goods80
6wifi networksHardware & Networking95
7twitter media agencyMedia & Communications90
\\n\",\n \"
\"\n ],\n \"text/plain\": [\n \" input_industry standarized_industry match_score\\n\",\n \"0 air LineZ Transportation & Logistics 80\\n\",\n \"1 airline Transportation & Logistics 90\\n\",\n \"2 aviation Transportation & Logistics 95\\n\",\n \"3 planes that fly Transportation & Logistics 85\\n\",\n \"4 farming Agriculture 90\\n\",\n \"5 bread Consumer Goods 80\\n\",\n \"6 wifi networks Hardware & Networking 95\\n\",\n \"7 twitter media agency Media & Communications 90\"\n ]\n },\n \"execution_count\": 41,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"pd.DataFrame(structured_data)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"b175a51a\",\n \"metadata\": {},\n \"source\": [\n \"#### To Do\\n\",\n \"1. Look at new incoming industries from the user\\n\",\n \"2. Match against your data base of values you've already mapped\\n\",\n \"3. For existing ones, save an API call and get the result from the data base\\n\",\n \"4. For new ones, batch them together for your LLM to return back to you\"\n ]\n }\n ],\n \"metadata\": {\n \"kernelspec\": {\n \"display_name\": \"Python 3 (ipykernel)\",\n \"language\": \"python\",\n \"name\": \"python3\"\n },\n \"language_info\": {\n \"codemirror_mode\": {\n \"name\": \"ipython\",\n \"version\": 3\n },\n \"file_extension\": \".py\",\n \"mimetype\": \"text/x-python\",\n \"name\": \"python\",\n \"nbconvert_exporter\": \"python\",\n \"pygments_lexer\": \"ipython3\",\n \"version\": \"3.9.13\"\n }\n },\n \"nbformat\": 4,\n \"nbformat_minor\": 5\n}\n" }, { "path": "data_generation/Custom Files Question & Answer.ipynb", "content": "{\n \"cells\": [\n {\n \"cell_type\": \"code\",\n \"execution_count\": 14,\n \"id\": \"ad66c9aa\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain.embeddings.openai import OpenAIEmbeddings\\n\",\n \"from langchain.vectorstores import FAISS\\n\",\n \"from langchain.text_splitter import RecursiveCharacterTextSplitter\\n\",\n \"from langchain import OpenAI\\n\",\n \"from langchain.chains import RetrievalQA\\n\",\n \"from langchain.document_loaders import DirectoryLoader\\n\",\n \"import magic\\n\",\n \"import os\\n\",\n \"import nltk\\n\",\n \"\\n\",\n \"openai_api_key = os.getenv(\\\"OPENAI_API_KEY\\\", \\\"YourAPIKey\\\")\\n\",\n \"\\n\",\n \"# nltk.download('averaged_perceptron_tagger')\\n\",\n \"\\n\",\n \"# pip install unstructured\\n\",\n \"# Other dependencies to install https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/unstructured_file.html\\n\",\n \"# pip install python-magic-bin\\n\",\n \"# pip install chromadb\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 2,\n \"id\": \"e8a28a08\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# Get your loader ready\\n\",\n \"loader = DirectoryLoader('../data/PaulGrahamEssaySmall/', glob='**/*.txt')\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 3,\n \"id\": \"6a9740d9\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# Load up your text into documents\\n\",\n \"documents = loader.load()\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 4,\n \"id\": \"3153f864\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# Get your text splitter ready\\n\",\n \"text_splitter = RecursiveCharacterTextSplitter(chunk_size=1000, chunk_overlap=0)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 5,\n \"id\": \"a792c6fb\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# Split your documents into texts\\n\",\n \"texts = text_splitter.split_documents(documents)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 6,\n \"id\": \"d2cad0de\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# Turn your texts into embeddings\\n\",\n \"embeddings = OpenAIEmbeddings(openai_api_key=openai_api_key)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 7,\n \"id\": \"734ed265\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# Get your docsearch ready\\n\",\n \"docsearch = FAISS.from_documents(texts, embeddings)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 8,\n \"id\": \"66826924\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# Load up your LLM\\n\",\n \"llm = OpenAI(openai_api_key=openai_api_key)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 9,\n \"id\": \"817a0ece\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# Create your Retriever\\n\",\n \"qa = RetrievalQA.from_chain_type(llm=llm, chain_type=\\\"stuff\\\", retriever=docsearch.as_retriever())\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 10,\n \"id\": \"20b81063\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"' McCarthy discovered that a programming language could be constructed from a handful of simple operators and a notation for functions, using a data structure called a list for both code and data.'\"\n ]\n },\n \"execution_count\": 10,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"# Run a query\\n\",\n \"query = \\\"What did McCarthy discover?\\\"\\n\",\n \"qa.run(query)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"f22231c5\",\n \"metadata\": {},\n \"source\": [\n \"### Sources\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 11,\n \"id\": \"694343cb\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"qa = RetrievalQA.from_chain_type(llm=llm,\\n\",\n \" chain_type=\\\"stuff\\\",\\n\",\n \" retriever=docsearch.as_retriever(),\\n\",\n \" return_source_documents=True)\\n\",\n \"query = \\\"What did McCarthy discover?\\\"\\n\",\n \"result = qa({\\\"query\\\": query})\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 12,\n \"id\": \"bec53323\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"' McCarthy discovered a way to build a whole programming language using a handful of simple operators and a notation for functions. He called this language Lisp, for \\\"List Processing,\\\" because one of his key ideas was to use a simple data structure called a list for both code and data.'\"\n ]\n },\n \"execution_count\": 12,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"result['result']\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 13,\n \"id\": \"32246ae3\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"[Document(page_content='May 2001\\\\n\\\\n(I wrote this article to help myself understand exactly\\\\n\\\\nwhat McCarthy discovered. You don\\\\'t need to know this stuff\\\\n\\\\nto program in Lisp, but it should be helpful to\\\\n\\\\nanyone who wants to\\\\n\\\\nunderstand the essence of Lisp \\\\x97 both in the sense of its\\\\n\\\\norigins and its semantic core. The fact that it has such a core\\\\n\\\\nis one of Lisp\\\\'s distinguishing features, and the reason why,\\\\n\\\\nunlike other languages, Lisp has dialects.)In 1960, John\\\\n\\\\nMcCarthy published a remarkable paper in\\\\n\\\\nwhich he did for programming something like what Euclid did for\\\\n\\\\ngeometry. He showed how, given a handful of simple\\\\n\\\\noperators and a notation for functions, you can\\\\n\\\\nbuild a whole programming language.\\\\n\\\\nHe called this language Lisp, for \\\"List Processing,\\\"\\\\n\\\\nbecause one of his key ideas was to use a simple\\\\n\\\\ndata structure called a list for both\\\\n\\\\ncode and data.It\\\\'s worth understanding what McCarthy discovered, not\\\\n\\\\njust as a landmark in the history of computers, but as', metadata={'source': '../data/PaulGrahamEssaySmall/rootsoflisp.txt'}),\\n\",\n \" Document(page_content=\\\"itself. To understand what McCarthy meant by this,\\\\n\\\\nwe're going to retrace his steps, with his mathematical\\\\n\\\\nnotation translated into running Common Lisp code.\\\", metadata={'source': '../data/PaulGrahamEssaySmall/rootsoflisp.txt'}),\\n\",\n \" Document(page_content=\\\"a model for what programming is tending to become in\\\\n\\\\nour own time. It seems to me that there have been\\\\n\\\\ntwo really clean, consistent models of programming so\\\\n\\\\nfar: the C model and the Lisp model.\\\\n\\\\nThese two seem points of high ground, with swampy lowlands\\\\n\\\\nbetween them. As computers have grown more powerful,\\\\n\\\\nthe new languages being developed have been moving\\\\n\\\\nsteadily toward the Lisp model. A popular recipe\\\\n\\\\nfor new programming languages in the past 20 years\\\\n\\\\nhas been to take the C model of computing and add to\\\\n\\\\nit, piecemeal, parts taken from the Lisp model,\\\\n\\\\nlike runtime typing and garbage collection.In this article I'm going to try to explain in the\\\\n\\\\nsimplest possible terms what McCarthy discovered.\\\\n\\\\nThe point is not just to learn about an interesting\\\\n\\\\ntheoretical result someone figured out forty years ago,\\\\n\\\\nbut to show where languages are heading.\\\\n\\\\nThe unusual thing about Lisp \\\\x97 in fact, the defining\\\\n\\\\nquality of Lisp \\\\x97 is that it can be written in\\\", metadata={'source': '../data/PaulGrahamEssaySmall/rootsoflisp.txt'}),\\n\",\n \" Document(page_content=\\\"January 2023(Someone fed my essays into GPT to make something that could answer\\\\n\\\\nquestions based on them, then asked it where good ideas come from. The\\\\n\\\\nanswer was ok, but not what I would have said. This is what I would have said.)The way to get new ideas is to notice anomalies: what seems strange,\\\\n\\\\nor missing, or broken? You can see anomalies in everyday life (much\\\\n\\\\nof standup comedy is based on this), but the best place to look for\\\\n\\\\nthem is at the frontiers of knowledge.Knowledge grows fractally.\\\\n\\\\nFrom a distance its edges look smooth, but when you learn enough\\\\n\\\\nto get close to one, you'll notice it's full of gaps. These gaps\\\\n\\\\nwill seem obvious; it will seem inexplicable that no one has tried\\\\n\\\\nx or wondered about y. In the best case, exploring such gaps yields\\\\n\\\\nwhole new fractal buds.\\\", metadata={'source': '../data/PaulGrahamEssaySmall/getideas.txt'})]\"\n ]\n },\n \"execution_count\": 13,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"result['source_documents']\"\n ]\n }\n ],\n \"metadata\": {\n \"kernelspec\": {\n \"display_name\": \"Python 3 (ipykernel)\",\n \"language\": \"python\",\n \"name\": \"python3\"\n },\n \"language_info\": {\n \"codemirror_mode\": {\n \"name\": \"ipython\",\n \"version\": 3\n },\n \"file_extension\": \".py\",\n \"mimetype\": \"text/x-python\",\n \"name\": \"python\",\n \"nbconvert_exporter\": \"python\",\n \"pygments_lexer\": \"ipython3\",\n \"version\": \"3.9.13\"\n }\n },\n \"nbformat\": 4,\n \"nbformat_minor\": 5\n}\n" }, { "path": "data_generation/Expert Structured Output (Using Function Calling).ipynb", "content": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"id\": \"f76d45d2\",\n \"metadata\": {},\n \"source\": [\n \"### Extract Structured Data From Text: Expert Mode (Using Function Calling)\\n\",\n \"\\n\",\n \"We are going to explore [OpenAI's Function Calling](https://openai.com/blog/function-calling-and-other-api-updates) for extracting structured data from unstructured sources.\\n\",\n \"\\n\",\n \"**Why is this important?**\\n\",\n \"LLMs are great at text output, but they need extra help outputing information in a structure that we want. A common request from developers is to get JSON data back from our LLMs.\\n\",\n \"\\n\",\n \"Spoiler: Jump down to the bottom to see a bonefied business idea that you can start and manage today.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 1,\n \"id\": \"7764b585\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# LangChain Models\\n\",\n \"from langchain.chat_models import ChatOpenAI\\n\",\n \"from langchain.llms import OpenAI\\n\",\n \"from langchain.schema import HumanMessage, SystemMessage, AIMessage\\n\",\n \"\\n\",\n \"# Standard Helpers\\n\",\n \"import pandas as pd\\n\",\n \"import requests\\n\",\n \"import time\\n\",\n \"import json\\n\",\n \"from datetime import datetime\\n\",\n \"import os\\n\",\n \"from dotenv import load_dotenv\\n\",\n \"\\n\",\n \"load_dotenv()\\n\",\n \"\\n\",\n \"# Text Helpers\\n\",\n \"from bs4 import BeautifulSoup\\n\",\n \"from markdownify import markdownify as md\\n\",\n \"\\n\",\n \"# For token counting\\n\",\n \"from langchain.callbacks import get_openai_callback\\n\",\n \"\\n\",\n \"def printOutput(output):\\n\",\n \" print(json.dumps(output,sort_keys=True, indent=3))\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 2,\n \"id\": \"e1728e00\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# It's better to do this an environment variable but putting it in plain text for clarity\\n\",\n \"openai_api_key = os.getenv(\\\"OPENAI_API_KEY\\\", 'YourAPIKey')\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"29c41e97\",\n \"metadata\": {},\n \"source\": [\n \"Let's start off by creating our LLM. We're using gpt4 to take advantage of its increased ability to follow instructions\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 3,\n \"id\": \"f0060ded\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"chat = ChatOpenAI(\\n\",\n \" model_name=\\\"gpt-3.5-turbo-0613\\\", # Cheaper but less reliable\\n\",\n \" temperature=0,\\n\",\n \" max_tokens=2000,\\n\",\n \" openai_api_key=openai_api_key\\n\",\n \")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"1b0786a3\",\n \"metadata\": {},\n \"source\": [\n \"### Function Calling Hello World Example\\n\",\n \"\\n\",\n \"Create an object that holds information about the fields you'd like to extract\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 4,\n \"id\": \"9d7d6783\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"functions = [\\n\",\n \" {\\n\",\n \" \\\"name\\\": \\\"get_food_mentioned\\\",\\n\",\n \" \\\"description\\\": \\\"Get the food that is mentioned in the review from the customer\\\",\\n\",\n \" \\\"parameters\\\": {\\n\",\n \" \\\"type\\\": \\\"object\\\",\\n\",\n \" \\\"properties\\\": {\\n\",\n \" \\\"food\\\": {\\n\",\n \" \\\"type\\\": \\\"string\\\",\\n\",\n \" \\\"description\\\": \\\"The type of food mentioned, ex: Ice cream\\\"\\n\",\n \" },\\n\",\n \" \\\"good_or_bad\\\": {\\n\",\n \" \\\"type\\\": \\\"string\\\",\\n\",\n \" \\\"description\\\": \\\"whether or not the user thought the food was good or bad\\\",\\n\",\n \" \\\"enum\\\": [\\\"good\\\", \\\"bad\\\"]\\n\",\n \" }\\n\",\n \" },\\n\",\n \" \\\"required\\\": [\\\"location\\\"]\\n\",\n \" }\\n\",\n \" }\\n\",\n \"]\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 5,\n \"id\": \"d120776d\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"output = chat(messages=\\n\",\n \" [\\n\",\n \" SystemMessage(content=\\\"You are an helpful AI bot\\\"),\\n\",\n \" HumanMessage(content=\\\"I thought the burgers were awesome\\\")\\n\",\n \" ],\\n\",\n \" functions=functions\\n\",\n \")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 6,\n \"id\": \"496d7d5b\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"{\\n\",\n \" \\\"function_call\\\": {\\n\",\n \" \\\"name\\\": \\\"get_food_mentioned\\\",\\n\",\n \" \\\"arguments\\\": \\\"{\\\\n \\\\\\\"food\\\\\\\": \\\\\\\"burgers\\\\\\\",\\\\n \\\\\\\"good_or_bad\\\\\\\": \\\\\\\"good\\\\\\\"\\\\n}\\\"\\n\",\n \" }\\n\",\n \"}\\n\"\n ]\n }\n ],\n \"source\": [\n \"print(json.dumps(output.additional_kwargs, indent=4))\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"ff82bc96\",\n \"metadata\": {},\n \"source\": [\n \"### Pydantic Model\\n\",\n \"\\n\",\n \"Now let's do the same thing but with a pydantic model rather than json schema\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 7,\n \"id\": \"966adb72\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain.pydantic_v1 import BaseModel, Field\\n\",\n \"import enum\\n\",\n \"\\n\",\n \"class GoodOrBad(str, enum.Enum):\\n\",\n \" GOOD = \\\"Good\\\"\\n\",\n \" BAD = \\\"Bad\\\"\\n\",\n \"\\n\",\n \"class Food(BaseModel):\\n\",\n \" \\\"\\\"\\\"Identifying information about a person's food review.\\\"\\\"\\\"\\n\",\n \"\\n\",\n \" name: str = Field(..., description=\\\"Name of the food mentioned\\\")\\n\",\n \" good_or_bad: GoodOrBad = Field(..., description=\\\"Whether or not the user thought the food was good or bad\\\")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 8,\n \"id\": \"323f6347\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"output = chat(messages=\\n\",\n \" [\\n\",\n \" SystemMessage(content=\\\"You are an helpful AI bot\\\"),\\n\",\n \" HumanMessage(content=\\\"I thought the burgers were awesome\\\")\\n\",\n \" ],\\n\",\n \" functions=[{\\n\",\n \" \\\"name\\\": \\\"FoodExtractor\\\",\\n\",\n \" \\\"description\\\": (\\n\",\n \" \\\"Identifying information about a person's food review.\\\"\\n\",\n \" ),\\n\",\n \" \\\"parameters\\\": Food.schema(),\\n\",\n \" }\\n\",\n \" ]\\n\",\n \")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 9,\n \"id\": \"1944735a\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"AIMessage(content='', additional_kwargs={'function_call': {'name': 'FoodExtractor', 'arguments': '{\\\\n \\\"name\\\": \\\"burgers\\\",\\\\n \\\"good_or_bad\\\": \\\"Good\\\"\\\\n}'}})\"\n ]\n },\n \"execution_count\": 9,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"output\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"95de736a\",\n \"metadata\": {},\n \"source\": [\n \"But LangChain has an abstraction for us that we can use\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 10,\n \"id\": \"954619a5\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"[Food(name='burgers', good_or_bad=)]\"\n ]\n },\n \"execution_count\": 10,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"from langchain.chains import create_extraction_chain_pydantic\\n\",\n \"\\n\",\n \"# Extraction\\n\",\n \"chain = create_extraction_chain_pydantic(pydantic_schema=Food, llm=chat)\\n\",\n \"\\n\",\n \"# Run \\n\",\n \"text = \\\"\\\"\\\"I like burgers they are great\\\"\\\"\\\"\\n\",\n \"chain.run(text)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"fbe68a3d\",\n \"metadata\": {},\n \"source\": [\n \"### Multiple Results\\n\",\n \"\\n\",\n \"Let's try to extract multiple objects from the same text. I'll create a person object now\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 11,\n \"id\": \"906c0f05\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from typing import Sequence\\n\",\n \"\\n\",\n \"chat = ChatOpenAI(\\n\",\n \" model_name=\\\"gpt-4-0613\\\", # Cheaper but less reliable\\n\",\n \" temperature=0,\\n\",\n \" max_tokens=2000,\\n\",\n \" openai_api_key=openai_api_key\\n\",\n \")\\n\",\n \"\\n\",\n \"class Person(BaseModel):\\n\",\n \" \\\"\\\"\\\"Someone who gives their review on different foods\\\"\\\"\\\"\\n\",\n \"\\n\",\n \" name: str = Field(..., description=\\\"Name of the person\\\")\\n\",\n \" foods: Sequence[Food] = Field(..., description=\\\"A food that a person mentioned\\\")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 12,\n \"id\": \"0a5a1f28\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# Extraction\\n\",\n \"chain = create_extraction_chain_pydantic(pydantic_schema=Person, llm=chat)\\n\",\n \"\\n\",\n \"# Run \\n\",\n \"text = \\\"\\\"\\\"amy likes burgers and fries but doesn't like salads\\\"\\\"\\\"\\n\",\n \"output = chain.run(text)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 13,\n \"id\": \"24d7c624\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"Person(name='amy', foods=[Food(name='burgers', good_or_bad=), Food(name='fries', good_or_bad=), Food(name='salads', good_or_bad=)])\"\n ]\n },\n \"execution_count\": 13,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"output[0]\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"52eb267c\",\n \"metadata\": {},\n \"source\": [\n \"**User Query Extraction**\\n\",\n \"\\n\",\n \"Let's do another fun example where we want to extract/convert a query from a user\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 14,\n \"id\": \"e98cdd1a\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"class Query(BaseModel):\\n\",\n \" \\\"\\\"\\\"Extract the change a user would like to make to a financial forecast\\\"\\\"\\\"\\n\",\n \"\\n\",\n \" entity: str = Field(..., description=\\\"Name of the category or account a person would like to change\\\")\\n\",\n \" amount: int = Field(..., description=\\\"Amount they would like to change it by\\\")\\n\",\n \" year: int = Field(..., description=\\\"The year they would like the change to\\\")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 15,\n \"id\": \"02f45b66\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"chain = create_extraction_chain_pydantic(pydantic_schema=Query, llm=chat)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 16,\n \"id\": \"0a42a784\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"[Query(entity='inventory', amount=10, year=2022)]\"\n ]\n },\n \"execution_count\": 16,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"chain.run(\\\"Can you please add 10 more units to inventory in 2022?\\\")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 17,\n \"id\": \"00a15023\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"[Query(entity='revenue', amount=-3, year=2021)]\"\n ]\n },\n \"execution_count\": 17,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"chain.run(\\\"Remove 3 million from revenue in 2021\\\")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"75568586\",\n \"metadata\": {},\n \"source\": [\n \"## Opening Attributes - Real World Example\\n\",\n \"\\n\",\n \"[Opening Attributes](https://twitter.com/GregKamradt/status/1643027796850253824) (my sample project for this application)\\n\",\n \"\\n\",\n \"If anyone wants to strategize on this project DM me on twitter\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"4932a241\",\n \"metadata\": {},\n \"source\": [\n \"We are going to be pulling jobs from Greenhouse. No API key is needed.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 18,\n \"id\": \"3cb6525f\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"def pull_from_greenhouse(board_token):\\n\",\n \" # If doing this in production, make sure you do retries and backoffs\\n\",\n \" \\n\",\n \" # Get your URL ready to accept a parameter\\n\",\n \" url = f'https://boards-api.greenhouse.io/v1/boards/{board_token}/jobs?content=true'\\n\",\n \" \\n\",\n \" try:\\n\",\n \" response = requests.get(url)\\n\",\n \" except:\\n\",\n \" # In case it doesn't work\\n\",\n \" print (\\\"Whoops, error\\\")\\n\",\n \" return\\n\",\n \" \\n\",\n \" status_code = response.status_code\\n\",\n \" \\n\",\n \" jobs = response.json()['jobs']\\n\",\n \" \\n\",\n \" print (f\\\"{board_token}: {status_code}, Found {len(jobs)} jobs\\\")\\n\",\n \" \\n\",\n \" return jobs\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"636e4e8b\",\n \"metadata\": {},\n \"source\": [\n \"Let's try it out for [Okta](https://www.okta.com/)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 19,\n \"id\": \"d2b794b9\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"okta: 200, Found 155 jobs\\n\"\n ]\n }\n ],\n \"source\": [\n \"jobs = pull_from_greenhouse(\\\"okta\\\")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"10c8651d\",\n \"metadata\": {},\n \"source\": [\n \"Let's look at a sample job with it's raw dictionary\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 20,\n \"id\": \"1a458cb9\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# Keep in mind that my job_ids will likely change when you run this depending on the postings of the company\\n\",\n \"job_index = 0\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 21,\n \"id\": \"b2b394e3\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"Preview:\\n\",\n \"\\n\",\n \"{\\\"absolute_url\\\": \\\"https://www.okta.com/company/careers/opportunity/5299914?gh_jid=5299914\\\", \\\"data_compliance\\\": [{\\\"type\\\": \\\"gdpr\\\", \\\"requires_consent\\\": false, \\\"requires_processing_consent\\\": false, \\\"requires_retention_consent\\\": false, \\\"retention_period\\\": null}], \\\"internal_job_id\\\": 2652958, \\\"location\\\": {\\\"name\\\": \\\"Bengaluru, India\\\"}, \\\"metadata\\\": null, \\\"id\\\": 5299914, \\\"updated_at\\\": \\\"2023-09-26T12:28:23-04:\\n\"\n ]\n }\n ],\n \"source\": [\n \"print (\\\"Preview:\\\\n\\\")\\n\",\n \"print (json.dumps(jobs[job_index])[:400])\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"5662c3cb\",\n \"metadata\": {},\n \"source\": [\n \"Let's clean this up a bit\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 22,\n \"id\": \"ce0ee96a\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# I parsed through an output to create the function below\\n\",\n \"def describeJob(job_description):\\n\",\n \" print(f\\\"Job ID: {job_description['id']}\\\")\\n\",\n \" print(f\\\"Link: {job_description['absolute_url']}\\\")\\n\",\n \" print(f\\\"Updated At: {datetime.fromisoformat(job_description['updated_at']).strftime('%B %-d, %Y')}\\\")\\n\",\n \" print(f\\\"Title: {job_description['title']}\\\\n\\\")\\n\",\n \" print(f\\\"Content:\\\\n{job_description['content'][:550]}\\\")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"72759972\",\n \"metadata\": {},\n \"source\": [\n \"We'll look at another job. This job_id may or may not work for you depending on if the position is still active.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 23,\n \"id\": \"12a43cea\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"Job ID: 5299914\\n\",\n \"Link: https://www.okta.com/company/careers/opportunity/5299914?gh_jid=5299914\\n\",\n \"Updated At: September 26, 2023\\n\",\n \"Title: Accounts Receivable Manager, AWS Marketplace (night shift)\\n\",\n \"\\n\",\n \"Content:\\n\",\n \"<div class="content-intro"><p><span style="color: #000000;"><strong>Get to know Okta</strong></span></p>\\n\",\n \"<p><span style="color: #000000;"><br></span>Okta is The World’s Identity Company. We free everyone to safely use any technology—anywhere, on any device or app. Our Workforce and Customer Identity Clouds enable secure yet flexible access, authentication, and automation that transforms how people move through the digital world, putting Identity at t\\n\"\n ]\n }\n ],\n \"source\": [\n \"# Note: I'm using a hard coded job id below. You'll need to switch this if this job ever changes\\n\",\n \"# and it most definitely will!\\n\",\n \"job_id = 5299914\\n\",\n \"\\n\",\n \"job_description = [item for item in jobs if item['id'] == job_id][0]\\n\",\n \" \\n\",\n \"describeJob(job_description)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"e2a3a009\",\n \"metadata\": {},\n \"source\": [\n \"I want to convert the html to text, we'll use BeautifulSoup to do this. There are multiple methods you could choose from. Pick what's best for you.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 24,\n \"id\": \"bd3e15c4\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"soup = BeautifulSoup(job_description['content'], 'html.parser')\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 25,\n \"id\": \"5a991fa4\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"**Get to know Okta**\\n\",\n \"\\n\",\n \"\\n\",\n \" \\n\",\n \"Okta is The World’s Identity Company. We free everyone to safely use any technology—anywhere, on any device or app. Our Workforce and Customer Identity Clouds enable secure yet flexible access, authentication, and automation that transforms how people move through the digital world, putting Identity at the heart of business security and growth.  \\n\",\n \" \\n\",\n \"At Okta, we celebrate a variety of perspectives and experiences. We are not looking for someone who checks every single box - we’re looking for lifelong learners and people who can make us better with their unique experie\\n\"\n ]\n }\n ],\n \"source\": [\n \"text = soup.get_text()\\n\",\n \"\\n\",\n \"# Convert your html to markdown. This reduces tokens and noise\\n\",\n \"text = md(text)\\n\",\n \"\\n\",\n \"print (text[:600])\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"8f673bc2\",\n \"metadata\": {},\n \"source\": [\n \"Let's create a Kor object that will look for tools. This is the meat and potatoes of the application\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 26,\n \"id\": \"ee906edf\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"class Tool(BaseModel):\\n\",\n \" \\\"\\\"\\\"The name of a tool or company\\\"\\\"\\\"\\n\",\n \"\\n\",\n \" name: str = Field(..., description=\\\"Name of the food mentioned\\\")\\n\",\n \" \\n\",\n \"class Tools(BaseModel):\\n\",\n \" \\\"\\\"\\\"A tool, application, or other company that is listed in a job description.\\\"\\\"\\\"\\n\",\n \"\\n\",\n \" tools: Sequence[Tool] = Field(..., description=\\\"\\\"\\\" A tool or technology listed\\n\",\n \" Examples:\\n\",\n \" * \\\"Experience in working with Netsuite, or Looker a plus.\\\" > NetSuite, Looker\\n\",\n \" * \\\"Experience with Microsoft Excel\\\" > Microsoft Excel\\n\",\n \" \\\"\\\"\\\")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 27,\n \"id\": \"fd0074a6\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"chain = create_extraction_chain_pydantic(pydantic_schema=Tools, llm=chat)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 28,\n \"id\": \"f8015920\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"output = chain(text)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 29,\n \"id\": \"decc90ed\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"[Tools(tools=[Tool(name='Okta'), Tool(name='AWS Marketplace'), Tool(name='Tackle.io'), Tool(name='Salesforce'), Tool(name='NetSuite'), Tool(name='SFDC'), Tool(name='Tackle')])]\"\n ]\n },\n \"execution_count\": 29,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"output['text']\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"6855ab40\",\n \"metadata\": {},\n \"source\": [\n \"[OpenAI GPT4 Pricing](https://help.openai.com/en/articles/7127956-how-much-does-gpt-4-cost)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 30,\n \"id\": \"4e67af85\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"Total Tokens: 1400\\n\",\n \"Prompt Tokens: 1295\\n\",\n \"Completion Tokens: 105\\n\",\n \"Successful Requests: 1\\n\",\n \"Total Cost (USD): $0.045149999999999996\\n\"\n ]\n }\n ],\n \"source\": [\n \"with get_openai_callback() as cb:\\n\",\n \" result = chain(text)\\n\",\n \" print(f\\\"Total Tokens: {cb.total_tokens}\\\")\\n\",\n \" print(f\\\"Prompt Tokens: {cb.prompt_tokens}\\\")\\n\",\n \" print(f\\\"Completion Tokens: {cb.completion_tokens}\\\")\\n\",\n \" print(f\\\"Successful Requests: {cb.successful_requests}\\\")\\n\",\n \" print(f\\\"Total Cost (USD): ${cb.total_cost}\\\")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"b770a9e8\",\n \"metadata\": {},\n \"source\": [\n \"Suggested To Do if you want to build this out:\\n\",\n \"\\n\",\n \"* Reduce amount of HTML and low-signal text that gets put into the prompt\\n\",\n \"* Gather list of 1000s of companies\\n\",\n \"* Run through most jobs (You'll likely start to see duplicate information after the first 10-15 jobs per department)\\n\",\n \"* Store results\\n\",\n \"* Snapshot daily as you look for new jobs\\n\",\n \"* Follow [Greg](https://twitter.com/GregKamradt) on Twitter for more tools or if you want to chat about this project\\n\",\n \"* Read the user feedback below for what else to build out with this project (I reached out to everyone who signed up on twitter)\\n\",\n \"\\n\",\n \"\\n\",\n \"### Business idea: Job Data As A Service\\n\",\n \"\\n\",\n \"Start a data service that collects information about company's jobs. This can be sold to investors looking for an edge.\\n\",\n \"\\n\",\n \"After posting [this tweet](https://twitter.com/GregKamradt/status/1643027796850253824) there were 80 people that signed up for the trial. I emailed all of them and most were job seekers looking for companies that used the tech they specialized in.\\n\",\n \"\\n\",\n \"The more interesting use case were sales teams + investors.\\n\",\n \"\\n\",\n \"#### Interesting User Feedback (Persona: Investor):\\n\",\n \"\\n\",\n \"> Hey Gregory, thanks for reaching out.

\\n\",\n \"I always thought that job posts were a gold mine of information, and often suggest identifying targets based on these (go look at relevant job posts for companies that might want to work with you). Secondly, I also automatically ping BuiltWith from our CRM and send that to OpenAI and have a summarized tech stack created - so I see the benefit of having this as an investor.

\\n\",\n \"For me personally, I like to get as much data as possible about a company. Would love to see job post cadence, type of jobs they post and when, notable keywords/phrases used, tech stack (which you have), and any other information we can glean from the job posts (sometimes they have the title of who you'll report to, etc.).

\\n\",\n \"For sales people, I think finer searches, maybe even in natural language if possible - such as \\\"search for companies who posted a data science related job for the first time\\\" - would be powerful.\\n\",\n \"\\n\",\n \"If you do this, let me know! I'd love to hear how it goes.\"\n ]\n }\n ],\n \"metadata\": {\n \"kernelspec\": {\n \"display_name\": \"Python 3 (ipykernel)\",\n \"language\": \"python\",\n \"name\": \"python3\"\n },\n \"language_info\": {\n \"codemirror_mode\": {\n \"name\": \"ipython\",\n \"version\": 3\n },\n \"file_extension\": \".py\",\n \"mimetype\": \"text/x-python\",\n \"name\": \"python\",\n \"nbconvert_exporter\": \"python\",\n \"pygments_lexer\": \"ipython3\",\n \"version\": \"3.9.13\"\n }\n },\n \"nbformat\": 4,\n \"nbformat_minor\": 5\n}\n" }, { "path": "data_generation/Expert Structured Output (Using Kor).ipynb", "content": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"id\": \"f76d45d2\",\n \"metadata\": {},\n \"source\": [\n \"### Extract Structured Data From Text: Expert Mode (Using Kor)\\n\",\n \"\\n\",\n \"For complicated data extraction you need a robust library. The [Kor Library](https://eyurtsev.github.io/kor/nested_objects.html) (created by [Eugene Yurtsev](https://twitter.com/veryboldbagel)) is an awesome tool just for this.\\n\",\n \"\\n\",\n \"We are going to explore using Kor with a practical use case.\\n\",\n \"\\n\",\n \"**Why is this important?**\\n\",\n \"LLMs are great at text output, but they need extra help outputing information in a structure that we want. A common request from developers is to get JSON data back from our LLMs.\\n\",\n \"\\n\",\n \"Spoiler: Jump down to the bottom to see a bonefied business idea that you can start and manage today.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 1,\n \"id\": \"7764b585\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# Kor!\\n\",\n \"from kor.extraction import create_extraction_chain\\n\",\n \"from kor.nodes import Object, Text, Number\\n\",\n \"\\n\",\n \"# LangChain Models\\n\",\n \"from langchain.chat_models import ChatOpenAI\\n\",\n \"from langchain.llms import OpenAI\\n\",\n \"\\n\",\n \"# Standard Helpers\\n\",\n \"import pandas as pd\\n\",\n \"import requests\\n\",\n \"import time\\n\",\n \"import json\\n\",\n \"from datetime import datetime\\n\",\n \"\\n\",\n \"# Text Helpers\\n\",\n \"from bs4 import BeautifulSoup\\n\",\n \"from markdownify import markdownify as md\\n\",\n \"\\n\",\n \"# For token counting\\n\",\n \"from langchain.callbacks import get_openai_callback\\n\",\n \"\\n\",\n \"def printOutput(output):\\n\",\n \" print(json.dumps(output,sort_keys=True, indent=3))\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 2,\n \"id\": \"e1728e00\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# It's better to do this an environment variable but putting it in plain text for clarity\\n\",\n \"openai_api_key = 'your_api_key'\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 34,\n \"id\": \"7f781711\",\n \"metadata\": {\n \"hide_input\": false\n },\n \"outputs\": [],\n \"source\": [\n \"openai_api_key = '...'\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"29c41e97\",\n \"metadata\": {},\n \"source\": [\n \"Let's start off by creating our LLM. We're using gpt4 to take advantage of its increased ability to follow instructions\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 4,\n \"id\": \"f0060ded\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"llm = ChatOpenAI(\\n\",\n \"# model_name=\\\"gpt-3.5-turbo\\\", # Cheaper but less reliable\\n\",\n \" model_name=\\\"gpt-4\\\",\\n\",\n \" temperature=0,\\n\",\n \" max_tokens=2000,\\n\",\n \" openai_api_key=openai_api_key\\n\",\n \")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"1b0786a3\",\n \"metadata\": {},\n \"source\": [\n \"### Kor Hello World Example\\n\",\n \"\\n\",\n \"Create an object that holds information about the fields you'd like to extract\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 5,\n \"id\": \"496d7d5b\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"person_schema = Object(\\n\",\n \" # This what will appear in your output. It's what the fields below will be nested under.\\n\",\n \" # It should be the parent of the fields below. Usually it's singular (not plural)\\n\",\n \" id=\\\"person\\\",\\n\",\n \" \\n\",\n \" # Natural language description about your object\\n\",\n \" description=\\\"Personal information about a person\\\",\\n\",\n \" \\n\",\n \" # Fields you'd like to capture from a piece of text about your object.\\n\",\n \" attributes=[\\n\",\n \" Text(\\n\",\n \" id=\\\"first_name\\\",\\n\",\n \" description=\\\"The first name of a person.\\\",\\n\",\n \" )\\n\",\n \" ],\\n\",\n \" \\n\",\n \" # Examples help go a long way with telling the LLM what you need\\n\",\n \" examples=[\\n\",\n \" (\\\"Alice and Bob are friends\\\", [{\\\"first_name\\\": \\\"Alice\\\"}, {\\\"first_name\\\": \\\"Bob\\\"}])\\n\",\n \" ]\\n\",\n \")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"e6ae5bd8\",\n \"metadata\": {},\n \"source\": [\n \"Create a chain that will extract the information and then parse it. This uses LangChain under the hood\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 6,\n \"id\": \"00e3c457\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"chain = create_extraction_chain(llm, person_schema)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 7,\n \"id\": \"109ba12a\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"{\\n\",\n \" \\\"person\\\": [\\n\",\n \" {\\n\",\n \" \\\"first_name\\\": \\\"Bobby\\\"\\n\",\n \" },\\n\",\n \" {\\n\",\n \" \\\"first_name\\\": \\\"Rachel\\\"\\n\",\n \" },\\n\",\n \" {\\n\",\n \" \\\"first_name\\\": \\\"Joe\\\"\\n\",\n \" }\\n\",\n \" ]\\n\",\n \"}\\n\"\n ]\n }\n ],\n \"source\": [\n \"text = \\\"\\\"\\\"\\n\",\n \" My name is Bobby.\\n\",\n \" My sister's name is Rachel.\\n\",\n \" My brother's name Joe. My dog's name is Spot\\n\",\n \"\\\"\\\"\\\"\\n\",\n \"output = chain.predict_and_parse(text=(text))[\\\"data\\\"]\\n\",\n \"\\n\",\n \"printOutput(output)\\n\",\n \"# Notice how there isn't \\\"spot\\\" in the results list because it's the name of a dog, not a person.\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"210c4f98\",\n \"metadata\": {},\n \"source\": [\n \"Kor also facilitates returning None when the LLM doesn't find what you're looking for\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 8,\n \"id\": \"b60e5f8d\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"{\\n\",\n \" \\\"person\\\": []\\n\",\n \"}\\n\"\n ]\n }\n ],\n \"source\": [\n \"output = chain.predict_and_parse(text=(\\\"The dog went to the park\\\"))[\\\"data\\\"]\\n\",\n \"printOutput(output)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"fbe68a3d\",\n \"metadata\": {},\n \"source\": [\n \"### Multiple Fields\\n\",\n \"You can pass multiple fields if you're looking for more information\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 9,\n \"id\": \"b48aeaf3\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"plant_schema = Object(\\n\",\n \" id=\\\"plant\\\",\\n\",\n \" description=\\\"Information about a plant\\\",\\n\",\n \" \\n\",\n \" # Notice I put multiple fields to pull out different attributes\\n\",\n \" attributes=[\\n\",\n \" Text(\\n\",\n \" id=\\\"plant_type\\\",\\n\",\n \" description=\\\"The common name of the plant.\\\"\\n\",\n \" ),\\n\",\n \" Text(\\n\",\n \" id=\\\"color\\\",\\n\",\n \" description=\\\"The color of the plant\\\"\\n\",\n \" ),\\n\",\n \" Number(\\n\",\n \" id=\\\"rating\\\",\\n\",\n \" description=\\\"The rating of the plant.\\\"\\n\",\n \" )\\n\",\n \" ],\\n\",\n \" examples=[\\n\",\n \" (\\n\",\n \" \\\"Roses are red, lilies are white and a 8 out of 10.\\\",\\n\",\n \" [\\n\",\n \" {\\\"plant_type\\\": \\\"Roses\\\", \\\"color\\\": \\\"red\\\"},\\n\",\n \" {\\\"plant_type\\\": \\\"Lily\\\", \\\"color\\\": \\\"white\\\", \\\"rating\\\" : 8},\\n\",\n \" ],\\n\",\n \" )\\n\",\n \" ]\\n\",\n \")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 10,\n \"id\": \"d662e926\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"{\\n\",\n \" \\\"plant\\\": [\\n\",\n \" {\\n\",\n \" \\\"color\\\": \\\"brown\\\",\\n\",\n \" \\\"plant_type\\\": \\\"Palm tree\\\",\\n\",\n \" \\\"rating\\\": \\\"6.0\\\"\\n\",\n \" },\\n\",\n \" {\\n\",\n \" \\\"color\\\": \\\"green\\\",\\n\",\n \" \\\"plant_type\\\": \\\"Sequoia tree\\\",\\n\",\n \" \\\"rating\\\": \\\"\\\"\\n\",\n \" }\\n\",\n \" ]\\n\",\n \"}\\n\"\n ]\n }\n ],\n \"source\": [\n \"text=\\\"Palm trees are brown with a 6 rating. Sequoia trees are green\\\"\\n\",\n \"\\n\",\n \"chain = create_extraction_chain(llm, plant_schema)\\n\",\n \"output = chain.predict_and_parse(text=text)['data']\\n\",\n \"\\n\",\n \"printOutput(output)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"87e0a551\",\n \"metadata\": {},\n \"source\": [\n \"### Working With Lists\\n\",\n \"\\n\",\n \"You can also extract lists as well.\\n\",\n \"\\n\",\n \"Note: Check out how I have a nested object. The 'parts' object is in the 'cars_schema'\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 11,\n \"id\": \"f51a975f\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"parts = Object(\\n\",\n \" id=\\\"parts\\\",\\n\",\n \" description=\\\"A single part of a car\\\",\\n\",\n \" attributes=[\\n\",\n \" Text(id=\\\"part\\\", description=\\\"The name of the part\\\")\\n\",\n \" ],\\n\",\n \" examples=[\\n\",\n \" (\\n\",\n \" \\\"the jeep has wheels and windows\\\",\\n\",\n \" [\\n\",\n \" {\\\"part\\\": \\\"wheel\\\"},\\n\",\n \" {\\\"part\\\": \\\"window\\\"}\\n\",\n \" ],\\n\",\n \" )\\n\",\n \" ]\\n\",\n \")\\n\",\n \"\\n\",\n \"cars_schema = Object(\\n\",\n \" id=\\\"car\\\",\\n\",\n \" description=\\\"Information about a car\\\",\\n\",\n \" examples=[\\n\",\n \" (\\n\",\n \" \\\"the bmw is red and has an engine and steering wheel\\\",\\n\",\n \" [\\n\",\n \" {\\\"type\\\": \\\"BMW\\\", \\\"color\\\": \\\"red\\\", \\\"parts\\\" : [\\\"engine\\\", \\\"steering wheel\\\"]}\\n\",\n \" ],\\n\",\n \" )\\n\",\n \" ],\\n\",\n \" attributes=[\\n\",\n \" Text(\\n\",\n \" id=\\\"type\\\",\\n\",\n \" description=\\\"The make or brand of the car\\\"\\n\",\n \" ),\\n\",\n \" Text(\\n\",\n \" id=\\\"color\\\",\\n\",\n \" description=\\\"The color of the car\\\"\\n\",\n \" ),\\n\",\n \" parts\\n\",\n \" ]\\n\",\n \")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 12,\n \"id\": \"ca4d0cdb\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"{\\n\",\n \" \\\"car\\\": {\\n\",\n \" \\\"color\\\": \\\"blue\\\",\\n\",\n \" \\\"parts\\\": [\\n\",\n \" {\\n\",\n \" \\\"part\\\": \\\"rear view mirror\\\"\\n\",\n \" },\\n\",\n \" {\\n\",\n \" \\\"part\\\": \\\"roof\\\"\\n\",\n \" },\\n\",\n \" {\\n\",\n \" \\\"part\\\": \\\"windshield\\\"\\n\",\n \" }\\n\",\n \" ],\\n\",\n \" \\\"type\\\": \\\"jeep\\\"\\n\",\n \" }\\n\",\n \"}\\n\"\n ]\n }\n ],\n \"source\": [\n \"# To do nested objects you need to specify encoder_or_encoder_class=\\\"json\\\"\\n\",\n \"text = \\\"The blue jeep has rear view mirror, roof, windshield\\\"\\n\",\n \"\\n\",\n \"# Changed the encoder to json\\n\",\n \"chain = create_extraction_chain(llm, cars_schema, encoder_or_encoder_class=\\\"json\\\")\\n\",\n \"output = chain.predict_and_parse(text=text)['data']\\n\",\n \"\\n\",\n \"printOutput(output)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"bcdac769\",\n \"metadata\": {},\n \"source\": [\n \"View the prompt that was sent over\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 13,\n \"id\": \"544e11fd\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"Your goal is to extract structured information from the user's input that matches the form described below. When extracting information please make sure it matches the type information exactly. Do not add any attributes that do not appear in the schema shown below.\\n\",\n \"\\n\",\n \"```TypeScript\\n\",\n \"\\n\",\n \"car: { // Information about a car\\n\",\n \" type: string // The make or brand of the car\\n\",\n \" color: string // The color of the car\\n\",\n \" parts: { // A single part of a car\\n\",\n \" part: string // The name of the part\\n\",\n \" }\\n\",\n \"}\\n\",\n \"```\\n\",\n \"\\n\",\n \"\\n\",\n \"Please output the extracted information in JSON format. Do not output anything except for the extracted information. Do not add any clarifying information. Do not add any fields that are not in the schema. If the text contains attributes that do not appear in the schema, please ignore them. All output must be in JSON format and follow the schema specified above. Wrap the JSON in tags.\\n\",\n \"\\n\",\n \"Input: the bmw is red and has an engine and steering wheel\\n\",\n \"Output: {\\\"car\\\": [{\\\"type\\\": \\\"BMW\\\", \\\"color\\\": \\\"red\\\", \\\"parts\\\": [\\\"engine\\\", \\\"steering wheel\\\"]}]}\\n\",\n \"Input: the jeep has wheels and windows\\n\",\n \"Output: {\\\"car\\\": {\\\"parts\\\": [{\\\"part\\\": \\\"wheel\\\"}, {\\\"part\\\": \\\"window\\\"}]}}\\n\",\n \"Input: The blue jeep has rear view mirror, roof, windshield\\n\",\n \"Output:\\n\"\n ]\n }\n ],\n \"source\": [\n \"prompt = chain.prompt.format_prompt(text=text).to_string()\\n\",\n \"\\n\",\n \"print(prompt)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"66d9388f\",\n \"metadata\": {},\n \"source\": [\n \"Kor is a really great way to extract actions from a user as well\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 14,\n \"id\": \"801b200b\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"schema = Object(\\n\",\n \" id=\\\"forecaster\\\",\\n\",\n \" description=(\\n\",\n \" \\\"User is controling an app that makes financial forecasts. \\\"\\n\",\n \" \\\"They will give a command to update a forecast in the future\\\"\\n\",\n \" ),\\n\",\n \" attributes=[\\n\",\n \" Text(\\n\",\n \" id=\\\"year\\\",\\n\",\n \" description=\\\"Year the user wants to update\\\",\\n\",\n \" examples=[(\\\"please increase 2014's customers by 15%\\\", \\\"2014\\\")],\\n\",\n \" many=True,\\n\",\n \" ),\\n\",\n \" Text(\\n\",\n \" id=\\\"metric\\\",\\n\",\n \" description=\\\"The unit or metric a user would like to influence\\\",\\n\",\n \" examples=[(\\\"please increase 2014's customers by 15%\\\", \\\"customers\\\")],\\n\",\n \" many=True,\\n\",\n \" ),\\n\",\n \" Text(\\n\",\n \" id=\\\"amount\\\",\\n\",\n \" description=\\\"The quantity of a forecast adjustment\\\",\\n\",\n \" examples=[(\\\"please increase 2014's customers by 15%\\\", \\\".15\\\")],\\n\",\n \" many=True,\\n\",\n \" )\\n\",\n \" ],\\n\",\n \" many=False,\\n\",\n \")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 15,\n \"id\": \"02f45b66\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"{\\n\",\n \" \\\"forecaster\\\": {\\n\",\n \" \\\"amount\\\": [\\n\",\n \" \\\"15\\\"\\n\",\n \" ],\\n\",\n \" \\\"metric\\\": [\\n\",\n \" \\\"units sold\\\"\\n\",\n \" ],\\n\",\n \" \\\"year\\\": [\\n\",\n \" \\\"2023\\\"\\n\",\n \" ]\\n\",\n \" }\\n\",\n \"}\\n\"\n ]\n }\n ],\n \"source\": [\n \"chain = create_extraction_chain(llm, schema, encoder_or_encoder_class='json')\\n\",\n \"output = chain.predict_and_parse(text=\\\"please add 15 more units sold to 2023\\\")['data']\\n\",\n \"\\n\",\n \"printOutput(output)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"75568586\",\n \"metadata\": {},\n \"source\": [\n \"## Opening Attributes - Real World Example\\n\",\n \"\\n\",\n \"[Opening Attributes](https://twitter.com/GregKamradt/status/1643027796850253824) (my sample project for this application)\\n\",\n \"\\n\",\n \"If anyone wants to strategize on this project DM me on twitter\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 16,\n \"id\": \"0777cb73\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"llm = ChatOpenAI(\\n\",\n \" # model_name=\\\"gpt-3.5-turbo\\\",\\n\",\n \" model_name=\\\"gpt-4\\\",\\n\",\n \" temperature=0,\\n\",\n \" max_tokens=2000,\\n\",\n \" openai_api_key=openai_api_key\\n\",\n \")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"4932a241\",\n \"metadata\": {},\n \"source\": [\n \"We are going to be pulling jobs from Greenhouse. No API key is needed.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 17,\n \"id\": \"3cb6525f\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"def pull_from_greenhouse(board_token):\\n\",\n \" # If doing this in production, make sure you do retries and backoffs\\n\",\n \" \\n\",\n \" # Get your URL ready to accept a parameter\\n\",\n \" url = f'https://boards-api.greenhouse.io/v1/boards/{board_token}/jobs?content=true'\\n\",\n \" \\n\",\n \" try:\\n\",\n \" response = requests.get(url)\\n\",\n \" except:\\n\",\n \" # In case it doesn't work\\n\",\n \" print (\\\"Whoops, error\\\")\\n\",\n \" return\\n\",\n \" \\n\",\n \" status_code = response.status_code\\n\",\n \" \\n\",\n \" jobs = response.json()['jobs']\\n\",\n \" \\n\",\n \" print (f\\\"{board_token}: {status_code}, Found {len(jobs)} jobs\\\")\\n\",\n \" \\n\",\n \" return jobs\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"636e4e8b\",\n \"metadata\": {},\n \"source\": [\n \"Let's try it out for [Okta](https://www.okta.com/)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 18,\n \"id\": \"d2b794b9\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"okta: 200, Found 142 jobs\\n\"\n ]\n }\n ],\n \"source\": [\n \"jobs = pull_from_greenhouse(\\\"okta\\\")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"10c8651d\",\n \"metadata\": {},\n \"source\": [\n \"Let's look at a sample job with it's raw dictionary\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 20,\n \"id\": \"1a458cb9\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# Keep in mind that my job_ids will likely change when you run this depending on the postings of the company\\n\",\n \"job_index = 0\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 21,\n \"id\": \"b2b394e3\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"Preview:\\n\",\n \"\\n\",\n \"{\\\"absolute_url\\\": \\\"https://www.okta.com/company/careers/opportunity/4977199?gh_jid=4977199\\\", \\\"data_compliance\\\": [{\\\"type\\\": \\\"gdpr\\\", \\\"requires_consent\\\": false, \\\"requires_processing_consent\\\": false, \\\"requires_retention_consent\\\": false, \\\"retention_period\\\": null}], \\\"internal_job_id\\\": 2518868, \\\"location\\\": {\\\"name\\\": \\\"Melbourne \\\"}, \\\"metadata\\\": null, \\\"id\\\": 4977199, \\\"updated_at\\\": \\\"2023-04-05T22:41:12-04:00\\\", \\\"\\n\"\n ]\n }\n ],\n \"source\": [\n \"print (\\\"Preview:\\\\n\\\")\\n\",\n \"print (json.dumps(jobs[job_index])[:400])\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"5662c3cb\",\n \"metadata\": {},\n \"source\": [\n \"Let's clean this up a bit\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 22,\n \"id\": \"ce0ee96a\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# I parsed through an output to create the function below\\n\",\n \"def describeJob(job_description):\\n\",\n \" print(f\\\"Job ID: {job_description['id']}\\\")\\n\",\n \" print(f\\\"Link: {job_description['absolute_url']}\\\")\\n\",\n \" print(f\\\"Updated At: {datetime.fromisoformat(job_description['updated_at']).strftime('%B %-d, %Y')}\\\")\\n\",\n \" print(f\\\"Title: {job_description['title']}\\\\n\\\")\\n\",\n \" print(f\\\"Content:\\\\n{job_description['content'][:550]}\\\")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"72759972\",\n \"metadata\": {},\n \"source\": [\n \"We'll look at another job. This job_id may or may not work for you depending on if the position is still active.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 23,\n \"id\": \"12a43cea\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"Job ID: 4982726\\n\",\n \"Link: https://www.okta.com/company/careers/opportunity/4982726?gh_jid=4982726\\n\",\n \"Updated At: April 11, 2023\\n\",\n \"Title: Staff Software Engineer \\n\",\n \"\\n\",\n \"Content:\\n\",\n \"<div class="content-intro"><p><span style="color: #000000;"><strong>Get to know Okta</strong></span></p>\\n\",\n \"<p><span style="color: #000000;"><br></span>Okta is The World’s Identity Company. We free everyone to safely use any technology—anywhere, on any device or app. Our Workforce and Customer Identity Clouds enable secure yet flexible access, authentication, and automation that transforms how people move through the digital world, putting Identity at t\\n\"\n ]\n }\n ],\n \"source\": [\n \"# Note: I'm using a hard coded job id below. You'll need to switch this if this job ever changes\\n\",\n \"# and it most definitely will!\\n\",\n \"job_id = 4982726\\n\",\n \"\\n\",\n \"job_description = [item for item in jobs if item['id'] == job_id][0]\\n\",\n \" \\n\",\n \"describeJob(job_description)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"e2a3a009\",\n \"metadata\": {},\n \"source\": [\n \"I want to convert the html to text, we'll use BeautifulSoup to do this. There are multiple methods you could choose from. Pick what's best for you.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 24,\n \"id\": \"bd3e15c4\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"soup = BeautifulSoup(job_description['content'], 'html.parser')\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 25,\n \"id\": \"5a991fa4\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"**Get to know Okta**\\n\",\n \"\\n\",\n \"\\n\",\n \" \\n\",\n \"Okta is The World’s Identity Company. We free everyone to safely use any technology—anywhere, on any device or app. Our Workforce and Customer Identity Clouds enable secure yet flexible access, authentication, and automation that transforms how people move through the digital world, putting Identity at the heart of business security and growth.  \\n\",\n \" \\n\",\n \"At Okta, we celebrate a variety of perspectives and experiences. We are not looking for someone who checks every single box, we’re looking for lifelong learners and people who can make us better with their unique experien\\n\"\n ]\n }\n ],\n \"source\": [\n \"text = soup.get_text()\\n\",\n \"\\n\",\n \"# Convert your html to markdown. This reduces tokens and noise\\n\",\n \"text = md(text)\\n\",\n \"\\n\",\n \"print (text[:600])\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"8f673bc2\",\n \"metadata\": {},\n \"source\": [\n \"Let's create a Kor object that will look for tools. This is the meat and potatoes of the application\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 26,\n \"id\": \"ee906edf\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"tools = Object(\\n\",\n \" id=\\\"tools\\\",\\n\",\n \" description=\\\"\\\"\\\"\\n\",\n \" A tool, application, or other company that is listed in a job description.\\n\",\n \" Analytics, eCommerce and GTM are not tools\\n\",\n \" \\\"\\\"\\\",\\n\",\n \" attributes=[\\n\",\n \" Text(\\n\",\n \" id=\\\"tool\\\",\\n\",\n \" description=\\\"The name of a tool or company\\\"\\n\",\n \" )\\n\",\n \" ],\\n\",\n \" examples=[\\n\",\n \" (\\n\",\n \" \\\"Experience in working with Netsuite, or Looker a plus.\\\",\\n\",\n \" [\\n\",\n \" {\\\"tool\\\": \\\"Netsuite\\\"},\\n\",\n \" {\\\"tool\\\": \\\"Looker\\\"},\\n\",\n \" ],\\n\",\n \" ),\\n\",\n \" (\\n\",\n \" \\\"Experience with Microsoft Excel\\\",\\n\",\n \" [\\n\",\n \" {\\\"tool\\\": \\\"Microsoft Excel\\\"}\\n\",\n \" ] \\n\",\n \" ),\\n\",\n \" (\\n\",\n \" \\\"You must know AWS to do well in the job\\\",\\n\",\n \" [\\n\",\n \" {\\\"tool\\\": \\\"AWS\\\"}\\n\",\n \" ] \\n\",\n \" ),\\n\",\n \" (\\n\",\n \" \\\"Troubleshooting customer issues and debugging from logs (Splunk, Syslogs, etc.) \\\",\\n\",\n \" [\\n\",\n \" {\\\"tool\\\": \\\"Splunk\\\"},\\n\",\n \" ] \\n\",\n \" )\\n\",\n \" ],\\n\",\n \" many=True,\\n\",\n \")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 27,\n \"id\": \"fd0074a6\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"chain = create_extraction_chain(llm, tools, input_formatter=\\\"triple_quotes\\\")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 28,\n \"id\": \"f8015920\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"{\\n\",\n \" \\\"tools\\\": [\\n\",\n \" {\\n\",\n \" \\\"tool\\\": \\\"Okta\\\"\\n\",\n \" },\\n\",\n \" {\\n\",\n \" \\\"tool\\\": \\\"Java\\\"\\n\",\n \" },\\n\",\n \" {\\n\",\n \" \\\"tool\\\": \\\"Hibernate\\\"\\n\",\n \" },\\n\",\n \" {\\n\",\n \" \\\"tool\\\": \\\"Spring Boot\\\"\\n\",\n \" },\\n\",\n \" {\\n\",\n \" \\\"tool\\\": \\\"AWS\\\"\\n\",\n \" },\\n\",\n \" {\\n\",\n \" \\\"tool\\\": \\\"GCP\\\"\\n\",\n \" },\\n\",\n \" {\\n\",\n \" \\\"tool\\\": \\\"SQL\\\"\\n\",\n \" },\\n\",\n \" {\\n\",\n \" \\\"tool\\\": \\\"ElasticSearch\\\"\\n\",\n \" },\\n\",\n \" {\\n\",\n \" \\\"tool\\\": \\\"Docker\\\"\\n\",\n \" },\\n\",\n \" {\\n\",\n \" \\\"tool\\\": \\\"Kubernetes\\\"\\n\",\n \" }\\n\",\n \" ]\\n\",\n \"}\\n\"\n ]\n }\n ],\n \"source\": [\n \"output = chain.predict_and_parse(text=text)[\\\"data\\\"]\\n\",\n \"\\n\",\n \"printOutput(output)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"09a7e59d\",\n \"metadata\": {},\n \"source\": [\n \"### Salary\\n\",\n \"\\n\",\n \"Let's grab salary information while we are at it.\\n\",\n \"\\n\",\n \"Not all jobs will list this information. If they do, it's rarely consistent across jobs. A great use case for LLMs to catch this information!\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 29,\n \"id\": \"8e93e9af\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"salary_range = Object(\\n\",\n \" id=\\\"salary_range\\\",\\n\",\n \" description=\\\"\\\"\\\"\\n\",\n \" The range of salary offered for a job mentioned in a job description\\n\",\n \" \\\"\\\"\\\",\\n\",\n \" attributes=[\\n\",\n \" Number(\\n\",\n \" id=\\\"low_end\\\",\\n\",\n \" description=\\\"The low end of a salary range\\\"\\n\",\n \" ),\\n\",\n \" Number(\\n\",\n \" id=\\\"high_end\\\",\\n\",\n \" description=\\\"The high end of a salary range\\\"\\n\",\n \" )\\n\",\n \" ],\\n\",\n \" examples=[\\n\",\n \" (\\n\",\n \" \\\"This position will make between $140 thousand and $230,000.00\\\",\\n\",\n \" [\\n\",\n \" {\\\"low_end\\\": 140000, \\\"high_end\\\": 230000},\\n\",\n \" ]\\n\",\n \" )\\n\",\n \" ]\\n\",\n \")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 30,\n \"id\": \"0d0045ba\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"cruise: 200, Found 219 jobs\\n\"\n ]\n }\n ],\n \"source\": [\n \"jobs = pull_from_greenhouse(\\\"cruise\\\")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 31,\n \"id\": \"9f514a5e\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"Job ID: 4858414\\n\",\n \"Link: https://boards.greenhouse.io/cruise/jobs/4858414?gh_jid=4858414\\n\",\n \"Updated At: April 12, 2023\\n\",\n \"Title: Senior Data Center Technician\\n\",\n \"\\n\",\n \"Content:\\n\",\n \"<div class="content-intro"><p><span style="font-weight: 400;">We're Cruise, a self-driving service designed for the cities we love.</span></p>\\n\",\n \"<p><span style="font-weight: 400;">We’re building the world’s most advanced self-driving vehicles to safely connect people to the places, things, and experiences they care about. We believe self-driving vehicles will help save lives, reshape cities, give back time in transit, and restore freedom of movement for many.</span>\\n\",\n \"We're Cruise, a self-driving service designed for the cities we love.\\n\",\n \"\\n\",\n \"\\n\",\n \"We’re building the world’s most advanced self-driving vehicles to safely connect people to the places, things, and experiences they care about. We believe self-driving vehicles will help save lives, reshape cities, give back time in transit, and restore freedom of movement for many.\\n\",\n \"\\n\",\n \"\\n\",\n \"In our cars, you’re free to be yourself. It’s the same here at Cruise. We’re creating a culture that values the experiences and contributions of all of the unique individuals who collectively make up Cruise, so that every employee can do thei\\n\"\n ]\n }\n ],\n \"source\": [\n \"# This job id may not work for you, pick another one from the list if it doesn't.\\n\",\n \"job_id = 4858414\\n\",\n \"\\n\",\n \"job_description = [item for item in jobs if item['id'] == job_id][0]\\n\",\n \" \\n\",\n \"describeJob(job_description)\\n\",\n \"\\n\",\n \"soup = BeautifulSoup(job_description['content'], 'html.parser')\\n\",\n \"text = soup.get_text()\\n\",\n \"\\n\",\n \"# Convert your html to markdown. This reduces tokens and noise\\n\",\n \"text = md(text)\\n\",\n \"\\n\",\n \"print (text[:600])\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 32,\n \"id\": \"bb307900\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"{\\n\",\n \" \\\"salary_range\\\": [\\n\",\n \" {\\n\",\n \" \\\"high_end\\\": \\\"165000\\\",\\n\",\n \" \\\"low_end\\\": \\\"112300\\\"\\n\",\n \" }\\n\",\n \" ]\\n\",\n \"}\\n\"\n ]\n }\n ],\n \"source\": [\n \"chain = create_extraction_chain(llm, salary_range)\\n\",\n \"output = chain.predict_and_parse(text=text)[\\\"data\\\"]\\n\",\n \"\\n\",\n \"printOutput(output)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"d25f76f9\",\n \"metadata\": {},\n \"source\": [\n \"> The salary range for this position is $112,300 - 165,000. Compensation will vary depending on location, job-related knowledge, skills, and experience. You may also be offered a bonus, restricted stock units, and benefits. These ranges are subject to change.\\n\",\n \"\\n\",\n \"Awesome!\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"6855ab40\",\n \"metadata\": {},\n \"source\": [\n \"[OpenAI GPT4 Pricing](https://help.openai.com/en/articles/7127956-how-much-does-gpt-4-cost)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 33,\n \"id\": \"4e67af85\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"Total Tokens: 1768\\n\",\n \"Prompt Tokens: 1757\\n\",\n \"Completion Tokens: 11\\n\",\n \"Successful Requests: 1\\n\",\n \"Total Cost (USD): $0.053369999999999994\\n\"\n ]\n }\n ],\n \"source\": [\n \"with get_openai_callback() as cb:\\n\",\n \" result = chain.predict_and_parse(text=text)\\n\",\n \" print(f\\\"Total Tokens: {cb.total_tokens}\\\")\\n\",\n \" print(f\\\"Prompt Tokens: {cb.prompt_tokens}\\\")\\n\",\n \" print(f\\\"Completion Tokens: {cb.completion_tokens}\\\")\\n\",\n \" print(f\\\"Successful Requests: {cb.successful_requests}\\\")\\n\",\n \" print(f\\\"Total Cost (USD): ${cb.total_cost}\\\")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"b770a9e8\",\n \"metadata\": {},\n \"source\": [\n \"Suggested To Do if you want to build this out:\\n\",\n \"\\n\",\n \"* Reduce amount of HTML and low-signal text that gets put into the prompt\\n\",\n \"* Gather list of 1000s of companies\\n\",\n \"* Run through most jobs (You'll likely start to see duplicate information after the first 10-15 jobs per department)\\n\",\n \"* Store results\\n\",\n \"* Snapshot daily as you look for new jobs\\n\",\n \"* Follow [Greg](https://twitter.com/GregKamradt) on Twitter for more tools or if you want to chat about this project\\n\",\n \"* Read the user feedback below for what else to build out with this project (I reached out to everyone who signed up on twitter)\\n\",\n \"\\n\",\n \"\\n\",\n \"### Business idea: Job Data As A Service\\n\",\n \"\\n\",\n \"Start a data service that collects information about company's jobs. This can be sold to investors looking for an edge.\\n\",\n \"\\n\",\n \"After posting [this tweet](https://twitter.com/GregKamradt/status/1643027796850253824) there were 80 people that signed up for the trial. I emailed all of them and most were job seekers looking for companies that used the tech they specialized in.\\n\",\n \"\\n\",\n \"The more interesting use case were sales teams + investors.\\n\",\n \"\\n\",\n \"#### Interesting User Feedback (Persona: Investor):\\n\",\n \"\\n\",\n \"> Hey Gregory, thanks for reaching out.

\\n\",\n \"I always thought that job posts were a gold mine of information, and often suggest identifying targets based on these (go look at relevant job posts for companies that might want to work with you). Secondly, I also automatically ping BuiltWith from our CRM and send that to OpenAI and have a summarized tech stack created - so I see the benefit of having this as an investor.

\\n\",\n \"For me personally, I like to get as much data as possible about a company. Would love to see job post cadence, type of jobs they post and when, notable keywords/phrases used, tech stack (which you have), and any other information we can glean from the job posts (sometimes they have the title of who you'll report to, etc.).

\\n\",\n \"For sales people, I think finer searches, maybe even in natural language if possible - such as \\\"search for companies who posted a data science related job for the first time\\\" - would be powerful.\\n\",\n \"\\n\",\n \"If you do this, let me know! I'd love to hear how it goes.\"\n ]\n }\n ],\n \"metadata\": {\n \"kernelspec\": {\n \"display_name\": \"Python 3 (ipykernel)\",\n \"language\": \"python\",\n \"name\": \"python3\"\n },\n \"language_info\": {\n \"codemirror_mode\": {\n \"name\": \"ipython\",\n \"version\": 3\n },\n \"file_extension\": \".py\",\n \"mimetype\": \"text/x-python\",\n \"name\": \"python\",\n \"nbconvert_exporter\": \"python\",\n \"pygments_lexer\": \"ipython3\",\n \"version\": \"3.9.13\"\n }\n },\n \"nbformat\": 4,\n \"nbformat_minor\": 5\n}\n" }, { "path": "data_generation/Exploring ChatGPT Function Calling.ipynb", "content": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"id\": \"7ce8bc84\",\n \"metadata\": {},\n \"source\": [\n \"# Function Calling with OpenAI's GPT Models: An Interactive Tutorial\\n\",\n \"\\n\",\n \"In this notebook, we'll dive deep into a powerful feature offered by the latest versions of OpenAI's GPT models (like gpt-3.5-turbo-0613 and gpt-4-0613): function calling.\\n\",\n \"\\n\",\n \"Let's imagine you're talking to a ChatGPT model and you want to have it use a tool. Traditionally you'd have to do some clever prompting to have it return the format you'd like.\\n\",\n \"\\n\",\n \"Now you can tell it about certain actions, or **\\\"functions\\\"**, it can take\\n\",\n \"\\n\",\n \"This doesn't mean the assistant actually performs these actions. Rather, it's aware of them and can instruct you on how to perform these actions based on the conversation at hand.\\n\",\n \"\\n\",\n \"For example, you can tell the assistant about a function that fetches weather data, and when asked \\\"What's the weather like in Boston?\\\", the assistant can reply with instructions on how to call this weather-fetching function with 'Boston' as the input.\\n\",\n \"\\n\",\n \"**Function calling** enables us to leverage the model's natural language understanding to effectively turn human language into structured data or specific function calls in our code.\\n\",\n \"\\n\",\n \"This capability is useful in numerous scenarios, from creating chatbots that can interact with other APIs, to automating tasks and extracting structured information from natural language inputs. See more information about [function calling](https://platform.openai.com/docs/guides/gpt/function-calling)\\n\",\n \"\\n\",\n \"Let's explore and start by importing our packages\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 1,\n \"id\": \"d8042fc3\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# !pip install langchain --upgrade\\n\",\n \"# Version: 0.0.199 Make sure you're on the latest version\\n\",\n \"\\n\",\n \"import langchain\\n\",\n \"import openai\\n\",\n \"import json\\n\",\n \"\\n\",\n \"# Environment Variables\\n\",\n \"import os\\n\",\n \"from dotenv import load_dotenv\\n\",\n \"\\n\",\n \"load_dotenv()\\n\",\n \"\\n\",\n \"openai.api_key = os.getenv('OPENAI_API_KEY', 'YourAPIKeyIfNotSet')\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"3ea3650a\",\n \"metadata\": {},\n \"source\": [\n \"## OpenAI Vanilla Example\\n\",\n \"\\n\",\n \"Let's run through OpenAI's vanilla example of calling a weather API.\\n\",\n \"\\n\",\n \"First let's define our functions. This is the meat and potatoes of the new update\\n\",\n \"\\n\",\n \"Functions are specified with the following fields:\\n\",\n \"\\n\",\n \"* **Name:** The name of the function.\\n\",\n \"* **Description:** A description of what the function does. The model will use this to decide when to call the function.\\n\",\n \"* **Parameters:** The parameters object contains all of the input fields the function requires. These inputs can be of the following types: String, Number, Boolean, Object, Null, AnyOf. Refer to the API reference docs for details.\\n\",\n \"* **Required:** Which of the parameters are required to make a query. The rest will be treated as optional.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 2,\n \"id\": \"3bd25223\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"function_descriptions = [\\n\",\n \" {\\n\",\n \" \\\"name\\\": \\\"get_current_weather\\\",\\n\",\n \" \\\"description\\\": \\\"Get the current weather in a given location\\\",\\n\",\n \" \\\"parameters\\\": {\\n\",\n \" \\\"type\\\": \\\"object\\\",\\n\",\n \" \\\"properties\\\": {\\n\",\n \" \\\"location\\\": {\\n\",\n \" \\\"type\\\": \\\"string\\\",\\n\",\n \" \\\"description\\\": \\\"The city and state, e.g. San Francisco, CA\\\",\\n\",\n \" },\\n\",\n \" \\\"unit\\\": {\\n\",\n \" \\\"type\\\": \\\"string\\\",\\n\",\n \" \\\"description\\\": \\\"The temperature unit to use. Infer this from the users location.\\\",\\n\",\n \" \\\"enum\\\": [\\\"celsius\\\", \\\"fahrenheit\\\"]\\n\",\n \" },\\n\",\n \" },\\n\",\n \" \\\"required\\\": [\\\"location\\\", \\\"unit\\\"],\\n\",\n \" },\\n\",\n \" }\\n\",\n \" ]\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"1bdb85b0\",\n \"metadata\": {},\n \"source\": [\n \"Then let's call the OpenAI API with this as a new parameter. Note: Make sure to use a model that can accept the function call. Here we are using `gpt-3.5-turbo-0613`.\\n\",\n \"\\n\",\n \"Let's first set a query that came from the user\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 3,\n \"id\": \"1afea666\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"user_query = \\\"What's the weather like in San Francisco?\\\"\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"443aee72\",\n \"metadata\": {},\n \"source\": [\n \"Then let's set up our API call to OpenAI. Note: `function_call=\\\"auto\\\"` will allow the model to choose whether or not it responds with a function. You can set this to `none` if you *don't* want a function response\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 4,\n \"id\": \"6a565cf6\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"response = openai.ChatCompletion.create(\\n\",\n \" model=\\\"gpt-4-0613\\\",\\n\",\n \" \\n\",\n \" # This is the chat message from the user\\n\",\n \" messages=[{\\\"role\\\": \\\"user\\\", \\\"content\\\": user_query}],\\n\",\n \" \\n\",\n \" \\n\",\n \" functions=function_descriptions,\\n\",\n \" function_call=\\\"auto\\\",\\n\",\n \" )\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"9344b392\",\n \"metadata\": {},\n \"source\": [\n \"Great, let's take a look at the response\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 10,\n \"id\": \"d5067356\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"{\\n\",\n \" \\\"content\\\": null,\\n\",\n \" \\\"function_call\\\": {\\n\",\n \" \\\"arguments\\\": \\\"{\\\\n \\\\\\\"location\\\\\\\": \\\\\\\"San Francisco, CA\\\\\\\",\\\\n \\\\\\\"unit\\\\\\\": \\\\\\\"fahrenheit\\\\\\\"\\\\n}\\\",\\n\",\n \" \\\"name\\\": \\\"get_current_weather\\\"\\n\",\n \" },\\n\",\n \" \\\"role\\\": \\\"assistant\\\"\\n\",\n \"}\\n\"\n ]\n }\n ],\n \"source\": [\n \"ai_response_message = response[\\\"choices\\\"][0][\\\"message\\\"]\\n\",\n \"print(ai_response_message)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"c158975c\",\n \"metadata\": {},\n \"source\": [\n \"Awesome, now we have our response w/ specific arguments called out.\\n\",\n \"\\n\",\n \"Let's clean up our response a bit better\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 11,\n \"id\": \"04ada914\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"user_location = eval(ai_response_message['function_call']['arguments']).get(\\\"location\\\")\\n\",\n \"user_unit = eval(ai_response_message['function_call']['arguments']).get(\\\"unit\\\")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"bbc81e28\",\n \"metadata\": {},\n \"source\": [\n \"Then let's make a function that will serve as an interface to a dummy api call\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 12,\n \"id\": \"a7e4fe28\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"def get_current_weather(location, unit):\\n\",\n \" \\n\",\n \" \\\"\\\"\\\"Get the current weather in a given location\\\"\\\"\\\"\\n\",\n \" \\n\",\n \" weather_info = {\\n\",\n \" \\\"location\\\": location,\\n\",\n \" \\\"temperature\\\": \\\"72\\\",\\n\",\n \" \\\"unit\\\": unit,\\n\",\n \" \\\"forecast\\\": [\\\"sunny\\\", \\\"windy\\\"],\\n\",\n \" }\\n\",\n \" return json.dumps(weather_info)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 13,\n \"id\": \"505806ea\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"function_response = get_current_weather(\\n\",\n \" location=user_location,\\n\",\n \" unit=user_unit,\\n\",\n \")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 14,\n \"id\": \"6c24e71c\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"'{\\\"location\\\": \\\"San Francisco, CA\\\", \\\"temperature\\\": \\\"72\\\", \\\"unit\\\": \\\"fahrenheit\\\", \\\"forecast\\\": [\\\"sunny\\\", \\\"windy\\\"]}'\"\n ]\n },\n \"execution_count\": 14,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"function_response\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"89694ba3\",\n \"metadata\": {},\n \"source\": [\n \"Now that we have our reponse from our service, we can pass this information back to our model for a natural language response\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 15,\n \"id\": \"2c4a5c78\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"second_response = openai.ChatCompletion.create(\\n\",\n \" model=\\\"gpt-4-0613\\\",\\n\",\n \" messages=[\\n\",\n \" {\\\"role\\\": \\\"user\\\", \\\"content\\\": user_query},\\n\",\n \" ai_response_message,\\n\",\n \" {\\n\",\n \" \\\"role\\\": \\\"function\\\",\\n\",\n \" \\\"name\\\": \\\"get_current_weather\\\",\\n\",\n \" \\\"content\\\": function_response,\\n\",\n \" },\\n\",\n \" ],\\n\",\n \")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 17,\n \"id\": \"e4020764\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"Currently in San Francisco, CA the weather is sunny and windy with a temperature of 72°F.\\n\"\n ]\n }\n ],\n \"source\": [\n \"print (second_response['choices'][0]['message']['content'])\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"519f57b4\",\n \"metadata\": {},\n \"source\": [\n \"## LangChain Support For Functions\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 18,\n \"id\": \"1d3f216d\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain.chat_models import ChatOpenAI\\n\",\n \"from langchain.schema import HumanMessage, AIMessage, ChatMessage\\n\",\n \"from langchain.tools import format_tool_to_openai_function, YouTubeSearchTool, MoveFileTool\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"c30ea30c\",\n \"metadata\": {},\n \"source\": [\n \"Let's load up our models\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 19,\n \"id\": \"d4aa0e58\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"llm = ChatOpenAI(model=\\\"gpt-4-0613\\\")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"fd72917e\",\n \"metadata\": {},\n \"source\": [\n \"Let's load our tools and then transform them into OpenAI's function framework\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 20,\n \"id\": \"93b8f50a\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"tools = [MoveFileTool()]\\n\",\n \"functions = [format_tool_to_openai_function(t) for t in tools]\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"47e978c0\",\n \"metadata\": {},\n \"source\": [\n \"Let's take a look at what this tool was transformed as\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 21,\n \"id\": \"4b56cdc6\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"[{'name': 'move_file',\\n\",\n \" 'description': 'Move or rename a file from one location to another',\\n\",\n \" 'parameters': {'title': 'FileMoveInput',\\n\",\n \" 'description': 'Input for MoveFileTool.',\\n\",\n \" 'type': 'object',\\n\",\n \" 'properties': {'source_path': {'title': 'Source Path',\\n\",\n \" 'description': 'Path of the file to move',\\n\",\n \" 'type': 'string'},\\n\",\n \" 'destination_path': {'title': 'Destination Path',\\n\",\n \" 'description': 'New path for the moved file',\\n\",\n \" 'type': 'string'}},\\n\",\n \" 'required': ['source_path', 'destination_path']}}]\"\n ]\n },\n \"execution_count\": 21,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"functions\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 26,\n \"id\": \"aff6280a\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"message = llm.predict_messages([HumanMessage(content='move file foo to bar')], functions=functions)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 28,\n \"id\": \"adf61d07\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"{'name': 'move_file',\\n\",\n \" 'arguments': '{\\\\n \\\"source_path\\\": \\\"foo\\\",\\\\n \\\"destination_path\\\": \\\"bar\\\"\\\\n}'}\"\n ]\n },\n \"execution_count\": 28,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"message.additional_kwargs['function_call']\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"4d139846\",\n \"metadata\": {},\n \"source\": [\n \"### Ad Hoc Example Financial Forecast Edit\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"12fd005b\",\n \"metadata\": {},\n \"source\": [\n \"I'm going to make a new function description that talks about updating a financial model. It'll take 3 params, year to update, category to update, and amount to update.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 29,\n \"id\": \"fed0f289\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"function_descriptions = [\\n\",\n \" {\\n\",\n \" \\\"name\\\": \\\"edit_financial_forecast\\\",\\n\",\n \" \\\"description\\\": \\\"Make an edit to a users financial forecast model\\\",\\n\",\n \" \\\"parameters\\\": {\\n\",\n \" \\\"type\\\": \\\"object\\\",\\n\",\n \" \\\"properties\\\": {\\n\",\n \" \\\"year\\\": {\\n\",\n \" \\\"type\\\": \\\"integer\\\",\\n\",\n \" \\\"description\\\": \\\"The year the user would like to make an edit to their forecast for\\\",\\n\",\n \" },\\n\",\n \" \\\"category\\\": {\\n\",\n \" \\\"type\\\": \\\"string\\\",\\n\",\n \" \\\"description\\\": \\\"The category of the edit a user would like to edit\\\"\\n\",\n \" },\\n\",\n \" \\\"amount\\\": {\\n\",\n \" \\\"type\\\": \\\"integer\\\",\\n\",\n \" \\\"description\\\": \\\"The amount of units the user would like to change\\\"\\n\",\n \" },\\n\",\n \" },\\n\",\n \" \\\"required\\\": [\\\"year\\\", \\\"category\\\", \\\"amount\\\"],\\n\",\n \" },\\n\",\n \" },\\n\",\n \" {\\n\",\n \" \\\"name\\\": \\\"print_financial_forecast\\\",\\n\",\n \" \\\"description\\\": \\\"Send the financial forecast to the printer\\\",\\n\",\n \" \\\"parameters\\\": {\\n\",\n \" \\\"type\\\": \\\"object\\\",\\n\",\n \" \\\"properties\\\": {\\n\",\n \" \\\"printer_name\\\": {\\n\",\n \" \\\"type\\\": \\\"string\\\",\\n\",\n \" \\\"description\\\": \\\"the name of the printer that the forecast should be sent to\\\",\\n\",\n \" \\\"enum\\\": [\\\"home_printer\\\", \\\"office_printer\\\"]\\n\",\n \" }\\n\",\n \" },\\n\",\n \" \\\"required\\\": [\\\"printer_name\\\"],\\n\",\n \" },\\n\",\n \" }\\n\",\n \" ]\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"2d43c0db\",\n \"metadata\": {},\n \"source\": [\n \"One of the cool parts about OpenAI's new function calls is that the LLM will decide if it should return a normal response to a user, or call the function again. Let's test this out with two different requests in the same query from the user\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 30,\n \"id\": \"1d8033c7\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"user_request = \\\"\\\"\\\"\\n\",\n \"Please do three things add 40 units to 2023 headcount\\n\",\n \"and subtract 23 units from 2022 opex\\n\",\n \"then print out the forecast at my home\\n\",\n \"\\\"\\\"\\\"\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"255d1c12\",\n \"metadata\": {},\n \"source\": [\n \"We are going to keep track of the message history ourselves. As more support for function conversations comes in we won't need to do this.\\n\",\n \"\\n\",\n \"First we'll send the message from the user to the LLM along with our function calls\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 31,\n \"id\": \"ddc46318\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"AIMessage(content='', additional_kwargs={'function_call': {'name': 'edit_financial_forecast', 'arguments': '{\\\\n \\\"year\\\": 2023,\\\\n \\\"category\\\": \\\"headcount\\\",\\\\n \\\"amount\\\": 40\\\\n}'}}, example=False)\"\n ]\n },\n \"execution_count\": 31,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"first_response = llm.predict_messages([HumanMessage(content=user_request)],\\n\",\n \" functions=function_descriptions)\\n\",\n \"first_response\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"8e81d80b\",\n \"metadata\": {},\n \"source\": [\n \"As you can see we get an AIMessage back with no content. However there are `additoinal_kwargs` with the information that we need. Let's pull these out to have a better look at them\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 32,\n \"id\": \"7722f24d\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"{'function_call': {'name': 'edit_financial_forecast',\\n\",\n \" 'arguments': '{\\\\n \\\"year\\\": 2023,\\\\n \\\"category\\\": \\\"headcount\\\",\\\\n \\\"amount\\\": 40\\\\n}'}}\"\n ]\n },\n \"execution_count\": 32,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"first_response.additional_kwargs\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 33,\n \"id\": \"bb754ed6\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"'edit_financial_forecast'\"\n ]\n },\n \"execution_count\": 33,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"function_name = first_response.additional_kwargs[\\\"function_call\\\"][\\\"name\\\"]\\n\",\n \"function_name\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"9b25db0b\",\n \"metadata\": {},\n \"source\": [\n \"Then print the arguments it gives back to us\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 34,\n \"id\": \"172de619\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"\\n\",\n \"Year: 2023\\n\",\n \"Category: headcount\\n\",\n \"Amount: 40\\n\",\n \"\\n\"\n ]\n }\n ],\n \"source\": [\n \"print (f\\\"\\\"\\\"\\n\",\n \"Year: {eval(first_response.additional_kwargs['function_call']['arguments']).get('year')}\\n\",\n \"Category: {eval(first_response.additional_kwargs['function_call']['arguments']).get('category')}\\n\",\n \"Amount: {eval(first_response.additional_kwargs['function_call']['arguments']).get('amount')}\\n\",\n \"\\\"\\\"\\\")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"912a08ca\",\n \"metadata\": {},\n \"source\": [\n \"But we aren't done! There was a second request in the user query so let's pass it back into the model\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 36,\n \"id\": \"daa08ebf\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"second_response = llm.predict_messages([HumanMessage(content=user_request),\\n\",\n \" AIMessage(content=str(first_response.additional_kwargs)),\\n\",\n \" ChatMessage(role='function',\\n\",\n \" additional_kwargs = {'name': function_name},\\n\",\n \" content = \\\"Just updated the financial forecast for year 2023, category headcount amd amount 40\\\"\\n\",\n \" )\\n\",\n \" ],\\n\",\n \" functions=function_descriptions)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"6a748f6b\",\n \"metadata\": {},\n \"source\": [\n \"Let's see the response from this one\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 37,\n \"id\": \"a015c49e\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"{'function_call': {'name': 'edit_financial_forecast',\\n\",\n \" 'arguments': '{\\\\n \\\"year\\\": 2022,\\\\n \\\"category\\\": \\\"opex\\\",\\\\n \\\"amount\\\": -23\\\\n}'}}\"\n ]\n },\n \"execution_count\": 37,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"second_response.additional_kwargs\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 38,\n \"id\": \"41c8bab8\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"'edit_financial_forecast'\"\n ]\n },\n \"execution_count\": 38,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"function_name = second_response.additional_kwargs['function_call']['name']\\n\",\n \"function_name\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"74df9449\",\n \"metadata\": {},\n \"source\": [\n \"Cool! It saw that the first response was done and then it went back to our function for us. Let's see what it says if we do it a third time\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 39,\n \"id\": \"ff0cabd3\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"third_response = llm.predict_messages([HumanMessage(content=user_request),\\n\",\n \" AIMessage(content=str(first_response.additional_kwargs)),\\n\",\n \" AIMessage(content=str(second_response.additional_kwargs)),\\n\",\n \" ChatMessage(role='function',\\n\",\n \" additional_kwargs = {'name': function_name},\\n\",\n \" content = \\\"\\\"\\\"\\n\",\n \" Just made the following updates: 2022, opex -23 and\\n\",\n \" Year: 2023\\n\",\n \" Category: headcount\\n\",\n \" Amount: 40\\n\",\n \" \\\"\\\"\\\"\\n\",\n \" )\\n\",\n \" ],\\n\",\n \" functions=function_descriptions)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 40,\n \"id\": \"4ee505df\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"{'function_call': {'name': 'print_financial_forecast',\\n\",\n \" 'arguments': '{\\\\n \\\"printer_name\\\": \\\"home_printer\\\"\\\\n}'}}\"\n ]\n },\n \"execution_count\": 40,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"third_response.additional_kwargs\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 42,\n \"id\": \"aa33a75c\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"'print_financial_forecast'\"\n ]\n },\n \"execution_count\": 42,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"function_name = third_response.additional_kwargs['function_call']['name']\\n\",\n \"function_name\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"ea1875f2\",\n \"metadata\": {},\n \"source\": [\n \"Nice! So it knew it was done with the financial forecasts (because we told it so) and then it sent our forecast to our home printer. Let's close it out\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 43,\n \"id\": \"b46f67ee\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"forth_response = llm.predict_messages([HumanMessage(content=user_request),\\n\",\n \" AIMessage(content=str(first_response.additional_kwargs)),\\n\",\n \" AIMessage(content=str(second_response.additional_kwargs)),\\n\",\n \" AIMessage(content=str(third_response.additional_kwargs)),\\n\",\n \" ChatMessage(role='function',\\n\",\n \" additional_kwargs = {'name': function_name},\\n\",\n \" content = \\\"\\\"\\\"\\n\",\n \" just printed the document at home\\n\",\n \" \\\"\\\"\\\"\\n\",\n \" )\\n\",\n \" ],\\n\",\n \" functions=function_descriptions)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 44,\n \"id\": \"0bfd8982\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"'I have updated the financial forecast as per your instructions. It has also been printed at your home.'\"\n ]\n },\n \"execution_count\": 44,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"forth_response.content\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"id\": \"11a9d1e0\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": []\n }\n ],\n \"metadata\": {\n \"kernelspec\": {\n \"display_name\": \"Python 3 (ipykernel)\",\n \"language\": \"python\",\n \"name\": \"python3\"\n },\n \"language_info\": {\n \"codemirror_mode\": {\n \"name\": \"ipython\",\n \"version\": 3\n },\n \"file_extension\": \".py\",\n \"mimetype\": \"text/x-python\",\n \"name\": \"python\",\n \"nbconvert_exporter\": \"python\",\n \"pygments_lexer\": \"ipython3\",\n \"version\": \"3.9.13\"\n }\n },\n \"nbformat\": 4,\n \"nbformat_minor\": 5\n}\n" }, { "path": "data_generation/Instructing LLMs To Match Tone.ipynb", "content": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"id\": \"72d39d60\",\n \"metadata\": {},\n \"source\": [\n \"# Instructing LLMs To Match Tone\\n\",\n \"\\n\",\n \"LLMs that generate text are awesome, but what if you want to edit the tone/style it responds with?\\n\",\n \"\\n\",\n \"We've all seen the [pirate](https://python.langchain.com/en/latest/modules/agents/agents/custom_llm_agent.html#:~:text=template%20%3D%20%22%22%22Answer%20the%20following%20questions%20as%20best%20you%20can%2C%20but%20speaking%20as%20a%20pirate%20might%20speak.%20You%20have%20access%20to%20the%20following%20tools%3A) examples, but it would be awesome if we could tune the prompt to match the tone of specific people?\\n\",\n \"\\n\",\n \"Below is a series of techniques aimed to generate text in the tone and style you want. No single technique will likely be *exactly* what you need, but I guarantee you can iterate with these tips to get a solid outcome for your project.\\n\",\n \"\\n\",\n \"But Greg, what about fine tuning? Fine tuning would likely give you a fabulous result, but the barriers to entry are too high for the average developer (as of May '23). I would rather get the 87% solution today rather than not ship something. If you're doing this in production and your differentiator is your ability to adapt to different styles you'll likely want to explore fine tuning.\\n\",\n \"\\n\",\n \"If you want to see a demo video of this, check out the Twitter post. For a full explination head over to YouTube.\\n\",\n \"\\n\",\n \"### 4 Levels Of Tone Matching Techniques:\\n\",\n \"1. **Simple:** As a human, try and describe the tone you would like\\n\",\n \"2. **Intermediate:** Include your description + examples\\n\",\n \"3. **AI-Assisted:** Ask the LLM to extract tone, use their output in your next prompt\\n\",\n \"4. **Technique Fusion:** Combine multiple techniques to mimic tone\\n\",\n \"\\n\",\n \"**Today's Goal**: Generate tweets mimicking the style of online personalities. You could customize this code to generate emails, chat messages, writing, etc.\\n\",\n \"\\n\",\n \"First let's import our packages\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 1,\n \"id\": \"e65bd69a\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"True\"\n ]\n },\n \"execution_count\": 1,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"# LangChain\\n\",\n \"from langchain.chat_models import ChatOpenAI\\n\",\n \"from langchain import PromptTemplate\\n\",\n \"\\n\",\n \"# Environment Variables\\n\",\n \"import os\\n\",\n \"from dotenv import load_dotenv\\n\",\n \"\\n\",\n \"# Twitter\\n\",\n \"import tweepy\\n\",\n \"\\n\",\n \"load_dotenv()\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"83886158\",\n \"metadata\": {},\n \"source\": [\n \"Set your OpenAI key. You can either put it as an environment variable or in the string below\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 2,\n \"id\": \"98123655\",\n \"metadata\": {\n \"hide_input\": false\n },\n \"outputs\": [],\n \"source\": [\n \"openai_api_key = os.getenv('OPENAI_API_KEY', 'YourAPIKeyIfNotSet')\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"60e572c7\",\n \"metadata\": {},\n \"source\": [\n \"We'll be using `gpt-4` today, but you can swap out for `gpt-3.5-turbo` if you'd like\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 3,\n \"id\": \"063daa43\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"llm = ChatOpenAI(temperature=0, openai_api_key=openai_api_key, model_name='gpt-4')\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"c76a9b7c\",\n \"metadata\": {},\n \"source\": [\n \"## Method #1: Simple - Describe the tone you would like\\n\",\n \"\\n\",\n \"Our first method is going to be simply describing the tone we would like.\\n\",\n \"\\n\",\n \"Let's try a few exmaples\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 4,\n \"id\": \"0c852071\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"\\\"Sunshine, fresh air, and a scrumptious sandwich in hand 🥪🌳 Just had the perfect afternoon at the park, soaking up nature's beauty while munching on my favorite meal! #ParkPicnic #SandwichLover\\\"\\n\"\n ]\n }\n ],\n \"source\": [\n \"prompt = \\\"\\\"\\\"\\n\",\n \"Please create me a tweet about going to the park and eating a sandwich.\\n\",\n \"\\\"\\\"\\\"\\n\",\n \"\\n\",\n \"output = llm.predict(prompt)\\n\",\n \"print (output)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"4f31c440\",\n \"metadata\": {},\n \"source\": [\n \"Not bad, but I don't love the emojis and I want it to use more conversational modern language.\\n\",\n \"\\n\",\n \"Let's try again\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 5,\n \"id\": \"4ad1f61f\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"Had a fun day at the park today! I played on the swings and ate a yummy sandwich for lunch. I love spending time outside!\\n\"\n ]\n }\n ],\n \"source\": [\n \"prompt = \\\"\\\"\\\"\\n\",\n \"Please create me a tweet about going to the park and eating a sandwich.\\n\",\n \"\\n\",\n \"% TONE\\n\",\n \" - Don't use any emojis or hashtags.\\n\",\n \" - Use simple language a 5 year old would understand\\n\",\n \"\\\"\\\"\\\"\\n\",\n \"\\n\",\n \"output = llm.predict(prompt)\\n\",\n \"print (output)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"0b738fc0\",\n \"metadata\": {},\n \"source\": [\n \"Ok cool! The tone has changed. Not bad but now I want it to sound like a specific person. Let's try Bill Gates:\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 6,\n \"id\": \"aa86db95\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"There's something truly delightful about spending an afternoon at the park, enjoying a well-crafted sandwich, and contemplating the beauty of nature. It's a simple pleasure that reminds us of the importance of taking a break from our busy lives to appreciate the world around us.\\n\"\n ]\n }\n ],\n \"source\": [\n \"prompt = \\\"\\\"\\\"\\n\",\n \"Please create me a tweet about going to the park and eating a sandwich.\\n\",\n \"\\n\",\n \"% TONE\\n\",\n \" - Don't use any emojis or hashtags.\\n\",\n \" - Respond in the tone of Bill Gates\\n\",\n \"\\\"\\\"\\\"\\n\",\n \"\\n\",\n \"output = llm.predict(prompt)\\n\",\n \"print (output)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"cdf41f09\",\n \"metadata\": {},\n \"source\": [\n \"It's ok, I'd give the response a `C+` right now.\\n\",\n \"\\n\",\n \"Let's give some example tweets so the model can better match tone/style.\\n\",\n \"\\n\",\n \"`⭐ Important Tip: When you're giving examples, make sure to have the examples the same as the desired output format. Ex: Tweets > Tweets, Email > Email`. Don't do `Tweets > Email`\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"06265a43\",\n \"metadata\": {},\n \"source\": [\n \"## Method #2: Intermediate - Specify your tone description + examples\\n\",\n \"\\n\",\n \"Examples speak a thousand words. Let's pass a few along with our instructions to see how it goes\\n\",\n \"\\n\",\n \"### Get a users Tweets\\n\",\n \"\\n\",\n \"Next let's grab a users tweets. We'll do this in a function so it's easy to pull them later\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"6aef30ad\",\n \"metadata\": {},\n \"source\": [\n \"Since we are live Tweets, you'll need to grather some Twitter api keys. You can get these on the [Twitter Developer Portal](https://developer.twitter.com/en/portal/dashboard). The free tier is fine, but watch out for rate limits.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 7,\n \"id\": \"093d7162\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# Replace these values with your own Twitter API credentials\\n\",\n \"TWITTER_API_KEY = os.getenv('TWITTER_API_KEY', 'YourAPIKeyIfNotSet')\\n\",\n \"TWITTER_API_KEY_SECRET = os.getenv('TWITTER_API_KEY_SECRET', 'YourAPIKeyIfNotSet')\\n\",\n \"TWITTER_ACCESS_TOKEN = os.getenv('TWITTER_ACCESS_TOKEN', 'YourAPIKeyIfNotSet')\\n\",\n \"TWITTER_ACCESS_TOKEN_SECRET = os.getenv('TWITTER_ACCESS_TOKEN_SECRET', 'YourAPIKeyIfNotSet')\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 9,\n \"id\": \"9c2b68b9\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# We'll query 70 tweets because we end up filtering out a bunch, but we'll only return the top 12.\\n\",\n \"# We will also only use a subset of the top tweets later\\n\",\n \"def get_original_tweets(screen_name, tweets_to_pull=70, tweets_to_return=12):\\n\",\n \" \\n\",\n \" # Tweepy set up\\n\",\n \" auth = tweepy.OAuthHandler(TWITTER_API_KEY, TWITTER_API_KEY_SECRET)\\n\",\n \" auth.set_access_token(TWITTER_ACCESS_TOKEN, TWITTER_ACCESS_TOKEN_SECRET)\\n\",\n \" api = tweepy.API(auth)\\n\",\n \"\\n\",\n \" tweets = []\\n\",\n \" \\n\",\n \" tweepy_results = tweepy.Cursor(api.user_timeline,\\n\",\n \" screen_name=screen_name,\\n\",\n \" tweet_mode='extended',\\n\",\n \" exclude_replies=True).items(tweets_to_pull)\\n\",\n \" \\n\",\n \" # Run through tweets and remove retweets and quote tweets so we can only look at a user's raw emotions\\n\",\n \" for status in tweepy_results:\\n\",\n \" if not hasattr(status, 'retweeted_status') and not hasattr(status, 'quoted_status'):\\n\",\n \" tweets.append({'full_text': status.full_text, 'likes': status.favorite_count})\\n\",\n \"\\n\",\n \" \\n\",\n \" # Sort the tweets by number of likes. This will help us short_list the top ones later\\n\",\n \" sorted_tweets = sorted(tweets, key=lambda x: x['likes'], reverse=True)\\n\",\n \"\\n\",\n \" # Get the text and drop the like count from the dictionary\\n\",\n \" full_text = [x['full_text'] for x in sorted_tweets][:tweets_to_return]\\n\",\n \" \\n\",\n \" # Conver the list of tweets into a string of tweets we can use in the prompt later\\n\",\n \" example_tweets = \\\"\\\\n\\\\n\\\".join(full_text)\\n\",\n \" \\n\",\n \" return example_tweets\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"d6a8a9f9\",\n \"metadata\": {},\n \"source\": [\n \"Let's grab Bill Gates tweets and use those as examples\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 10,\n \"id\": \"e70a1173\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"user_screen_name = 'billgates' # Replace this with the desired user's screen name\\n\",\n \"users_tweets = get_original_tweets(user_screen_name)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"ac488978\",\n \"metadata\": {},\n \"source\": [\n \"Let's look at a sample of Bill's tweets\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 11,\n \"id\": \"38043e2c\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"These numbers prove why India plays such a crucial role in the world’s fight to improve health, reduce poverty, prevent climate change, and more. https://t.co/xMpmcoYQhi\\n\",\n \"\\n\",\n \"Mann ki Baat has catalyzed community led action on sanitation, health, women’s economic empowerment and other issues linked to the Sustainable Development Goals. Congratulations @narendramodi on the 100th episode. https://t.co/yg1Di2srjE\\n\",\n \"\\n\",\n \"The development of AI is as fundamental as the creation of the microprocessor, the personal computer, the Internet, and the mobile phone. It will change the way people work, learn, travel, get health care, and communicate with each other. https://t.co/uuaOQyxBTl\\n\",\n \"\\n\",\n \"I just returned from my visit to India, and I can’t wait to go back again. I love visiting India because every trip is an incredible opportunity to learn. Here are some photos from my trip and some of the stories behind them: https://t.co/We6PtJWDnp https://t.co/QxZW7gfUmI\\n\",\n \"\\n\",\n \"Superintelligent AIs are in our future. Compared to a computer, our brains operate at a snail’s pace. An electrical signal in the brain moves at ___________ the speed of the signal in a silicon chip. Check your answer here: https://t.co/wqZG1BdoTc\\n\",\n \"\\n\",\n \"Thinking of President Carter and his family. This is a lovely tribute to one of his biggest accomplishments. https://t.co/g53c4ty0qI\\n\",\n \"\\n\",\n \"Uganda’s maternal mortality rate is at least double the global average. That's why Eva Nangalo has dedicated her life to making childbirth in the country safer for everyone involved. https://t.co/29AjdJehNY\\n\",\n \"\\n\",\n \"I am so impressed with Eva Nangalo—it’s hard not to be. She’s spent decades making childbirth safer in Uganda for everyone involved, and she’s become a mentor to countless other midwives in the process. https://t.co/79RHbrCt01\\n\",\n \"\\n\",\n \"I recently had the chance to test drive—or test ride, I guess—one of @wayve_ai’s autonomous vehicles. It was a pretty wild ride: https://t.co/PrwrxU49dd https://t.co/NtnkVx7sBx\\n\",\n \"\\n\",\n \"When I transitioned from @Microsoft to working full-time at the @GatesFoundation, I finally had the time to learn more about physics, chemistry, biology, and other sciences. So, I looked around for the best books and read as many of them as I could find. https://t.co/z2D5xGSeMj\\n\",\n \"\\n\",\n \"As big as the problems facing the world are right now, my visit to India reminded me that our capacity to solve them is even bigger: https://t.co/zp7XfRIpV9 https://t.co/aFHUu987u3\\n\",\n \"\\n\",\n \"I’m grateful for the Lauder family’s dedication to solving Alzheimer’s. https://t.co/vX0qtjBFxt\\n\"\n ]\n }\n ],\n \"source\": [\n \"print(users_tweets)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"6765f2e5\",\n \"metadata\": {},\n \"source\": [\n \"### Pass the tweets as examples\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 12,\n \"id\": \"da9d25d8\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"\\n\",\n \"Please create me a tweet about going to the park and eating a sandwich.\\n\",\n \"\\n\",\n \"% TONE\\n\",\n \" - Don't use any emojis or hashtags.\\n\",\n \" - Respond in the tone of Bill Gates\\n\",\n \"\\n\",\n \"% START OF EXAMPLE TWEETS TO MIMIC\\n\",\n \"These numbers prove why India plays such a crucial role in the world’s fight to improve health, reduce poverty, prevent climate change, and more. https://t.co/xMpmcoYQhi\\n\",\n \"\\n\",\n \"Mann ki Baat has catalyzed community led action on sanitation, health, women’s economic empowerment and other issues linked to the Sustainable Development Goals. Congratulations @narendramodi on the 100th episode. https://t.co/yg1Di2srjE\\n\",\n \"\\n\",\n \"The development of AI is as fundamental as the creation of the microprocessor, the personal computer, the Internet, and the mobile phone. It will change the way people work, learn, travel, get health care, and communicate with each other. https://t.co/uuaOQyxBTl\\n\",\n \"\\n\",\n \"I just returned from my visit to India, and I can’t wait to go back again. I love visiting India because every trip is an incredible opportunity to learn. Here are some photos from my trip and some of the stories behind them: https://t.co/We6PtJWDnp https://t.co/QxZW7gfUmI\\n\",\n \"\\n\",\n \"Superintelligent AIs are in our future. Compared to a computer, our brains operate at a snail’s pace. An electrical signal in the brain moves at ___________ the speed of the signal in a silicon chip. Check your answer here: https://t.co/wqZG1BdoTc\\n\",\n \"\\n\",\n \"Thinking of President Carter and his family. This is a lovely tribute to one of his biggest accomplishments. https://t.co/g53c4ty0qI\\n\",\n \"\\n\",\n \"Uganda’s maternal mortality rate is at least double the global average. That's why Eva Nangalo has dedicated her life to making childbirth in the country safer for everyone involved. https://t.co/29AjdJehNY\\n\",\n \"\\n\",\n \"I am so impressed with Eva Nangalo—it’s hard not to be. She’s spent decades making childbirth safer in Uganda for everyone involved, and she’s become a mentor to countless other midwives in the process. https://t.co/79RHbrCt01\\n\",\n \"\\n\",\n \"I recently had the chance to test drive—or test ride, I guess—one of @wayve_ai’s autonomous vehicles. It was a pretty wild ride: https://t.co/PrwrxU49dd https://t.co/NtnkVx7sBx\\n\",\n \"\\n\",\n \"When I transitioned from @Microsoft to working full-time at the @GatesFoundation, I finally had the time to learn more about physics, chemistry, biology, and other sciences. So, I looked around for the best books and read as many of them as I could find. https://t.co/z2D5xGSeMj\\n\",\n \"\\n\",\n \"As big as the problems facing the world are right now, my visit to India reminded me that our capacity to solve them is even bigger: https://t.co/zp7XfRIpV9 https://t.co/aFHUu987u3\\n\",\n \"\\n\",\n \"I’m grateful for the Lauder family’s dedication to solving Alzheimer’s. https://t.co/vX0qtjBFxt\\n\",\n \"% END OF EXAMPLE TWEETS TO MIMIC\\n\",\n \"\\n\",\n \"YOUR TWEET:\\n\",\n \"\\n\"\n ]\n }\n ],\n \"source\": [\n \"template = \\\"\\\"\\\"\\n\",\n \"Please create me a tweet about going to the park and eating a sandwich.\\n\",\n \"\\n\",\n \"% TONE\\n\",\n \" - Don't use any emojis or hashtags.\\n\",\n \" - Respond in the tone of Bill Gates\\n\",\n \"\\n\",\n \"% START OF EXAMPLE TWEETS TO MIMIC\\n\",\n \"{example_tweets}\\n\",\n \"% END OF EXAMPLE TWEETS TO MIMIC\\n\",\n \"\\n\",\n \"YOUR TWEET:\\n\",\n \"\\\"\\\"\\\"\\n\",\n \"\\n\",\n \"prompt = PromptTemplate(\\n\",\n \" input_variables=[\\\"example_tweets\\\"],\\n\",\n \" template=template,\\n\",\n \")\\n\",\n \"\\n\",\n \"final_prompt = prompt.format(example_tweets=users_tweets)\\n\",\n \"\\n\",\n \"print (final_prompt)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 13,\n \"id\": \"8a7b8b12\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"A simple pleasure like visiting the park and enjoying a sandwich can remind us of the importance of preserving our environment and supporting local food systems. Let's continue to innovate for a sustainable future.\\n\"\n ]\n }\n ],\n \"source\": [\n \"output = llm.predict(final_prompt)\\n\",\n \"print (output)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"b65a69b5\",\n \"metadata\": {},\n \"source\": [\n \"Wow! Ok now that is starting to get somewhere. Not bad at all! Sounds like Bill is in the room with us now.\\n\",\n \"\\n\",\n \"Let's see if we can refine it even more.\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"afba6f42\",\n \"metadata\": {},\n \"source\": [\n \"## Method #3: AI-Assisted: Ask the LLM help with tone descriptions\\n\",\n \"\\n\",\n \"Turns out I'm not great at describing tone. Examples are a good way to help, but can we do more? Let's find out.\\n\",\n \"\\n\",\n \"I want to have the model tell me what tone *it* sees, then use that output as an *input* to the final prompt where I ask it to generate a tweet.\\n\",\n \"\\n\",\n \"Almost like reverse engineering tone.\\n\",\n \"\\n\",\n \"Why don't I do this all in one step? You likely could, but it would be nice to save this \\\"tone\\\" description for future use. Plus, I don't want the model to take too many logic jumps in a single response.\\n\",\n \"\\n\",\n \"I first thought, 'well... what are the qualities of tone I should have it describe?'\\n\",\n \"\\n\",\n \"Then I thought, Greg, c'mon man, you know better than that, see if the LLM has a good sense of what tone qualities there are. Duh.\\n\",\n \"\\n\",\n \"Let's see what are the qualities of tone we should extract\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 14,\n \"id\": \"20ee37ac\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"1. Pace: The speed at which the story unfolds and events occur.\\n\",\n \"2. Mood: The overall emotional atmosphere or feeling of the piece.\\n\",\n \"3. Tone: The author's attitude towards the subject matter or characters.\\n\",\n \"4. Voice: The unique style and personality of the author as it comes through in the writing.\\n\",\n \"5. Diction: The choice of words and phrases used by the author.\\n\",\n \"6. Syntax: The arrangement of words and phrases to create well-formed sentences.\\n\",\n \"7. Imagery: The use of vivid and descriptive language to create mental images for the reader.\\n\",\n \"8. Theme: The central idea or message of the piece.\\n\",\n \"9. Point of View: The perspective from which the story is told (first person, third person, etc.).\\n\",\n \"10. Structure: The organization and arrangement of the piece, including its chapters, sections, or stanzas.\\n\",\n \"11. Dialogue: The conversations between characters in the piece.\\n\",\n \"12. Characterization: The way the author presents and develops characters in the story.\\n\",\n \"13. Setting: The time and place in which the story takes place.\\n\",\n \"14. Foreshadowing: The use of hints or clues to suggest future events in the story.\\n\",\n \"15. Irony: The use of words or situations to convey a meaning that is opposite of its literal meaning.\\n\",\n \"16. Symbolism: The use of objects, characters, or events to represent abstract ideas or concepts.\\n\",\n \"17. Allusion: A reference to another work of literature, person, or event within the piece.\\n\",\n \"18. Conflict: The struggle between opposing forces or characters in the story.\\n\",\n \"19. Suspense: The tension or excitement created by uncertainty about what will happen next in the story.\\n\",\n \"20. Climax: The turning point or most intense moment in the story.\\n\",\n \"21. Resolution: The conclusion of the story, where conflicts are resolved and loose ends are tied up.\\n\"\n ]\n }\n ],\n \"source\": [\n \"prompt = \\\"\\\"\\\"\\n\",\n \"Can you please generate a list of tone attributes and a description to describe a piece of writing by?\\n\",\n \"\\n\",\n \"Things like pace, mood, etc.\\n\",\n \"\\n\",\n \"Respond with nothing else besides the list\\n\",\n \"\\\"\\\"\\\"\\n\",\n \"\\n\",\n \"how_to_describe_tone = llm.predict(prompt)\\n\",\n \"print (how_to_describe_tone)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"fd75f2c0\",\n \"metadata\": {},\n \"source\": [\n \"Ok great! Now that we have a solid list of ideas on how to instruct our language model for tone. Let's do some tone extraction!\\n\",\n \"\\n\",\n \"I found that when I asked the model for a description of the tone it would be passive and noncommittal so I included a line in the prompt about taking an active voice \"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 15,\n \"id\": \"8b1a75c5\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"def get_authors_tone_description(how_to_describe_tone, users_tweets):\\n\",\n \" template = \\\"\\\"\\\"\\n\",\n \" You are an AI Bot that is very good at generating writing in a similar tone as examples.\\n\",\n \" Be opinionated and have an active voice.\\n\",\n \" Take a strong stance with your response.\\n\",\n \"\\n\",\n \" % HOW TO DESCRIBE TONE\\n\",\n \" {how_to_describe_tone}\\n\",\n \"\\n\",\n \" % START OF EXAMPLES\\n\",\n \" {tweet_examples}\\n\",\n \" % END OF EXAMPLES\\n\",\n \"\\n\",\n \" List out the tone qualities of the examples above\\n\",\n \" \\\"\\\"\\\"\\n\",\n \"\\n\",\n \" prompt = PromptTemplate(\\n\",\n \" input_variables=[\\\"how_to_describe_tone\\\", \\\"tweet_examples\\\"],\\n\",\n \" template=template,\\n\",\n \" )\\n\",\n \"\\n\",\n \" final_prompt = prompt.format(how_to_describe_tone=how_to_describe_tone, tweet_examples=users_tweets)\\n\",\n \"\\n\",\n \" authors_tone_description = llm.predict(final_prompt)\\n\",\n \"\\n\",\n \" return authors_tone_description\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"f7dfbe6a\",\n \"metadata\": {},\n \"source\": [\n \"Let's combine the tone description and examples to see what tone attributes the model assigned to Bill Gates\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 19,\n \"id\": \"183464e3\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"1. Pace: Moderate, allowing for thoughtful reflection on the topics discussed.\\n\",\n \"2. Mood: Optimistic and enthusiastic, highlighting positive aspects and potential solutions.\\n\",\n \"3. Tone: Engaging and informative, with a strong emphasis on personal experiences and opinions.\\n\",\n \"4. Voice: Confident and authoritative, showcasing expertise and passion for the subjects.\\n\",\n \"5. Diction: Clear and concise, using accessible language to convey complex ideas.\\n\",\n \"6. Syntax: Straightforward and well-structured sentences, making the content easy to follow.\\n\",\n \"7. Imagery: Evocative and descriptive, painting vivid pictures of experiences and situations.\\n\",\n \"8. Theme: Focused on innovation, progress, and the potential for positive change.\\n\",\n \"9. Point of View: First person, providing a personal perspective on the topics discussed.\\n\",\n \"10. Structure: Organized and coherent, with a logical flow of ideas and information.\\n\",\n \"11. Dialogue: Limited, but when present, it is engaging and relevant to the topic.\\n\",\n \"12. Characterization: Presents individuals in a positive light, emphasizing their dedication and achievements.\\n\",\n \"13. Setting: Global, with a focus on specific countries or regions where progress is being made.\\n\",\n \"14. Foreshadowing: Hints at future developments and breakthroughs in various fields.\\n\",\n \"15. Irony: Minimal, as the focus is on genuine progress and optimism.\\n\",\n \"16. Symbolism: Limited, with more emphasis on real-world examples and achievements.\\n\",\n \"17. Allusion: Occasional references to other works, events, or individuals to provide context or support.\\n\",\n \"18. Conflict: Implicit, as the challenges faced by humanity are the driving force behind the discussed innovations and solutions.\\n\",\n \"19. Suspense: Minimal, as the focus is on sharing information and insights rather than creating tension.\\n\",\n \"20. Climax: Not applicable, as the content is primarily informative and opinion-based.\\n\",\n \"21. Resolution: Concludes with a sense of hope and optimism for the future, as well as a call to action for continued progress.\\n\"\n ]\n }\n ],\n \"source\": [\n \"authors_tone_description = get_authors_tone_description(how_to_describe_tone, users_tweets)\\n\",\n \"print (authors_tone_description)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"8eeead41\",\n \"metadata\": {},\n \"source\": [\n \"Great, now that we have Bill Gate's tone style, let's put those tone instructions in with the prompt we had before to see if it helps\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 20,\n \"id\": \"a99dee96\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"template = \\\"\\\"\\\"\\n\",\n \"% INSTRUCTIONS\\n\",\n \" - You are an AI Bot that is very good at mimicking an author writing style.\\n\",\n \" - Your goal is to write content with the tone that is described below.\\n\",\n \" - Do not go outside the tone instructions below\\n\",\n \" - Do not use hashtags or emojis\\n\",\n \" - Respond in the tone of Bill Gates\\n\",\n \"\\n\",\n \"% Description of the authors tone:\\n\",\n \"{authors_tone_description}\\n\",\n \"\\n\",\n \"% Authors writing samples\\n\",\n \"{tweet_examples}\\n\",\n \"\\n\",\n \"% YOUR TASK\\n\",\n \"Please create a tweet about going to the park and eating a sandwich.\\n\",\n \"\\\"\\\"\\\"\\n\",\n \"\\n\",\n \"prompt = PromptTemplate(\\n\",\n \" input_variables=[\\\"authors_tone_description\\\", \\\"tweet_examples\\\"],\\n\",\n \" template=template,\\n\",\n \")\\n\",\n \"\\n\",\n \"final_prompt = prompt.format(authors_tone_description=authors_tone_description, tweet_examples=users_tweets)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 21,\n \"id\": \"d7b48094\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stderr\",\n \"output_type\": \"stream\",\n \"text\": [\n \"Retrying langchain.chat_models.openai.ChatOpenAI.completion_with_retry.._completion_with_retry in 1.0 seconds as it raised RateLimitError: The server is currently overloaded with other requests. Sorry about that! You can retry your request, or contact us through our help center at help.openai.com if the error persists..\\n\"\n ]\n },\n {\n \"data\": {\n \"text/plain\": [\n \"\\\"I recently took a leisurely stroll through the park, enjoying the beauty of nature and savoring a delicious sandwich. It's moments like these that remind us of the simple pleasures in life and inspire us to continue working towards a brighter future for all. https://t.co/9YzF8KJ6rP\\\"\"\n ]\n },\n \"execution_count\": 21,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"llm.predict(final_prompt)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"f289c285\",\n \"metadata\": {},\n \"source\": [\n \"Hmm, better! Not wonderful.\\n\",\n \"\\n\",\n \"Let's try out the final approach\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"c00fe80b\",\n \"metadata\": {},\n \"source\": [\n \"## Method 4 - **Technique Fusion:** Combine multiple techniques to mimic tone\\n\",\n \"\\n\",\n \"After a lot of experimentation I've found the below tips to be helpful\\n\",\n \"\\n\",\n \"* **Don't reference the word 'tweet' in your prompt** - The model has an extremely strong bias towards what a 'tweet' is an will overload you with hashtags and emojis. Rather call it \\\"a short public statement around 300 characters\\\"\\n\",\n \"* **Ask the LLM for similar sounding authors** - Whereas model bias on the word 'tweet' (point #1) isn't great, we can use it in our favor. Ask the LLM which authors the writing style sounds like, then ask the LLM to respond like that author. It's not great that the model is basing the tone off *another* person but it's a great 89% solution. I learned of this technique from [Scott Mitchell](https://twitter.com/mitchell360/status/1657909800389464064).\\n\",\n \"* **Examples should be in the output format you want** - Everyone has a different voice. Twitter voice, email voice etc. Make sure that the examples you feed to the prompt are the same voice as the output you want. Ex: Don't exect a book to be written from twitter examples.\\n\",\n \"* **Use the Language Model to extract tone** - If you are at a loss for words on how to describe the tone you want, have the language model describe it for you. I found I needed to tell the model to be opinionated, it was too grey-area before.\\n\",\n \"* **Topics matter** - Have the model propose topics *first*, *then* give you a tweet. Not only is it better to have things the author would actually talk about, but it's also really good to keep the model on track by having it outline the topics *first* then respond\\n\",\n \"\\n\",\n \"Let's first identify authors the model thinks the example tweets sound like, then we'll reference those later. Keep in mind this isn't a true classification exercise and the point isn't to be 100% correct on similar people, it's to get a reference to who the model *thinks* is similar so we can use that inuition for instructions later.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 22,\n \"id\": \"a24aa819\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"def get_similar_public_figures(tweet_examples):\\n\",\n \" template = \\\"\\\"\\\"\\n\",\n \" You are an AI Bot that is very good at identifying authors, public figures, or writers whos style matches a piece of text\\n\",\n \" Your goal is to identify which authors, public figures, or writers sound most similar to the text below\\n\",\n \"\\n\",\n \" % START EXAMPLES\\n\",\n \" {tweet_examples}\\n\",\n \" % END EXAMPLES\\n\",\n \"\\n\",\n \" Which authors (list up to 4 if necessary) most closely resemble the examples above? Only respond with the names separated by commas\\n\",\n \" \\\"\\\"\\\"\\n\",\n \"\\n\",\n \" prompt = PromptTemplate(\\n\",\n \" input_variables=[\\\"tweet_examples\\\"],\\n\",\n \" template=template,\\n\",\n \" )\\n\",\n \"\\n\",\n \" # Using the short list of examples so save on tokens and (hopefully) the top tweets\\n\",\n \" final_prompt = prompt.format(tweet_examples=tweet_examples)\\n\",\n \"\\n\",\n \" authors = llm.predict(final_prompt)\\n\",\n \" return authors\\n\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 23,\n \"id\": \"b0a83b83\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"Bill Gates\\n\"\n ]\n }\n ],\n \"source\": [\n \"authors = get_similar_public_figures(users_tweets)\\n\",\n \"print (authors)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"7c1502d1\",\n \"metadata\": {},\n \"source\": [\n \"Ok that's not that exciting! Becuase we used Bill Gates' example tweets. Trust me that it's better with less-known people. We'll try this more later.\\n\",\n \"\\n\",\n \"At last, the final output. Let's bring it all together in a single prompt. Notice the 2 step process in the \\\"your task\\\" section below\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 24,\n \"id\": \"eeb512dc\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"template = \\\"\\\"\\\"\\n\",\n \"% INSTRUCTIONS\\n\",\n \" - You are an AI Bot that is very good at mimicking an author writing style.\\n\",\n \" - Your goal is to write content with the tone that is described below.\\n\",\n \" - Do not go outside the tone instructions below\\n\",\n \"\\n\",\n \"% Mimic These Authors:\\n\",\n \"{authors}\\n\",\n \"\\n\",\n \"% Description of the authors tone:\\n\",\n \"{tone}\\n\",\n \"\\n\",\n \"% Authors writing samples\\n\",\n \"{example_text}\\n\",\n \"% End of authors writing samples\\n\",\n \"\\n\",\n \"% YOUR TASK\\n\",\n \"1st - Write out topics that this author may talk about\\n\",\n \"2nd - Write a concise passage (under 300 characters) as if you were the author described above\\n\",\n \"\\\"\\\"\\\"\\n\",\n \"\\n\",\n \"method_4_prompt_template = PromptTemplate(\\n\",\n \" input_variables=[\\\"authors\\\", \\\"tone\\\", \\\"example_text\\\"],\\n\",\n \" template=template,\\n\",\n \")\\n\",\n \"\\n\",\n \"# Using the short list of examples so save on tokens and (hopefully) the top tweets\\n\",\n \"final_prompt = method_4_prompt_template.format(authors=authors,\\n\",\n \" tone=authors_tone_description,\\n\",\n \" example_text=users_tweets)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 26,\n \"id\": \"a99a9e8a\",\n \"metadata\": {\n \"scrolled\": false\n },\n \"outputs\": [],\n \"source\": [\n \"# print(final_prompt) # Print this out if you want to see the full final prompt. It's long so I'll omit it for now\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 27,\n \"id\": \"9e844c7a\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"1. Topics that this author may talk about:\\n\",\n \"- Global health and healthcare innovations\\n\",\n \"- Education and its impact on society\\n\",\n \"- Climate change and sustainable development\\n\",\n \"- Technological advancements, such as artificial intelligence and autonomous vehicles\\n\",\n \"- Poverty reduction and economic empowerment\\n\",\n \"- Personal experiences and learnings from travels\\n\",\n \"- Inspirational stories of individuals making a difference\\n\",\n \"\\n\",\n \"2. Concise passage as the author:\\n\",\n \"I recently visited a remarkable school in Kenya, where students are using solar-powered tablets to access quality education. It's inspiring to see how technology can transform lives and create a brighter future for these children.\\n\"\n ]\n }\n ],\n \"source\": [\n \"output = llm.predict(final_prompt)\\n\",\n \"print (output)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"bc9653e8\",\n \"metadata\": {},\n \"source\": [\n \"After a ton of iteration, I'm actually happy with that. But let's see this thing spread it's wings on multiple people.\\n\",\n \"\\n\",\n \"## Extra Credit: Loop this process through many twitter accounts\\n\",\n \"\\n\",\n \"Let's see what different twitter accounts sound like. Note, this will burn tokens so use at your own risk!\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 30,\n \"id\": \"e93f245b\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"results = {} # To store the results\\n\",\n \"\\n\",\n \"# # Or if you just wanna see the results of the loop below you can open up this json\\n\",\n \"# import json\\n\",\n \"# with open(\\\"../data/matching_tone_samples.json\\\", \\\"r\\\") as f:\\n\",\n \"# tone_samples = json.load(f)\\n\",\n \"# print (tone_samples)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"id\": \"db4e440a\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"accounts_to_mimic = ['jaltma', 'lindayacc', 'ShaanVP', 'dharmesh', 'sweatystartup', 'levelsio', 'Suhail', \\\\\\n\",\n \" 'hwchase17', 'elonmusk', 'packyM', 'benedictevans', 'paulg', 'AlexHormozi', 'DavidDeutschOxf', \\\\\\n\",\n \" 'stephsmithio', 'sophiaamoruso']\\n\",\n \" \\n\",\n \"\\n\",\n \"for user_screen_name in accounts_to_mimic:\\n\",\n \" \\n\",\n \" # Checking to see if we already have done the user. If so, move to the next one\\n\",\n \" if user_screen_name in results:\\n\",\n \" continue\\n\",\n \" \\n\",\n \" results[user_screen_name] = \\\"\\\"\\n\",\n \" \\n\",\n \" user_screenname_string = f\\\"User: {user_screen_name}\\\"\\n\",\n \" print (user_screenname_string)\\n\",\n \" results[user_screen_name] += user_screenname_string\\n\",\n \" \\n\",\n \" # Get their top tweets\\n\",\n \" users_tweets = get_original_tweets(user_screen_name)\\n\",\n \" \\n\",\n \" # Get their similar authors\\n\",\n \" authors = get_similar_public_figures(users_tweets)\\n\",\n \" authors_string = f\\\"Similar Authors: {authors}\\\"\\n\",\n \" print (authors_string)\\n\",\n \" results[user_screen_name] += \\\"\\\\n\\\" + authors_string\\n\",\n \" \\n\",\n \" # Get their tone description\\n\",\n \" authors_tone_description = get_authors_tone_description(how_to_describe_tone, users_tweets)\\n\",\n \" \\n\",\n \" # Only printing the first four attributes to save space\\n\",\n \" sample_description = authors_tone_description.split('\\\\n')[:4]\\n\",\n \" sample_decscription_string = f\\\"Tone Description: {sample_description}\\\"\\n\",\n \" print(sample_decscription_string)\\n\",\n \" results[user_screen_name] += \\\"\\\\n\\\" + sample_decscription_string + \\\"\\\\n\\\"\\n\",\n \" \\n\",\n \" \\n\",\n \" # Bring it all together in a single prompt\\n\",\n \" prompt = method_4_prompt_template.format(authors=authors,\\n\",\n \" tone=authors_tone_description,\\n\",\n \" example_text=users_tweets)\\n\",\n \" \\n\",\n \" output = llm.predict(prompt)\\n\",\n \" results[user_screen_name] += \\\"\\\\n\\\" + output\\n\",\n \" \\n\",\n \" print (\\\"\\\\n\\\")\\n\",\n \" print (output)\\n\",\n \" print (\\\"\\\\n\\\\n\\\")\"\n ]\n }\n ],\n \"metadata\": {\n \"kernelspec\": {\n \"display_name\": \"Python 3 (ipykernel)\",\n \"language\": \"python\",\n \"name\": \"python3\"\n },\n \"language_info\": {\n \"codemirror_mode\": {\n \"name\": \"ipython\",\n \"version\": 3\n },\n \"file_extension\": \".py\",\n \"mimetype\": \"text/x-python\",\n \"name\": \"python\",\n \"nbconvert_exporter\": \"python\",\n \"pygments_lexer\": \"ipython3\",\n \"version\": \"3.9.13\"\n }\n },\n \"nbformat\": 4,\n \"nbformat_minor\": 5\n}\n" }, { "path": "data_generation/Personalized Email Generation.ipynb", "content": "{\n \"cells\": [\n {\n \"cell_type\": \"code\",\n \"execution_count\": 1,\n \"id\": \"d3058a52\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain.document_loaders import UnstructuredURLLoader\\n\",\n \"from langchain.chains.summarize import load_summarize_chain\\n\",\n \"from langchain.llms import OpenAI\\n\",\n \"from langchain.text_splitter import RecursiveCharacterTextSplitter\\n\",\n \"from langchain.prompts import PromptTemplate\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 27,\n \"id\": \"615ee4b1\",\n \"metadata\": {\n \"hide_input\": false\n },\n \"outputs\": [],\n \"source\": [\n \"openai_api_key = '...'\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"c611b91a\",\n \"metadata\": {},\n \"source\": [\n \"### Load up your HTML from your company page\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 18,\n \"id\": \"69d427bb\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"https://www.ycombinator.com/companies/poly\\n\",\n \"You have 1 document(s)\\n\"\n ]\n }\n ],\n \"source\": [\n \"def get_company_page(company_path):\\n\",\n \" y_combinator_url = f\\\"https://www.ycombinator.com{company_path}\\\"\\n\",\n \" \\n\",\n \" print (y_combinator_url)\\n\",\n \"\\n\",\n \" loader = UnstructuredURLLoader(urls=[y_combinator_url])\\n\",\n \" return loader.load()\\n\",\n \"\\n\",\n \"\\n\",\n \"# Get the data of the company you're interested in\\n\",\n \"data = get_company_page(\\\"/companies/poly\\\")\\n\",\n \" \\n\",\n \"print (f\\\"You have {len(data)} document(s)\\\")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 19,\n \"id\": \"cf5c4961\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"Preview of your data:\\n\",\n \"\\n\",\n \"Accelerator\\n\",\n \"\\n\",\n \"About\\n\",\n \"\\n\",\n \"Apply\\n\",\n \"\\n\",\n \"FAQ\\n\"\n ]\n }\n ],\n \"source\": [\n \"print (f\\\"Preview of your data:\\\\n\\\\n{data[0].page_content[:30]}\\\")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 20,\n \"id\": \"d0fdfece\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# Split up the texts so you don't run into token limits\\n\",\n \"text_splitter = RecursiveCharacterTextSplitter(\\n\",\n \" # Set a really small chunk size, just to show.\\n\",\n \" chunk_size = 800,\\n\",\n \" chunk_overlap = 0\\n\",\n \")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 21,\n \"id\": \"a9e30ed0\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"You now have 3 documents\\n\"\n ]\n }\n ],\n \"source\": [\n \"docs = text_splitter.split_documents(data)\\n\",\n \"\\n\",\n \"print (f\\\"You now have {len(docs)} documents\\\")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"515de61f\",\n \"metadata\": {},\n \"source\": [\n \"### Write your custom prompt templates\\n\",\n \"These will be used for your specific use case:\\n\",\n \"\\n\",\n \"1. `map_prompt` will be the prompt that is done on your first pass of your documents\\n\",\n \"2. `combine_prompt` will be the prompt that is used when you combine the outputs of your map pass\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 22,\n \"id\": \"fb34ba34\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"map_prompt = \\\"\\\"\\\"Below is a section of a website about {prospect}\\n\",\n \"\\n\",\n \"Write a concise summary about {prospect}. If the information is not about {prospect}, exclude it from your summary.\\n\",\n \"\\n\",\n \"{text}\\n\",\n \"\\n\",\n \"% CONCISE SUMMARY:\\\"\\\"\\\"\\n\",\n \"map_prompt_template = PromptTemplate(template=map_prompt, input_variables=[\\\"text\\\", \\\"prospect\\\"])\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 23,\n \"id\": \"481b1fe2\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"combine_prompt = \\\"\\\"\\\"\\n\",\n \"Your goal is to write a personalized outbound email from {sales_rep}, a sales rep at {company} to {prospect}.\\n\",\n \"\\n\",\n \"A good email is personalized and combines information about the two companies on how they can help each other.\\n\",\n \"Be sure to use value selling: A sales methodology that focuses on how your product or service will provide value to the customer instead of focusing on price or solution.\\n\",\n \"\\n\",\n \"% INFORMATION ABOUT {company}:\\n\",\n \"{company_information}\\n\",\n \"\\n\",\n \"% INFORMATION ABOUT {prospect}:\\n\",\n \"{text}\\n\",\n \"\\n\",\n \"% INCLUDE THE FOLLOWING PIECES IN YOUR RESPONSE:\\n\",\n \"- Start the email with the sentence: \\\"We love that {prospect} helps teams...\\\" then insert what they help teams do.\\n\",\n \"- The sentence: \\\"We can help you do XYZ by ABC\\\" Replace XYZ with what {prospect} does and ABC with what {company} does \\n\",\n \"- A 1-2 sentence description about {company}, be brief\\n\",\n \"- End your email with a call-to-action such as asking them to set up time to talk more\\n\",\n \"\\n\",\n \"% YOUR RESPONSE:\\n\",\n \"\\\"\\\"\\\"\\n\",\n \"combine_prompt_template = PromptTemplate(template=combine_prompt, input_variables=[\\\"sales_rep\\\", \\\"company\\\", \\\"prospect\\\", \\\\\\n\",\n \" \\\"text\\\", \\\"company_information\\\"])\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 24,\n \"id\": \"340842c5\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"company_information = \\\"\\\"\\\"\\n\",\n \"* RapidRoad helps product teams build product faster\\n\",\n \"* We have a platform that allows product teams to talk more, exchange ideas, and listen to more customers\\n\",\n \"* Automated project tracking: RapidRoad could use machine learning algorithms to automatically track project progress, identify potential bottlenecks, and suggest ways to optimize workflows. This could help product teams stay on track and deliver faster results.\\n\",\n \"* Collaboration tools: RapidRoad could offer built-in collaboration tools, such as shared task lists, real-time messaging, and team calendars. This would make it easier for teams to communicate and work together, even if they are in different locations or time zones.\\n\",\n \"* Agile methodology support: RapidRoad could be specifically designed to support agile development methodologies, such as Scrum or Kanban. This could include features like sprint planning, backlog management, and burndown charts, which would help teams stay organized and focused on their goals.\\n\",\n \"\\\"\\\"\\\"\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"82406bae\",\n \"metadata\": {},\n \"source\": [\n \"### LangChain Magic\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 25,\n \"id\": \"32f28761\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"llm = OpenAI(temperature=.7, openai_api_key=openai_api_key)\\n\",\n \"\\n\",\n \"chain = load_summarize_chain(llm,\\n\",\n \" chain_type=\\\"map_reduce\\\",\\n\",\n \" map_prompt=map_prompt_template,\\n\",\n \" combine_prompt=combine_prompt_template,\\n\",\n \" verbose=True\\n\",\n \" )\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 26,\n \"id\": \"5b556562\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"\\n\",\n \"\\n\",\n \"\\u001b[1m> Entering new MapReduceDocumentsChain chain...\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3mBelow is a section of a website about Poly\\n\",\n \"\\n\",\n \"Write a concise summary about Poly. If the information is not about Poly, exclude it from your summary.\\n\",\n \"\\n\",\n \"Accelerator\\n\",\n \"\\n\",\n \"About\\n\",\n \"\\n\",\n \"Apply\\n\",\n \"\\n\",\n \"FAQ\\n\",\n \"\\n\",\n \"People\\n\",\n \"\\n\",\n \"YC Blog\\n\",\n \"\\n\",\n \"Companies\\n\",\n \"\\n\",\n \"Startup Directory\\n\",\n \"\\n\",\n \"Top Companies\\n\",\n \"\\n\",\n \"Founder Directory\\n\",\n \"\\n\",\n \"Launch YC\\n\",\n \"\\n\",\n \"Startup Jobs\\n\",\n \"\\n\",\n \"All Jobs\\n\",\n \"\\n\",\n \"Engineering\\n\",\n \"\\n\",\n \"Operations\\n\",\n \"\\n\",\n \"Marketing\\n\",\n \"\\n\",\n \"Sales\\n\",\n \"\\n\",\n \"Career Coaching\\n\",\n \"\\n\",\n \"Pioneer Program 2023\\n\",\n \"\\n\",\n \"Startup Job Guide\\n\",\n \"\\n\",\n \"YC Startup Jobs Blog\\n\",\n \"\\n\",\n \"Upcoming Events\\n\",\n \"\\n\",\n \"Startup School\\n\",\n \"\\n\",\n \"About\\n\",\n \"\\n\",\n \"Co-Founder Matching\\n\",\n \"\\n\",\n \"Startup School Blog\\n\",\n \"\\n\",\n \"Library\\n\",\n \"\\n\",\n \"SAFE\\n\",\n \"\\n\",\n \"Resources\\n\",\n \"\\n\",\n \"Event Calendar\\n\",\n \"\\n\",\n \"Newsletter\\n\",\n \"\\n\",\n \"For Investors\\n\",\n \"\\n\",\n \"Hacker News\\n\",\n \"\\n\",\n \"Open main menu\\n\",\n \"\\n\",\n \"Apply for S2023 batch.\\n\",\n \"\\n\",\n \"Apply\\n\",\n \"\\n\",\n \"Home\\n\",\n \"\\n\",\n \"Companies\\n\",\n \"\\n\",\n \"Poly\\n\",\n \"\\n\",\n \"Poly\\n\",\n \"\\n\",\n \"Generate Design Assets in Seconds\\n\",\n \"\\n\",\n \"Y Combinator LogoS22\\n\",\n \"\\n\",\n \"Active\\n\",\n \"\\n\",\n \"Artificial Intelligence\\n\",\n \"\\n\",\n \"Design Tools\\n\",\n \"\\n\",\n \"Generative AI\\n\",\n \"\\n\",\n \"Consumer\\n\",\n \"\\n\",\n \"API\\n\",\n \"\\n\",\n \"Company\\n\",\n \"\\n\",\n \"Jobs\\n\",\n \"\\n\",\n \"News\\n\",\n \"\\n\",\n \"https://withpoly.com/\\n\",\n \"\\n\",\n \"Generate Design Assets in Seconds\\n\",\n \"\\n\",\n \"% CONCISE SUMMARY:\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3mBelow is a section of a website about Poly\\n\",\n \"\\n\",\n \"Write a concise summary about Poly. If the information is not about Poly, exclude it from your summary.\\n\",\n \"\\n\",\n \"Generate unlimited customizable, 4K, and commercially-licensed creative design assets of any kind with a simple text prompt.\\n\",\n \"\\n\",\n \"Latest News\\n\",\n \"\\n\",\n \"Y Combinator-backed Poly uses AI to generate art assets • TechCrunch\\n\",\n \"\\n\",\n \"Dec 27, 2022\\n\",\n \"\\n\",\n \"Jobs at Poly\\n\",\n \"\\n\",\n \"View all jobs →\\n\",\n \"\\n\",\n \"Founding ML Engineer - Co-founder level role at a YC startup backed by Bloomberg, Felicis, Figma, AI grant\\n\",\n \"\\n\",\n \"San Francisco, CA / Remote\\n\",\n \"\\n\",\n \"$120K - $250K\\n\",\n \"\\n\",\n \"0.25% - 5.00%\\n\",\n \"\\n\",\n \"Any (new grads ok)\\n\",\n \"\\n\",\n \"Apply Now\\n\",\n \"\\n\",\n \"Company Launches\\n\",\n \"\\n\",\n \"🚀 Poly - Generate Design Assets in Seconds with AI 🚀\\n\",\n \"\\n\",\n \"Poly enables designers to generate unlimited customizable, 4K UHD, commercially-licensed design assets with a single text command in seconds.\\n\",\n \"\\n\",\n \"Read Launch ›\\n\",\n \"\\n\",\n \"Poly\\n\",\n \"\\n\",\n \"Founded:\\n\",\n \"\\n\",\n \"2022\\n\",\n \"\\n\",\n \"Team Size:\\n\",\n \"\\n\",\n \"Location:\\n\",\n \"\\n\",\n \"San Francisco\\n\",\n \"\\n\",\n \"Active Founders\\n\",\n \"\\n\",\n \"Abhay Agarwal\\n\",\n \"\\n\",\n \"% CONCISE SUMMARY:\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3mBelow is a section of a website about Poly\\n\",\n \"\\n\",\n \"Write a concise summary about Poly. If the information is not about Poly, exclude it from your summary.\\n\",\n \"\\n\",\n \"I'm an AI researcher and designer, and founder of Poly. Previously a research fellow at Microsoft Research and lecturer at Stanford. BS in EECS from UC Berkeley, MS from Stanford.\\n\",\n \"\\n\",\n \"Abhay Agarwal\\n\",\n \"\\n\",\n \"Poly\\n\",\n \"\\n\",\n \"Sam Young\\n\",\n \"\\n\",\n \"Built and operated consumer and B2B SaaS businesses. Grew a computer vision startup from an idea to series A. Stanford MBA.\\n\",\n \"\\n\",\n \"Sam Young\\n\",\n \"\\n\",\n \"Poly\\n\",\n \"\\n\",\n \"Footer\\n\",\n \"\\n\",\n \"Y Combinator\\n\",\n \"\\n\",\n \"Programs\\n\",\n \"\\n\",\n \"YC Program\\n\",\n \"\\n\",\n \"Startup School\\n\",\n \"\\n\",\n \"Work at a Startup\\n\",\n \"\\n\",\n \"Company\\n\",\n \"\\n\",\n \"YC Blog\\n\",\n \"\\n\",\n \"Contact\\n\",\n \"\\n\",\n \"Press\\n\",\n \"\\n\",\n \"People\\n\",\n \"\\n\",\n \"Careers\\n\",\n \"\\n\",\n \"Privacy Policy\\n\",\n \"\\n\",\n \"Security\\n\",\n \"\\n\",\n \"Terms of Use\\n\",\n \"\\n\",\n \"Resources\\n\",\n \"\\n\",\n \"Startup Directory\\n\",\n \"\\n\",\n \"Startup Library\\n\",\n \"\\n\",\n \"Investors\\n\",\n \"\\n\",\n \"SAFE\\n\",\n \"\\n\",\n \"Hacker News\\n\",\n \"\\n\",\n \"Launch YC\\n\",\n \"\\n\",\n \"YC Deals\\n\",\n \"\\n\",\n \"Make something people want.\\n\",\n \"\\n\",\n \"Apply\\n\",\n \"\\n\",\n \"TwitterTwitter\\n\",\n \"\\n\",\n \"FacebookFacebook\\n\",\n \"\\n\",\n \"InstagramInstagram\\n\",\n \"\\n\",\n \"LinkedInLinkedIn\\n\",\n \"\\n\",\n \"YoutubeYouTube\\n\",\n \"\\n\",\n \"© 2023 Y Combinator.\\n\",\n \"\\n\",\n \"% CONCISE SUMMARY:\\u001b[0m\\n\",\n \"\\n\",\n \"\\n\",\n \"\\u001b[1m> Entering new LLMChain chain...\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3m\\n\",\n \"Your goal is to write a personalized outbound email from Greg, a sales rep at RapidRoad to Poly.\\n\",\n \"\\n\",\n \"A good email is personalized and combines information about the two companies on how they can help each other.\\n\",\n \"Be sure to use value selling: A sales methodology that focuses on how your product or service will provide value to the customer instead of focusing on price or solution.\\n\",\n \"\\n\",\n \"% INFORMATION ABOUT RapidRoad:\\n\",\n \"\\n\",\n \"* RapidRoad helps product teams build product faster\\n\",\n \"* We have a platform that allows product teams to talk more, exchange ideas, and listen to more customers\\n\",\n \"* Automated project tracking: RapidRoad could use machine learning algorithms to automatically track project progress, identify potential bottlenecks, and suggest ways to optimize workflows. This could help product teams stay on track and deliver faster results.\\n\",\n \"* Collaboration tools: RapidRoad could offer built-in collaboration tools, such as shared task lists, real-time messaging, and team calendars. This would make it easier for teams to communicate and work together, even if they are in different locations or time zones.\\n\",\n \"* Agile methodology support: RapidRoad could be specifically designed to support agile development methodologies, such as Scrum or Kanban. This could include features like sprint planning, backlog management, and burndown charts, which would help teams stay organized and focused on their goals.\\n\",\n \"\\n\",\n \"\\n\",\n \"% INFORMATION ABOUT Poly:\\n\",\n \"\\n\",\n \"\\n\",\n \"Poly is a design tool that uses artificial intelligence and generative AI to quickly create design assets. It is an active consumer API company that is part of the Y Combinator program.\\n\",\n \"\\n\",\n \"\\n\",\n \"\\n\",\n \"Poly is an AI-based platform that enables designers to generate unlimited customizable, 4K UHD, commercially-licensed design assets with a single text command in seconds. It was founded in 2022 by Abhay Agarwal and is located in San Francisco. Y Combinator and Bloomberg have invested in the project.\\n\",\n \"\\n\",\n \"\\n\",\n \"\\n\",\n \"Poly is an AI research and design company founded by Abhay Agarwal, a research fellow at Microsoft Research and lecturer at Stanford. The company is also operated by Sam Young, a former computer vision startup founder with an MBA from Stanford. Poly is affiliated with Y Combinator, a program that helps entrepreneurs make something people want.\\n\",\n \"\\n\",\n \"% INCLUDE THE FOLLOWING PIECES IN YOUR RESPONSE:\\n\",\n \"- Start the email with the sentence: \\\"We love that Poly helps teams...\\\" then insert what they help teams do.\\n\",\n \"- The sentence: \\\"We can help you do XYZ by ABC\\\" Replace XYZ with what Poly does and ABC with what RapidRoad does \\n\",\n \"- A 1-2 setenece description about RapidRoad, be brief\\n\",\n \"- End your email with a call-to-action such as asking them to set up time to talk more\\n\",\n \"\\n\",\n \"% YOUR RESPONSE:\\n\",\n \"\\u001b[0m\\n\",\n \"\\n\",\n \"\\u001b[1m> Finished chain.\\u001b[0m\\n\",\n \"\\n\",\n \"\\u001b[1m> Finished chain.\\u001b[0m\\n\"\n ]\n }\n ],\n \"source\": [\n \"output = chain({\\\"input_documents\\\": docs, # The seven docs that were created before\\n\",\n \" \\\"company\\\": \\\"RapidRoad\\\", \\\\\\n\",\n \" \\\"company_information\\\" : company_information,\\n\",\n \" \\\"sales_rep\\\" : \\\"Greg\\\", \\\\\\n\",\n \" \\\"prospect\\\" : \\\"Poly\\\"\\n\",\n \" })\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 17,\n \"id\": \"c3152c06\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"\\n\",\n \"Dear GitLab Team,\\n\",\n \"\\n\",\n \"We love that GitLab helps teams collaborate, plan, and manage projects, while also providing visibility and consistent controls for security and compliance. We believe that RapidRoad could help you take your DevOps processes to the next level. \\n\",\n \"\\n\",\n \"RapidRoad is a platform that helps product teams build faster. We have tools like automated project tracking, collaboration tools, and agile methodology support that could help your teams stay on track and deliver faster results.\\n\",\n \"\\n\",\n \"We believe that combining GitLab and RapidRoad would unlock your organization from the constraints of the current toolchain. We would love to set up a time to discuss how we can help each other and how we can help you improve your DevOps processes.\\n\",\n \"\\n\",\n \"Thank you for your time,\\n\",\n \"\\n\",\n \"Greg \\n\",\n \"Sales Rep at RapidRoad\\n\"\n ]\n }\n ],\n \"source\": [\n \"print (output['output_text'])\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"5491e5bb\",\n \"metadata\": {},\n \"source\": [\n \"### Rinse and Repeat: Loop Through Companies\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 18,\n \"id\": \"ddf9a955\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"import pandas as pd\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 19,\n \"id\": \"70e22389\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"df_companies = pd.read_clipboard()\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 20,\n \"id\": \"fca1ffb3\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/html\": [\n \"
\\n\",\n \"\\n\",\n \"\\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \"
NameLink
0Findly/companies/findly
1Maya Labs/companies/maya-labs
2Phind/companies/phind
3Juicebox/companies/juicebox
4Penguin AI/companies/penguin-ai
5Poly/companies/poly
6Olli.ai/companies/olli-ai
\\n\",\n \"
\"\n ],\n \"text/plain\": [\n \" Name Link\\n\",\n \"0 Findly /companies/findly\\n\",\n \"1 Maya Labs /companies/maya-labs\\n\",\n \"2 Phind /companies/phind\\n\",\n \"3 Juicebox /companies/juicebox\\n\",\n \"4 Penguin AI /companies/penguin-ai\\n\",\n \"5 Poly /companies/poly\\n\",\n \"6 Olli.ai /companies/olli-ai\"\n ]\n },\n \"execution_count\": 20,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"df_companies\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 21,\n \"id\": \"094bb943\",\n \"metadata\": {\n \"scrolled\": false\n },\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"1. Findly\\n\",\n \"https://www.ycombinator.com/companies/findly\\n\",\n \"\\n\",\n \"Dear Findly Team,\\n\",\n \"\\n\",\n \"We love that Findly helps teams quickly and accurately access data insights without having to learn SQL or Python. We can help you provide more actionable insights by using our platform to talk more, exchange ideas, and listen to more customers. \\n\",\n \"\\n\",\n \"RapidRoad is a platform that helps product teams build product faster. It offers automated project tracking, collaboration tools, and agile methodology support to help teams stay organized and deliver faster results. \\n\",\n \"\\n\",\n \"We believe that our platform and your AI chatbot will be a great combination to help teams develop products faster and with actionable insights. Let's talk soon and see how we can work together to make this happen. \\n\",\n \"\\n\",\n \"Best, \\n\",\n \"Greg \\n\",\n \"Sales Rep, RapidRoad\\n\",\n \"\\n\",\n \"\\n\",\n \"\\n\",\n \"2. Maya Labs\\n\",\n \"https://www.ycombinator.com/companies/maya-labs\\n\",\n \"\\n\",\n \"Dear Maya Labs, \\n\",\n \"\\n\",\n \"We love that Maya Labs helps teams build custom software in minutes using natural language. We at RapidRoad are dedicated to helping product teams build their products faster. We can help you build custom software faster by providing automated project tracking, collaboration tools, and agile methodology support.\\n\",\n \"\\n\",\n \"Our platform allows product teams to talk more, exchange ideas, and listen to more customers. We have machine learning algorithms to automatically track project progress, identify potential bottlenecks, and suggest ways to optimize workflows. We also offer built-in collaboration tools, such as shared task lists, real-time messaging, and team calendars. Finally, we are specifically designed to support agile development methodologies, such as Scrum or Kanban.\\n\",\n \"\\n\",\n \"We believe that our platform can help Maya Labs build custom software faster and with higher quality. Let's set up a time to talk more about how we can help each other.\\n\",\n \"\\n\",\n \"Best,\\n\",\n \"Greg \\n\",\n \"RapidRoad Sales Rep\\n\",\n \"\\n\",\n \"\\n\",\n \"\\n\",\n \"3. Phind\\n\",\n \"https://www.ycombinator.com/companies/phind\\n\",\n \"\\n\",\n \"Dear Michael and Justin, \\n\",\n \"\\n\",\n \"We love that Phind helps teams find the technical answers they need quickly and easily. At RapidRoad, we want to help product teams build faster, smarter and more efficiently. We can help you do this by providing an automated project tracking platform, collaboration tools, and agile methodology support. \\n\",\n \"\\n\",\n \"RapidRoad is a platform that allows product teams to talk more, exchange ideas, and listen to more customers. Our platform uses machine learning algorithms to automatically track project progress, identify potential bottlenecks, and suggest ways to optimize workflows. We also offer built-in collaboration tools like shared task lists, real-time messaging, and team calendars, as well as agile methodology support like sprint planning, backlog management, and burndown charts. \\n\",\n \"\\n\",\n \"We would love to discuss further how we can help your team to build faster, smarter and more efficiently. Please let me know when is the best time for us to have a call to discuss this further. \\n\",\n \"\\n\",\n \"Regards,\\n\",\n \"\\n\",\n \"Greg \\n\",\n \"RapidRoad\\n\",\n \"\\n\",\n \"\\n\",\n \"\\n\",\n \"4. Juicebox\\n\",\n \"https://www.ycombinator.com/companies/juicebox\\n\",\n \"\\n\",\n \"Dear Ishan and David, \\n\",\n \"\\n\",\n \"We love that Juicebox helps teams find pre-vetted independent contractors quickly and efficiently in a zero-commission marketplace. We at RapidRoad are passionate about helping product teams build products faster and more efficiently. We can help you do this by providing a platform that allows product teams to talk more, exchange ideas, and listen to more customers, as well as providing automated project tracking, collaboration tools, and agile methodology support. \\n\",\n \"\\n\",\n \"At RapidRoad, we believe that teams should be able to work together efficiently and effectively, and our platform is specifically designed to help them do just that. \\n\",\n \"\\n\",\n \"We would love to learn more about what you need to help your team succeed and see how RapidRoad can help. When would be a good time for us to connect and discuss further? \\n\",\n \"\\n\",\n \"Best, \\n\",\n \"Greg \\n\",\n \"Sales Rep, RapidRoad\\n\",\n \"\\n\",\n \"\\n\",\n \"\\n\",\n \"5. Penguin AI\\n\",\n \"https://www.ycombinator.com/companies/penguin-ai\\n\",\n \"\\n\",\n \"Dear Rohan Doshi,\\n\",\n \"\\n\",\n \"We love that Penguin AI helps teams create agency-quality visual assets quickly and affordably. At RapidRoad, we help product teams build products faster. Our platform allows product teams to talk more, exchange ideas, and listen to more customers. We also have automated project tracking and collaboration tools, as well as support for agile methodology. \\n\",\n \"\\n\",\n \"We can help you save time and money by providing the tools and resources to create high-quality visual assets quickly and cost-effectively. Our platform allows product teams to communicate and work together, even if they are in different locations or time zones, and stay on track and deliver faster results.\\n\",\n \"\\n\",\n \"I would love to learn more about your product and how we can help each other. Would you be available for a call next week to discuss further?\\n\",\n \"\\n\",\n \"Best,\\n\",\n \"\\n\",\n \"Greg\\n\",\n \"RapidRoad\\n\",\n \"\\n\",\n \"\\n\",\n \"\\n\",\n \"6. Poly\\n\",\n \"https://www.ycombinator.com/companies/poly\\n\",\n \"\\n\",\n \"Dear Poly Team,\\n\",\n \"\\n\",\n \"We love that Poly helps teams generate customizable, 4K, and commercially-licensed creative design assets with a simple text prompt. We believe that RapidRoad can help you create and collaborate more effectively by offering automated project tracking, collaboration tools, and agile methodology support.\\n\",\n \"\\n\",\n \"RapidRoad is a platform that helps product teams build product faster. We have a suite of tools to help product teams talk more, exchange ideas, and listen to more customers. We provide automated project tracking, which uses machine learning algorithms to automatically track project progress, identify potential bottlenecks, and suggest ways to optimize workflows. Our collaboration tools include shared task lists, real-time messaging, and team calendars, which makes it easier for teams to communicate and work together, even if they are in different locations or time zones. RapidRoad is also specifically designed to support agile development methodologies, such as Scrum or Kanban, with features like sprint planning, backlog management, and burndown charts to help teams stay organized and focused on their goals.\\n\",\n \"\\n\",\n \"I would love to learn more about Poly and discuss how RapidRoad can help your team create and collaborate more effectively. Please let me know if you’d like to set up a time to\\n\",\n \"\\n\",\n \"\\n\",\n \"\\n\",\n \"7. Olli.ai\\n\",\n \"https://www.ycombinator.com/companies/olli-ai\\n\",\n \"We love that Olli.ai helps teams generate insights quickly and efficiently through powerful AI models. We can help you do this by automating project tracking, providing collaboration tools, and supporting agile methodology. \\n\",\n \"\\n\",\n \"RapidRoad is a platform that helps product teams build product faster by allowing them to talk more, exchange ideas, and listen to more customers.\\n\",\n \"\\n\",\n \"We believe that our combination of services can provide immense value to your company and would love to discuss more about how we can work together. Would you be interested in setting up some time to talk? We look forward to hearing from you.\\n\",\n \"\\n\",\n \"\\n\",\n \"\\n\"\n ]\n }\n ],\n \"source\": [\n \"for i, company in df_companies.iterrows():\\n\",\n \" print (f\\\"{i + 1}. {company['Name']}\\\")\\n\",\n \" page_data = get_company_page(company['Link'])\\n\",\n \" docs = text_splitter.split_documents(page_data)\\n\",\n \"\\n\",\n \" output = chain({\\\"input_documents\\\": docs, \\\\\\n\",\n \" \\\"company\\\":\\\"RapidRoad\\\", \\\\\\n\",\n \" \\\"sales_rep\\\" : \\\"Greg\\\", \\\\\\n\",\n \" \\\"prospect\\\" : company['Name'],\\n\",\n \" \\\"company_information\\\" : company_information\\n\",\n \" })\\n\",\n \" \\n\",\n \" print (output['output_text'])\\n\",\n \" print (\\\"\\\\n\\\\n\\\")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"id\": \"5d037f61\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": []\n }\n ],\n \"metadata\": {\n \"kernelspec\": {\n \"display_name\": \"Python 3 (ipykernel)\",\n \"language\": \"python\",\n \"name\": \"python3\"\n },\n \"language_info\": {\n \"codemirror_mode\": {\n \"name\": \"ipython\",\n \"version\": 3\n },\n \"file_extension\": \".py\",\n \"mimetype\": \"text/x-python\",\n \"name\": \"python\",\n \"nbconvert_exporter\": \"python\",\n \"pygments_lexer\": \"ipython3\",\n \"version\": \"3.9.13\"\n }\n },\n \"nbformat\": 4,\n \"nbformat_minor\": 5\n}\n" }, { "path": "data_generation/Retrieval_With_MMR.ipynb", "content": "{\n \"cells\": [\n {\n \"cell_type\": \"code\",\n \"execution_count\": 1,\n \"id\": \"6a63bd39-9b87-4316-8680-a9cf0672158a\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from dotenv import load_dotenv\\n\",\n \"import os\\n\",\n \"\\n\",\n \"load_dotenv()\\n\",\n \"\\n\",\n \"openai_api_key=os.getenv('OPENAI_API_KEY', 'YourAPIKey')\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 2,\n \"id\": \"dd94cd99-82bc-4cad-81c2-6cac78c18e70\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain.document_loaders import DirectoryLoader\\n\",\n \"from langchain.embeddings.openai import OpenAIEmbeddings\\n\",\n \"from langchain.text_splitter import RecursiveCharacterTextSplitter\\n\",\n \"from langchain.vectorstores import Chroma\\n\",\n \"from langchain.document_loaders import WebBaseLoader\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 3,\n \"id\": \"2bc6d009-fd25-41cb-b4bf-2d2dfb27751d\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"Your 1 documents have been split into 28 chunks\\n\"\n ]\n }\n ],\n \"source\": [\n \"# Loading a single website\\n\",\n \"loader = WebBaseLoader(\\\"http://www.paulgraham.com/wealth.html\\\")\\n\",\n \"docs = loader.load()\\n\",\n \"\\n\",\n \"# Split your website into big chunks\\n\",\n \"text_splitter = RecursiveCharacterTextSplitter(chunk_size=2000, chunk_overlap=0)\\n\",\n \"chunks = text_splitter.split_documents(docs)\\n\",\n \"\\n\",\n \"print (f\\\"Your {len(docs)} documents have been split into {len(chunks)} chunks\\\")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 4,\n \"id\": \"0af17f88-e32c-455f-93b6-e747e0b15bdb\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"embedding = OpenAIEmbeddings()\\n\",\n \"vectordb = Chroma.from_documents(documents=chunks, embedding=embedding)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 5,\n \"id\": \"7ebada96-e58c-4941-8b5d-8e95bc459683\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"retriever_vanilla = vectordb.as_retriever(search_type=\\\"similarity\\\", search_kwargs={\\\"k\\\": 8})\\n\",\n \"\\n\",\n \"retriever_mmr = vectordb.as_retriever(search_type=\\\"mmr\\\", search_kwargs={\\\"k\\\": 8})\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 6,\n \"id\": \"181d06cb-ac3a-45c3-bb4b-162e0925d45b\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"vanilla_relevant_docs = retriever_vanilla.get_relevant_documents(\\\"What is the best way to make and keep wealth?\\\")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 7,\n \"id\": \"268d4aa1-9df5-47c2-af44-5460a0cd9343\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"mmr_relevant_docs = retriever_mmr.get_relevant_documents(\\\"What is the best way to make and keep wealth?\\\")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 8,\n \"id\": \"b149fe0e-60aa-49c6-8721-d4a5ce838ef1\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"def analyze_list_overlap(list1, list2, content_attr='page_content'):\\n\",\n \" \\\"\\\"\\\"\\n\",\n \" Analyze the overlap and uniqueness between two lists of objects using a specified content attribute.\\n\",\n \"\\n\",\n \" Parameters:\\n\",\n \" list1 (list): The first list of objects to compare.\\n\",\n \" list2 (list): The second list of objects to compare.\\n\",\n \" content_attr (str): The attribute name of the content to use for comparison.\\n\",\n \"\\n\",\n \" Returns:\\n\",\n \" dict: A dictionary with counts of overlapping, unique to list1, unique to list2 items,\\n\",\n \" and total counts for each list.\\n\",\n \" \\\"\\\"\\\"\\n\",\n \" # Extract unique content attributes from the lists\\n\",\n \" set1_contents = {getattr(doc, content_attr) for doc in list1}\\n\",\n \" set2_contents = {getattr(doc, content_attr) for doc in list2}\\n\",\n \"\\n\",\n \" # Find the number of overlapping content attributes\\n\",\n \" overlap_contents = set1_contents & set2_contents\\n\",\n \" overlap_count = len(overlap_contents)\\n\",\n \"\\n\",\n \" # Find the unique content attributes in each list\\n\",\n \" unique_to_list1_contents = set1_contents - set2_contents\\n\",\n \" unique_to_list2_contents = set2_contents - set1_contents\\n\",\n \" unique_to_list1_count = len(unique_to_list1_contents)\\n\",\n \" unique_to_list2_count = len(unique_to_list2_contents)\\n\",\n \"\\n\",\n \" # Use the unique content attributes to retrieve the unique objects\\n\",\n \" unique_to_list1 = [doc for doc in list1 if getattr(doc, content_attr) in unique_to_list1_contents]\\n\",\n \" unique_to_list2 = [doc for doc in list2 if getattr(doc, content_attr) in unique_to_list2_contents]\\n\",\n \"\\n\",\n \" # Count the total number of items in each list\\n\",\n \" total_list1 = len(list1)\\n\",\n \" total_list2 = len(list2)\\n\",\n \"\\n\",\n \" # Return the results in a dictionary\\n\",\n \" return {\\n\",\n \" 'total_list1': total_list1,\\n\",\n \" 'total_list2': total_list2,\\n\",\n \" 'overlap_count': overlap_count,\\n\",\n \" 'unique_to_list1_count': unique_to_list1_count,\\n\",\n \" 'unique_to_list2_count': unique_to_list2_count,\\n\",\n \" }\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 9,\n \"id\": \"c546588b-3428-427e-b264-56c25222a84f\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"{'total_list1': 8,\\n\",\n \" 'total_list2': 8,\\n\",\n \" 'overlap_count': 6,\\n\",\n \" 'unique_to_list1_count': 2,\\n\",\n \" 'unique_to_list2_count': 2}\"\n ]\n },\n \"execution_count\": 9,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"analyze_list_overlap(vanilla_relevant_docs, mmr_relevant_docs)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"id\": \"bc7d4e89-964c-4f37-bfcc-69d846c6070f\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": []\n }\n ],\n \"metadata\": {\n \"kernelspec\": {\n \"display_name\": \"Python 3 (ipykernel)\",\n \"language\": \"python\",\n \"name\": \"python3\"\n },\n \"language_info\": {\n \"codemirror_mode\": {\n \"name\": \"ipython\",\n \"version\": 3\n },\n \"file_extension\": \".py\",\n \"mimetype\": \"text/x-python\",\n \"name\": \"python\",\n \"nbconvert_exporter\": \"python\",\n \"pygments_lexer\": \"ipython3\",\n \"version\": \"3.11.6\"\n }\n },\n \"nbformat\": 4,\n \"nbformat_minor\": 5\n}\n" }, { "path": "data_generation/Topic Modeling With Language Models.ipynb", "content": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"id\": \"821ad079\",\n \"metadata\": {},\n \"source\": [\n \"# Topic Modeling With Language Models\\n\",\n \"\\n\",\n \"*View this code on [Github](https://github.com/gkamradt/langchain-tutorials/blob/main/data_generation/Topic%20Modeling%20With%20Language%20Models.ipynb)*\\n\",\n \"\\n\",\n \"\\n\",\n \"Topic Modeling is the practice of pulling out categorized groups of information from a piece of longer text.\\n\",\n \"\\n\",\n \"Example: Inferring chapters from a book or segments of a movie. This is a classic data science topic that has been studied for years. Check out examples from previous research like [scikit-learn](https://towardsdatascience.com/introduction-to-topic-modeling-using-scikit-learn-4c3f3290f5b9) and [BERTopic](https://www.youtube.com/watch?v=uZxQz87lb84) if you want to see these techniques.\\n\",\n \"\\n\",\n \"However today we are going to take a pass at this problem using language models. Why? Language models are extremely good at processing text and pulling out big picture ideas from a document.\\n\",\n \"\\n\",\n \"There are many methods to do this and my goal for today's tutorial is to show you a few different approaches so you can apply it to your own scenario.\\n\",\n \"\\n\",\n \"In this lesson we are prioritizing comprehensiveness and robustness of information over API costs so please be mindful of your expense comfortability.\\n\",\n \"\\n\",\n \"I'll be taking a 2-pass approach today:\\n\",\n \"* **1st Pass:** Run through the entire document via map reduce and pull out topics as bullet points\\n\",\n \"* **2nd Pass:** Iterate through your topic bullet points and expand on them with a subset of context that was selected via retrieval\\n\",\n \"\\n\",\n \"\\n\",\n \"Today we are going to be looking at a [My First Million](https://www.mfmpod.com/) podcast because it's rich with segments, ideas, sayings, and stories. Great for topic parsing!\\n\",\n \"\\n\",\n \"**Bonus**: As a bonus we are also going to be looking at how to auto generate timestamps for each topic as well. The most common use case of this is YouTube Chapters\\n\",\n \"\\n\",\n \"**My Assumptions**\\n\",\n \"* You don't have a table of contents. That would definitely help out (since a human likely generated them) but I want to make this method as general as possible so you can apply it\\n\",\n \"* You want to *learn* the nuts and bolts how to do this. If you wanted a 3rd party tool to do this for you I suggest something like [AssemblyAI](https://www.assemblyai.com/) or [PodcastNotes](https://podcastnotes.org/) \\n\",\n \"\\n\",\n \"### Use Cases:\\n\",\n \"\\n\",\n \"* **YouTube Videos** - Auto Chapter Generation\\n\",\n \"* **Podcasts** - Extract structured information\\n\",\n \"* **Meeting Notes** - Send topic summaries to participants\\n\",\n \"* **Town Hall Meetings** - Structured information\\n\",\n \"* **Earnings Report Calls** - Sell structured data to investment groups\\n\",\n \"* **Legal Documents** - Quickly summarize by topic\\n\",\n \"* **Movie Scripts** - Quick bullet points for production recaps\\n\",\n \"* **Books** - Auto generate table of contents\\n\",\n \"\\n\",\n \"Finally, if you want to see the inspiration for this tutorial, [here's the tweet](https://twitter.com/GregKamradt/status/1651957952725807106) that started it all.\\n\",\n \"\\n\",\n \"Let's get started!\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 20,\n \"id\": \"de3e5a4b\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"True\"\n ]\n },\n \"execution_count\": 20,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"# Make the display a bit wider\\n\",\n \"# from IPython.display import display, HTML\\n\",\n \"# display(HTML(\\\"\\\"))\\n\",\n \"\\n\",\n \"# LangChain basics\\n\",\n \"from langchain.chat_models import ChatOpenAI\\n\",\n \"from langchain.text_splitter import RecursiveCharacterTextSplitter\\n\",\n \"from langchain.chains.summarize import load_summarize_chain\\n\",\n \"from langchain.chains import create_extraction_chain\\n\",\n \"\\n\",\n \"# Vector Store and retrievals\\n\",\n \"from langchain.embeddings.openai import OpenAIEmbeddings\\n\",\n \"from langchain.chains import RetrievalQA\\n\",\n \"from langchain.vectorstores import Chroma, Pinecone\\n\",\n \"import pinecone\\n\",\n \"\\n\",\n \"# Chat Prompt templates for dynamic values\\n\",\n \"from langchain.prompts.chat import (\\n\",\n \" ChatPromptTemplate,\\n\",\n \" SystemMessagePromptTemplate,\\n\",\n \" HumanMessagePromptTemplate\\n\",\n \")\\n\",\n \"\\n\",\n \"# Supporting libraries\\n\",\n \"import os\\n\",\n \"from dotenv import load_dotenv\\n\",\n \"\\n\",\n \"load_dotenv()\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"c67bf65b\",\n \"metadata\": {},\n \"source\": [\n \"### The Set Up - Create your LLMs and get data\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 2,\n \"id\": \"17ef4d09\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# Creating two versions of the model so I can swap between gpt3.5 and gpt4\\n\",\n \"llm3 = ChatOpenAI(temperature=0,\\n\",\n \" openai_api_key=os.getenv('OPENAI_API_KEY', 'YourAPIKeyIfNotSet'),\\n\",\n \" model_name=\\\"gpt-3.5-turbo-0613\\\",\\n\",\n \" request_timeout = 180\\n\",\n \" )\\n\",\n \"\\n\",\n \"llm4 = ChatOpenAI(temperature=0,\\n\",\n \" openai_api_key=os.getenv('OPENAI_API_KEY', 'YourAPIKeyIfNotSet'),\\n\",\n \" model_name=\\\"gpt-4-0613\\\",\\n\",\n \" request_timeout = 180\\n\",\n \" )\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"97df506a\",\n \"metadata\": {},\n \"source\": [\n \"First we'll need to get transcripts. I put a few pre-processed transcripts in the data folder of this repo.\\n\",\n \"\\n\",\n \"If you need transcripts for your own audio I suggest a transcription tool like [AssemblyAI](https://www.assemblyai.com/). I also tried [Steno.ai](https://steno.ai/my-first-million) but the quality and speaker detection wasn't that high.\\n\",\n \"\\n\",\n \"Reach out if you want me to grab transcripts in bulk for you.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 3,\n \"id\": \"be6fb49b\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# I put three prepared transcripts\\n\",\n \"transcript_paths = [\\n\",\n \" '../data/Transcripts/MFMPod/mfm_pod_steph.txt',\\n\",\n \" '../data/Transcripts/MFMPod/mfm_pod_alex.txt',\\n\",\n \" '../data/Transcripts/MFMPod/mfm_pod_rob.txt'\\n\",\n \"]\\n\",\n \"\\n\",\n \"with open('../data/Transcripts/MFMPod/mfm_pod_steph.txt') as file:\\n\",\n \" transcript = file.read()\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 4,\n \"id\": \"8fd28ab9\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"Shaan Puri (0:00:00-0:00:03): D to see hearing AIDS. I think that's actually going to be a big deal. \\n\",\n \"\\n\",\n \"Sam Parr (0:00:03-0:00:05): And they're profitable. \\n\",\n \"\\n\",\n \"Shaan Puri (0:00:05-0:00:08): I mean, I'm just turning you on. Yeah, they were. \\n\",\n \"\\n\",\n \"Sam Parr (0:00:12-0:00:13): They Mormon. \\n\"\n ]\n }\n ],\n \"source\": [\n \"print(transcript[:280])\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"29c7b13f\",\n \"metadata\": {},\n \"source\": [\n \"Then we are going to split our text up into chunks. We do this so:\\n\",\n \"\\n\",\n \"1. The context size is smaller and the LLM can increase it's attention to context ratio\\n\",\n \"2. In case the text is too long and it wouldn't fit in the prompt anyway\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 5,\n \"id\": \"ce687f77\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"You have 3 docs. First doc is 2801 tokens\\n\"\n ]\n }\n ],\n \"source\": [\n \"# Load up your text splitter\\n\",\n \"text_splitter = RecursiveCharacterTextSplitter(separators=[\\\"\\\\n\\\\n\\\", \\\"\\\\n\\\", \\\" \\\"], chunk_size=10000, chunk_overlap=2200)\\n\",\n \"\\n\",\n \"# I'm only doing the first 23250 characters. This to save on costs. When you're doing your exercise you can remove this to let all the data through\\n\",\n \"transcript_subsection_characters = 23250\\n\",\n \"docs = text_splitter.create_documents([transcript[:transcript_subsection_characters]])\\n\",\n \"print (f\\\"You have {len(docs)} docs. First doc is {llm3.get_num_tokens(docs[0].page_content)} tokens\\\")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"cb048dd1\",\n \"metadata\": {},\n \"source\": [\n \"## Step 1: Extract Topic Titles & Short Description\\n\",\n \"\\n\",\n \"### The Custom Prompts - Customize your prompt to fit your use case\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"4b5e4b2a\",\n \"metadata\": {},\n \"source\": [\n \"Next up I'm going to use custom prompts to instruct the LLM on how to pull out the topics I want.\\n\",\n \"\\n\",\n \"This will be heavily dependent on your domain. You should adjust the prompt below to use descriptions and examples that are relevant to you.\\n\",\n \"\\n\",\n \"I built these descriptions over many iterations playing with prompts and checking the output. If you ever start a business this will be part of your IP!\\n\",\n \"\\n\",\n \"I will ask the LLM for a topic title and a short description. I found it was too much for the LLM to ask for a long description in the first pass. Results weren't great and high latency.\\n\",\n \"\\n\",\n \"Let's start with our map prompt which will iterate over the chunks we just made\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 6,\n \"id\": \"f9792cb0\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"template=\\\"\\\"\\\"\\n\",\n \"You are a helpful assistant that helps retrieve topics talked about in a podcast transcript\\n\",\n \"- Your goal is to extract the topic names and brief 1-sentence description of the topic\\n\",\n \"- Topics include:\\n\",\n \" - Themes\\n\",\n \" - Business Ideas\\n\",\n \" - Interesting Stories\\n\",\n \" - Money making businesses\\n\",\n \" - Quick stories about people\\n\",\n \" - Mental Frameworks\\n\",\n \" - Stories about an industry\\n\",\n \" - Analogies mentioned\\n\",\n \" - Advice or words of caution\\n\",\n \" - Pieces of news or current events\\n\",\n \"- Provide a brief description of the topics after the topic name. Example: 'Topic: Brief Description'\\n\",\n \"- Use the same words and terminology that is said in the podcast\\n\",\n \"- Do not respond with anything outside of the podcast. If you don't see any topics, say, 'No Topics'\\n\",\n \"- Do not respond with numbers, just bullet points\\n\",\n \"- Do not include anything about 'Marketing Against the Grain'\\n\",\n \"- Only pull topics from the transcript. Do not use the examples\\n\",\n \"- Make your titles descriptive but concise. Example: 'Shaan's Experience at Twitch' should be 'Shaan's Interesting Projects At Twitch'\\n\",\n \"- A topic should be substantial, more than just a one-off comment\\n\",\n \"\\n\",\n \"% START OF EXAMPLES\\n\",\n \" - Sam’s Elisabeth Murdoch Story: Sam got a call from Elizabeth Murdoch when he had just launched The Hustle. She wanted to generate video content.\\n\",\n \" - Shaan’s Rupert Murdoch Story: When Shaan was running Blab he was invited to an event organized by Rupert Murdoch during CES in Las Vegas.\\n\",\n \" - Revenge Against The Spam Calls: A couple of businesses focused on protecting consumers: RoboCall, TrueCaller, DoNotPay, FitIt\\n\",\n \" - Wildcard CEOs vs. Prudent CEOs: However, Munger likes to surround himself with prudent CEO’s and says he would never hire Musk.\\n\",\n \" - Chess Business: Priyav, a college student, expressed his doubts on the MFM Facebook group about his Chess training business, mychesstutor.com, making $12.5K MRR with 90 enrolled.\\n\",\n \" - Restaurant Refiller: An MFM Facebook group member commented on how they pay AirMark $1,000/month for toilet paper and toilet cover refills for their restaurant. Shaan sees an opportunity here for anyone wanting to compete against AirMark.\\n\",\n \" - Collecting: Shaan shared an idea to build a mobile only marketplace for a collectors’ category; similar to what StockX does for premium sneakers.\\n\",\n \"% END OF EXAMPLES\\n\",\n \"\\\"\\\"\\\"\\n\",\n \"system_message_prompt_map = SystemMessagePromptTemplate.from_template(template)\\n\",\n \"\\n\",\n \"human_template=\\\"Transcript: {text}\\\" # Simply just pass the text as a human message\\n\",\n \"human_message_prompt_map = HumanMessagePromptTemplate.from_template(human_template)\\n\",\n \"\\n\",\n \"chat_prompt_map = ChatPromptTemplate.from_messages(messages=[system_message_prompt_map, human_message_prompt_map])\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"4e6825c1\",\n \"metadata\": {},\n \"source\": [\n \"Then we have our combine prompt which will run once over the results of the map prompt above\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 7,\n \"id\": \"75d6fc74\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"template=\\\"\\\"\\\"\\n\",\n \"You are a helpful assistant that helps retrieve topics talked about in a podcast transcript\\n\",\n \"- You will be given a series of bullet topics of topics vound\\n\",\n \"- Your goal is to exract the topic names and brief 1-sentence description of the topic\\n\",\n \"- Deduplicate any bullet points you see\\n\",\n \"- Only pull topics from the transcript. Do not use the examples\\n\",\n \"\\n\",\n \"% START OF EXAMPLES\\n\",\n \" - Sam’s Elisabeth Murdoch Story: Sam got a call from Elizabeth Murdoch when he had just launched The Hustle. She wanted to generate video content.\\n\",\n \" - Shaan’s Rupert Murdoch Story: When Shaan was running Blab he was invited to an event organized by Rupert Murdoch during CES in Las Vegas.\\n\",\n \"% END OF EXAMPLES\\n\",\n \"\\\"\\\"\\\"\\n\",\n \"system_message_prompt_map = SystemMessagePromptTemplate.from_template(template)\\n\",\n \"\\n\",\n \"human_template=\\\"Transcript: {text}\\\" # Simply just pass the text as a human message\\n\",\n \"human_message_prompt_map = HumanMessagePromptTemplate.from_template(human_template)\\n\",\n \"\\n\",\n \"chat_prompt_combine = ChatPromptTemplate.from_messages(messages=[system_message_prompt_map, human_message_prompt_map])\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"ce1e906a\",\n \"metadata\": {},\n \"source\": [\n \"### The First Pass - Run through your text and extract the topics per your custom prompts\\n\",\n \"Then we get our chain ready. This is object that will do the actual processing for us when we call it. I'm using gpt4 because we need the increased reasoning ability to pull out topics. You could use gpt3.5 but results may vary.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 8,\n \"id\": \"d0bb61ab\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"chain = load_summarize_chain(llm4,\\n\",\n \" chain_type=\\\"map_reduce\\\",\\n\",\n \" map_prompt=chat_prompt_map,\\n\",\n \" combine_prompt=chat_prompt_combine,\\n\",\n \"# verbose=True\\n\",\n \" )\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"68b12aed\",\n \"metadata\": {},\n \"source\": [\n \"Then the `.run()` code below will do the actual API calls and work\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 9,\n \"id\": \"98b9b205\",\n \"metadata\": {\n \"scrolled\": true\n },\n \"outputs\": [],\n \"source\": [\n \"topics_found = chain.run({\\\"input_documents\\\": docs})\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 10,\n \"id\": \"8f6bcb6e\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"- Hearing Aids Business: Shaan and Sam explore the potential profitability of the hearing aids industry.\\n\",\n \"- Children's Play Space Business: Shaan revisits a business idea about a membership-based children's play space.\\n\",\n \"- Steph Smith's Career: The hosts discuss Steph Smith's career progression, including her current role at Andreessen Horowitz.\\n\",\n \"- Working at Andreessen Horowitz: Steph shares insights about her experience at Andreessen Horowitz, a leading VC firm.\\n\",\n \"- Office Culture: The trio discuss the differences between working in an office environment and working remotely.\\n\",\n \"- Sam's Master Plan at Facebook: Sam shares advice he gave to his wife Sarah about making an impact at Facebook.\\n\",\n \"- Shaan's Strategy at Twitch: Shaan recounts his networking strategy during his time at Twitch.\\n\",\n \"- Commercial Real Estate Crisis: The hosts discuss the high vacancy rates in commercial real estate, particularly in cities like San Francisco.\\n\",\n \"- Opportunity in Fractional Real Estate: Steph suggests that the commercial real estate crisis could lead to opportunities in fractional real estate.\\n\",\n \"- Temple Immersive: The hosts discuss Temple Immersive, a nightclub that doubles as a yoga studio, as an example of fractional real estate.\\n\",\n \"- Rage Rooms: Steph introduces the concept of rage rooms, where people pay to destroy objects in a controlled environment.\\n\",\n \"- Escape Room Business Success: The hosts discuss Raleigh Williams' successful escape room business, which sold for $26 million.\\n\"\n ]\n }\n ],\n \"source\": [\n \"print (topics_found)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"99caca7c\",\n \"metadata\": {},\n \"source\": [\n \"### Structured Data - Turn your LLM output into structured data\\n\",\n \"\\n\",\n \"The LLM just returned a wall of text to us, I want to convert this into structured data I can more easily use elsewhere.\\n\",\n \"\\n\",\n \"We might have been able to do add structured output instructions to the pull above but I preferred to do it in two steps for clarity. Plus the cost us super low so we only have latency to worry about, but that isn't a priority for this tutorial.\\n\",\n \"\\n\",\n \"We will use OpenAI's [function calling](function Calling via ChatGPT API - First Look With LangChain - YouTube) to extract each topic.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 11,\n \"id\": \"0b1e14c2\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"schema = {\\n\",\n \" \\\"properties\\\": {\\n\",\n \" # The title of the topic\\n\",\n \" \\\"topic_name\\\": {\\n\",\n \" \\\"type\\\": \\\"string\\\",\\n\",\n \" \\\"description\\\" : \\\"The title of the topic listed\\\"\\n\",\n \" },\\n\",\n \" # The description\\n\",\n \" \\\"description\\\": {\\n\",\n \" \\\"type\\\": \\\"string\\\",\\n\",\n \" \\\"description\\\" : \\\"The description of the topic listed\\\"\\n\",\n \" },\\n\",\n \" \\\"tag\\\": {\\n\",\n \" \\\"type\\\": \\\"string\\\",\\n\",\n \" \\\"description\\\" : \\\"The type of content being described\\\",\\n\",\n \" \\\"enum\\\" : ['Business Models', 'Life Advice', 'Health & Wellness', 'Stories']\\n\",\n \" }\\n\",\n \" },\\n\",\n \" \\\"required\\\": [\\\"topic\\\", \\\"description\\\"],\\n\",\n \"}\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 12,\n \"id\": \"32e3b595\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# Using gpt3.5 here because this is an easy extraction task and no need to jump to gpt4\\n\",\n \"chain = create_extraction_chain(schema, llm3)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 13,\n \"id\": \"767cfbc5\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"topics_structured = chain.run(topics_found)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 14,\n \"id\": \"28ccaa5a\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"[{'topic_name': 'Hearing Aids Business',\\n\",\n \" 'description': 'Shaan and Sam explore the potential profitability of the hearing aids industry.',\\n\",\n \" 'tag': 'Business Models'},\\n\",\n \" {'topic_name': \\\"Children's Play Space Business\\\",\\n\",\n \" 'description': \\\"Shaan revisits a business idea about a membership-based children's play space.\\\",\\n\",\n \" 'tag': 'Business Models'},\\n\",\n \" {'topic_name': \\\"Steph Smith's Career\\\",\\n\",\n \" 'description': \\\"The hosts discuss Steph Smith's career progression, including her current role at Andreessen Horowitz.\\\",\\n\",\n \" 'tag': 'Business Models'},\\n\",\n \" {'topic_name': 'Working at Andreessen Horowitz',\\n\",\n \" 'description': 'Steph shares insights about her experience at Andreessen Horowitz, a leading VC firm.',\\n\",\n \" 'tag': 'Business Models'},\\n\",\n \" {'topic_name': 'Office Culture',\\n\",\n \" 'description': 'The trio discuss the differences between working in an office environment and working remotely.',\\n\",\n \" 'tag': 'Business Models'},\\n\",\n \" {'topic_name': \\\"Sam's Master Plan at Facebook\\\",\\n\",\n \" 'description': 'Sam shares advice he gave to his wife Sarah about making an impact at Facebook.',\\n\",\n \" 'tag': 'Life Advice'},\\n\",\n \" {'topic_name': \\\"Shaan's Strategy at Twitch\\\",\\n\",\n \" 'description': 'Shaan recounts his networking strategy during his time at Twitch.',\\n\",\n \" 'tag': 'Life Advice'},\\n\",\n \" {'topic_name': 'Commercial Real Estate Crisis',\\n\",\n \" 'description': 'The hosts discuss the high vacancy rates in commercial real estate, particularly in cities like San Francisco.',\\n\",\n \" 'tag': 'Business Models'},\\n\",\n \" {'topic_name': 'Opportunity in Fractional Real Estate',\\n\",\n \" 'description': 'Steph suggests that the commercial real estate crisis could lead to opportunities in fractional real estate.',\\n\",\n \" 'tag': 'Business Models'},\\n\",\n \" {'topic_name': 'Temple Immersive',\\n\",\n \" 'description': 'The hosts discuss Temple Immersive, a nightclub that doubles as a yoga studio, as an example of fractional real estate.',\\n\",\n \" 'tag': 'Business Models'},\\n\",\n \" {'topic_name': 'Rage Rooms',\\n\",\n \" 'description': 'Steph introduces the concept of rage rooms, where people pay to destroy objects in a controlled environment.',\\n\",\n \" 'tag': 'Business Models'},\\n\",\n \" {'topic_name': 'Escape Room Business Success',\\n\",\n \" 'description': \\\"The hosts discuss Raleigh Williams' successful escape room business, which sold for $26 million.\\\",\\n\",\n \" 'tag': 'Business Models'}]\"\n ]\n },\n \"execution_count\": 14,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"topics_structured\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"3bea8d61\",\n \"metadata\": {},\n \"source\": [\n \"Great, now we have our structured topics. Let's move into the next step and *expand* on those topics even more.\\n\",\n \"\\n\",\n \"## Step 2: Expand on the topics you found\\n\",\n \"\\n\",\n \"In order to expand on the topics we found we are going to do the vectorstore dance. We'll chunk our podcast into *small* chunks and then modify the retrieval and qa chain to help us pull out more information.\\n\",\n \"\\n\",\n \"I want to split into small chunks to hopefully increase the signal to noise ratio. Here I'll only do 4K characters which is less than half of what we did above.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 15,\n \"id\": \"d0b6b833\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"You have 8 docs. First doc is 776 tokens\\n\"\n ]\n }\n ],\n \"source\": [\n \"text_splitter = RecursiveCharacterTextSplitter(chunk_size=4000, chunk_overlap=800)\\n\",\n \"\\n\",\n \"docs = text_splitter.create_documents([transcript[:transcript_subsection_characters]])\\n\",\n \"\\n\",\n \"print (f\\\"You have {len(docs)} docs. First doc is {llm3.get_num_tokens(docs[0].page_content)} tokens\\\")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"80145b03\",\n \"metadata\": {},\n \"source\": [\n \"Because I want to do Question & Answer Retrieval, we need to get embeddings for our documents so we can pull out the docs which are similar for context later.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 16,\n \"id\": \"faa3a638\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"embeddings = OpenAIEmbeddings(openai_api_key=os.getenv('OPENAI_API_KEY', 'YourAPIKeyIfNotSet'))\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"fbdd1aeb\",\n \"metadata\": {},\n \"source\": [\n \"### Option #1: Pinecone\\n\",\n \"\\n\",\n \"Use this if you're looking for scale in the cloud\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 17,\n \"id\": \"88a021c4\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# initialize pinecone\\n\",\n \"pinecone.init(\\n\",\n \" api_key=os.getenv('PINECONE_API_KEY', 'YourAPIKeyIfNotSet'), # find at app.pinecone.io\\n\",\n \" environment=os.getenv('PINECONE_ENV', 'YourAPIKeyIfNotSet'), # next to api key in console\\n\",\n \")\\n\",\n \"\\n\",\n \"index_name = \\\"topic-modeling\\\"\\n\",\n \"\\n\",\n \"docsearch = Pinecone.from_documents(docs, embeddings, index_name=index_name)\\n\",\n \"\\n\",\n \"# # If you want to delete your vectors in your index to start over, run the code below!\\n\",\n \"# index = pinecone.Index(index_name)\\n\",\n \"# index.delete(delete_all='true')\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"7b914a90\",\n \"metadata\": {},\n \"source\": [\n \"### Option #2: Chroma\\n\",\n \"\\n\",\n \"Use this if you're looking for local and easy to set up\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 22,\n \"id\": \"31ce1b1a\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# load it into Chroma\\n\",\n \"docsearch = Chroma.from_documents(docs, embeddings)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"5ee90371\",\n \"metadata\": {},\n \"source\": [\n \"Then we are going to create a custom prompt for our Retriever. I'm doing this because the out of the [out-of-the-box](https://github.com/hwchase17/langchain/blob/7414e9d19603c962063dd337cdcf3c3168d4b8be/langchain/chains/question_answering/stuff_prompt.py#L20) prompt used here isn't bad, but a bit generic for my use case. Plus, I only really want to *answer a question* I want to generated a mini-summary based off of docs.\\n\",\n \"\\n\",\n \"Let's switch it up!\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 23,\n \"id\": \"b6ee1f6e\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# The system instructions. Notice the 'context' placeholder down below. This is where our relevant docs will go.\\n\",\n \"# The 'question' in the human message below won't be a question per se, but rather a topic we want to get relevant information on\\n\",\n \"system_template = \\\"\\\"\\\"\\n\",\n \"You will be given text from a podcast transcript which contains many topics.\\n\",\n \"You goal is to write a summary (5 sentences or less) about a topic the user chooses\\n\",\n \"Do not respond with information that isn't relevant to the topic that the user gives you\\n\",\n \"----------------\\n\",\n \"{context}\\\"\\\"\\\"\\n\",\n \"\\n\",\n \"messages = [\\n\",\n \" SystemMessagePromptTemplate.from_template(system_template),\\n\",\n \" HumanMessagePromptTemplate.from_template(\\\"{question}\\\"),\\n\",\n \"]\\n\",\n \"\\n\",\n \"# This will pull the two messages together and get them ready to be sent to the LLM through the retriever\\n\",\n \"CHAT_PROMPT = ChatPromptTemplate.from_messages(messages)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 24,\n \"id\": \"35eb54d3\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# I'm using gpt4 for the increased reasoning power.\\n\",\n \"# I'm also setting k=4 so the number of relevant docs we get back is 4. This parameter should be tuned to your use case\\n\",\n \"qa = RetrievalQA.from_chain_type(llm=llm4,\\n\",\n \" chain_type=\\\"stuff\\\",\\n\",\n \" retriever=docsearch.as_retriever(k=4),\\n\",\n \" chain_type_kwargs = {\\n\",\n \"# 'verbose': True,\\n\",\n \" 'prompt': CHAT_PROMPT\\n\",\n \" })\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"6cdd1fe6\",\n \"metadata\": {},\n \"source\": [\n \"Then let's iterate through the topics that we found and run our QA query on them.\\n\",\n \"\\n\",\n \"This will print out our expanded topics. This is the final result you can use wherever you want!\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 25,\n \"id\": \"319bebc5\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"Hearing Aids Business: Shaan and Sam explore the potential profitability of the hearing aids industry.\\n\",\n \"Shaan Puri and Sam Parr discussed the potential of the hearing aids industry, noting that it could be a profitable venture. They did not provide specific details about the industry but expressed optimism about its potential.\\n\",\n \"\\n\",\n \"\\n\",\n \"\\n\",\n \"Children's Play Space Business: Shaan revisits a business idea about a membership-based children's play space.\\n\",\n \"Shaan Puri discussed a business idea he had previously mentioned about a children's play space. This business operates on a membership basis where parents pay a fee for their children to play with various toys inside the facility. However, Shaan clarified that he does not endorse this business idea, as he only had a single experience with it and does not know if it is profitable or not. He expressed concern that listeners might have taken his discussion as a recommendation and invested in similar franchises.\\n\",\n \"\\n\",\n \"\\n\",\n \"\\n\",\n \"Steph Smith's Career: The hosts discuss Steph Smith's career progression, including her current role at Andreessen Horowitz.\\n\",\n \"Steph Smith, who started her career with a blog, was invited by Sam Parr to join Trends due to her impressive headline writing. After working there for a couple of years, she moved on to Andreessen Horowitz, one of the world's largest venture capital firms. Despite initially feeling out of place, she has now settled into her role and is enjoying her work. She also runs a podcast which she considers an asset to the firm. The hosts encourage her to take advantage of her position to network and learn from the smart people around her.\\n\",\n \"\\n\",\n \"\\n\",\n \"\\n\",\n \"Working at Andreessen Horowitz: Steph shares insights about her experience at Andreessen Horowitz, a leading VC firm.\\n\",\n \"Steph Smith, who works at Andreessen Horowitz, discussed her experience at the firm during a podcast. She mentioned that she initially felt out of place among the high-achieving individuals at the firm, but has since grown more comfortable. Her colleagues advised her to take advantage of the opportunity to interact with some of the smartest people in the world, rather than just focusing on her job. They suggested she should be present in the office every day to seize any potential opportunities. Steph also mentioned that she feels the podcast she runs is an asset to the firm.\\n\",\n \"\\n\",\n \"\\n\",\n \"\\n\",\n \"Office Culture: The trio discuss the differences between working in an office environment and working remotely.\\n\",\n \"Shaan Puri and Sam Parr encourage Steph Smith to take advantage of her position at Andreessen Horowitz by being physically present in the office and interacting with the high-profile individuals there. They argue that the real value of her job is the opportunity to network and learn from some of the smartest people in the world. Steph, who has been working remotely for the past eight years, admits she needs to be more proactive in creating these interactions. Shaan shares his own experience at Twitch, where he prioritized attending interesting meetings over his actual job responsibilities, which he believes led to his success.\\n\",\n \"\\n\",\n \"\\n\",\n \"\\n\"\n ]\n }\n ],\n \"source\": [\n \"# Only doing the first 3 for conciseness \\n\",\n \"for topic in topics_structured[:5]:\\n\",\n \" query = f\\\"\\\"\\\"\\n\",\n \" {topic['topic_name']}: {topic['description']}\\n\",\n \" \\\"\\\"\\\"\\n\",\n \"\\n\",\n \" expanded_topic = qa.run(query)\\n\",\n \"\\n\",\n \" print(f\\\"{topic['topic_name']}: {topic['description']}\\\")\\n\",\n \" print(expanded_topic)\\n\",\n \" print (\\\"\\\\n\\\\n\\\")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"2af12d27\",\n \"metadata\": {},\n \"source\": [\n \"## Bonus: Chapters With Timestamps\\n\",\n \"\\n\",\n \"Because why not?\\n\",\n \"\\n\",\n \"We have the timestamps on the transcript so let's pull them out and get timestamp chapters. This is helpful so you can scrub to the topic when you're listening.\\n\",\n \"\\n\",\n \"I tried a few methods to do this, including function calling, but I found just a regular prompt worked great. It's not *that* hard of a task to pull out a timestamp. I did the Retrieval chain again to get relevant documents, then asked the LLM to pull out the earliest timestamp it saw a topic was talked about.\\n\",\n \"\\n\",\n \"**Hardcore**: Right now this will pull out the timestamp of the monologue. However the topic may or may not start at the beginning, maybe it's the middle? Timestamps could be off. If you wanted to go more hardcore accurate you could go down to the word level and make a guestimate as to when the topic actually started.\\n\",\n \"\\n\",\n \"Same as above, we'll make custom prompts for our QA chain\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 26,\n \"id\": \"fffe4acd\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"system_template = \\\"\\\"\\\"\\n\",\n \"What is the first timestamp when the speakers started talking about a topic the user gives?\\n\",\n \"Only respond with the timestamp, nothing else. Example: 0:18:24\\n\",\n \"----------------\\n\",\n \"{context}\\\"\\\"\\\"\\n\",\n \"messages = [\\n\",\n \" SystemMessagePromptTemplate.from_template(system_template),\\n\",\n \" HumanMessagePromptTemplate.from_template(\\\"{question}\\\"),\\n\",\n \"]\\n\",\n \"CHAT_PROMPT = ChatPromptTemplate.from_messages(messages)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 27,\n \"id\": \"53da58b7\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"qa = RetrievalQA.from_chain_type(llm=llm4,\\n\",\n \" chain_type=\\\"stuff\\\",\\n\",\n \" retriever=docsearch.as_retriever(k=4),\\n\",\n \" chain_type_kwargs = {\\n\",\n \"# 'verbose': True,\\n\",\n \" 'prompt': CHAT_PROMPT\\n\",\n \" })\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 28,\n \"id\": \"ff8085a8\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# Holder for our topic timestamps\\n\",\n \"topic_timestamps = []\\n\",\n \"\\n\",\n \"for topic in topics_structured:\\n\",\n \"\\n\",\n \" query = f\\\"{topic['topic_name']} - {topic['description']}\\\"\\n\",\n \" timestamp = qa.run(query)\\n\",\n \" \\n\",\n \" topic_timestamps.append(f\\\"{timestamp} - {topic['topic_name']}\\\")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"88a0a1f1\",\n \"metadata\": {},\n \"source\": [\n \"They might be out of order so let's sort them and print\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 29,\n \"id\": \"35f75f16\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"0:00:00 - Hearing Aids Business\\n\",\n \"0:00:40 - Children's Play Space Business\\n\",\n \"0:04:24 - Office Culture\\n\",\n \"0:04:26 - Steph Smith's Career\\n\",\n \"0:05:27 - Working at Andreessen Horowitz\\n\",\n \"0:06:37 - Sam's Master Plan at Facebook\\n\",\n \"0:09:21 - Shaan's Strategy at Twitch\\n\",\n \"0:12:32 - Commercial Real Estate Crisis\\n\",\n \"0:12:32 - Opportunity in Fractional Real Estate\\n\",\n \"0:13:10 - Temple Immersive\\n\",\n \"0:14:56 - Rage Rooms\\n\",\n \"0:16:43 - Escape Room Business Success\\n\"\n ]\n }\n ],\n \"source\": [\n \"print (\\\"\\\\n\\\".join(sorted(topic_timestamps)))\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"d053fb4c\",\n \"metadata\": {},\n \"source\": [\n \"Check out the audio for this episode [here](https://steno.ai/my-first-million/steph-smith-jobs-of-the-future-fractional-real-estate-mouth)\\n\",\n \"\\n\",\n \"Awesome! This is great, what domain are you going to parse topics from? Please let me know on [Twitter](https://twitter.com/GregKamradt) or contact me directly at contact@dataindependent.com\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"id\": \"9fc1da1e\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": []\n }\n ],\n \"metadata\": {\n \"kernelspec\": {\n \"display_name\": \"Python 3 (ipykernel)\",\n \"language\": \"python\",\n \"name\": \"python3\"\n },\n \"language_info\": {\n \"codemirror_mode\": {\n \"name\": \"ipython\",\n \"version\": 3\n },\n \"file_extension\": \".py\",\n \"mimetype\": \"text/x-python\",\n \"name\": \"python\",\n \"nbconvert_exporter\": \"python\",\n \"pygments_lexer\": \"ipython3\",\n \"version\": \"3.9.13\"\n }\n },\n \"nbformat\": 4,\n \"nbformat_minor\": 5\n}\n" }, { "path": "data_generation/Using LLMs To Summarize Personal Research.ipynb", "content": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"id\": \"4396197f\",\n \"metadata\": {},\n \"source\": [\n \"# Using LLMs To Summarize Personal Research\\n\",\n \"\\n\",\n \"Our goal is to have LLM aid us in generating interview quetions for someone. I find that I'm constantly trying to ramp up to a person's background and story when preparing to meet them.\\n\",\n \"\\n\",\n \"There is a ton of awesome resources about a person online we can use\\n\",\n \"\\n\",\n \"* Twitter Profiles\\n\",\n \"* Websites\\n\",\n \"* Other Interviews (YouTube or Text)\\n\",\n \"\\n\",\n \"Let's bring all these together by first pulling the information and then generating questions or bullet points we can use as preparation.\\n\",\n \"\\n\",\n \"First let's import our packages! We'll be using LangChain to help us interact with OpenAI\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 1,\n \"id\": \"3311cda3\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"True\"\n ]\n },\n \"execution_count\": 1,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"# LLMs\\n\",\n \"from langchain import PromptTemplate\\n\",\n \"from langchain.llms import OpenAI\\n\",\n \"from langchain.chat_models import ChatOpenAI\\n\",\n \"from langchain.text_splitter import RecursiveCharacterTextSplitter\\n\",\n \"from langchain.chains.summarize import load_summarize_chain\\n\",\n \"from langchain.prompts import PromptTemplate\\n\",\n \"\\n\",\n \"# Twitter\\n\",\n \"import tweepy\\n\",\n \"\\n\",\n \"# Scraping\\n\",\n \"import requests\\n\",\n \"from bs4 import BeautifulSoup\\n\",\n \"from markdownify import markdownify as md\\n\",\n \"\\n\",\n \"# YouTube\\n\",\n \"from langchain.document_loaders import YoutubeLoader\\n\",\n \"# !pip install youtube-transcript-api\\n\",\n \"\\n\",\n \"# Environment Variables\\n\",\n \"import os\\n\",\n \"from dotenv import load_dotenv\\n\",\n \"\\n\",\n \"load_dotenv()\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"1578a7f5\",\n \"metadata\": {},\n \"source\": [\n \"You'll need a few API keys to complete the script below. It's modular so if you don't want to pull from Twitter feel free to leave those blank\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 2,\n \"id\": \"394a7c4e\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"TWITTER_API_KEY = os.getenv('TWITTER_API_KEY', 'YourAPIKeyIfNotSet')\\n\",\n \"TWITTER_API_SECRET = os.getenv('TWITTER_API_SECRET', 'YourAPIKeyIfNotSet')\\n\",\n \"TWITTER_ACCESS_TOKEN = os.getenv('TWITTER_ACCESS_TOKEN', 'YourAPIKeyIfNotSet')\\n\",\n \"TWITTER_ACCESS_TOKEN_SECRET = os.getenv('TWITTER_ACCESS_TOKEN_SECRET', 'YourAPIKeyIfNotSet')\\n\",\n \"OPENAI_API_KEY = os.getenv('OPENAI_API_KEY', 'YourAPIKeyIfNotSet')\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"dc50fe5e\",\n \"metadata\": {},\n \"source\": [\n \"For this tutorial, let's pretend we are going to be interviewing [Elad Gil](https://eladgil.com/) since he has a bunch of content online\\n\",\n \"\\n\",\n \"### Pulling Data From Twitter\\n\",\n \"Great, now let's set up a function that will pull tweets for us. This will help us get current events that the user is talking about. I'm excluding replies since they usually don't have a ton of high signal text from the user. This is the same code that was used in the [Twitter AI Bot tutorial](https://youtu.be/yLWLDjT01q8).\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 3,\n \"id\": \"edd68521\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"def get_original_tweets(screen_name, tweets_to_pull=80, tweets_to_return=80):\\n\",\n \" \\n\",\n \" # Tweepy set up\\n\",\n \" auth = tweepy.OAuthHandler(TWITTER_API_KEY, TWITTER_API_SECRET)\\n\",\n \" auth.set_access_token(TWITTER_ACCESS_TOKEN, TWITTER_ACCESS_TOKEN_SECRET)\\n\",\n \" api = tweepy.API(auth)\\n\",\n \"\\n\",\n \" # Holder for the tweets you'll find\\n\",\n \" tweets = []\\n\",\n \" \\n\",\n \" # Go and pull the tweets\\n\",\n \" tweepy_results = tweepy.Cursor(api.user_timeline,\\n\",\n \" screen_name=screen_name,\\n\",\n \" tweet_mode='extended',\\n\",\n \" exclude_replies=True).items(tweets_to_pull)\\n\",\n \" \\n\",\n \" # Run through tweets and remove retweets and quote tweets so we can only look at a user's raw emotions\\n\",\n \" for status in tweepy_results:\\n\",\n \" if hasattr(status, 'retweeted_status') or hasattr(status, 'quoted_status'):\\n\",\n \" # Skip if it's a retweet or quote tweet\\n\",\n \" continue\\n\",\n \" else:\\n\",\n \" tweets.append({'full_text': status.full_text, 'likes': status.favorite_count})\\n\",\n \"\\n\",\n \" \\n\",\n \" # Sort the tweets by number of likes. This will help us short_list the top ones later\\n\",\n \" sorted_tweets = sorted(tweets, key=lambda x: x['likes'], reverse=True)\\n\",\n \"\\n\",\n \" # Get the text and drop the like count from the dictionary\\n\",\n \" full_text = [x['full_text'] for x in sorted_tweets][:tweets_to_return]\\n\",\n \" \\n\",\n \" # Convert the list of tweets into a string of tweets we can use in the prompt later\\n\",\n \" users_tweets = \\\"\\\\n\\\\n\\\".join(full_text)\\n\",\n \" \\n\",\n \" return users_tweets\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"0c968c57\",\n \"metadata\": {},\n \"source\": [\n \"Ok cool, let's try it out!\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 4,\n \"id\": \"c9871622\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"More AI companies with sudden virality + paying customers should just bootstrap\\n\",\n \"\\n\",\n \"0. Running co for cash may be best success\\n\",\n \"\\n\",\n \"1. If it does scale, being profitable or near to it creates lot of options\\n\",\n \"\\n\",\n \"2. it may not scale, or only work for a few months\\n\",\n \"\\n\",\n \"3. Why get on the… https://t.co/Q9TRQo4yau\\n\",\n \"\\n\",\n \"Som\\n\"\n ]\n }\n ],\n \"source\": [\n \"user_tweets = get_original_tweets(\\\"eladgil\\\")\\n\",\n \"print (user_tweets[:300])\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"bba8191a\",\n \"metadata\": {},\n \"source\": [\n \"Awesome, now we have a few tweets let's move onto pulling data from a web page or two.\\n\",\n \"\\n\",\n \"### Pulling Data From Websites\\n\",\n \"\\n\",\n \"Let's do two pages\\n\",\n \"\\n\",\n \"1. His personal website which has his background - https://eladgil.com/\\n\",\n \"2. One of my favorite blog posts from him around AI defensibility & moats - https://blog.eladgil.com/p/defensibility-and-competition\\n\",\n \"\\n\",\n \"First let's create a function that will scrape a website for us.\\n\",\n \"\\n\",\n \"We'll do this by pulling the raw html, put it in a BeautifulSoup object, then convert that object to Markdown for better parsing\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 5,\n \"id\": \"67c5c796\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"def pull_from_website(url):\\n\",\n \" \\n\",\n \" # Doing a try in case it doesn't work\\n\",\n \" try:\\n\",\n \" response = requests.get(url)\\n\",\n \" except:\\n\",\n \" # In case it doesn't work\\n\",\n \" print (\\\"Whoops, error\\\")\\n\",\n \" return\\n\",\n \" \\n\",\n \" # Put your response in a beautiful soup\\n\",\n \" soup = BeautifulSoup(response.text, 'html.parser')\\n\",\n \" \\n\",\n \" # Get your text\\n\",\n \" text = soup.get_text()\\n\",\n \"\\n\",\n \" # Convert your html to markdown. This reduces tokens and noise\\n\",\n \" text = md(text)\\n\",\n \" \\n\",\n \" return text\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 6,\n \"id\": \"a24e408e\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# I'm going to store my website data in a simple string.\\n\",\n \"# There is likely optimization to make this better but it's a solid 80% solution\\n\",\n \"\\n\",\n \"website_data = \\\"\\\"\\n\",\n \"urls = [\\\"https://eladgil.com/\\\", \\\"https://blog.eladgil.com/p/defensibility-and-competition\\\"]\\n\",\n \"\\n\",\n \"for url in urls:\\n\",\n \" text = pull_from_website(url)\\n\",\n \" \\n\",\n \" website_data += text\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"a05784b1\",\n \"metadata\": {},\n \"source\": [\n \"Awesome, now that we have both of those data sources, let's check out a sample\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 7,\n \"id\": \"207a6b1a\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"\\n\",\n \"\\n\",\n \"\\n\",\n \"Elad Gil\\n\",\n \"\\n\",\n \"\\n\",\n \"\\n\",\n \"\\n\",\n \"Welcome to Elad Gil's retro homepage!\\n\",\n \"\\n\",\n \" Who? I am a technology entrepreneur. LinkedIn profile is here.\\n\",\n \"What?\\n\",\n \"I am an investor or advisor to companies including Airbnb, Airtable, Anduril, Brex, Checkr, Coinbase, dbt Labs, Deel, Figma, Flexport, Gitlab, Gusto, Instacart, Navan, Notion, Opendoor, PagerDuty, Pinterest, Retool, Rippling, Samsara, Square, Stripe\\n\",\n \"I am involved with AI com\\n\"\n ]\n }\n ],\n \"source\": [\n \"print (website_data[:400])\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"1b7ba6f4\",\n \"metadata\": {},\n \"source\": [\n \"Awesome, to round us off, let's get the information from a youtube video. YouTube has tons of data like Podcasts and interviews. This will be valuable for us to have.\\n\",\n \"\\n\",\n \"### Pulling Data From YouTube\\n\",\n \"\\n\",\n \"We'll use LangChains YouTube loaders for this. It only works if there is a transcript on the YT video already, if there isn't then we'll move on. You could get the transcript via Whisper if you really wanted to, but that's out of scope for today.\\n\",\n \"\\n\",\n \"We'll make a function we can use to loop through videos\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 11,\n \"id\": \"9ee1b47d\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# Pulling data from YouTube in text form\\n\",\n \"def get_video_transcripts(url):\\n\",\n \" loader = YoutubeLoader.from_youtube_url(url, add_video_info=True)\\n\",\n \" documents = loader.load()\\n\",\n \" transcript = ' '.join([doc.page_content for doc in documents])\\n\",\n \" return transcript\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 13,\n \"id\": \"b9bd52eb\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# Using a regular string to store the youtube transcript data\\n\",\n \"# Video selection will be important.\\n\",\n \"# Parsing interviews is a whole other can of worms so I'm opting for one where Elad is mostly talking about himself\\n\",\n \"video_urls = ['https://www.youtube.com/watch?v=nglHX4B33_o']\\n\",\n \"videos_text = \\\"\\\"\\n\",\n \"\\n\",\n \"for video_url in video_urls:\\n\",\n \" video_text = get_video_transcripts(video_url)\\n\",\n \" \\n\",\n \" videos_text += video_text\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"ba8befc0\",\n \"metadata\": {},\n \"source\": [\n \"Let's look at at sample from the video\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 14,\n \"id\": \"48a3119e\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"I like to say that startups are an act of desperation and the desperation went out of the ecosystem over the last two or three years and we just had people showing up for the status and the money and now I think it's getting back to people who are doing it for a variety of reasons including the impa\\n\"\n ]\n }\n ],\n \"source\": [\n \"print(video_text[:300])\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"feb2238e\",\n \"metadata\": {},\n \"source\": [\n \"Awesome now that we have all of our data, let's combine it together into a single information block\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 15,\n \"id\": \"879b32fd\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"user_information = user_tweets + website_data + video_text\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"502e8be1\",\n \"metadata\": {},\n \"source\": [\n \"Our `user_information` variable is a big messy wall of text. Ideally we would clean this up more and try to increase the signal to noise ratio. However for this project we'll just focus on the core use case of gathering data.\\n\",\n \"\\n\",\n \"Next we'll chunk our wall of text into pieces so we can do a map_reduce process on it. If you want learn more about techniques to split up your data check out my video on [OpenAI Token Workarounds](https://www.youtube.com/watch?v=f9_BWhCI4Zo)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 16,\n \"id\": \"61a563bb\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# First we make our text splitter\\n\",\n \"text_splitter = RecursiveCharacterTextSplitter(chunk_size=20000, chunk_overlap=2000)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 17,\n \"id\": \"4e98c609\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# Then we split our user information into different documents\\n\",\n \"docs = text_splitter.create_documents([user_information])\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 18,\n \"id\": \"e2c6799e\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"3\"\n ]\n },\n \"execution_count\": 18,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"# Let's see how many documents we created\\n\",\n \"len(docs)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"2c2d766c\",\n \"metadata\": {},\n \"source\": [\n \"Because we have a special requset for the LLM on our data, I want to make custom prompts. This will allow me to tinker with what data the LLM pulls out. I'll use Langchain's `load_summarize_chain` with custom prompts to do this. We aren't making a summary, but rather just using `load_summarize_chain` for its easy mapreduce functionality.\\n\",\n \"\\n\",\n \"First let's make our custom map prompt. This is where we'll instruction the LLM that it will pull out interview questoins and what makes a good question.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 19,\n \"id\": \"835c6cd7\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"map_prompt = \\\"\\\"\\\"You are a helpful AI bot that aids a user in research.\\n\",\n \"Below is information about a person named {persons_name}.\\n\",\n \"Information will include tweets, interview transcripts, and blog posts about {persons_name}\\n\",\n \"Your goal is to generate interview questions that we can ask {persons_name}\\n\",\n \"Use specifics from the research when possible\\n\",\n \"\\n\",\n \"% START OF INFORMATION ABOUT {persons_name}:\\n\",\n \"{text}\\n\",\n \"% END OF INFORMATION ABOUT {persons_name}:\\n\",\n \"\\n\",\n \"Please respond with list of a few interview questions based on the topics above\\n\",\n \"\\n\",\n \"YOUR RESPONSE:\\\"\\\"\\\"\\n\",\n \"map_prompt_template = PromptTemplate(template=map_prompt, input_variables=[\\\"text\\\", \\\"persons_name\\\"])\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"48ef7a88\",\n \"metadata\": {},\n \"source\": [\n \"Then we'll make our custom combine promopt. This is the set of instructions that we'll LLM on how to handle the list of questions that is returned in the first step above.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 20,\n \"id\": \"f09dee43\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"combine_prompt = \\\"\\\"\\\"\\n\",\n \"You are a helpful AI bot that aids a user in research.\\n\",\n \"You will be given a list of potential interview questions that we can ask {persons_name}.\\n\",\n \"\\n\",\n \"Please consolidate the questions and return a list\\n\",\n \"\\n\",\n \"% INTERVIEW QUESTIONS\\n\",\n \"{text}\\n\",\n \"\\\"\\\"\\\"\\n\",\n \"combine_prompt_template = PromptTemplate(template=combine_prompt, input_variables=[\\\"text\\\", \\\"persons_name\\\"])\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"7d58ea84\",\n \"metadata\": {},\n \"source\": [\n \"Let's create our LLM and chain. I'm increasing the color a bit for more creative language. If you notice that your questions have hallucinations in them, turn temperature to 0\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 21,\n \"id\": \"583e4696\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"llm = ChatOpenAI(temperature=.25, model_name='gpt-4')\\n\",\n \"\\n\",\n \"chain = load_summarize_chain(llm,\\n\",\n \" chain_type=\\\"map_reduce\\\",\\n\",\n \" map_prompt=map_prompt_template,\\n\",\n \" combine_prompt=combine_prompt_template,\\n\",\n \"# verbose=True\\n\",\n \" )\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"5645594d\",\n \"metadata\": {},\n \"source\": [\n \"Ok, finally! With all of our data gathered and prompts ready, let's run our chain\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 22,\n \"id\": \"9cde3021\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stderr\",\n \"output_type\": \"stream\",\n \"text\": [\n \"Warning: model not found. Using cl100k_base encoding.\\n\"\n ]\n }\n ],\n \"source\": [\n \"output = chain({\\\"input_documents\\\": docs, # The seven docs that were created before\\n\",\n \" \\\"persons_name\\\": \\\"Elad Gil\\\"\\n\",\n \" })\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 23,\n \"id\": \"b4f49991\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"1. As an investor and advisor to various AI companies, what are some common challenges you've observed in the industry, and how do you recommend overcoming them?\\n\",\n \"\\n\",\n \"2. Can you elaborate on the advantages of bootstrapping for AI startups and share any success stories you've come across?\\n\",\n \"\\n\",\n \"3. What are some key lessons you've learned from your experiences in high-profile companies like Twitter, Google, and Color Health that have shaped your approach to investing and advising startups?\\n\",\n \"\\n\",\n \"4. How do you think AI will continue to shape the job market in the coming years?\\n\",\n \"\\n\",\n \"5. What motivated you to enter the healthcare space as a co-founder of Color Health, and how do you envision the role of AI in improving healthcare outcomes?\\n\",\n \"\\n\",\n \"6. Can you share some insights on what sets high growth companies apart from others and the key factors that contribute to their rapid growth?\\n\",\n \"\\n\",\n \"7. How do you evaluate the defensibility of AI startups when considering investment or advisory opportunities?\\n\",\n \"\\n\",\n \"8. What excites you the most about the future of AI, and what challenges do you foresee in its development and implementation?\\n\",\n \"\\n\",\n \"9. Can you share your vision for Color Health and how it aims to revolutionize the healthcare industry?\\n\",\n \"\\n\",\n \"10. What were the key challenges you faced during the rapid growth of Twitter, and how did you overcome them?\\n\",\n \"\\n\",\n \"11. What advice would you give to founders looking to build defensibility into their startups from the beginning?\\n\",\n \"\\n\",\n \"12. Can you share an example of a company that has successfully maintained a user-centric focus and how it has contributed to their success?\\n\",\n \"\\n\",\n \"13. How do you see the balance between serving customer needs and building defensibility evolving in the future of AI-driven products and services?\\n\",\n \"\\n\",\n \"14. Can you elaborate on the factors that contribute to your prediction of 2023 being a rough year for mid to late-stage private technology companies and how startups can prepare for these challenges?\\n\",\n \"\\n\",\n \"15. What do you think are the most promising applications of large language models like GPT in the near future, and how can startups leverage them for growth?\\n\",\n \"\\n\",\n \"16. How do you see the open versus closed structure playing out in the AI industry, and what implications could it have for startups and established companies in the AI space?\\n\",\n \"\\n\",\n \"17. How do you think the costs involved in training large language models like GPT-3 and GPT-4 will affect competition and innovation in the AI industry, particularly for startups with limited resources?\\n\",\n \"\\n\",\n \"18. What do you think are the key factors driving growth in the space and defense technology sector, and what opportunities do you see for startups in this industry?\\n\",\n \"\\n\",\n \"19. How do you envision the future of defense tech startups, and what challenges do they need to overcome to succeed in this competitive landscape?\\n\",\n \"\\n\",\n \"20. What lessons can other startups in the defense sector learn from Anduril's success, and how can they apply these strategies to their own businesses?\\n\"\n ]\n }\n ],\n \"source\": [\n \"print (output['output_text'])\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"73d84509\",\n \"metadata\": {},\n \"source\": [\n \"Awesome! Now we have some questions we can iterate on before we chat with the person. You can swap out different sources for different people.\\n\",\n \"\\n\",\n \"These questions won't be 100% 'copy & paste' ready, but they should serve as a really solid starting point for you to build on top of.\\n\",\n \"\\n\",\n \"Next, let's port this code over to a [Streamlit](https://streamlit.io/) app so we can share a deployed version easily\"\n ]\n }\n ],\n \"metadata\": {\n \"kernelspec\": {\n \"display_name\": \"Python 3 (ipykernel)\",\n \"language\": \"python\",\n \"name\": \"python3\"\n },\n \"language_info\": {\n \"codemirror_mode\": {\n \"name\": \"ipython\",\n \"version\": 3\n },\n \"file_extension\": \".py\",\n \"mimetype\": \"text/x-python\",\n \"name\": \"python\",\n \"nbconvert_exporter\": \"python\",\n \"pygments_lexer\": \"ipython3\",\n \"version\": \"3.9.13\"\n }\n },\n \"nbformat\": 4,\n \"nbformat_minor\": 5\n}\n" }, { "path": "data_generation/Working With Call or Video Transcripts.ipynb", "content": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"id\": \"89bbc4d0\",\n \"metadata\": {},\n \"source\": [\n \"### Extract Data From Calls & Video Transcripts/Interviews\\n\",\n \"\\n\",\n \"There is a lot of spoke word out there. Podcasts, interviews, sales calls, phone calls.\\n\",\n \"\\n\",\n \"It is extremely useful to be able to extract this information and create value with it. We're going to run through an example focusing on the B2B sales use case.\\n\",\n \"\\n\",\n \"**Small plug:** This is a mini-preview on how I built [Thimble](https://thimbleai.com/) which helps Account Executives pull information from their sales calls. Sign up at https://thimbleai.com/ if you want to check it out or here's the [demo video](https://youtu.be/DIw4rbpI9ic) or see more information on [Twitter](https://twitter.com/GregKamradt)\\n\",\n \"\\n\",\n \"Plug over, Let's learn! 😈\\n\",\n \"\\n\",\n \"Through building Thimble I've learned a few tricks to make working with transcripts easier:\\n\",\n \"1. **Name/Role -** Put the name of each person before their sentence. Bonus points if you have their role/company included too. Example: Greg (Marin Transitions): Hey! How's it going?\\n\",\n \"2. **System instructions -** Be specific with your system prompt about the role you need you bot to play\\n\",\n \"3. **Only pull from the call -** Emphasize not to make anything up\\n\",\n \"4. **Don't make the user prompt -** Abstract away any user prompting necessary with key:value pairs\\n\",\n \"\\n\",\n \"First let's import our packages\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 1,\n \"id\": \"37dedf37\",\n \"metadata\": {\n \"hide_input\": false\n },\n \"outputs\": [\n {\n \"data\": {\n \"text/html\": [\n \"\"\n ],\n \"text/plain\": [\n \"\"\n ]\n },\n \"metadata\": {},\n \"output_type\": \"display_data\"\n }\n ],\n \"source\": [\n \"# To get environment variables\\n\",\n \"import os\\n\",\n \"\\n\",\n \"# Make the display a bit wider\\n\",\n \"from IPython.display import display, HTML\\n\",\n \"display(HTML(\\\"\\\"))\\n\",\n \"\\n\",\n \"# To split our transcript into pieces\\n\",\n \"from langchain.text_splitter import RecursiveCharacterTextSplitter\\n\",\n \"\\n\",\n \"# Our chat model. We'll use the default which is gpt-3.5-turbo\\n\",\n \"from langchain.chat_models import ChatOpenAI\\n\",\n \"from langchain.chains.summarize import load_summarize_chain\\n\",\n \"\\n\",\n \"# Prompt templates for dynamic values\\n\",\n \"from langchain.prompts.chat import (\\n\",\n \" ChatPromptTemplate,\\n\",\n \" SystemMessagePromptTemplate,\\n\",\n \" AIMessagePromptTemplate, # I included this one so you know you'll have it but we won't be using it\\n\",\n \" HumanMessagePromptTemplate\\n\",\n \")\\n\",\n \"\\n\",\n \"# To create our chat messages\\n\",\n \"from langchain.schema import (\\n\",\n \" AIMessage,\\n\",\n \" HumanMessage,\\n\",\n \" SystemMessage\\n\",\n \")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 22,\n \"id\": \"9cae352a\",\n \"metadata\": {\n \"hide_input\": false\n },\n \"outputs\": [],\n \"source\": [\n \"os.environ['OPENAI_API_KEY'] = '...'\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"aacd8f98\",\n \"metadata\": {},\n \"source\": [\n \"Then let's load up our data. This is already a formatted transcript of a mock sales call. 70% of the hard part is getting clean data. Don't under estimate the reward you get for cleaning up your data first!\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 3,\n \"id\": \"1f13dda0\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"with open('../data/Transcripts/acme_co_v2.txt', 'r') as file:\\n\",\n \" content = file.read()\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 4,\n \"id\": \"32b146c6\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"Transcript:\\n\",\n \"\\n\",\n \"Greg (Marin Transitions Partner): Does this say the call is recording for you at all? \\n\",\n \"\\n\",\n \"Eliza (ACME Co): But it says the request, the report or in here? \\n\",\n \"\\n\",\n \"Greg (Marin Transitions Partner): Nice. All right… one sec. \\n\"\n ]\n }\n ],\n \"source\": [\n \"print (\\\"Transcript:\\\\n\\\")\\n\",\n \"print(content[:215]) # Why 215? Because it cut off at a clean line\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"8f6b6ceb\",\n \"metadata\": {},\n \"source\": [\n \"Split our documents so we don't run into token issues. Experiment with what chunk size words best for your use case\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 5,\n \"id\": \"042b7d95\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"text_splitter = RecursiveCharacterTextSplitter(separators=[\\\"\\\\n\\\\n\\\", \\\"\\\\n\\\"], chunk_size=2000, chunk_overlap=250)\\n\",\n \"texts = text_splitter.create_documents([content])\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 6,\n \"id\": \"f22c76e1\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"You have 5 texts\\n\"\n ]\n },\n {\n \"data\": {\n \"text/plain\": [\n \"Document(page_content=\\\"Greg (Marin Transitions Partner): Does this say the call is recording for you at all? \\\\n\\\\nEliza (ACME Co): But it says the request, the report or in here? \\\\n\\\\nGreg (Marin Transitions Partner): Nice. All right… one sec. \\\\n\\\\nGreg (Marin Transitions Partner): Cool. Absolutely. Well, I tell you what, thank you very much for joining me today. \\\\n\\\\nEliza (ACME Co): Yeah, glad to be chatting with you Greg. \\\\n\\\\nGreg (Marin Transitions Partner): Absolutely. Well. So, first of all, my name is Greg and I am from Marin transitions and we help people do social modeling on top of their businesses. So say somebody were to mention you on read it or mentioned you on Twitter or Facebook, then we help you understand what they're saying and the sentiment behind it. And I'm very excited to be chatting with you today. My first awesome. Well, I'll tell you what I've looked at your LinkedIn a little bit, but could you tell me more about your position and what you do? \\\\n\\\\nEliza (ACME Co): Absolutely. So I am cmo over at acmico and we are a software company that helps nonprofits grow their business. \\\\n\\\\nGreg (Marin Transitions Partner): Awesome. That's fabulous. And how many employees does acmico have? \\\\n\\\\nEliza (ACME Co): We have about 45 employees today. \\\\n\\\\nGreg (Marin Transitions Partner): Nice. That's great. And how big is the marketing team? \\\\n\\\\nEliza (ACME Co): The marketing team is, I think seven of us today. \\\\n\\\\nGreg (Marin Transitions Partner): Awesome. That's cool. And what technology stack does acme co use? \\\\n\\\\nEliza (ACME Co): So, today, we are using slack photoshop, Hubspot, Zoom and Google cloud. \\\\n\\\\nGreg (Marin Transitions Partner): That's awesome. And so, because we do social monitoring, I wanna go into a little bit of questions around your social experience, if you will, and what acne code does. So, how many times would you say that you post on social media per month? \\\\n\\\\nEliza (ACME Co): I'd say about 10 times a month?\\\", metadata={})\"\n ]\n },\n \"execution_count\": 6,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"print (f\\\"You have {len(texts)} texts\\\")\\n\",\n \"texts[0]\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 7,\n \"id\": \"d1415339\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# Your api key should be an environment variable, or else put it here\\n\",\n \"# We are using a chat model in case you wanted to use gpt4\\n\",\n \"llm = ChatOpenAI(temperature=0)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"2950a62d\",\n \"metadata\": {},\n \"source\": [\n \"We're going to start with the vanilla load_summarize_chain to see how it goes.\\n\",\n \"If you want to see the default prompts that are used you can explore the LangChain code. Here are the [map reduce prompts](https://github.com/hwchase17/langchain/blob/master/langchain/chains/summarize/map_reduce_prompt.py)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 8,\n \"id\": \"f57da26f\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# verbose=True will output the prompts being sent to the \\n\",\n \"chain = load_summarize_chain(llm, chain_type=\\\"map_reduce\\\", verbose=True)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"cde515c0\",\n \"metadata\": {},\n \"source\": [\n \"**Note:** At this point you might be asking, \\\"Greg, what about embeddings?\\\" Since we're just doing one call, I'm not worry about embeddings right now and putting the whole thing in a map reduce summarizer. If you have multiple calls and a lot of history then you should be embedding them for retrieval later. See tutorial on embeddings [here.](https://youtu.be/h0DHDp1FbmQ). [Tutorial on chain types.](https://youtu.be/f9_BWhCI4Zo)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 9,\n \"id\": \"b1d2572f\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"\\n\",\n \"\\n\",\n \"\\u001b[1m> Entering new MapReduceDocumentsChain chain...\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3mWrite a concise summary of the following:\\n\",\n \"\\n\",\n \"\\n\",\n \"\\\"Greg (Marin Transitions Partner): Does this say the call is recording for you at all? \\n\",\n \"\\n\",\n \"Eliza (ACME Co): But it says the request, the report or in here? \\n\",\n \"\\n\",\n \"Greg (Marin Transitions Partner): Nice. All right… one sec. \\n\",\n \"\\n\",\n \"Greg (Marin Transitions Partner): Cool. Absolutely. Well, I tell you what, thank you very much for joining me today. \\n\",\n \"\\n\",\n \"Eliza (ACME Co): Yeah, glad to be chatting with you Greg. \\n\",\n \"\\n\",\n \"Greg (Marin Transitions Partner): Absolutely. Well. So, first of all, my name is Greg and I am from Marin transitions and we help people do social modeling on top of their businesses. So say somebody were to mention you on read it or mentioned you on Twitter or Facebook, then we help you understand what they're saying and the sentiment behind it. And I'm very excited to be chatting with you today. My first awesome. Well, I'll tell you what I've looked at your LinkedIn a little bit, but could you tell me more about your position and what you do? \\n\",\n \"\\n\",\n \"Eliza (ACME Co): Absolutely. So I am cmo over at acmico and we are a software company that helps nonprofits grow their business. \\n\",\n \"\\n\",\n \"Greg (Marin Transitions Partner): Awesome. That's fabulous. And how many employees does acmico have? \\n\",\n \"\\n\",\n \"Eliza (ACME Co): We have about 45 employees today. \\n\",\n \"\\n\",\n \"Greg (Marin Transitions Partner): Nice. That's great. And how big is the marketing team? \\n\",\n \"\\n\",\n \"Eliza (ACME Co): The marketing team is, I think seven of us today. \\n\",\n \"\\n\",\n \"Greg (Marin Transitions Partner): Awesome. That's cool. And what technology stack does acme co use? \\n\",\n \"\\n\",\n \"Eliza (ACME Co): So, today, we are using slack photoshop, Hubspot, Zoom and Google cloud. \\n\",\n \"\\n\",\n \"Greg (Marin Transitions Partner): That's awesome. And so, because we do social monitoring, I wanna go into a little bit of questions around your social experience, if you will, and what acne code does. So, how many times would you say that you post on social media per month? \\n\",\n \"\\n\",\n \"Eliza (ACME Co): I'd say about 10 times a month?\\\"\\n\",\n \"\\n\",\n \"\\n\",\n \"CONCISE SUMMARY:\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3mWrite a concise summary of the following:\\n\",\n \"\\n\",\n \"\\n\",\n \"\\\"Eliza (ACME Co): I'd say about 10 times a month? \\n\",\n \"\\n\",\n \"Greg (Marin Transitions Partner): Interesting. And do you do any sort of social monitoring today? Do you know what customers are saying about you on those platforms? \\n\",\n \"\\n\",\n \"Eliza (ACME Co): No, we have no idea. \\n\",\n \"\\n\",\n \"Greg (Marin Transitions Partner): Interesting. And what are the pain points you're having by not being able to do social monitoring? \\n\",\n \"\\n\",\n \"Eliza (ACME Co): Yeah, I'd say the pain points of not having social monitoring revolve around the lack of transparency. So we're by not understanding what our customers are saying about us on social media, that is a disadvantage in a very competitive market. \\n\",\n \"\\n\",\n \"Greg (Marin Transitions Partner): Yeah, absolutely. And would you or I guess, let me rephrase how valuable would it be to you to understand what customers are saying about your brand in real time? \\n\",\n \"\\n\",\n \"Eliza (ACME Co): I think it could have significant value to understand in real time. What's ap? \\n\",\n \"\\n\",\n \"Greg (Marin Transitions Partner): Happening. Nice. And if you were to put a dollar amount on that, what would you say? What would you say? The dollar amount would be? \\n\",\n \"\\n\",\n \"Eliza (ACME Co): I would estimate, you know, if each… having this kind of transparency and visibility into our market, if that enables us to close one more deal per month. Now, with, given our average contract values, I'd say 50,000 dollars. \\n\",\n \"\\n\",\n \"Greg (Marin Transitions Partner): Yeah, no, that's very cool. And who would be the person that would sign off on this purchase? \\n\",\n \"\\n\",\n \"Eliza (ACME Co): So there would be, that would be a committee decision between myself and the rest of the leadership team. But the ultimate signer of the contract would be my CEO Christina. \\n\",\n \"\\n\",\n \"Greg (Marin Transitions Partner): Interesting. And so as we think about this social monitoring even more, what are your priorities for a tool? What would you like to see?\\\"\\n\",\n \"\\n\",\n \"\\n\",\n \"CONCISE SUMMARY:\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3mWrite a concise summary of the following:\\n\",\n \"\\n\",\n \"\\n\",\n \"\\\"Greg (Marin Transitions Partner): Interesting. And so as we think about this social monitoring even more, what are your priorities for a tool? What would you like to see? \\n\",\n \"\\n\",\n \"Eliza (ACME Co): I would like to see a tool that is able to accurately… in real time, tell me about… the data that my customers are saying about the company about our product… to stay ahead of, you know, potential risks. So protect that revenue and our existing customers. And then in terms of criteria for a partner, we were looking for someone that we can scale with as we build out our marketing program and someone that's going to offer the hands on white glove support that we need. \\n\",\n \"\\n\",\n \"Greg (Marin Transitions Partner): Yeah, no, that's awesome. And what is the process to get a new deal across the finish? Line? So, what is your evaluation process look like? \\n\",\n \"\\n\",\n \"Eliza (ACME Co): So, it is usually pretty easy process for us being a, an agile team over here. That process looks like I evaluate vendors, narrow that list down. We have about two options narrowed down today, one being your company. And then from there, I'll present and make my recommendations to the CEO. \\n\",\n \"\\n\",\n \"Greg (Marin Transitions Partner): Nice and say you make a decision, you're happy with it, what is the paper process that you need to go through to complete the decision? Is there accounting or legal or anybody? \\n\",\n \"\\n\",\n \"Eliza (ACME Co): Yes, there is a legal and security review as part of the process which would be conducted by our in house council. So you could send through your terms at any point and we could get ahead of that review if that would be… helpful. \\n\",\n \"\\n\",\n \"Greg (Marin Transitions Partner): Yeah, that's sweet. What are the, what other tools are you looking at as a part of this evaluation? \\n\",\n \"\\n\",\n \"Eliza (ACME Co): We're also looking at Hootsuite. \\n\",\n \"\\n\",\n \"Greg (Marin Transitions Partner): Interesting. Well, first, I wanna thank you very much for being such a big supporter of what we're doing here at Marin transitions?\\\"\\n\",\n \"\\n\",\n \"\\n\",\n \"CONCISE SUMMARY:\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3mWrite a concise summary of the following:\\n\",\n \"\\n\",\n \"\\n\",\n \"\\\"Eliza (ACME Co): We're also looking at Hootsuite. \\n\",\n \"\\n\",\n \"Greg (Marin Transitions Partner): Interesting. Well, first, I wanna thank you very much for being such a big supporter of what we're doing here at Marin transitions? \\n\",\n \"\\n\",\n \"Eliza (ACME Co): Absolutely. I'm happy to be your champion over here. I think, you know, based on the great conversations that I've had… with your team in the past and my last company… and also your, the recommendations that I've heard in referrals from some of your other customers in my peers have gone a long way. \\n\",\n \"\\n\",\n \"Greg (Marin Transitions Partner): That's awesome. Do you have any questions for me? \\n\",\n \"\\n\",\n \"Eliza (ACME Co): Yeah. So as I mentioned, support is going to be important. I'm sure you're aware everyone is wanting to avoid shelfware these days. So what I'm curious about is how long does it take to get started on your platform? And what does that implementation process look? \\n\",\n \"\\n\",\n \"Greg (Marin Transitions Partner): Absolutely. So the implementation process is really in two parts. Part number one is just gonna be a about an hour long session with one of our implementation partners and your head of social media that's just to make sure that your accounts get set up and that we're doing the tracking properly. Then part two is going to be the actual monitoring part. It takes about four hours to start monitoring, but after that, it'll be available for you in real time and that's just so we can go scrape all the data off the social sites. So that net you should be up and running in about half a day's work. That sounds. \\n\",\n \"\\n\",\n \"Eliza (ACME Co): Perfect.\\\"\\n\",\n \"\\n\",\n \"\\n\",\n \"CONCISE SUMMARY:\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3mWrite a concise summary of the following:\\n\",\n \"\\n\",\n \"\\n\",\n \"\\\"Eliza (ACME Co): Perfect. \\n\",\n \"\\n\",\n \"Greg (Marin Transitions Partner): Yeah, absolutely. Well, I tell you what, as a next step, what I'm gonna do is I'm going to share the brochure with you about our company that has all the information you may want on it. And I'm also going to share with you the pricing information as well. And so this is some deck that I'll send over. And so you can see that. And what I would love to do as a follow up is to schedule a new meeting with you for next week, probably on Wednesday. Is there a time that works on Wednesday for you? \\n\",\n \"\\n\",\n \"Eliza (ACME Co): Yes, I'm available any time between two and four PM on Wednesday, Pacific Time. So if you want that invite, I'll go ahead and accept it. \\n\",\n \"\\n\",\n \"Greg (Marin Transitions Partner): Cool. Absolutely. I'll send an invite for that time. \\n\",\n \"\\n\",\n \"Greg (Marin Transitions Partner): One last thing too. I always like to get to know my prospects a bit more on a personal level too. Do you have any pets or animals inside the house that are close to you? \\n\",\n \"\\n\",\n \"Eliza (ACME Co): I do. In fact, I have an Australian Shepherd dog. He's very cute and very crazy. \\n\",\n \"\\n\",\n \"Greg (Marin Transitions Partner): Awesome. No, that's great. And what do you like to do outside of? \\n\",\n \"\\n\",\n \"Eliza (ACME Co): Well, I live in the beautiful bay area in the north bay just north of San Francisco. So my husband and I really enjoy hiking on the nearby trails. We enjoy wine tasting up in wine country… and those are a couple of our favorite things to do on the weekends. \\n\",\n \"\\n\",\n \"Greg (Marin Transitions Partner): That's fabulous. Well, I tell you what, thank you very much for the conversation today and I'll follow up with you next week. \\n\",\n \"\\n\",\n \"Eliza (ACME Co): Great. I'm looking forward to. \\n\",\n \"\\n\",\n \"Greg (Marin Transitions Partner): It all right. We'll see you later. Bye bye.\\\"\\n\",\n \"\\n\",\n \"\\n\",\n \"CONCISE SUMMARY:\\u001b[0m\\n\"\n ]\n },\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"\\n\",\n \"\\n\",\n \"\\u001b[1m> Entering new StuffDocumentsChain chain...\\u001b[0m\\n\",\n \"\\n\",\n \"\\n\",\n \"\\u001b[1m> Entering new LLMChain chain...\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3mWrite a concise summary of the following:\\n\",\n \"\\n\",\n \"\\n\",\n \"\\\"Greg from Marin Transitions Partner speaks with Eliza from ACME Co about their business and social media presence. They discuss ACME Co's position as a software company that helps nonprofits grow their business, their number of employees and marketing team, and their technology stack. Greg also asks about their social media activity, to which Eliza responds that they post about 10 times a month.\\n\",\n \"\\n\",\n \"Eliza from ACME Co discusses with Greg from Marin Transitions Partner about their social monitoring practices and the pain points of not having transparency. Eliza estimates that having real-time visibility into their market could potentially close one more deal per month, which equates to $50,000. The decision to purchase a social monitoring tool would be a committee decision, with the CEO ultimately signing off on the contract. Greg asks about ACME Co's priorities for a social monitoring tool.\\n\",\n \"\\n\",\n \"Eliza from ACME Co is looking for a social monitoring tool that can accurately and in real-time tell her about customer feedback to protect revenue and existing customers. She is also looking for a partner that can scale with their marketing program and offer hands-on support. The evaluation process involves evaluating vendors, narrowing down options, and presenting recommendations to the CEO. There is a legal and security review process, and they are also considering Hootsuite as a tool. Marin Transitions Partner thanks Eliza for her support.\\n\",\n \"\\n\",\n \"Eliza from ACME Co is considering using Hootsuite and discusses her interest with Greg from Marin Transitions Partner. She asks about the implementation process and Greg explains that it involves an hour-long session and four hours of monitoring, with the platform being available in real-time afterwards. The process should take about half a day's work.\\n\",\n \"\\n\",\n \"Greg, a Marin Transitions Partner, plans to send a brochure and pricing information to Eliza from ACME Co. He schedules a follow-up meeting for next week and asks about her personal interests, including her Australian Shepherd dog and hiking in the bay area. They end the conversation with plans to speak again next week.\\\"\\n\",\n \"\\n\",\n \"\\n\",\n \"CONCISE SUMMARY:\\u001b[0m\\n\",\n \"\\n\",\n \"\\u001b[1m> Finished chain.\\u001b[0m\\n\",\n \"\\n\",\n \"\\u001b[1m> Finished chain.\\u001b[0m\\n\",\n \"\\n\",\n \"\\u001b[1m> Finished chain.\\u001b[0m\\n\"\n ]\n }\n ],\n \"source\": [\n \"output = chain.run(texts)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 10,\n \"id\": \"2805165f\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"Eliza from ACME Co discusses their business and social media presence with Greg from Marin Transitions Partner. They talk about ACME Co's position as a software company that helps nonprofits grow their business, their social media activity, and their need for a social monitoring tool. Eliza is looking for a tool that can accurately and in real-time tell her about customer feedback to protect revenue and existing customers. They discuss the implementation process for Hootsuite and schedule a follow-up meeting for next week.\\n\"\n ]\n }\n ],\n \"source\": [\n \"print (output)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"6334e4f9\",\n \"metadata\": {},\n \"source\": [\n \"Not bad, but it's giving me the perspective of a 3rd party watching the conversation that is agnostic to the content. I want the AI bot to me on my side! I'll need to switch up the prompts to do this.\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"3758a0e0\",\n \"metadata\": {},\n \"source\": [\n \"### Custom Prompts\\n\",\n \"\\n\",\n \"I'm going to write custom prompts that give the AI more instructions on what role I want it to play\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 11,\n \"id\": \"b6933934\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"template=\\\"\\\"\\\"\\n\",\n \"\\n\",\n \"You are a helpful assistant that helps {sales_rep_name}, a sales rep at {sales_rep_company}, summarize information from a sales call.\\n\",\n \"Your goal is to write a summary from the perspective of {sales_rep_name} that will highlight key points that will be relevant to making a sale\\n\",\n \"Do not respond with anything outside of the call transcript. If you don't know, say, \\\"I don't know\\\"\\n\",\n \"Do not repeat {sales_rep_name}'s name in your output\\n\",\n \"\\n\",\n \"\\\"\\\"\\\"\\n\",\n \"system_message_prompt = SystemMessagePromptTemplate.from_template(template)\\n\",\n \"\\n\",\n \"human_template=\\\"{text}\\\" # Simply just pass the text as a human message\\n\",\n \"human_message_prompt = HumanMessagePromptTemplate.from_template(human_template)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 12,\n \"id\": \"05042a43\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"chat_prompt = ChatPromptTemplate.from_messages(messages=[system_message_prompt, human_message_prompt])\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 13,\n \"id\": \"a3daced9\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"chain = load_summarize_chain(llm,\\n\",\n \" chain_type=\\\"map_reduce\\\",\\n\",\n \" map_prompt=chat_prompt\\n\",\n \" )\\n\",\n \"\\n\",\n \"# Because we aren't specifying a combine prompt the default one will be used\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 14,\n \"id\": \"d4ef0a5c\",\n \"metadata\": {\n \"scrolled\": false\n },\n \"outputs\": [],\n \"source\": [\n \"output = chain.run({\\n\",\n \" \\\"input_documents\\\": texts,\\n\",\n \" \\\"sales_rep_company\\\": \\\"Marin Transitions Partner\\\", \\\\\\n\",\n \" \\\"sales_rep_name\\\" : \\\"Greg\\\"\\n\",\n \" })\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 15,\n \"id\": \"ca00b447\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"ACME Co, a software company that helps nonprofits grow their business, is looking for a social monitoring tool to gain real-time visibility into their market and address their pain points. They have narrowed down their options to two vendors, including Marin Transitions Partner, and are interested in a partner that can scale with them as they build out their marketing program and offer hands-on white-glove support. Greg from Marin Transitions Partner spoke with Eliza, the CMO of ACME Co, and will be sending over a brochure and pricing information. They have scheduled a follow-up meeting for next Wednesday.\\n\"\n ]\n }\n ],\n \"source\": [\n \"print (output)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"5fda2fa3\",\n \"metadata\": {},\n \"source\": [\n \"Better! But say I wanted to change the format of the output without needing the user to do extra prompting.\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"ff62d842\",\n \"metadata\": {},\n \"source\": [\n \"### Promptless changes\\n\",\n \"\\n\",\n \"To do this I'll write a few points about the different output types I would like. However, I'll that I'll expose to the user is a simple selection, radio button, or drop down. (We'll use text for now but you can do this in your app).\\n\",\n \"\\n\",\n \"I want to give the user the option to select between different summary output types.\\n\",\n \"\\n\",\n \"I'll have them pick between:\\n\",\n \"1. One Sentence\\n\",\n \"2. Bullet Points\\n\",\n \"3. Short\\n\",\n \"4. Long\\n\",\n \"\\n\",\n \"I could try to pass these words to the LLM, but I want to be more explicit with it. Plus, giving good instructions is the way to go!\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 16,\n \"id\": \"5a4b52e5\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"summary_output_options = {\\n\",\n \" 'one_sentence' : \\\"\\\"\\\"\\n\",\n \" - Only one sentence\\n\",\n \" \\\"\\\"\\\",\\n\",\n \" \\n\",\n \" 'bullet_points': \\\"\\\"\\\"\\n\",\n \" - Bullet point format\\n\",\n \" - Separate each bullet point with a new line\\n\",\n \" - Each bullet point should be concise\\n\",\n \" \\\"\\\"\\\",\\n\",\n \" \\n\",\n \" 'short' : \\\"\\\"\\\"\\n\",\n \" - A few short sentences\\n\",\n \" - Do not go longer than 4-5 sentences\\n\",\n \" \\\"\\\"\\\",\\n\",\n \" \\n\",\n \" 'long' : \\\"\\\"\\\"\\n\",\n \" - A verbose summary\\n\",\n \" - You may do a few paragraphs to describe the transcript if needed\\n\",\n \" \\\"\\\"\\\"\\n\",\n \"}\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"21b81dac\",\n \"metadata\": {},\n \"source\": [\n \"Create a new template that takes an additional parameter. I need to put this in the combined prompt so that the LLM will output in my format. If I did this in the map section I would lose the format after the combined prompt was done\\n\",\n \"\\n\",\n \"**Map Prompt**\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 17,\n \"id\": \"926ec377\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"template=\\\"\\\"\\\"\\n\",\n \"\\n\",\n \"You are a helpful assistant that helps {sales_rep_name}, a sales rep at {sales_rep_company}, summarize information from a sales call.\\n\",\n \"Your goal is to write a summary from the perspective of Greg that will highlight key points that will be relevant to making a sale\\n\",\n \"Do not respond with anything outside of the call transcript. If you don't know, say, \\\"I don't know\\\"\\n\",\n \"\\\"\\\"\\\"\\n\",\n \"system_message_prompt_map = SystemMessagePromptTemplate.from_template(template)\\n\",\n \"\\n\",\n \"human_template=\\\"{text}\\\" # Simply just pass the text as a human message\\n\",\n \"human_message_prompt_map = HumanMessagePromptTemplate.from_template(human_template)\\n\",\n \"\\n\",\n \"chat_prompt_map = ChatPromptTemplate.from_messages(messages=[system_message_prompt_map, human_message_prompt_map])\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"bb7b8c0d\",\n \"metadata\": {},\n \"source\": [\n \"**Combined Prompt**\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 18,\n \"id\": \"178eb07d\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"template=\\\"\\\"\\\"\\n\",\n \"\\n\",\n \"You are a helpful assistant that helps {sales_rep_name}, a sales rep at {sales_rep_company}, summarize information from a sales call.\\n\",\n \"Your goal is to write a summary from the perspective of Greg that will highlight key points that will be relevant to making a sale\\n\",\n \"Do not respond with anything outside of the call transcript. If you don't know, say, \\\"I don't know\\\"\\n\",\n \"\\n\",\n \"Respond with the following format\\n\",\n \"{output_format}\\n\",\n \"\\n\",\n \"\\\"\\\"\\\"\\n\",\n \"system_message_prompt_combine = SystemMessagePromptTemplate.from_template(template)\\n\",\n \"\\n\",\n \"human_template=\\\"{text}\\\" # Simply just pass the text as a human message\\n\",\n \"human_message_prompt_combine = HumanMessagePromptTemplate.from_template(human_template)\\n\",\n \"\\n\",\n \"chat_prompt_combine = ChatPromptTemplate.from_messages(messages=[system_message_prompt_combine, human_message_prompt_combine])\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 19,\n \"id\": \"8c3e9fc0\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"chain = load_summarize_chain(llm,\\n\",\n \" chain_type=\\\"map_reduce\\\",\\n\",\n \" map_prompt=chat_prompt_map,\\n\",\n \" combine_prompt=chat_prompt_combine,\\n\",\n \" verbose=True\\n\",\n \" )\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 20,\n \"id\": \"65e01887\",\n \"metadata\": {\n \"scrolled\": false\n },\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"\\n\",\n \"\\n\",\n \"\\u001b[1m> Entering new MapReduceDocumentsChain chain...\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3mSystem: \\n\",\n \"\\n\",\n \"You are a helpful assistant that helps Greg, a sales rep at Marin Transitions Partner, summarize information from a sales call.\\n\",\n \"Your goal is to write a summary from the perspective of Greg that will highlight key points that will be relevant to making a sale\\n\",\n \"Do not respond with anything outside of the call transcript. If you don't know, say, \\\"I don't know\\\"\\n\",\n \"\\n\",\n \"Human: Greg (Marin Transitions Partner): Does this say the call is recording for you at all? \\n\",\n \"\\n\",\n \"Eliza (ACME Co): But it says the request, the report or in here? \\n\",\n \"\\n\",\n \"Greg (Marin Transitions Partner): Nice. All right… one sec. \\n\",\n \"\\n\",\n \"Greg (Marin Transitions Partner): Cool. Absolutely. Well, I tell you what, thank you very much for joining me today. \\n\",\n \"\\n\",\n \"Eliza (ACME Co): Yeah, glad to be chatting with you Greg. \\n\",\n \"\\n\",\n \"Greg (Marin Transitions Partner): Absolutely. Well. So, first of all, my name is Greg and I am from Marin transitions and we help people do social modeling on top of their businesses. So say somebody were to mention you on read it or mentioned you on Twitter or Facebook, then we help you understand what they're saying and the sentiment behind it. And I'm very excited to be chatting with you today. My first awesome. Well, I'll tell you what I've looked at your LinkedIn a little bit, but could you tell me more about your position and what you do? \\n\",\n \"\\n\",\n \"Eliza (ACME Co): Absolutely. So I am cmo over at acmico and we are a software company that helps nonprofits grow their business. \\n\",\n \"\\n\",\n \"Greg (Marin Transitions Partner): Awesome. That's fabulous. And how many employees does acmico have? \\n\",\n \"\\n\",\n \"Eliza (ACME Co): We have about 45 employees today. \\n\",\n \"\\n\",\n \"Greg (Marin Transitions Partner): Nice. That's great. And how big is the marketing team? \\n\",\n \"\\n\",\n \"Eliza (ACME Co): The marketing team is, I think seven of us today. \\n\",\n \"\\n\",\n \"Greg (Marin Transitions Partner): Awesome. That's cool. And what technology stack does acme co use? \\n\",\n \"\\n\",\n \"Eliza (ACME Co): So, today, we are using slack photoshop, Hubspot, Zoom and Google cloud. \\n\",\n \"\\n\",\n \"Greg (Marin Transitions Partner): That's awesome. And so, because we do social monitoring, I wanna go into a little bit of questions around your social experience, if you will, and what acne code does. So, how many times would you say that you post on social media per month? \\n\",\n \"\\n\",\n \"Eliza (ACME Co): I'd say about 10 times a month?\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3mSystem: \\n\",\n \"\\n\",\n \"You are a helpful assistant that helps Greg, a sales rep at Marin Transitions Partner, summarize information from a sales call.\\n\",\n \"Your goal is to write a summary from the perspective of Greg that will highlight key points that will be relevant to making a sale\\n\",\n \"Do not respond with anything outside of the call transcript. If you don't know, say, \\\"I don't know\\\"\\n\",\n \"\\n\",\n \"Human: Eliza (ACME Co): I'd say about 10 times a month? \\n\",\n \"\\n\",\n \"Greg (Marin Transitions Partner): Interesting. And do you do any sort of social monitoring today? Do you know what customers are saying about you on those platforms? \\n\",\n \"\\n\",\n \"Eliza (ACME Co): No, we have no idea. \\n\",\n \"\\n\",\n \"Greg (Marin Transitions Partner): Interesting. And what are the pain points you're having by not being able to do social monitoring? \\n\",\n \"\\n\",\n \"Eliza (ACME Co): Yeah, I'd say the pain points of not having social monitoring revolve around the lack of transparency. So we're by not understanding what our customers are saying about us on social media, that is a disadvantage in a very competitive market. \\n\",\n \"\\n\",\n \"Greg (Marin Transitions Partner): Yeah, absolutely. And would you or I guess, let me rephrase how valuable would it be to you to understand what customers are saying about your brand in real time? \\n\",\n \"\\n\",\n \"Eliza (ACME Co): I think it could have significant value to understand in real time. What's ap? \\n\",\n \"\\n\",\n \"Greg (Marin Transitions Partner): Happening. Nice. And if you were to put a dollar amount on that, what would you say? What would you say? The dollar amount would be? \\n\",\n \"\\n\",\n \"Eliza (ACME Co): I would estimate, you know, if each… having this kind of transparency and visibility into our market, if that enables us to close one more deal per month. Now, with, given our average contract values, I'd say 50,000 dollars. \\n\",\n \"\\n\",\n \"Greg (Marin Transitions Partner): Yeah, no, that's very cool. And who would be the person that would sign off on this purchase? \\n\",\n \"\\n\",\n \"Eliza (ACME Co): So there would be, that would be a committee decision between myself and the rest of the leadership team. But the ultimate signer of the contract would be my CEO Christina. \\n\",\n \"\\n\",\n \"Greg (Marin Transitions Partner): Interesting. And so as we think about this social monitoring even more, what are your priorities for a tool? What would you like to see?\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3mSystem: \\n\",\n \"\\n\",\n \"You are a helpful assistant that helps Greg, a sales rep at Marin Transitions Partner, summarize information from a sales call.\\n\",\n \"Your goal is to write a summary from the perspective of Greg that will highlight key points that will be relevant to making a sale\\n\",\n \"Do not respond with anything outside of the call transcript. If you don't know, say, \\\"I don't know\\\"\\n\",\n \"\\n\",\n \"Human: Greg (Marin Transitions Partner): Interesting. And so as we think about this social monitoring even more, what are your priorities for a tool? What would you like to see? \\n\",\n \"\\n\",\n \"Eliza (ACME Co): I would like to see a tool that is able to accurately… in real time, tell me about… the data that my customers are saying about the company about our product… to stay ahead of, you know, potential risks. So protect that revenue and our existing customers. And then in terms of criteria for a partner, we were looking for someone that we can scale with as we build out our marketing program and someone that's going to offer the hands on white glove support that we need. \\n\",\n \"\\n\",\n \"Greg (Marin Transitions Partner): Yeah, no, that's awesome. And what is the process to get a new deal across the finish? Line? So, what is your evaluation process look like? \\n\",\n \"\\n\",\n \"Eliza (ACME Co): So, it is usually pretty easy process for us being a, an agile team over here. That process looks like I evaluate vendors, narrow that list down. We have about two options narrowed down today, one being your company. And then from there, I'll present and make my recommendations to the CEO. \\n\",\n \"\\n\",\n \"Greg (Marin Transitions Partner): Nice and say you make a decision, you're happy with it, what is the paper process that you need to go through to complete the decision? Is there accounting or legal or anybody? \\n\",\n \"\\n\",\n \"Eliza (ACME Co): Yes, there is a legal and security review as part of the process which would be conducted by our in house council. So you could send through your terms at any point and we could get ahead of that review if that would be… helpful. \\n\",\n \"\\n\",\n \"Greg (Marin Transitions Partner): Yeah, that's sweet. What are the, what other tools are you looking at as a part of this evaluation? \\n\",\n \"\\n\",\n \"Eliza (ACME Co): We're also looking at Hootsuite. \\n\",\n \"\\n\",\n \"Greg (Marin Transitions Partner): Interesting. Well, first, I wanna thank you very much for being such a big supporter of what we're doing here at Marin transitions?\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3mSystem: \\n\",\n \"\\n\",\n \"You are a helpful assistant that helps Greg, a sales rep at Marin Transitions Partner, summarize information from a sales call.\\n\",\n \"Your goal is to write a summary from the perspective of Greg that will highlight key points that will be relevant to making a sale\\n\",\n \"Do not respond with anything outside of the call transcript. If you don't know, say, \\\"I don't know\\\"\\n\",\n \"\\n\",\n \"Human: Eliza (ACME Co): We're also looking at Hootsuite. \\n\",\n \"\\n\",\n \"Greg (Marin Transitions Partner): Interesting. Well, first, I wanna thank you very much for being such a big supporter of what we're doing here at Marin transitions? \\n\",\n \"\\n\",\n \"Eliza (ACME Co): Absolutely. I'm happy to be your champion over here. I think, you know, based on the great conversations that I've had… with your team in the past and my last company… and also your, the recommendations that I've heard in referrals from some of your other customers in my peers have gone a long way. \\n\",\n \"\\n\",\n \"Greg (Marin Transitions Partner): That's awesome. Do you have any questions for me? \\n\",\n \"\\n\",\n \"Eliza (ACME Co): Yeah. So as I mentioned, support is going to be important. I'm sure you're aware everyone is wanting to avoid shelfware these days. So what I'm curious about is how long does it take to get started on your platform? And what does that implementation process look? \\n\",\n \"\\n\",\n \"Greg (Marin Transitions Partner): Absolutely. So the implementation process is really in two parts. Part number one is just gonna be a about an hour long session with one of our implementation partners and your head of social media that's just to make sure that your accounts get set up and that we're doing the tracking properly. Then part two is going to be the actual monitoring part. It takes about four hours to start monitoring, but after that, it'll be available for you in real time and that's just so we can go scrape all the data off the social sites. So that net you should be up and running in about half a day's work. That sounds. \\n\",\n \"\\n\",\n \"Eliza (ACME Co): Perfect.\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3mSystem: \\n\",\n \"\\n\",\n \"You are a helpful assistant that helps Greg, a sales rep at Marin Transitions Partner, summarize information from a sales call.\\n\",\n \"Your goal is to write a summary from the perspective of Greg that will highlight key points that will be relevant to making a sale\\n\",\n \"Do not respond with anything outside of the call transcript. If you don't know, say, \\\"I don't know\\\"\\n\",\n \"\\n\",\n \"Human: Eliza (ACME Co): Perfect. \\n\",\n \"\\n\",\n \"Greg (Marin Transitions Partner): Yeah, absolutely. Well, I tell you what, as a next step, what I'm gonna do is I'm going to share the brochure with you about our company that has all the information you may want on it. And I'm also going to share with you the pricing information as well. And so this is some deck that I'll send over. And so you can see that. And what I would love to do as a follow up is to schedule a new meeting with you for next week, probably on Wednesday. Is there a time that works on Wednesday for you? \\n\",\n \"\\n\",\n \"Eliza (ACME Co): Yes, I'm available any time between two and four PM on Wednesday, Pacific Time. So if you want that invite, I'll go ahead and accept it. \\n\",\n \"\\n\",\n \"Greg (Marin Transitions Partner): Cool. Absolutely. I'll send an invite for that time. \\n\",\n \"\\n\",\n \"Greg (Marin Transitions Partner): One last thing too. I always like to get to know my prospects a bit more on a personal level too. Do you have any pets or animals inside the house that are close to you? \\n\",\n \"\\n\",\n \"Eliza (ACME Co): I do. In fact, I have an Australian Shepherd dog. He's very cute and very crazy. \\n\",\n \"\\n\",\n \"Greg (Marin Transitions Partner): Awesome. No, that's great. And what do you like to do outside of? \\n\",\n \"\\n\",\n \"Eliza (ACME Co): Well, I live in the beautiful bay area in the north bay just north of San Francisco. So my husband and I really enjoy hiking on the nearby trails. We enjoy wine tasting up in wine country… and those are a couple of our favorite things to do on the weekends. \\n\",\n \"\\n\",\n \"Greg (Marin Transitions Partner): That's fabulous. Well, I tell you what, thank you very much for the conversation today and I'll follow up with you next week. \\n\",\n \"\\n\",\n \"Eliza (ACME Co): Great. I'm looking forward to. \\n\",\n \"\\n\",\n \"Greg (Marin Transitions Partner): It all right. We'll see you later. Bye bye.\\u001b[0m\\n\"\n ]\n },\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"\\n\",\n \"\\n\",\n \"\\u001b[1m> Entering new StuffDocumentsChain chain...\\u001b[0m\\n\",\n \"\\n\",\n \"\\n\",\n \"\\u001b[1m> Entering new LLMChain chain...\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3mSystem: \\n\",\n \"\\n\",\n \"You are a helpful assistant that helps Greg, a sales rep at Marin Transitions Partner, summarize information from a sales call.\\n\",\n \"Your goal is to write a summary from the perspective of Greg that will highlight key points that will be relevant to making a sale\\n\",\n \"Do not respond with anything outside of the call transcript. If you don't know, say, \\\"I don't know\\\"\\n\",\n \"\\n\",\n \"Respond with the following format\\n\",\n \"\\n\",\n \" - Only one sentence\\n\",\n \" \\n\",\n \"\\n\",\n \"\\n\",\n \"Human: Greg from Marin Transitions Partner spoke with Eliza, the CMO of ACME Co, about their business and social media presence. ACME Co is a software company that helps nonprofits grow their business with 45 employees and a marketing team of seven. They use Slack, Photoshop, Hubspot, Zoom, and Google Cloud. Eliza estimates that they post about 10 times a month on social media. Marin Transitions Partner helps businesses with social modeling to understand sentiment behind mentions on social media.\\n\",\n \"\\n\",\n \"Greg from Marin Transitions Partner spoke with Eliza from ACME Co about their social monitoring practices. Eliza stated that they have no idea what customers are saying about them on social media, which is a disadvantage in a competitive market. Greg highlighted the value of understanding what customers are saying about their brand in real-time and asked Eliza to put a dollar amount on it. Eliza estimated that having this kind of transparency and visibility into their market could enable them to close one more deal per month, which would be worth $50,000. The decision to purchase would be made by a committee, with the ultimate signer being the CEO Christina. Greg asked about their priorities for a social monitoring tool.\\n\",\n \"\\n\",\n \"Eliza from ACME Co is interested in a social monitoring tool that can accurately and in real-time tell her about the data that her customers are saying about the company and its products to stay ahead of potential risks. She is also looking for a partner that can scale with them as they build out their marketing program and offer hands-on white-glove support. The evaluation process involves Eliza evaluating vendors, narrowing down the list to two options, and presenting her recommendations to the CEO. There is a legal and security review as part of the process, which would be conducted by their in-house counsel. ACME Co is also evaluating Hootsuite as another option.\\n\",\n \"\\n\",\n \"Eliza from ACME Co is interested in Hootsuite, but is a big supporter of Marin Transitions Partner. She is concerned about support and avoiding shelfware. She asks about the implementation process and how long it takes to get started on the platform. Greg explains that the implementation process is in two parts, with an hour-long session with an implementation partner and the head of social media to set up accounts and ensure proper tracking. The second part is the monitoring process, which takes about four hours to start, but after that, it will be available in real-time. Overall, the implementation process takes about half a day's work.\\n\",\n \"\\n\",\n \"Greg from Marin Transitions Partner had a successful sales call with Eliza from ACME Co. He will be sending over a brochure and pricing information for their company. They scheduled a follow-up meeting for next Wednesday between 2-4 PM Pacific Time. Greg also asked Eliza about her personal life and found out that she has an Australian Shepherd dog and enjoys hiking and wine tasting in the nearby trails and wine country.\\u001b[0m\\n\",\n \"\\n\",\n \"\\u001b[1m> Finished chain.\\u001b[0m\\n\",\n \"\\n\",\n \"\\u001b[1m> Finished chain.\\u001b[0m\\n\",\n \"\\n\",\n \"\\u001b[1m> Finished chain.\\u001b[0m\\n\"\n ]\n }\n ],\n \"source\": [\n \"user_selection = 'one_sentence'\\n\",\n \"\\n\",\n \"output = chain.run({\\n\",\n \" \\\"input_documents\\\": texts,\\n\",\n \" \\\"sales_rep_company\\\": \\\"Marin Transitions Partner\\\", \\\\\\n\",\n \" \\\"sales_rep_name\\\" : \\\"Greg\\\",\\n\",\n \" \\\"output_format\\\" : summary_output_options[user_selection]\\n\",\n \" })\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 21,\n \"id\": \"65e65c2c\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"ACME Co is interested in a social monitoring tool that can accurately and in real-time tell her about the data that her customers are saying about the company and its products to stay ahead of potential risks, and is evaluating Marin Transitions Partner and Hootsuite as options.\\n\"\n ]\n }\n ],\n \"source\": [\n \"print(output)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"04e44a1e\",\n \"metadata\": {},\n \"source\": [\n \"Awesome! Now we have a bullet point format without needing to have the user specify any additional information.\\n\",\n \"\\n\",\n \"If you wanted to productionize this you would need to add additional prompts to extract other information from the calls that may be helpful to a sales person. Example: Key Points + Next Steps from the call. You should also parallelize the map calls if you do the map reduce method.\\n\",\n \"\\n\",\n \"Have other ideas about how something like this could be used? Send me a tweet or DM on [Twitter](https://twitter.com/GregKamradt) or contact@dataindependent.com\"\n ]\n }\n ],\n \"metadata\": {\n \"kernelspec\": {\n \"display_name\": \"Python 3 (ipykernel)\",\n \"language\": \"python\",\n \"name\": \"python3\"\n },\n \"language_info\": {\n \"codemirror_mode\": {\n \"name\": \"ipython\",\n \"version\": 3\n },\n \"file_extension\": \".py\",\n \"mimetype\": \"text/x-python\",\n \"name\": \"python\",\n \"nbconvert_exporter\": \"python\",\n \"pygments_lexer\": \"ipython3\",\n \"version\": \"3.9.13\"\n }\n },\n \"nbformat\": 4,\n \"nbformat_minor\": 5\n}\n" }, { "path": "getting_started/Quickstart Guide.ipynb", "content": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"id\": \"2ed4da4d\",\n \"metadata\": {},\n \"source\": [\n \"## Quickstart Guide\\n\",\n \"https://langchain.readthedocs.io/en/latest/getting_started/getting_started.html\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 1,\n \"id\": \"a05530b1\",\n \"metadata\": {\n \"collapsed\": true\n },\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"Requirement already satisfied: langchain in /Users/gregorykamradt/opt/anaconda3/lib/python3.9/site-packages (0.0.75)\\n\",\n \"Requirement already satisfied: PyYAML<7,>=6 in /Users/gregorykamradt/opt/anaconda3/lib/python3.9/site-packages (from langchain) (6.0)\\n\",\n \"Requirement already satisfied: dataclasses-json<0.6.0,>=0.5.7 in /Users/gregorykamradt/opt/anaconda3/lib/python3.9/site-packages (from langchain) (0.5.7)\\n\",\n \"Requirement already satisfied: numpy<2,>=1 in /Users/gregorykamradt/opt/anaconda3/lib/python3.9/site-packages (from langchain) (1.21.5)\\n\",\n \"Requirement already satisfied: SQLAlchemy<2,>=1 in /Users/gregorykamradt/opt/anaconda3/lib/python3.9/site-packages (from langchain) (1.4.39)\\n\",\n \"Requirement already satisfied: pydantic<2,>=1 in /Users/gregorykamradt/opt/anaconda3/lib/python3.9/site-packages (from langchain) (1.10.4)\\n\",\n \"Requirement already satisfied: requests<3,>=2 in /Users/gregorykamradt/opt/anaconda3/lib/python3.9/site-packages (from langchain) (2.28.1)\\n\",\n \"Requirement already satisfied: marshmallow<4.0.0,>=3.3.0 in /Users/gregorykamradt/opt/anaconda3/lib/python3.9/site-packages (from dataclasses-json<0.6.0,>=0.5.7->langchain) (3.19.0)\\n\",\n \"Requirement already satisfied: marshmallow-enum<2.0.0,>=1.5.1 in /Users/gregorykamradt/opt/anaconda3/lib/python3.9/site-packages (from dataclasses-json<0.6.0,>=0.5.7->langchain) (1.5.1)\\n\",\n \"Requirement already satisfied: typing-inspect>=0.4.0 in /Users/gregorykamradt/opt/anaconda3/lib/python3.9/site-packages (from dataclasses-json<0.6.0,>=0.5.7->langchain) (0.8.0)\\n\",\n \"Requirement already satisfied: typing-extensions>=4.2.0 in /Users/gregorykamradt/opt/anaconda3/lib/python3.9/site-packages (from pydantic<2,>=1->langchain) (4.3.0)\\n\",\n \"Requirement already satisfied: certifi>=2017.4.17 in /Users/gregorykamradt/opt/anaconda3/lib/python3.9/site-packages (from requests<3,>=2->langchain) (2022.9.24)\\n\",\n \"Requirement already satisfied: charset-normalizer<3,>=2 in /Users/gregorykamradt/opt/anaconda3/lib/python3.9/site-packages (from requests<3,>=2->langchain) (2.0.4)\\n\",\n \"Requirement already satisfied: idna<4,>=2.5 in /Users/gregorykamradt/opt/anaconda3/lib/python3.9/site-packages (from requests<3,>=2->langchain) (3.3)\\n\",\n \"Requirement already satisfied: urllib3<1.27,>=1.21.1 in /Users/gregorykamradt/opt/anaconda3/lib/python3.9/site-packages (from requests<3,>=2->langchain) (1.26.11)\\n\",\n \"Requirement already satisfied: greenlet!=0.4.17 in /Users/gregorykamradt/opt/anaconda3/lib/python3.9/site-packages (from SQLAlchemy<2,>=1->langchain) (1.1.1)\\n\",\n \"Requirement already satisfied: packaging>=17.0 in /Users/gregorykamradt/opt/anaconda3/lib/python3.9/site-packages (from marshmallow<4.0.0,>=3.3.0->dataclasses-json<0.6.0,>=0.5.7->langchain) (21.3)\\n\",\n \"Requirement already satisfied: mypy-extensions>=0.3.0 in /Users/gregorykamradt/opt/anaconda3/lib/python3.9/site-packages (from typing-inspect>=0.4.0->dataclasses-json<0.6.0,>=0.5.7->langchain) (0.4.3)\\n\",\n \"Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /Users/gregorykamradt/opt/anaconda3/lib/python3.9/site-packages (from packaging>=17.0->marshmallow<4.0.0,>=3.3.0->dataclasses-json<0.6.0,>=0.5.7->langchain) (3.0.9)\\n\",\n \"Note: you may need to restart the kernel to use updated packages.\\n\"\n ]\n }\n ],\n \"source\": [\n \"pip install langchain\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 2,\n \"id\": \"3b556fc2\",\n \"metadata\": {\n \"collapsed\": true\n },\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"Requirement already satisfied: openai in /Users/gregorykamradt/opt/anaconda3/lib/python3.9/site-packages (0.26.3)\\n\",\n \"Requirement already satisfied: tqdm in /Users/gregorykamradt/opt/anaconda3/lib/python3.9/site-packages (from openai) (4.64.1)\\n\",\n \"Requirement already satisfied: aiohttp in /Users/gregorykamradt/opt/anaconda3/lib/python3.9/site-packages (from openai) (3.8.3)\\n\",\n \"Requirement already satisfied: requests>=2.20 in /Users/gregorykamradt/opt/anaconda3/lib/python3.9/site-packages (from openai) (2.28.1)\\n\",\n \"Requirement already satisfied: idna<4,>=2.5 in /Users/gregorykamradt/opt/anaconda3/lib/python3.9/site-packages (from requests>=2.20->openai) (3.3)\\n\",\n \"Requirement already satisfied: charset-normalizer<3,>=2 in /Users/gregorykamradt/opt/anaconda3/lib/python3.9/site-packages (from requests>=2.20->openai) (2.0.4)\\n\",\n \"Requirement already satisfied: certifi>=2017.4.17 in /Users/gregorykamradt/opt/anaconda3/lib/python3.9/site-packages (from requests>=2.20->openai) (2022.9.24)\\n\",\n \"Requirement already satisfied: urllib3<1.27,>=1.21.1 in /Users/gregorykamradt/opt/anaconda3/lib/python3.9/site-packages (from requests>=2.20->openai) (1.26.11)\\n\",\n \"Requirement already satisfied: async-timeout<5.0,>=4.0.0a3 in /Users/gregorykamradt/opt/anaconda3/lib/python3.9/site-packages (from aiohttp->openai) (4.0.2)\\n\",\n \"Requirement already satisfied: yarl<2.0,>=1.0 in /Users/gregorykamradt/opt/anaconda3/lib/python3.9/site-packages (from aiohttp->openai) (1.8.2)\\n\",\n \"Requirement already satisfied: attrs>=17.3.0 in /Users/gregorykamradt/opt/anaconda3/lib/python3.9/site-packages (from aiohttp->openai) (21.4.0)\\n\",\n \"Requirement already satisfied: frozenlist>=1.1.1 in /Users/gregorykamradt/opt/anaconda3/lib/python3.9/site-packages (from aiohttp->openai) (1.3.3)\\n\",\n \"Requirement already satisfied: aiosignal>=1.1.2 in /Users/gregorykamradt/opt/anaconda3/lib/python3.9/site-packages (from aiohttp->openai) (1.3.1)\\n\",\n \"Requirement already satisfied: multidict<7.0,>=4.5 in /Users/gregorykamradt/opt/anaconda3/lib/python3.9/site-packages (from aiohttp->openai) (6.0.4)\\n\",\n \"Note: you may need to restart the kernel to use updated packages.\\n\"\n ]\n }\n ],\n \"source\": [\n \"pip install openai\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 9,\n \"id\": \"0c07fe20\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"import os\\n\",\n \"# os.environ[\\\"OPENAI_API_KEY\\\"] = \\\"\\\"\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"0126a6a1\",\n \"metadata\": {},\n \"source\": [\n \"# Building A Language Model Application\\n\",\n \"### LLMS: Get predictions from a language model\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 10,\n \"id\": \"4bef95a9\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain.llms import OpenAI\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 11,\n \"id\": \"3596e426\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"llm = OpenAI(temperature=0.9)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 12,\n \"id\": \"9ebe6d15\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"\\n\",\n \"\\n\",\n \"1. Rome, Italy \\n\",\n \"2. Bologna, Italy \\n\",\n \"3. Venice, Italy\\n\",\n \"4. Amalfi Coast, Italy\\n\",\n \"5. Sicily, Italy\\n\"\n ]\n }\n ],\n \"source\": [\n \"text = \\\"What are 5 vacation destinations for someone who likes to eat pasta?\\\"\\n\",\n \"print(llm(text))\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"7657e1e9\",\n \"metadata\": {},\n \"source\": [\n \"### Prompt Templates: Manage prompts for LLMs\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 13,\n \"id\": \"168f2277\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain.prompts import PromptTemplate\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 14,\n \"id\": \"9d6d3761\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"prompt = PromptTemplate(\\n\",\n \" input_variables=[\\\"food\\\"],\\n\",\n \" template=\\\"What are 5 vacation destinations for someone who likes to eat {food}?\\\",\\n\",\n \")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 15,\n \"id\": \"160f8a0f\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"What are 5 vacation destinations for someone who likes to eat dessert?\\n\"\n ]\n }\n ],\n \"source\": [\n \"print(prompt.format(food=\\\"dessert\\\"))\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 16,\n \"id\": \"4309f2a0\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"\\n\",\n \"\\n\",\n \"1. New York City, USA\\n\",\n \"2. Tokyo, Japan\\n\",\n \"3. Paris, France\\n\",\n \"4. San Francisco, USA\\n\",\n \"5. Vancouver, Canada\\n\"\n ]\n }\n ],\n \"source\": [\n \"print(llm(prompt.format(food=\\\"dessert\\\")))\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"9cd0c523\",\n \"metadata\": {},\n \"source\": [\n \"### Chains: Combine LLMs and prompts in multi-step workflows\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 17,\n \"id\": \"a34ff024\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain.prompts import PromptTemplate\\n\",\n \"from langchain.llms import OpenAI\\n\",\n \"from langchain.chains import LLMChain\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 18,\n \"id\": \"ffbdf4a9\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"llm = OpenAI(temperature=0.9)\\n\",\n \"\\n\",\n \"prompt = PromptTemplate(\\n\",\n \" input_variables=[\\\"food\\\"],\\n\",\n \" template=\\\"What are 5 vacation destinations for someone who likes to eat {food}?\\\",\\n\",\n \")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 19,\n \"id\": \"7efda77b\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"chain = LLMChain(llm=llm, prompt=prompt)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 20,\n \"id\": \"0b08b76a\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"\\n\",\n \"\\n\",\n \"1. Costa Rica \\n\",\n \"2. Hawaii \\n\",\n \"3. Malaysia \\n\",\n \"4. India \\n\",\n \"5. Thailand\\n\"\n ]\n }\n ],\n \"source\": [\n \"print(chain.run(\\\"fruit\\\"))\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"850668f0\",\n \"metadata\": {},\n \"source\": [\n \"### Agents: Dynamically call chains based on user input\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"id\": \"c19db4aa\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"pip install google-search-results\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 21,\n \"id\": \"6d22c464\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain.agents import load_tools\\n\",\n \"from langchain.agents import initialize_agent\\n\",\n \"from langchain.llms import OpenAI\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 22,\n \"id\": \"ba25bb42\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# Load the model\\n\",\n \"llm = OpenAI(temperature=0)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 23,\n \"id\": \"0740ce8f\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# Load in some tools to use\\n\",\n \"\\n\",\n \"# os.environ[\\\"SERPAPI_API_KEY\\\"] = \\\"...\\\"\\n\",\n \"\\n\",\n \"tools = load_tools([\\\"serpapi\\\", \\\"llm-math\\\"], llm=llm)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 24,\n \"id\": \"b20f48e3\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# Finally, let's initialize an agent with:\\n\",\n \"# 1. The tools\\n\",\n \"# 2. The language model\\n\",\n \"# 3. The type of agent we want to use.\\n\",\n \"\\n\",\n \"agent = initialize_agent(tools, llm, agent=\\\"zero-shot-react-description\\\", verbose=True)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"45f2cf54\",\n \"metadata\": {},\n \"source\": [\n \"See list of agents types [here](https://python.langchain.com/docs/modules/agents/agent_types/)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 25,\n \"id\": \"89728919\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"\\n\",\n \"\\n\",\n \"\\u001b[1m> Entering new AgentExecutor chain...\\u001b[0m\\n\",\n \"\\u001b[32;1m\\u001b[1;3m I need to find out who the leader of Japan is and then calculate the largest prime number that is smaller than their age.\\n\",\n \"Action: Search\\n\",\n \"Action Input: \\\"current leader of Japan\\\"\\u001b[0m\\n\",\n \"Observation: \\u001b[36;1m\\u001b[1;3mFumio Kishida\\u001b[0m\\n\",\n \"Thought:\\u001b[32;1m\\u001b[1;3m I need to find out the age of the leader of Japan\\n\",\n \"Action: Search\\n\",\n \"Action Input: \\\"age of Fumio Kishida\\\"\\u001b[0m\\n\",\n \"Observation: \\u001b[36;1m\\u001b[1;3m65 years\\u001b[0m\\n\",\n \"Thought:\\u001b[32;1m\\u001b[1;3m I need to calculate the largest prime number that is smaller than 65\\n\",\n \"Action: Calculator\\n\",\n \"Action Input: 65\\u001b[0m\\n\",\n \"Observation: \\u001b[33;1m\\u001b[1;3mAnswer: 65\\u001b[0m\\n\",\n \"Thought:\\u001b[32;1m\\u001b[1;3m I now know the final answer\\n\",\n \"Final Answer: The current leader of Japan is Fumio Kishida and the largest prime number that is smaller than their age is 61.\\u001b[0m\\n\",\n \"\\n\",\n \"\\u001b[1m> Finished chain.\\u001b[0m\\n\"\n ]\n },\n {\n \"data\": {\n \"text/plain\": [\n \"'The current leader of Japan is Fumio Kishida and the largest prime number that is smaller than their age is 61.'\"\n ]\n },\n \"execution_count\": 25,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"# Now let's test it out!\\n\",\n \"agent.run(\\\"Who is the current leader of Japan? What is the largest prime number that is smaller than their age?\\\")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"8808dc66\",\n \"metadata\": {},\n \"source\": [\n \"### Memory: Add state to chains and agents\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 26,\n \"id\": \"dc3294d3\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain import OpenAI, ConversationChain\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 27,\n \"id\": \"397ac43c\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"llm = OpenAI(temperature=0)\\n\",\n \"conversation = ConversationChain(llm=llm, verbose=True)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 28,\n \"id\": \"9823cde5\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"\\n\",\n \"\\n\",\n \"\\u001b[1m> Entering new ConversationChain chain...\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3mThe following is a friendly conversation between a human and an AI. The AI is talkative and provides lots of specific details from its context. If the AI does not know the answer to a question, it truthfully says it does not know.\\n\",\n \"\\n\",\n \"Current conversation:\\n\",\n \"\\n\",\n \"Human: Hi there!\\n\",\n \"AI:\\u001b[0m\\n\",\n \"\\n\",\n \"\\u001b[1m> Finished chain.\\u001b[0m\\n\"\n ]\n },\n {\n \"data\": {\n \"text/plain\": [\n \"\\\" Hi there! It's nice to meet you. How can I help you today?\\\"\"\n ]\n },\n \"execution_count\": 28,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"conversation.predict(input=\\\"Hi there!\\\")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 29,\n \"id\": \"a3d547bc\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"\\n\",\n \"\\n\",\n \"\\u001b[1m> Entering new ConversationChain chain...\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3mThe following is a friendly conversation between a human and an AI. The AI is talkative and provides lots of specific details from its context. If the AI does not know the answer to a question, it truthfully says it does not know.\\n\",\n \"\\n\",\n \"Current conversation:\\n\",\n \"\\n\",\n \"Human: Hi there!\\n\",\n \"AI: Hi there! It's nice to meet you. How can I help you today?\\n\",\n \"Human: I'm doing well! Just having a conversation with an AI.\\n\",\n \"AI:\\u001b[0m\\n\",\n \"\\n\",\n \"\\u001b[1m> Finished chain.\\u001b[0m\\n\"\n ]\n },\n {\n \"data\": {\n \"text/plain\": [\n \"\\\" That's great! It's always nice to have a conversation with someone new. What would you like to talk about?\\\"\"\n ]\n },\n \"execution_count\": 29,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"conversation.predict(input=\\\"I'm doing well! Just having a conversation with an AI.\\\")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 30,\n \"id\": \"bb71a25c\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"\\n\",\n \"\\n\",\n \"\\u001b[1m> Entering new ConversationChain chain...\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3mThe following is a friendly conversation between a human and an AI. The AI is talkative and provides lots of specific details from its context. If the AI does not know the answer to a question, it truthfully says it does not know.\\n\",\n \"\\n\",\n \"Current conversation:\\n\",\n \"\\n\",\n \"Human: Hi there!\\n\",\n \"AI: Hi there! It's nice to meet you. How can I help you today?\\n\",\n \"Human: I'm doing well! Just having a conversation with an AI.\\n\",\n \"AI: That's great! It's always nice to have a conversation with someone new. What would you like to talk about?\\n\",\n \"Human: What was the first thing I said to you?\\n\",\n \"AI:\\u001b[0m\\n\",\n \"\\n\",\n \"\\u001b[1m> Finished chain.\\u001b[0m\\n\"\n ]\n },\n {\n \"data\": {\n \"text/plain\": [\n \"' You said \\\"Hi there!\\\"'\"\n ]\n },\n \"execution_count\": 30,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"conversation.predict(input=\\\"What was the first thing I said to you?\\\")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 31,\n \"id\": \"0d7daf49\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"\\n\",\n \"\\n\",\n \"\\u001b[1m> Entering new ConversationChain chain...\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3mThe following is a friendly conversation between a human and an AI. The AI is talkative and provides lots of specific details from its context. If the AI does not know the answer to a question, it truthfully says it does not know.\\n\",\n \"\\n\",\n \"Current conversation:\\n\",\n \"\\n\",\n \"Human: Hi there!\\n\",\n \"AI: Hi there! It's nice to meet you. How can I help you today?\\n\",\n \"Human: I'm doing well! Just having a conversation with an AI.\\n\",\n \"AI: That's great! It's always nice to have a conversation with someone new. What would you like to talk about?\\n\",\n \"Human: What was the first thing I said to you?\\n\",\n \"AI: You said \\\"Hi there!\\\"\\n\",\n \"Human: what is an alternative phrase for the first thing I said to you?\\n\",\n \"AI:\\u001b[0m\\n\",\n \"\\n\",\n \"\\u001b[1m> Finished chain.\\u001b[0m\\n\"\n ]\n },\n {\n \"data\": {\n \"text/plain\": [\n \"' An alternative phrase for the first thing you said to me could be \\\"Greetings!\\\"'\"\n ]\n },\n \"execution_count\": 31,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"conversation.predict(input=\\\"what is an alternative phrase for the first thing I said to you?\\\")\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"id\": \"f3934501\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": []\n }\n ],\n \"metadata\": {\n \"kernelspec\": {\n \"display_name\": \"Python 3 (ipykernel)\",\n \"language\": \"python\",\n \"name\": \"python3\"\n },\n \"language_info\": {\n \"codemirror_mode\": {\n \"name\": \"ipython\",\n \"version\": 3\n },\n \"file_extension\": \".py\",\n \"mimetype\": \"text/x-python\",\n \"name\": \"python\",\n \"nbconvert_exporter\": \"python\",\n \"pygments_lexer\": \"ipython3\",\n \"version\": \"3.9.13\"\n }\n },\n \"nbformat\": 4,\n \"nbformat_minor\": 5\n}\n" }, { "path": "loaders/Google Drive Loader.ipynb", "content": "{\n \"cells\": [\n {\n \"cell_type\": \"code\",\n \"execution_count\": 3,\n \"id\": \"2804f2bf\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain.document_loaders import GoogleDriveLoader\\n\",\n \"import os\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 4,\n \"id\": \"3f988238\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"loader = GoogleDriveLoader(document_ids=[\\\"1BT5apJMTUvG9_59-ceHbuZXVTJKeyyknQsz9ZNIEwQ8\\\"],\\n\",\n \" credentials_path=\\\"../../desktop_credetnaisl.json\\\")\\n\",\n \"docs = loader.load()\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 2,\n \"id\": \"1cb4ae65\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# %set_env OPENAI_API_KEY = ...\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"6419b536\",\n \"metadata\": {},\n \"source\": [\n \"### Summarizing\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 7,\n \"id\": \"bfa4d948\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain.llms import OpenAI\\n\",\n \"from langchain.chains.summarize import load_summarize_chain\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 8,\n \"id\": \"1c7a6d81\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"llm = OpenAI(temperature=0, openai_api_key=os.environ['OPENAI_API_KEY'])\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 10,\n \"id\": \"d9220c03\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"\\n\",\n \"\\n\",\n \"\\u001b[1m> Entering new MapReduceDocumentsChain chain...\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3mWrite a concise summary of the following:\\n\",\n \"\\n\",\n \"\\n\",\n \"\\\"SecondaryEquityHub\\n\",\n \"2/21/2023\\n\",\n \"\\n\",\n \"\\n\",\n \"Introduction\\n\",\n \"\\n\",\n \"\\n\",\n \"Our product is a marketplace that connects startup employees who want to sell vested equity to buyers of secondary market shares.\\n\",\n \"\\n\",\n \"\\n\",\n \"Startups typically take several years to exit, leaving employees with vested equity tied up for an extended period. Our platform aims to address this issue by providing a marketplace for startup employees to sell their vested equity to buyers of secondary market shares.\\n\",\n \"\\n\",\n \"\\n\",\n \"This helps employees to unlock the value of their vested equity for personal financial goals, such as buying a home or paying down loans. At the same time, it provides buyers with the opportunity to invest in startup equity that has already passed the early-stage risks.\\n\",\n \"\\n\",\n \"\\n\",\n \"Our platform creates a win-win situation for both parties and fosters a more efficient secondary market for startup equity.\\n\",\n \"\\n\",\n \"\\n\",\n \"Problem Statement\\n\",\n \"\\n\",\n \"\\n\",\n \"The traditional path for startups from founding to exit can be a long and arduous journey. Often, it takes several years for a startup to exit, leaving employees with vested equity tied up for an extended period. This can create a significant financial burden for employees who may need to access the value of their equity for personal financial goals, such as buying a home or paying down loans.\\n\",\n \"\\n\",\n \"\\n\",\n \"On the other hand, there is an increasing demand for investment opportunities in the startup ecosystem. Buyers of secondary market shares are looking for investment options that have already passed the early-stage risks.\\n\",\n \"\\n\",\n \"\\n\",\n \"The lack of a viable secondary market for startup equity often results in a significant gap between demand and supply. This problem is significant for startup employees who are looking for liquidity, and buyers of secondary market shares who are looking for investment opportunities.\\n\",\n \"\\n\",\n \"\\n\",\n \"Our product aims to address this problem by providing a marketplace that connects startup employees who want to sell vested equity to buyers of secondary market shares, creating a more efficient and accessible secondary market for startup equity.\\n\",\n \"\\n\",\n \"\\n\",\n \"Product Features\\n\",\n \"1. Marketplace for Vested Equity: Our platform provides a marketplace for startup employees to sell their vested equity to buyers of secondary market shares.\\n\",\n \" 1. Benefit: This feature provides startup employees with liquidity options and helps them unlock the value of their equity for personal financial goals. It also provides buyers with an opportunity to invest in startup equity that has already passed the early-stage risks.\\n\",\n \"2. Secure Transaction: Our platform ensures secure and hassle-free transactions through its escrow service\\n\",\n \" 1. Benefit: This feature ensures a safe and secure transaction process for both buyers and sellers, mitigating the risk of fraud or financial loss.\\n\",\n \"3. Automated Compliance: Our platform automates compliance requirements, including tax withholdings and regulatory filings, ensuring legal compliance for both buyers and sellers\\n\",\n \" 1. Benefit: This feature eliminates the complexity and legal risks associated with selling and buying vested equity. It ensures compliance with legal and regulatory requirements and reduces the transactional costs associated with these compliance procedures.\\n\",\n \"4. Transparent Pricing: Our platform provides transparent pricing, including price history and market trends, ensuring a fair and competitive pricing system\\n\",\n \" 1. Benefit: This feature ensures a transparent and fair pricing system, providing buyers and sellers with a clear understanding of market trends and price history.\\n\",\n \"5. Efficient Matching System: Our platform uses an efficient matching system that matches buyers with sellers based on their investment goals and preferences\\n\",\n \" 1. Benefit: This feature ensures that buyers and sellers are matched efficiently based on their preferences, resulting in a faster and more efficient transaction process. It provides buyers with a wider range of investment options, while also ensuring that sellers can access a larger pool of potential buyers.\\\"\\n\",\n \"\\n\",\n \"\\n\",\n \"CONCISE SUMMARY:\\u001b[0m\\n\",\n \"\\n\",\n \"\\n\",\n \"\\u001b[1m> Entering new LLMChain chain...\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3mWrite a concise summary of the following:\\n\",\n \"\\n\",\n \"\\n\",\n \"\\\" SecondaryEquityHub is a marketplace that connects startup employees who want to sell vested equity to buyers of secondary market shares. It provides a win-win situation for both parties by providing liquidity options for employees and investment opportunities for buyers. The platform also ensures secure transactions, automated compliance, transparent pricing, and an efficient matching system.\\\"\\n\",\n \"\\n\",\n \"\\n\",\n \"CONCISE SUMMARY:\\u001b[0m\\n\",\n \"\\n\",\n \"\\u001b[1m> Finished chain.\\u001b[0m\\n\",\n \"\\n\",\n \"\\u001b[1m> Finished chain.\\u001b[0m\\n\"\n ]\n },\n {\n \"data\": {\n \"text/plain\": [\n \"' SecondaryEquityHub is a marketplace that connects startup employees who want to sell vested equity with buyers of secondary market shares. It provides a secure, compliant, and efficient platform for both parties to benefit from liquidity options and investment opportunities.'\"\n ]\n },\n \"execution_count\": 10,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"chain = load_summarize_chain(llm, chain_type=\\\"map_reduce\\\", verbose=True)\\n\",\n \"chain.run(docs)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"cdaf482f\",\n \"metadata\": {},\n \"source\": [\n \"### Asking Questions\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 11,\n \"id\": \"e123a924\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain.chains.question_answering import load_qa_chain\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 12,\n \"id\": \"fd19d27c\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"query = \\\"What problem is this product solving?\\\"\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 13,\n \"id\": \"dc399ac7\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"' This product is solving the problem of the lack of a viable secondary market for startup equity, which often results in a significant gap between demand and supply. This problem is significant for startup employees who are looking for liquidity, and buyers of secondary market shares who are looking for investment opportunities.'\"\n ]\n },\n \"execution_count\": 13,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"chain = load_qa_chain(llm, chain_type=\\\"stuff\\\")\\n\",\n \"chain.run(input_documents=docs, question=query)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 15,\n \"id\": \"5c295ba5\",\n \"metadata\": {\n \"collapsed\": true\n },\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"\\n\",\n \"\\n\",\n \"\\u001b[1m> Entering new StuffDocumentsChain chain...\\u001b[0m\\n\",\n \"\\n\",\n \"\\n\",\n \"\\u001b[1m> Entering new LLMChain chain...\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3mUse the following pieces of context to answer the question at the end. If you don't know the answer, just say that you don't know, don't try to make up an answer.\\n\",\n \"\\n\",\n \"SecondaryEquityHub\\n\",\n \"2/21/2023\\n\",\n \"\\n\",\n \"\\n\",\n \"Introduction\\n\",\n \"\\n\",\n \"\\n\",\n \"Our product is a marketplace that connects startup employees who want to sell vested equity to buyers of secondary market shares.\\n\",\n \"\\n\",\n \"\\n\",\n \"Startups typically take several years to exit, leaving employees with vested equity tied up for an extended period. Our platform aims to address this issue by providing a marketplace for startup employees to sell their vested equity to buyers of secondary market shares.\\n\",\n \"\\n\",\n \"\\n\",\n \"This helps employees to unlock the value of their vested equity for personal financial goals, such as buying a home or paying down loans. At the same time, it provides buyers with the opportunity to invest in startup equity that has already passed the early-stage risks.\\n\",\n \"\\n\",\n \"\\n\",\n \"Our platform creates a win-win situation for both parties and fosters a more efficient secondary market for startup equity.\\n\",\n \"\\n\",\n \"\\n\",\n \"Problem Statement\\n\",\n \"\\n\",\n \"\\n\",\n \"The traditional path for startups from founding to exit can be a long and arduous journey. Often, it takes several years for a startup to exit, leaving employees with vested equity tied up for an extended period. This can create a significant financial burden for employees who may need to access the value of their equity for personal financial goals, such as buying a home or paying down loans.\\n\",\n \"\\n\",\n \"\\n\",\n \"On the other hand, there is an increasing demand for investment opportunities in the startup ecosystem. Buyers of secondary market shares are looking for investment options that have already passed the early-stage risks.\\n\",\n \"\\n\",\n \"\\n\",\n \"The lack of a viable secondary market for startup equity often results in a significant gap between demand and supply. This problem is significant for startup employees who are looking for liquidity, and buyers of secondary market shares who are looking for investment opportunities.\\n\",\n \"\\n\",\n \"\\n\",\n \"Our product aims to address this problem by providing a marketplace that connects startup employees who want to sell vested equity to buyers of secondary market shares, creating a more efficient and accessible secondary market for startup equity.\\n\",\n \"\\n\",\n \"\\n\",\n \"Product Features\\n\",\n \"1. Marketplace for Vested Equity: Our platform provides a marketplace for startup employees to sell their vested equity to buyers of secondary market shares.\\n\",\n \" 1. Benefit: This feature provides startup employees with liquidity options and helps them unlock the value of their equity for personal financial goals. It also provides buyers with an opportunity to invest in startup equity that has already passed the early-stage risks.\\n\",\n \"2. Secure Transaction: Our platform ensures secure and hassle-free transactions through its escrow service\\n\",\n \" 1. Benefit: This feature ensures a safe and secure transaction process for both buyers and sellers, mitigating the risk of fraud or financial loss.\\n\",\n \"3. Automated Compliance: Our platform automates compliance requirements, including tax withholdings and regulatory filings, ensuring legal compliance for both buyers and sellers\\n\",\n \" 1. Benefit: This feature eliminates the complexity and legal risks associated with selling and buying vested equity. It ensures compliance with legal and regulatory requirements and reduces the transactional costs associated with these compliance procedures.\\n\",\n \"4. Transparent Pricing: Our platform provides transparent pricing, including price history and market trends, ensuring a fair and competitive pricing system\\n\",\n \" 1. Benefit: This feature ensures a transparent and fair pricing system, providing buyers and sellers with a clear understanding of market trends and price history.\\n\",\n \"5. Efficient Matching System: Our platform uses an efficient matching system that matches buyers with sellers based on their investment goals and preferences\\n\",\n \" 1. Benefit: This feature ensures that buyers and sellers are matched efficiently based on their preferences, resulting in a faster and more efficient transaction process. It provides buyers with a wider range of investment options, while also ensuring that sellers can access a larger pool of potential buyers.\\n\",\n \"\\n\",\n \"Question: How should we reach our target audience of this product?\\n\",\n \"Helpful Answer:\\u001b[0m\\n\",\n \"\\n\",\n \"\\u001b[1m> Finished chain.\\u001b[0m\\n\",\n \"\\n\",\n \"\\u001b[1m> Finished chain.\\u001b[0m\\n\"\n ]\n },\n {\n \"data\": {\n \"text/plain\": [\n \"' We should reach our target audience by leveraging digital marketing channels such as social media, search engine optimization, and content marketing. We should also consider using traditional marketing channels such as print, radio, and television advertising. Additionally, we should consider partnering with influencers and industry experts to help spread the word about our product.'\"\n ]\n },\n \"execution_count\": 15,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"query = \\\"How should we reach our target audience of this product?\\\"\\n\",\n \"\\n\",\n \"chain = load_qa_chain(llm, chain_type=\\\"stuff\\\", verbose=True)\\n\",\n \"chain.run(input_documents=docs, question=query)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"6dc5afa3\",\n \"metadata\": {},\n \"source\": [\n \"## And there's more: Add documents to your list\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 16,\n \"id\": \"2d921ee7\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"loader = GoogleDriveLoader(document_ids=[\\\"1ETW9siA8EBkdms7R1UTw1ysXag2U6gb9wMzRpSxjqY8\\\"],\\n\",\n \" credentials_path=\\\"../../desktop_credetnaisl.json\\\")\\n\",\n \"new_doc = loader.load()\\n\",\n \"\\n\",\n \"docs.extend(new_doc)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 19,\n \"id\": \"1fe49414\",\n \"metadata\": {\n \"collapsed\": true\n },\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"\\n\",\n \"\\n\",\n \"\\u001b[1m> Entering new StuffDocumentsChain chain...\\u001b[0m\\n\",\n \"\\n\",\n \"\\n\",\n \"\\u001b[1m> Entering new LLMChain chain...\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3mUse the following pieces of context to answer the question at the end. If you don't know the answer, just say that you don't know, don't try to make up an answer.\\n\",\n \"\\n\",\n \"SecondaryEquityHub\\n\",\n \"2/21/2023\\n\",\n \"\\n\",\n \"\\n\",\n \"Introduction\\n\",\n \"\\n\",\n \"\\n\",\n \"Our product is a marketplace that connects startup employees who want to sell vested equity to buyers of secondary market shares.\\n\",\n \"\\n\",\n \"\\n\",\n \"Startups typically take several years to exit, leaving employees with vested equity tied up for an extended period. Our platform aims to address this issue by providing a marketplace for startup employees to sell their vested equity to buyers of secondary market shares.\\n\",\n \"\\n\",\n \"\\n\",\n \"This helps employees to unlock the value of their vested equity for personal financial goals, such as buying a home or paying down loans. At the same time, it provides buyers with the opportunity to invest in startup equity that has already passed the early-stage risks.\\n\",\n \"\\n\",\n \"\\n\",\n \"Our platform creates a win-win situation for both parties and fosters a more efficient secondary market for startup equity.\\n\",\n \"\\n\",\n \"\\n\",\n \"Problem Statement\\n\",\n \"\\n\",\n \"\\n\",\n \"The traditional path for startups from founding to exit can be a long and arduous journey. Often, it takes several years for a startup to exit, leaving employees with vested equity tied up for an extended period. This can create a significant financial burden for employees who may need to access the value of their equity for personal financial goals, such as buying a home or paying down loans.\\n\",\n \"\\n\",\n \"\\n\",\n \"On the other hand, there is an increasing demand for investment opportunities in the startup ecosystem. Buyers of secondary market shares are looking for investment options that have already passed the early-stage risks.\\n\",\n \"\\n\",\n \"\\n\",\n \"The lack of a viable secondary market for startup equity often results in a significant gap between demand and supply. This problem is significant for startup employees who are looking for liquidity, and buyers of secondary market shares who are looking for investment opportunities.\\n\",\n \"\\n\",\n \"\\n\",\n \"Our product aims to address this problem by providing a marketplace that connects startup employees who want to sell vested equity to buyers of secondary market shares, creating a more efficient and accessible secondary market for startup equity.\\n\",\n \"\\n\",\n \"\\n\",\n \"Product Features\\n\",\n \"1. Marketplace for Vested Equity: Our platform provides a marketplace for startup employees to sell their vested equity to buyers of secondary market shares.\\n\",\n \" 1. Benefit: This feature provides startup employees with liquidity options and helps them unlock the value of their equity for personal financial goals. It also provides buyers with an opportunity to invest in startup equity that has already passed the early-stage risks.\\n\",\n \"2. Secure Transaction: Our platform ensures secure and hassle-free transactions through its escrow service\\n\",\n \" 1. Benefit: This feature ensures a safe and secure transaction process for both buyers and sellers, mitigating the risk of fraud or financial loss.\\n\",\n \"3. Automated Compliance: Our platform automates compliance requirements, including tax withholdings and regulatory filings, ensuring legal compliance for both buyers and sellers\\n\",\n \" 1. Benefit: This feature eliminates the complexity and legal risks associated with selling and buying vested equity. It ensures compliance with legal and regulatory requirements and reduces the transactional costs associated with these compliance procedures.\\n\",\n \"4. Transparent Pricing: Our platform provides transparent pricing, including price history and market trends, ensuring a fair and competitive pricing system\\n\",\n \" 1. Benefit: This feature ensures a transparent and fair pricing system, providing buyers and sellers with a clear understanding of market trends and price history.\\n\",\n \"5. Efficient Matching System: Our platform uses an efficient matching system that matches buyers with sellers based on their investment goals and preferences\\n\",\n \" 1. Benefit: This feature ensures that buyers and sellers are matched efficiently based on their preferences, resulting in a faster and more efficient transaction process. It provides buyers with a wider range of investment options, while also ensuring that sellers can access a larger pool of potential buyers.\\n\",\n \"\\n\",\n \"SecondaryEquityHub - User Interviews\\n\",\n \"2/21/2023\\n\",\n \"\\n\",\n \"\\n\",\n \"Interview #1 - Sally\\n\",\n \"\\n\",\n \"\\n\",\n \"Eliza: Hi Sally, thanks for coming in today. Can you tell me a bit about your experience in the startup world?\\n\",\n \"\\n\",\n \"\\n\",\n \"Sally: Hi Eliza, thanks for having me. Sure, I've been working in the startup world for about 5 years now. I've worked for a few different startups in various roles, from marketing to product management.\\n\",\n \"\\n\",\n \"\\n\",\n \"Eliza: Great, well our product is a marketplace that connects startup employees who want to sell vested equity to buyers of secondary market shares. What do you think of this idea?\\n\",\n \"Sally: I think it's a really interesting concept. It's not uncommon for startup employees to have vested equity tied up for several years, and having a marketplace to sell that equity could be really helpful for those who want to unlock its value.\\n\",\n \"\\n\",\n \"\\n\",\n \"Eliza: Yes, exactly. The platform aims to help employees achieve personal financial goals, such as buying a home or paying down loans, while also providing buyers with the opportunity to invest in startup equity that has already passed the early-stage risks. How do you think we can ensure that the buyers are getting a fair deal?\\n\",\n \"\\n\",\n \"\\n\",\n \"Sally: That's a good question. I think it would be important to have some kind of vetting process for the sellers and the shares they're selling. We would need to make sure that the shares are legitimate and that the sellers have the right to sell them. It would also be important to have some kind of transparency around the pricing, so that buyers can make informed decisions.\\n\",\n \"\\n\",\n \"\\n\",\n \"Eliza: Yes, those are all great points. We've been working on developing a secure platform that includes a vetting process for the sellers and the shares they're selling, and we're also planning to provide transparent pricing information. Thank you for your input, Sally. It was great to chat with you today.\\n\",\n \"\\n\",\n \"Question: What are users saying about our product?\\n\",\n \"Helpful Answer:\\u001b[0m\\n\",\n \"\\n\",\n \"\\u001b[1m> Finished chain.\\u001b[0m\\n\",\n \"\\n\",\n \"\\u001b[1m> Finished chain.\\u001b[0m\\n\"\n ]\n },\n {\n \"data\": {\n \"text/plain\": [\n \"\\\" Users are saying that the product is a good idea and that it could be helpful for startup employees who want to unlock the value of their vested equity for personal financial goals. They are also suggesting that there should be a vetting process for the sellers and the shares they're selling, as well as transparent pricing information, to ensure that buyers are getting a fair deal.\\\"\"\n ]\n },\n \"execution_count\": 19,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"query = \\\"What are users saying about our product?\\\"\\n\",\n \"\\n\",\n \"chain = load_qa_chain(llm, chain_type=\\\"stuff\\\", verbose=True)\\n\",\n \"chain.run(input_documents=docs, question=query)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"38901b7f\",\n \"metadata\": {},\n \"source\": [\n \"### Remove Documents\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 20,\n \"id\": \"7a0eb0f4\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"list\"\n ]\n },\n \"execution_count\": 20,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"type(docs)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 21,\n \"id\": \"7151f84a\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"Document(page_content=\\\"\\\\ufeffSecondaryEquityHub - User Interviews\\\\r\\\\n2/21/2023\\\\r\\\\n\\\\r\\\\n\\\\r\\\\nInterview #1 - Sally\\\\r\\\\n\\\\r\\\\n\\\\r\\\\nEliza: Hi Sally, thanks for coming in today. Can you tell me a bit about your experience in the startup world?\\\\r\\\\n\\\\r\\\\n\\\\r\\\\nSally: Hi Eliza, thanks for having me. Sure, I've been working in the startup world for about 5 years now. I've worked for a few different startups in various roles, from marketing to product management.\\\\r\\\\n\\\\r\\\\n\\\\r\\\\nEliza: Great, well our product is a marketplace that connects startup employees who want to sell vested equity to buyers of secondary market shares. What do you think of this idea?\\\\r\\\\nSally: I think it's a really interesting concept. It's not uncommon for startup employees to have vested equity tied up for several years, and having a marketplace to sell that equity could be really helpful for those who want to unlock its value.\\\\r\\\\n\\\\r\\\\n\\\\r\\\\nEliza: Yes, exactly. The platform aims to help employees achieve personal financial goals, such as buying a home or paying down loans, while also providing buyers with the opportunity to invest in startup equity that has already passed the early-stage risks. How do you think we can ensure that the buyers are getting a fair deal?\\\\r\\\\n\\\\r\\\\n\\\\r\\\\nSally: That's a good question. I think it would be important to have some kind of vetting process for the sellers and the shares they're selling. We would need to make sure that the shares are legitimate and that the sellers have the right to sell them. It would also be important to have some kind of transparency around the pricing, so that buyers can make informed decisions.\\\\r\\\\n\\\\r\\\\n\\\\r\\\\nEliza: Yes, those are all great points. We've been working on developing a secure platform that includes a vetting process for the sellers and the shares they're selling, and we're also planning to provide transparent pricing information. Thank you for your input, Sally. It was great to chat with you today.\\\", lookup_str='', metadata={'source': 'https://docs.google.com/document/d/1ETW9siA8EBkdms7R1UTw1ysXag2U6gb9wMzRpSxjqY8/edit'}, lookup_index=0)\"\n ]\n },\n \"execution_count\": 21,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"docs.pop()\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"id\": \"e8a0b907\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": []\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 22,\n \"id\": \"c2bd62dc\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"{'page_content': '\\\\ufeffSecondaryEquityHub\\\\r\\\\n2/21/2023\\\\r\\\\n\\\\r\\\\n\\\\r\\\\nIntroduction\\\\r\\\\n\\\\r\\\\n\\\\r\\\\nOur product is a marketplace that connects startup employees who want to sell vested equity to buyers of secondary market shares.\\\\r\\\\n\\\\r\\\\n\\\\r\\\\nStartups typically take several years to exit, leaving employees with vested equity tied up for an extended period. Our platform aims to address this issue by providing a marketplace for startup employees to sell their vested equity to buyers of secondary market shares.\\\\r\\\\n\\\\r\\\\n\\\\r\\\\nThis helps employees to unlock the value of their vested equity for personal financial goals, such as buying a home or paying down loans. At the same time, it provides buyers with the opportunity to invest in startup equity that has already passed the early-stage risks.\\\\r\\\\n\\\\r\\\\n\\\\r\\\\nOur platform creates a win-win situation for both parties and fosters a more efficient secondary market for startup equity.\\\\r\\\\n\\\\r\\\\n\\\\r\\\\nProblem Statement\\\\r\\\\n\\\\r\\\\n\\\\r\\\\nThe traditional path for startups from founding to exit can be a long and arduous journey. Often, it takes several years for a startup to exit, leaving employees with vested equity tied up for an extended period. This can create a significant financial burden for employees who may need to access the value of their equity for personal financial goals, such as buying a home or paying down loans.\\\\r\\\\n\\\\r\\\\n\\\\r\\\\nOn the other hand, there is an increasing demand for investment opportunities in the startup ecosystem. Buyers of secondary market shares are looking for investment options that have already passed the early-stage risks.\\\\r\\\\n\\\\r\\\\n\\\\r\\\\nThe lack of a viable secondary market for startup equity often results in a significant gap between demand and supply. This problem is significant for startup employees who are looking for liquidity, and buyers of secondary market shares who are looking for investment opportunities.\\\\r\\\\n\\\\r\\\\n\\\\r\\\\nOur product aims to address this problem by providing a marketplace that connects startup employees who want to sell vested equity to buyers of secondary market shares, creating a more efficient and accessible secondary market for startup equity.\\\\r\\\\n\\\\r\\\\n\\\\r\\\\nProduct Features\\\\r\\\\n1. Marketplace for Vested Equity: Our platform provides a marketplace for startup employees to sell their vested equity to buyers of secondary market shares.\\\\r\\\\n 1. Benefit: This feature provides startup employees with liquidity options and helps them unlock the value of their equity for personal financial goals. It also provides buyers with an opportunity to invest in startup equity that has already passed the early-stage risks.\\\\r\\\\n2. Secure Transaction: Our platform ensures secure and hassle-free transactions through its escrow service\\\\r\\\\n 1. Benefit: This feature ensures a safe and secure transaction process for both buyers and sellers, mitigating the risk of fraud or financial loss.\\\\r\\\\n3. Automated Compliance: Our platform automates compliance requirements, including tax withholdings and regulatory filings, ensuring legal compliance for both buyers and sellers\\\\r\\\\n 1. Benefit: This feature eliminates the complexity and legal risks associated with selling and buying vested equity. It ensures compliance with legal and regulatory requirements and reduces the transactional costs associated with these compliance procedures.\\\\r\\\\n4. Transparent Pricing: Our platform provides transparent pricing, including price history and market trends, ensuring a fair and competitive pricing system\\\\r\\\\n 1. Benefit: This feature ensures a transparent and fair pricing system, providing buyers and sellers with a clear understanding of market trends and price history.\\\\r\\\\n5. Efficient Matching System: Our platform uses an efficient matching system that matches buyers with sellers based on their investment goals and preferences\\\\r\\\\n 1. Benefit: This feature ensures that buyers and sellers are matched efficiently based on their preferences, resulting in a faster and more efficient transaction process. It provides buyers with a wider range of investment options, while also ensuring that sellers can access a larger pool of potential buyers.',\\n\",\n \" 'lookup_str': '',\\n\",\n \" 'metadata': {'source': 'https://docs.google.com/document/d/1BT5apJMTUvG9_59-ceHbuZXVTJKeyyknQsz9ZNIEwQ8/edit'},\\n\",\n \" 'lookup_index': 0}\"\n ]\n },\n \"execution_count\": 22,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"docs[0].dict()\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"id\": \"9a66c436\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": []\n }\n ],\n \"metadata\": {\n \"kernelspec\": {\n \"display_name\": \"Python 3 (ipykernel)\",\n \"language\": \"python\",\n \"name\": \"python3\"\n },\n \"language_info\": {\n \"codemirror_mode\": {\n \"name\": \"ipython\",\n \"version\": 3\n },\n \"file_extension\": \".py\",\n \"mimetype\": \"text/x-python\",\n \"name\": \"python\",\n \"nbconvert_exporter\": \"python\",\n \"pygments_lexer\": \"ipython3\",\n \"version\": \"3.9.13\"\n }\n },\n \"nbformat\": 4,\n \"nbformat_minor\": 5\n}\n" }, { "path": "loaders/YouTube Loader.ipynb", "content": "{\n \"cells\": [\n {\n \"cell_type\": \"code\",\n \"execution_count\": 6,\n \"id\": \"dd186bb6\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain.document_loaders import YoutubeLoader\\n\",\n \"from langchain.llms import OpenAI\\n\",\n \"from langchain.chains.summarize import load_summarize_chain\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 7,\n \"id\": \"2ba51e36\",\n \"metadata\": {\n \"hide_input\": false\n },\n \"outputs\": [],\n \"source\": [\n \"OPENAI_API_KEY = '...'\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"id\": \"e567d2ef\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# pip install youtube-transcript-api\\n\",\n \"# pip install pytube\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"0b913708\",\n \"metadata\": {},\n \"source\": [\n \"### 1. Simple Videos\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 2,\n \"id\": \"e30060ab\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"loader = YoutubeLoader.from_youtube_url(\\\"https://www.youtube.com/watch?v=QsYGlZkevEg\\\", add_video_info=True)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 3,\n \"id\": \"ba6e2832\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"result = loader.load()\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 4,\n \"id\": \"52a99b6d\",\n \"metadata\": {\n \"collapsed\": true\n },\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"\\n\",\n \"Found video from Saturday Night Live that is 224 seconds long\\n\",\n \"\\n\",\n \"[Document(page_content='LADIES AND GENTLEMEN, PEDRO PASCAL! [ CHEERS AND APPLAUSE ] >> THANK YOU, THANK YOU. THANK YOU VERY MUCH. I\\\\'M SO EXCITED TO BE HERE. THANK YOU. I SPENT THE LAST YEAR SHOOTING A SHOW CALLED \\\"THE LAST OF US\\\" ON HBO. FOR SOME HBO SHOES, YOU GET TO SHOOT IN A FIVE STAR ITALIAN RESORT SURROUNDED BY BEAUTIFUL PEOPLE, BUT I SAID, NO, THAT\\\\'S TOO EASY. I WANT TO SHOOT IN A FREEZING CANADIAN FOREST WHILE BEING CHASED AROUND BY A GUY WHOSE HEAD LOOKS LIKE A GENITAL WART. IT IS AN HONOR BEING A PART OF THESE HUGE FRANCHISEs LIKE \\\"GAME OF THRONES\\\" AND \\\"STAR WARS,\\\" BUT I\\\\'M STILL GETTING USED TO PEOPLE RECOGNIZING ME. THE OTHER DAY, A GUY STOPPED ME ON THE STREET AND SAYS, MY SON LOVES \\\"THE MANDALORIAN\\\" AND THE NEXT THING I KNOW, I\\\\'M FACE TIMING WITH A 6-YEAR-OLD WHO HAS NO IDEA WHO I AM BECAUSE MY CHARACTER WEARS A MASK THE ENTIRE SHOW. THE GUY IS LIKE, DO THE MANDO VOICE, BUT IT\\\\'S LIKE A BEDROOM VOICE. WITHOUT THE MASK, IT JUST SOUNDS PORNY. PEOPLE WALKING BY ON THE STREET SEE ME WHISPERING TO A 6-YEAR-OLD KID. I CAN BRING YOU IN WARM, OR I CAN BRING YOU IN COLD. EVEN THOUGH I CAME TO THE U.S. WHEN I WAS LITTLE, I WAS BORN IN CHILE, AND I HAVE 34 FIRST COUSINS WHO ARE STILL THERE. THEY\\\\'RE VERY PROUD OF ME. I KNOW THEY\\\\'RE PROUD BECAUSE THEY GIVE MY PHONE NUMBER TO EVERY PERSON THEY MEET, WHICH MEANS EVERY DAY, SOMEONE IN SANTIAGO WILL TEXT ME STUFF LIKE, CAN YOU COME TO MY WEDDING, OR CAN YOU SING MY PRIEST HAPPY BIRTHDAY, OR IS BABY YODA MEAN IN REAL LIFE. SO I HAVE TO BE LIKE NO, NO, AND HIS NAME IS GROGU. BUT MY COUSINS WEREN\\\\'T ALWAYS SO PROUD. EARLY IN MY CAREER, I PLAYED SMALL PARTS IN EVERY CRIME SHOW. I EVEN PLAYED TWO DIFFERENT CHARACTERS ON \\\"LAW AND ORDER.\\\" TITO CABASSA WHO LOOKED LIKE THIS. AND ONE YEAR LATER, I PLAYED REGGIE LUCKMAN WHO LOOKS LIKE THIS. AND THAT, MY FRIENDS, IS CALLED RANGE. BUT IT IS AMAZING TO BE HERE, LIKE I SAID. I WAS BORN IN CHILE, AND NINE MONTHS LATER, MY PARENTS FLED AND BROUGHT ME AND MY SISTER TO THE U.S. THEY WERE SO BRAVE, AND WITHOUT THEM, I WOULDN\\\\'T BE HERE IN THIS WONDERFUL COUNTRY, AND I CERTAINLY WOULDN\\\\'T BE STANDING HERE WITH YOU ALL TONIGHT. SO TO ALL MY FAMILY WATCHING IN CHILE, I WANT TO SAY [ SPEAKING NON-ENGLISH ] WHICH MEANS, I LOVE YOU, I MISS YOU, AND STOP GIVING OUT MY PHONE NUMBER. WE\\\\'VE GOT AN AMAZING SHOW FOR YOU TONIGHT. COLDPLAY IS HERE, SO STICK', lookup_str='', metadata={'source': 'QsYGlZkevEg', 'title': 'Pedro Pascal Monologue - SNL', 'description': 'First-time host Pedro Pascal talks about filming The Last of Us and being recognized by fans.\\\\n\\\\nSaturday Night Live. Stream now on Peacock: https://pck.tv/3uQxh4q\\\\n\\\\nSubscribe to SNL: https://goo.gl/tUsXwM\\\\nStream Current Full Episodes: http://www.nbc.com/saturday-night-live\\\\n\\\\nWATCH PAST SNL SEASONS\\\\nGoogle Play - http://bit.ly/SNLGooglePlay\\\\niTunes - http://bit.ly/SNLiTunes\\\\n\\\\nSNL ON SOCIAL\\\\nSNL Instagram: http://instagram.com/nbcsnl\\\\nSNL Facebook: https://www.facebook.com/snl\\\\nSNL Twitter: https://twitter.com/nbcsnl\\\\nSNL TikTok: https://www.tiktok.com/@nbcsnl\\\\n\\\\nGET MORE NBC\\\\nLike NBC: http://Facebook.com/NBC\\\\nFollow NBC: http://Twitter.com/NBC\\\\nNBC Tumblr: http://NBCtv.tumblr.com/\\\\nYouTube: http://www.youtube.com/nbc\\\\nNBC Instagram: http://instagram.com/nbc\\\\n\\\\n#SNL #PedroPascal #SNL48 #Coldplay', 'view_count': 1433225, 'thumbnail_url': 'https://i.ytimg.com/vi/QsYGlZkevEg/sddefault.jpg', 'publish_date': datetime.datetime(2023, 2, 4, 0, 0), 'length': 224, 'author': 'Saturday Night Live'}, lookup_index=0)]\\n\"\n ]\n }\n ],\n \"source\": [\n \"print (type(result))\\n\",\n \"print (f\\\"Found video from {result[0].metadata['author']} that is {result[0].metadata['length']} seconds long\\\")\\n\",\n \"print (\\\"\\\")\\n\",\n \"print (result)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 8,\n \"id\": \"0a675091\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"llm = OpenAI(temperature=0, openai_api_key=OPENAI_API_KEY)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 9,\n \"id\": \"580bceb8\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"' Pedro Pascal shared his experience shooting for HBO\\\\'s \\\"The Last of Us\\\" and his journey to becoming a recognizable actor. He also spoke about his Chilean family, who were initially not proud of his acting career, but are now supportive. He concluded his speech by introducing Coldplay, who will be performing at the show.'\"\n ]\n },\n \"execution_count\": 9,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"chain = load_summarize_chain(llm, chain_type=\\\"stuff\\\", verbose=False)\\n\",\n \"chain.run(result)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"f47acaa5\",\n \"metadata\": {},\n \"source\": [\n \"### 2. Long Videos\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 10,\n \"id\": \"985523d3\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"loader = YoutubeLoader.from_youtube_url(\\\"https://www.youtube.com/watch?v=6Ub7Z1AGIuk\\\", add_video_info=True)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 11,\n \"id\": \"d2c95abe\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"result = loader.load()\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 12,\n \"id\": \"f7454d1c\",\n \"metadata\": {\n \"collapsed\": true\n },\n \"outputs\": [\n {\n \"ename\": \"InvalidRequestError\",\n \"evalue\": \"This model's maximum context length is 4097 tokens, however you requested 14199 tokens (13943 in your prompt; 256 for the completion). Please reduce your prompt; or completion length.\",\n \"output_type\": \"error\",\n \"traceback\": [\n \"\\u001b[0;31m---------------------------------------------------------------------------\\u001b[0m\",\n \"\\u001b[0;31mInvalidRequestError\\u001b[0m Traceback (most recent call last)\",\n \"\\u001b[0;32m/var/folders/5c/csjfqsk97xz704h7v3fzjqph0000gn/T/ipykernel_10827/3887462961.py\\u001b[0m in \\u001b[0;36m\\u001b[0;34m\\u001b[0m\\n\\u001b[1;32m 1\\u001b[0m \\u001b[0mchain\\u001b[0m \\u001b[0;34m=\\u001b[0m \\u001b[0mload_summarize_chain\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0mllm\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0mchain_type\\u001b[0m\\u001b[0;34m=\\u001b[0m\\u001b[0;34m\\\"stuff\\\"\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0mverbose\\u001b[0m\\u001b[0;34m=\\u001b[0m\\u001b[0;32mFalse\\u001b[0m\\u001b[0;34m)\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0;32m----> 2\\u001b[0;31m \\u001b[0mchain\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0mrun\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0mresult\\u001b[0m\\u001b[0;34m)\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0m\",\n \"\\u001b[0;32m~/opt/anaconda3/lib/python3.9/site-packages/langchain/chains/base.py\\u001b[0m in \\u001b[0;36mrun\\u001b[0;34m(self, *args, **kwargs)\\u001b[0m\\n\\u001b[1;32m 237\\u001b[0m \\u001b[0;32mif\\u001b[0m \\u001b[0mlen\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0margs\\u001b[0m\\u001b[0;34m)\\u001b[0m \\u001b[0;34m!=\\u001b[0m \\u001b[0;36m1\\u001b[0m\\u001b[0;34m:\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[1;32m 238\\u001b[0m \\u001b[0;32mraise\\u001b[0m \\u001b[0mValueError\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0;34m\\\"`run` supports only one positional argument.\\\"\\u001b[0m\\u001b[0;34m)\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0;32m--> 239\\u001b[0;31m \\u001b[0;32mreturn\\u001b[0m \\u001b[0mself\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0margs\\u001b[0m\\u001b[0;34m[\\u001b[0m\\u001b[0;36m0\\u001b[0m\\u001b[0;34m]\\u001b[0m\\u001b[0;34m)\\u001b[0m\\u001b[0;34m[\\u001b[0m\\u001b[0mself\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0moutput_keys\\u001b[0m\\u001b[0;34m[\\u001b[0m\\u001b[0;36m0\\u001b[0m\\u001b[0;34m]\\u001b[0m\\u001b[0;34m]\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0m\\u001b[1;32m 240\\u001b[0m \\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[1;32m 241\\u001b[0m \\u001b[0;32mif\\u001b[0m \\u001b[0mkwargs\\u001b[0m \\u001b[0;32mand\\u001b[0m \\u001b[0;32mnot\\u001b[0m \\u001b[0margs\\u001b[0m\\u001b[0;34m:\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\",\n \"\\u001b[0;32m~/opt/anaconda3/lib/python3.9/site-packages/langchain/chains/base.py\\u001b[0m in \\u001b[0;36m__call__\\u001b[0;34m(self, inputs, return_only_outputs)\\u001b[0m\\n\\u001b[1;32m 140\\u001b[0m \\u001b[0;32mexcept\\u001b[0m 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return_only_outputs)\\u001b[0m\\n\\u001b[1;32m 137\\u001b[0m )\\n\\u001b[1;32m 138\\u001b[0m \\u001b[0;32mtry\\u001b[0m\\u001b[0;34m:\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0;32m--> 139\\u001b[0;31m \\u001b[0moutputs\\u001b[0m \\u001b[0;34m=\\u001b[0m \\u001b[0mself\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0m_call\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0minputs\\u001b[0m\\u001b[0;34m)\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0m\\u001b[1;32m 140\\u001b[0m \\u001b[0;32mexcept\\u001b[0m \\u001b[0;34m(\\u001b[0m\\u001b[0mKeyboardInterrupt\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0mException\\u001b[0m\\u001b[0;34m)\\u001b[0m \\u001b[0;32mas\\u001b[0m \\u001b[0me\\u001b[0m\\u001b[0;34m:\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[1;32m 141\\u001b[0m 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88\\u001b[0m \\u001b[0;31m# Call predict on the LLM.\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0;32m---> 89\\u001b[0;31m \\u001b[0;32mreturn\\u001b[0m \\u001b[0mself\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0mllm_chain\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0mpredict\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0;34m**\\u001b[0m\\u001b[0minputs\\u001b[0m\\u001b[0;34m)\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0;34m{\\u001b[0m\\u001b[0;34m}\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0m\\u001b[1;32m 90\\u001b[0m \\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[1;32m 91\\u001b[0m async def acombine_docs(\\n\",\n \"\\u001b[0;32m~/opt/anaconda3/lib/python3.9/site-packages/langchain/chains/llm.py\\u001b[0m in \\u001b[0;36mpredict\\u001b[0;34m(self, **kwargs)\\u001b[0m\\n\\u001b[1;32m 151\\u001b[0m \\u001b[0mcompletion\\u001b[0m \\u001b[0;34m=\\u001b[0m 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timeout)\\u001b[0m\\n\\u001b[1;32m 437\\u001b[0m \\u001b[0;32mraise\\u001b[0m \\u001b[0mCancelledError\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0;34m)\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[1;32m 438\\u001b[0m \\u001b[0;32melif\\u001b[0m \\u001b[0mself\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0m_state\\u001b[0m \\u001b[0;34m==\\u001b[0m \\u001b[0mFINISHED\\u001b[0m\\u001b[0;34m:\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0;32m--> 439\\u001b[0;31m \\u001b[0;32mreturn\\u001b[0m \\u001b[0mself\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0m__get_result\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0;34m)\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0m\\u001b[1;32m 440\\u001b[0m \\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[1;32m 441\\u001b[0m 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\\u001b[0mfn\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0;34m*\\u001b[0m\\u001b[0margs\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0;34m**\\u001b[0m\\u001b[0mkwargs\\u001b[0m\\u001b[0;34m)\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0m\\u001b[1;32m 383\\u001b[0m \\u001b[0;32mexcept\\u001b[0m \\u001b[0mBaseException\\u001b[0m\\u001b[0;34m:\\u001b[0m \\u001b[0;31m# noqa: B902\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[1;32m 384\\u001b[0m \\u001b[0mretry_state\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0mset_exception\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0msys\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0mexc_info\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0;34m)\\u001b[0m\\u001b[0;34m)\\u001b[0m \\u001b[0;31m# type: ignore[arg-type]\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\",\n \"\\u001b[0;32m~/opt/anaconda3/lib/python3.9/site-packages/langchain/llms/openai.py\\u001b[0m in \\u001b[0;36m_completion_with_retry\\u001b[0;34m(**kwargs)\\u001b[0m\\n\\u001b[1;32m 202\\u001b[0m \\u001b[0;34m@\\u001b[0m\\u001b[0mretry_decorator\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[1;32m 203\\u001b[0m \\u001b[0;32mdef\\u001b[0m \\u001b[0m_completion_with_retry\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0;34m**\\u001b[0m\\u001b[0mkwargs\\u001b[0m\\u001b[0;34m:\\u001b[0m \\u001b[0mAny\\u001b[0m\\u001b[0;34m)\\u001b[0m \\u001b[0;34m->\\u001b[0m \\u001b[0mAny\\u001b[0m\\u001b[0;34m:\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0;32m--> 204\\u001b[0;31m \\u001b[0;32mreturn\\u001b[0m \\u001b[0mself\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0mclient\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0mcreate\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0;34m**\\u001b[0m\\u001b[0mkwargs\\u001b[0m\\u001b[0;34m)\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0m\\u001b[1;32m 205\\u001b[0m \\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[1;32m 206\\u001b[0m \\u001b[0;32mreturn\\u001b[0m \\u001b[0m_completion_with_retry\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0;34m**\\u001b[0m\\u001b[0mkwargs\\u001b[0m\\u001b[0;34m)\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\",\n \"\\u001b[0;32m~/opt/anaconda3/lib/python3.9/site-packages/openai/api_resources/completion.py\\u001b[0m in \\u001b[0;36mcreate\\u001b[0;34m(cls, *args, **kwargs)\\u001b[0m\\n\\u001b[1;32m 23\\u001b[0m \\u001b[0;32mwhile\\u001b[0m \\u001b[0;32mTrue\\u001b[0m\\u001b[0;34m:\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[1;32m 24\\u001b[0m \\u001b[0;32mtry\\u001b[0m\\u001b[0;34m:\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0;32m---> 25\\u001b[0;31m \\u001b[0;32mreturn\\u001b[0m \\u001b[0msuper\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0;34m)\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0mcreate\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0;34m*\\u001b[0m\\u001b[0margs\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0;34m**\\u001b[0m\\u001b[0mkwargs\\u001b[0m\\u001b[0;34m)\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0m\\u001b[1;32m 26\\u001b[0m \\u001b[0;32mexcept\\u001b[0m \\u001b[0mTryAgain\\u001b[0m \\u001b[0;32mas\\u001b[0m \\u001b[0me\\u001b[0m\\u001b[0;34m:\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[1;32m 27\\u001b[0m \\u001b[0;32mif\\u001b[0m \\u001b[0mtimeout\\u001b[0m \\u001b[0;32mis\\u001b[0m \\u001b[0;32mnot\\u001b[0m \\u001b[0;32mNone\\u001b[0m \\u001b[0;32mand\\u001b[0m \\u001b[0mtime\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0mtime\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0;34m)\\u001b[0m \\u001b[0;34m>\\u001b[0m \\u001b[0mstart\\u001b[0m \\u001b[0;34m+\\u001b[0m \\u001b[0mtimeout\\u001b[0m\\u001b[0;34m:\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\",\n \"\\u001b[0;32m~/opt/anaconda3/lib/python3.9/site-packages/openai/api_resources/abstract/engine_api_resource.py\\u001b[0m in \\u001b[0;36mcreate\\u001b[0;34m(cls, api_key, api_base, api_type, request_id, api_version, organization, **params)\\u001b[0m\\n\\u001b[1;32m 151\\u001b[0m )\\n\\u001b[1;32m 152\\u001b[0m \\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0;32m--> 153\\u001b[0;31m response, _, api_key = requestor.request(\\n\\u001b[0m\\u001b[1;32m 154\\u001b[0m \\u001b[0;34m\\\"post\\\"\\u001b[0m\\u001b[0;34m,\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[1;32m 155\\u001b[0m \\u001b[0murl\\u001b[0m\\u001b[0;34m,\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\",\n \"\\u001b[0;32m~/opt/anaconda3/lib/python3.9/site-packages/openai/api_requestor.py\\u001b[0m in \\u001b[0;36mrequest\\u001b[0;34m(self, method, url, params, headers, files, stream, request_id, request_timeout)\\u001b[0m\\n\\u001b[1;32m 225\\u001b[0m \\u001b[0mrequest_timeout\\u001b[0m\\u001b[0;34m=\\u001b[0m\\u001b[0mrequest_timeout\\u001b[0m\\u001b[0;34m,\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[1;32m 226\\u001b[0m )\\n\\u001b[0;32m--> 227\\u001b[0;31m \\u001b[0mresp\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0mgot_stream\\u001b[0m \\u001b[0;34m=\\u001b[0m \\u001b[0mself\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0m_interpret_response\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0mresult\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0mstream\\u001b[0m\\u001b[0;34m)\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0m\\u001b[1;32m 228\\u001b[0m \\u001b[0;32mreturn\\u001b[0m \\u001b[0mresp\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0mgot_stream\\u001b[0m\\u001b[0;34m,\\u001b[0m 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\\u001b[0mresult\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0mstatus_code\\u001b[0m\\u001b[0;34m,\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\",\n \"\\u001b[0;32m~/opt/anaconda3/lib/python3.9/site-packages/openai/api_requestor.py\\u001b[0m in \\u001b[0;36m_interpret_response_line\\u001b[0;34m(self, rbody, rcode, rheaders, stream)\\u001b[0m\\n\\u001b[1;32m 678\\u001b[0m \\u001b[0mstream_error\\u001b[0m \\u001b[0;34m=\\u001b[0m \\u001b[0mstream\\u001b[0m \\u001b[0;32mand\\u001b[0m \\u001b[0;34m\\\"error\\\"\\u001b[0m \\u001b[0;32min\\u001b[0m \\u001b[0mresp\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0mdata\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[1;32m 679\\u001b[0m \\u001b[0;32mif\\u001b[0m \\u001b[0mstream_error\\u001b[0m \\u001b[0;32mor\\u001b[0m \\u001b[0;32mnot\\u001b[0m \\u001b[0;36m200\\u001b[0m \\u001b[0;34m<=\\u001b[0m \\u001b[0mrcode\\u001b[0m \\u001b[0;34m<\\u001b[0m \\u001b[0;36m300\\u001b[0m\\u001b[0;34m:\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0;32m--> 680\\u001b[0;31m raise self.handle_error_response(\\n\\u001b[0m\\u001b[1;32m 681\\u001b[0m \\u001b[0mrbody\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0mrcode\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0mresp\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0mdata\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0mrheaders\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0mstream_error\\u001b[0m\\u001b[0;34m=\\u001b[0m\\u001b[0mstream_error\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[1;32m 682\\u001b[0m )\\n\",\n \"\\u001b[0;31mInvalidRequestError\\u001b[0m: This model's maximum context length is 4097 tokens, however you requested 14199 tokens (13943 in your prompt; 256 for the completion). Please reduce your prompt; or completion length.\"\n ]\n }\n ],\n \"source\": [\n \"chain = load_summarize_chain(llm, chain_type=\\\"stuff\\\", verbose=False)\\n\",\n \"chain.run(result)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"92a9de4b\",\n \"metadata\": {},\n \"source\": [\n \"Problem, your transcript/document is too long\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 13,\n \"id\": \"6d071a07\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain.text_splitter import RecursiveCharacterTextSplitter\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 26,\n \"id\": \"36968fb9\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"text_splitter = RecursiveCharacterTextSplitter(chunk_size=2000, chunk_overlap=0)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 27,\n \"id\": \"cb6beb06\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"texts = text_splitter.split_documents(result)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 31,\n \"id\": \"b7889046\",\n \"metadata\": {\n \"collapsed\": true\n },\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"\\n\",\n \"\\n\",\n \"\\u001b[1m> Entering new MapReduceDocumentsChain chain...\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3mWrite a concise summary of the following:\\n\",\n \"\\n\",\n \"\\n\",\n \"\\\"somehow five years later covet hits and you know what they decide to do they're like you know what let's go all in on creating like safety safety stuff for covert like masks respirators um gloves things like that and they become one of the like core providers right at the start of covet they shifted all their production manufacturing stuff they're like forget the vodka bottles forget the LED screens we need n95 masks and we need respirators and we need you know these testing kits and we need and they started producing this stuff and they started just winning all these contracts [Music] we're live Sean uh we have a bunch of stuff you you have a you have a a full menu over here and so do I yeah all right I want you to look at my menu here and I want you to just pick something off the menu go ahead and I'll Riff Off it we don't prefer people who they don't they don't know we only write like one or two words so you get like a teaser you're like man what the hell is this about but you don't know what it actually is but I have I put all my stuff in here an accident I have this new researcher who's crushing it he just gives me all the content like five minutes ahead of time but uh Rich neighbor how did I know you'd pick a rich neighbor so there's somebody in my neighborhood who I bumped into and I've just I'm you know I sort of get out there and I collect signals is this you know where where do I place this person on the uh the Billy scale like are they you know are they on their way up are they are they have they made it in life are they really balling out of control where where is this person these people have been balling out of control like when Christmas time came up there was just like the wife went outside and it was just pointing at windows and all of a sudden the house was lit up like a Christmas tree they had like so they had almost like decked out things and they go hey hey um invite your kids over uh this Thursday we have a snow machine they're we're building a Snow Hill in our driveway like uh you you want to do sledding without going to Tahoe what's that like a big snow cone is that what that no it's like a giant truck that comes that creates snow and it piles it up so that your like their house looked like it was in you know Michigan or something like that yeah but it's just like like it's like an ice machine or something yeah it's like yeah something like that yeah like a big snow cone like a big shaved ice thing yeah yeah you were right from the\\\"\\n\",\n \"\\n\",\n \"\\n\",\n \"CONCISE SUMMARY:\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3mWrite a concise summary of the following:\\n\",\n \"\\n\",\n \"\\n\",\n \"\\\"from the beginning you're right so they did this and they had a fake Santa there and I was like man this is a lot for a Thursday afternoon but okay uh this is cool like these people's style they seem really nice and I didn't know what they did so I kind of I hit it with the Google the other day and I was like let's see who these people are and they have a crazy story so they created a company that back in 2014 did this thing it basically it lets you take a vodka bottle they had a vodka bottle that had an LED sign going around it so you could give somebody a vodka bottle that would say happy birthday Sam or like you could program any message I could be like you know uh whatever I could be like you're getting an old [ __ ] whatever I could write any message on it it would go on your your vodka bottle all right seems kind of gimmicky I don't really you know not a bad idea but but balling out of control from that didn't didn't 100 make sense but that was it sounds like a Drop Shipping like joke sounds like my first idea out of college it's like this is like me in college would have been like bro next next Google I got it what if we took you know this Jager bomb and we put an LED screen on it wouldn't that be incredible and so so they had this thing and they were like licensing this out or something like that somehow like Shaq became an advisor to their company it was really crazy it makes sense yeah as you would five years later covet hits and you know what they decide to do they're like you know what [ __ ] this vodka thing let's go all in on creating like safety safety stuff for cover like masks respirators um gloves things like that and they become one of the like core providers right at the start of covert they shifted all their production manufacturing stuff they're like forget the vodka bottles forget the LED screens we need n95 masks and we need respirators and we need you know these testing kits and we need and they started producing this stuff and they started just winning all these contracts and so now like if you go look at their website it's one of those I know your Rich websites because there's like not a lot of information on it but if you go to like the P they have like a press release section and it's like PR Newswire company gets 113 million dollar contract with the government for safety equipment oh my God local East Bay success story where they uh they're now the the sole testing provider for you know with the Lakers Stadium\\\"\\n\",\n \"\\n\",\n \"\\n\",\n \"CONCISE SUMMARY:\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3mWrite a concise summary of the following:\\n\",\n \"\\n\",\n \"\\n\",\n \"\\\"Levi's Stadium like all these different places and so these guys are getting 100 million dollar plus contracts for their stuff now I think probably it's like you know probably only like 10 margin when you buy you think it's that selling masks I think for things like that probably it's like 10 15 is my guess maybe maybe during coven everyone was completely price insensitive and they could just charge whatever they wanted I'm not sure I would have thought that but um but wow dude what a what a pivot and uh you know that isn't that just kind of crazy and that was an opportunity kind of available to a lot of people right dude I know a bunch of people who did that and like I had a friend that did it and he's like dude check this out and he sends me a picture of a Shopify store and it's doing like 2 million a month I know a lot of people who did that and I've only followed up with one or two of them and uh I have a feeling that like of the eight people I know who did it like three of them it worked out and then the rest it was like a really quick cash grab but then they over bought inventory and it and it's like nothing do you know people who did that yes we there was a guy in um I had started this Mastermind group that's actually where I found Ben uh but like one of the other guys in The Mastermind group he like every time we came to the testimony does he live in Texas no he's in Canada every time he came to the Mastermind group I feel like he had a different business which is like not what you want in a mastermind group but he was a good dude and he would always be like oh I have this other business that's like oh you know for auto repair blah blah we do their SEO and I was like okay but then what about that thing you told me last time and then one time you came dude we're doing mobile covet testing trucks that will drive up to places and we can just do rapid testing for covet and we were like all right I mean that sounds cool but like are you like do you know anything about covet testing like does anybody in the world know about this like what he's like oh I got the scientist that's going to be great and then he came back and he was like hey um really excited to be here I need you guys help um like three months later he was like I really need you guys help about going public and I was like and he's like yeah we're gonna do like 85 million this year in revenue and I was like what and he's like yeah we're getting all these contracts with the state of uh with like the you\\\"\\n\",\n \"\\n\",\n \"\\n\",\n \"CONCISE SUMMARY:\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3mWrite a concise summary of the following:\\n\",\n \"\\n\",\n \"\\n\",\n \"\\\"know the [ __ ] in Canada like these country Country-Wide contracts and um you know yeah we think maybe we should take this public next year and I was like oh my God so how did it end I I don't even know because I that that guy my head was just spinning every time uh you know he would talk because I'm like this is either too good to be true or I'm too dumb and this is amazing and I can't tell which one it is it's probably some mix of both but you're right I know several people that went all in on covid right when it happened and like low-key got like an absurd amount of traction very very fast yeah like a ton my dad had actually called me one day and he goes my friend works at this hospital they need extra equipment they need extra masks I talked to somebody in India and they could produce these masks and like I think we could do like a two or three million dollar contract and I was like fantastic um should do it and he's like yeah I wanna but my dad has this problem where my dad is addicted to meetings like he thinks winning is like this important person met with me and then he'll tell me the duration of the meeting to show me the value he's like only scheduled for one hour but we sat there for 90 minutes and I'd be like okay so what like everybody so you know he was really interested two hours right and he was just like he just like always just obsessed with that so he was he just had a bunch of meetings and I was like Dad you're gonna it's all about that action boss you're gonna take some action here what what's gonna happen like go go for it do it and he's like well no I want he's like I want everybody to like sign off on it and de-risk it completely pay me up front and I was just like dude this is this is like the cheap way to do business like you got to take a little risk here you're throwing shade on your dad right now I hope he doesn't listen to this and you called him boss if I said Cosby boss he's getting in the headlock yeah my dad yeah we make fun of each other like we call it like it is I do a bunch of dumb things and I say when I do dumb things this is his dumb thing he is high planning low action on these things and he says it all the time like um we went I went I took him to Tony Robbins and Tony Robbins is all about like taking massive action on like the things you want and he's like I was like what's your big takeaway he's like oh man I need to take Massive Action and I was like that yeah that's that you did it you learned the right lesson from this thing he\\\"\\n\",\n \"\\n\",\n \"\\n\",\n \"CONCISE SUMMARY:\\u001b[0m\\n\"\n ]\n },\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"\\n\",\n \"\\n\",\n \"\\u001b[1m> Entering new LLMChain chain...\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3mWrite a concise summary of the following:\\n\",\n \"\\n\",\n \"\\n\",\n \"\\\"\\n\",\n \"\\n\",\n \"Covet shifted their production from vodka bottles and LED screens to safety equipment such as masks, respirators, and gloves when the pandemic hit. They won contracts and became one of the core providers. They also created a snow machine to create a snow hill in their driveway for sledding without going to Tahoe.\\n\",\n \"\\n\",\n \" A company created in 2014 developed a vodka bottle with an LED sign that could be programmed with any message. When the COVID-19 pandemic hit, they shifted their production to safety equipment such as masks, respirators, gloves, and testing kits. They have since become a successful provider of safety equipment, winning contracts with the government and becoming the sole testing provider for the Lakers Stadium.\\n\",\n \"\\n\",\n \"\\n\",\n \"Levi's Stadium and other places are offering contracts worth over $100 million for products such as masks. During the COVID-19 pandemic, people were able to take advantage of this opportunity and make a lot of money. A friend of the speaker had a Shopify store that was making $2 million a month. Another person in the speaker's Mastermind group had a business doing mobile COVID testing trucks, and eventually went public with 85 million in revenue.\\n\",\n \"\\n\",\n \" A person's father was interested in a two or three million dollar contract, but was hesitant to take action due to wanting to de-risk it completely and get everyone to sign off on it. The person encouraged their father to take a risk and take action, and they both joked about it. The father attended a Tony Robbins event and learned the lesson to take massive action on the things he wants.\\\"\\n\",\n \"\\n\",\n \"\\n\",\n \"CONCISE SUMMARY:\\u001b[0m\\n\",\n \"\\n\",\n \"\\u001b[1m> Finished chain.\\u001b[0m\\n\",\n \"\\n\",\n \"\\u001b[1m> Finished chain.\\u001b[0m\\n\"\n ]\n },\n {\n \"data\": {\n \"text/plain\": [\n \"'\\\\n\\\\nCovet shifted their production from vodka bottles and LED screens to safety equipment such as masks, respirators, and gloves when the pandemic hit, winning contracts and becoming one of the core providers. They also created a snow machine to create a snow hill in their driveway for sledding. During the pandemic, people were able to take advantage of the opportunity to make a lot of money, with one friend making $2 million a month and another going public with 85 million in revenue. The speaker encouraged their father to take a risk and take action, which he learned from a Tony Robbins event.'\"\n ]\n },\n \"execution_count\": 31,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"chain = load_summarize_chain(llm, chain_type=\\\"map_reduce\\\", verbose=True)\\n\",\n \"chain.run(texts[:4])\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"7d5cf285\",\n \"metadata\": {},\n \"source\": [\n \"### 3. Multiple Videos\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 32,\n \"id\": \"2dad798e\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"youtube_url_list = [\\\"https://www.youtube.com/watch?v=AXq0QHUwmh8\\\", \\\"https://www.youtube.com/watch?v=EwHrjZxAT7g\\\"]\\n\",\n \"\\n\",\n \"texts = []\\n\",\n \"\\n\",\n \"text_splitter = RecursiveCharacterTextSplitter(chunk_size=2000, chunk_overlap=0)\\n\",\n \"\\n\",\n \"for url in youtube_url_list:\\n\",\n \" loader = YoutubeLoader.from_youtube_url(url, add_video_info=True)\\n\",\n \" result = loader.load()\\n\",\n \" \\n\",\n \" texts.extend(text_splitter.split_documents(result))\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 33,\n \"id\": \"862af735\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"' This article discusses the process of building a backyard golf green, including the cost of materials and the steps involved. Bella Ramsey and Pedro Pascal also discuss their experiences on the set of Game of Thrones and The Last of Us, including their first impressions of each other, what they took from set, and what item from the Game of Thrones world they would bring to The Last of Us. Bella talks about her most prized possession, a tear stick, and her best attribute in a survival scenario. Finally, they discuss their first jobs.'\"\n ]\n },\n \"execution_count\": 33,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"chain = load_summarize_chain(llm, chain_type=\\\"map_reduce\\\", verbose=False)\\n\",\n \"chain.run(texts)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"id\": \"9bd0b571\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": []\n }\n ],\n \"metadata\": {\n \"kernelspec\": {\n \"display_name\": \"Python 3 (ipykernel)\",\n \"language\": \"python\",\n \"name\": \"python3\"\n },\n \"language_info\": {\n \"codemirror_mode\": {\n \"name\": \"ipython\",\n \"version\": 3\n },\n \"file_extension\": \".py\",\n \"mimetype\": \"text/x-python\",\n \"name\": \"python\",\n \"nbconvert_exporter\": \"python\",\n \"pygments_lexer\": \"ipython3\",\n \"version\": \"3.9.13\"\n }\n },\n \"nbformat\": 4,\n \"nbformat_minor\": 5\n}\n" }, { "path": "requirements.txt", "content": "aenum==3.1.15\naiohttp==3.9.1\naiosignal==1.3.1\naiostream==0.5.2\nalembic==1.13.1\nalphashape==1.3.1\nannotated-types==0.6.0\nanthropic==0.6.0\nantlr4-python3-runtime==4.9.3\nanyio==3.7.1\nappnope==0.1.3\nargon2-cffi==23.1.0\nargon2-cffi-bindings==21.2.0\narrow==1.3.0\nasteroid-filterbanks==0.4.0\nasttokens==2.4.1\nasync-lru==2.0.4\nasync-timeout==4.0.3\nasyncio==3.4.3\nattrs==23.1.0\naudioread==3.0.1\nBabel==2.13.1\nbackoff==2.2.1\nbcrypt==4.0.1\nbeautifulsoup4==4.12.2\nbleach==6.1.0\nblinker==1.7.0\ncachetools==5.3.2\ncertifi==2023.7.22\ncffi==1.16.0\nchardet==5.2.0\ncharset-normalizer==3.3.1\nchroma-hnswlib==0.7.3\nchromadb==0.4.15\nclick==8.1.7\nclick-log==0.4.0\nclick-plugins==1.1.1\ncligj==0.7.2\ncloudevents==1.10.1\ncolorama==0.4.6\ncoloredlogs==15.0.1\ncolorlog==6.8.0\ncomm==0.1.4\ncontourpy==1.2.0\ncryptography==41.0.7\ncycler==0.12.1\ndataclasses-json==0.6.3\ndatasets==2.15.0\ndebugpy==1.8.0\ndecorator==4.4.2\ndeepgram-sdk==3.1.0\ndefusedxml==0.7.1\nDeprecated==1.2.14\ndeprecation==2.1.0\ndescartes==1.1.0\ndill==0.3.7\ndistro==1.8.0\ndnspython==2.4.2\ndocopt==0.6.2\neffdet==0.4.1\neinops==0.7.0\nemoji==2.8.0\net-xmlfile==1.1.0\nexecuting==2.0.1\nfastapi==0.104.1\nfastjsonschema==2.18.1\nffmpeg-python==0.2.0\nfilelock==3.13.1\nfiletype==1.2.0\nfiona==1.9.5\nFlask==2.3.3\nflatbuffers==23.5.26\nfonttools==4.44.0\nfqdn==1.5.1\nfrozenlist==1.4.0\nfsspec==2023.10.0\nfunctions-framework==3.4.0\nfuture==0.18.3\ngeopandas==0.14.0\ngitdb==4.0.11\nGitPython==3.1.40\ngoogle-api-core==2.12.0\ngoogle-auth==2.23.4\ngoogle-cloud==0.34.0\ngoogle-cloud-core==2.3.3\ngoogle-cloud-storage==2.13.0\ngoogle-crc32c==1.5.0\ngoogle-resumable-media==2.6.0\ngoogleapis-common-protos==1.61.0\ngradientai==1.2.0\ngreenlet==3.0.1\ngrpcio==1.59.2\ngunicorn==20.1.0\nh11==0.14.0\nhttpcore==1.0.2\nhttptools==0.6.1\nhttpx==0.26.0\nhttpx-sse==0.3.1\nhuggingface-hub==0.19.4\nhumanfriendly==10.0\nHyperPyYAML==1.2.2\nidna==3.4\nimageio==2.33.1\nimageio-ffmpeg==0.4.9\nimportlib-metadata==6.8.0\nimportlib-resources==6.1.0\niopath==0.1.10\nipykernel==6.26.0\nipython==8.17.1\nipython-genutils==0.2.0\nipywidgets==8.1.1\nisoduration==20.11.0\nitsdangerous==2.1.2\njedi==0.19.1\nJinja2==3.1.2\njoblib==1.3.2\njson5==0.9.14\njsonlines==4.0.0\njsonpatch==1.33\njsonpath-python==1.0.6\njsonpointer==2.4\njsonschema==4.19.2\njsonschema-specifications==2023.7.1\njulius==0.2.7\njupyter==1.0.0\njupyter-console==6.6.3\njupyter-events==0.8.0\njupyter-lsp==2.2.0\njupyter_client==8.5.0\njupyter_core==5.5.0\njupyter_server==2.9.1\njupyter_server_terminals==0.4.4\njupyterlab==4.0.7\njupyterlab-pygments==0.2.2\njupyterlab-widgets==3.0.9\njupyterlab_server==2.25.0\nkiwisolver==1.4.5\nkubernetes==28.1.0\nlangchain==0.0.352\nlangchain-cli==0.0.9\nlangchain-community==0.0.6\nlangchain-core==0.1.10\nlangchain-experimental==0.0.47\nlangchain-openai==0.0.2.post1\nlangchainhub==0.1.14\nlangdetect==1.0.9\nlangserve==0.0.19\nlangsmith==0.0.73\nlayoutparser==0.3.4\nlazy_loader==0.3\nlibrosa==0.10.1\nlightning==2.1.3\nlightning-utilities==0.10.0\nllama-index==0.9.17\nllvmlite==0.41.1\nloguru==0.7.2\nlxml==4.9.3\nMako==1.3.0\nMarkdown==3.5.1\nmarkdown-it-py==3.0.0\nMarkupSafe==2.1.3\nmarshmallow==3.20.1\nmatplotlib==3.8.2\nmatplotlib-inline==0.1.6\nmdurl==0.1.2\nmetaphor-python==0.1.20\nmistune==3.0.2\nmonotonic==1.6\nmoviepy==1.0.3\nmpmath==1.3.0\nmsg-parser==1.2.0\nmsgpack==1.0.7\nmteb==1.1.1\nmultidict==6.0.4\nmultiprocess==0.70.15\nmypy-extensions==1.0.0\nnbclient==0.9.0\nnbconvert==7.13.0\nnbformat==5.9.2\nneo4j==5.15.0\nnest-asyncio==1.5.8\nnetworkx==3.2.1\nnltk==3.8.1\nnotebook==7.0.6\nnotebook_shim==0.2.3\nnumba==0.58.1\nnumpy==1.26.1\noauthlib==3.2.2\nolefile==0.47\nomegaconf==2.3.0\nonnx==1.15.0\nonnxruntime==1.15.1\nopenai==1.7.2\nopencv-python==4.8.1.78\nopenpyxl==3.1.2\nopentelemetry-api==1.20.0\nopentelemetry-exporter-otlp-proto-common==1.20.0\nopentelemetry-exporter-otlp-proto-grpc==1.20.0\nopentelemetry-proto==1.20.0\nopentelemetry-sdk==1.20.0\nopentelemetry-semantic-conventions==0.41b0\noptuna==3.5.0\nosmnx==1.7.1\noverrides==7.4.0\npackaging==23.2\npandas==2.1.2\npandocfilters==1.5.0\nparso==0.8.3\npdf2image==1.16.3\npdfminer.six==20221105\npdfplumber==0.10.3\npexpect==4.8.0\npikepdf==8.10.1\nPillow==10.1.0\npinecone-client==2.2.4\n# Editable install with no version control (pirate_speak==0.0.1)\n-e /Users/gregorykamradt/Desktop/gk/Projects/LangChain/LangServ/my-app/packages/pirate_speak\nplatformdirs==3.11.0\npooch==1.8.0\nportalocker==2.8.2\nposthog==3.0.2\nprimePy==1.3\nproglog==0.1.10\nprometheus-client==0.18.0\nprompt-toolkit==3.0.39\nprotobuf==4.25.0\npsutil==5.9.6\nptyprocess==0.7.0\npulsar-client==3.3.0\npure-eval==0.2.2\npyannote.audio==3.1.1\npyannote.core==5.0.0\npyannote.database==5.0.1\npyannote.metrics==3.2.1\npyannote.pipeline==3.0.1\npyarrow==14.0.2\npyarrow-hotfix==0.6\npyasn1==0.5.0\npyasn1-modules==0.3.0\npycocotools==2.0.7\npycparser==2.21\npycryptodome==3.19.0\npydantic==1.10.13\npydantic_core==2.10.1\npydub==0.25.1\nPygments==2.16.1\npypandoc==1.12\npyparsing==3.1.1\npypdf==3.17.3\npypdfium2==4.25.0\nPyPika==0.48.9\npyproj==3.6.1\npysbd==0.3.4\npytesseract==0.3.10\npython-dateutil==2.8.2\npython-docx==1.1.0\npython-dotenv==1.0.0\npython-iso639==2023.6.15\npython-json-logger==2.0.7\npython-magic==0.4.27\npython-multipart==0.0.6\npython-pptx==0.6.23\npytorch-lightning==2.1.3\npytorch-metric-learning==2.4.1\npytz==2023.3.post1\nPyYAML==6.0.1\npyzmq==25.1.1\nqtconsole==5.4.4\nQtPy==2.4.1\nragas==0.0.22\nrapidfuzz==3.5.2\nreferencing==0.30.2\nregex==2023.10.3\nrequests==2.31.0\nrequests-oauthlib==1.3.1\nrfc3339-validator==0.1.4\nrfc3986-validator==0.1.1\nrich==13.6.0\nrpds-py==0.10.6\nrsa==4.9\nRtree==1.1.0\nruamel.yaml==0.18.5\nruamel.yaml.clib==0.2.8\nsafetensors==0.4.1\nscikit-learn==1.3.2\nscipy==1.11.3\nseaborn==0.13.0\nsemver==3.0.2\nSend2Trash==1.8.2\nsentence-transformers==2.2.2\nsentencepiece==0.1.99\nshapely==2.0.2\nshellingham==1.5.4\nsix==1.16.0\nsmmap==5.0.1\nsniffio==1.3.0\nsortedcontainers==2.4.0\nsoundfile==0.12.1\nsoupsieve==2.5\nsoxr==0.3.7\nspeechbrain==0.5.16\nSQLAlchemy==2.0.22\nsse-starlette==1.6.5\nstack-data==0.6.3\nstarlette==0.27.0\nsympy==1.12\ntabulate==0.9.0\ntenacity==8.2.3\ntensorboardX==2.6.2.2\nterminado==0.17.1\nthreadpoolctl==3.2.0\ntiktoken==0.5.2\ntimm==0.9.12\ntinycss2==1.2.1\ntokenizers==0.15.0\ntomli==2.0.1\ntorch==2.1.2\ntorch-audiomentations==0.11.0\ntorch-pitch-shift==1.2.4\ntorchaudio==2.1.2\ntorchmetrics==1.3.0.post0\ntorchvision==0.16.2\ntornado==6.3.3\ntqdm==4.66.1\ntraitlets==5.13.0\ntransformers==4.36.2\ntrimesh==4.0.4\ntyper==0.9.0\ntypes-python-dateutil==2.8.19.14\ntypes-requests==2.31.0.10\ntyping-inspect==0.9.0\ntyping_extensions==4.9.0\ntzdata==2023.3\nunstructured==0.11.5\nunstructured-client==0.15.0\nunstructured-inference==0.7.18\nunstructured.pytesseract==0.3.12\nuri-template==1.3.0\nurllib3==2.1.0\nuvicorn==0.23.2\nuvloop==0.19.0\nverboselogs==1.7\nwatchdog==3.0.0\nwatchfiles==0.21.0\nwcwidth==0.2.9\nwebcolors==1.13\nwebencodings==0.5.1\nwebsocket-client==1.6.4\nwebsockets==12.0\nWerkzeug==3.0.1\nwidgetsnbextension==4.0.9\nwikipedia==1.4.0\nwrapt==1.15.0\nxlrd==2.0.1\nXlsxWriter==3.1.9\nxmltodict==0.13.0\nxxhash==3.4.1\nyarl==1.9.2\nzipp==3.17.0\n" }, { "path": "tutorials/Google Drive Loader.ipynb", "content": "{\n \"cells\": [\n {\n \"cell_type\": \"code\",\n \"execution_count\": 3,\n \"id\": \"2804f2bf\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain.document_loaders import GoogleDriveLoader\\n\",\n \"import os\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 4,\n \"id\": \"3f988238\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"loader = GoogleDriveLoader(document_ids=[\\\"1BT5apJMTUvG9_59-ceHbuZXVTJKeyyknQsz9ZNIEwQ8\\\"],\\n\",\n \" credentials_path=\\\"../../desktop_credetnaisl.json\\\")\\n\",\n \"docs = loader.load()\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 2,\n \"id\": \"1cb4ae65\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# %set_env OPENAI_API_KEY = ...\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"6419b536\",\n \"metadata\": {},\n \"source\": [\n \"### Summarizing\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 7,\n \"id\": \"bfa4d948\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain.llms import OpenAI\\n\",\n \"from langchain.chains.summarize import load_summarize_chain\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 8,\n \"id\": \"1c7a6d81\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"llm = OpenAI(temperature=0, openai_api_key=os.environ['OPENAI_API_KEY'])\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 10,\n \"id\": \"d9220c03\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"\\n\",\n \"\\n\",\n \"\\u001b[1m> Entering new MapReduceDocumentsChain chain...\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3mWrite a concise summary of the following:\\n\",\n \"\\n\",\n \"\\n\",\n \"\\\"SecondaryEquityHub\\n\",\n \"2/21/2023\\n\",\n \"\\n\",\n \"\\n\",\n \"Introduction\\n\",\n \"\\n\",\n \"\\n\",\n \"Our product is a marketplace that connects startup employees who want to sell vested equity to buyers of secondary market shares.\\n\",\n \"\\n\",\n \"\\n\",\n \"Startups typically take several years to exit, leaving employees with vested equity tied up for an extended period. Our platform aims to address this issue by providing a marketplace for startup employees to sell their vested equity to buyers of secondary market shares.\\n\",\n \"\\n\",\n \"\\n\",\n \"This helps employees to unlock the value of their vested equity for personal financial goals, such as buying a home or paying down loans. At the same time, it provides buyers with the opportunity to invest in startup equity that has already passed the early-stage risks.\\n\",\n \"\\n\",\n \"\\n\",\n \"Our platform creates a win-win situation for both parties and fosters a more efficient secondary market for startup equity.\\n\",\n \"\\n\",\n \"\\n\",\n \"Problem Statement\\n\",\n \"\\n\",\n \"\\n\",\n \"The traditional path for startups from founding to exit can be a long and arduous journey. Often, it takes several years for a startup to exit, leaving employees with vested equity tied up for an extended period. This can create a significant financial burden for employees who may need to access the value of their equity for personal financial goals, such as buying a home or paying down loans.\\n\",\n \"\\n\",\n \"\\n\",\n \"On the other hand, there is an increasing demand for investment opportunities in the startup ecosystem. Buyers of secondary market shares are looking for investment options that have already passed the early-stage risks.\\n\",\n \"\\n\",\n \"\\n\",\n \"The lack of a viable secondary market for startup equity often results in a significant gap between demand and supply. This problem is significant for startup employees who are looking for liquidity, and buyers of secondary market shares who are looking for investment opportunities.\\n\",\n \"\\n\",\n \"\\n\",\n \"Our product aims to address this problem by providing a marketplace that connects startup employees who want to sell vested equity to buyers of secondary market shares, creating a more efficient and accessible secondary market for startup equity.\\n\",\n \"\\n\",\n \"\\n\",\n \"Product Features\\n\",\n \"1. Marketplace for Vested Equity: Our platform provides a marketplace for startup employees to sell their vested equity to buyers of secondary market shares.\\n\",\n \" 1. Benefit: This feature provides startup employees with liquidity options and helps them unlock the value of their equity for personal financial goals. It also provides buyers with an opportunity to invest in startup equity that has already passed the early-stage risks.\\n\",\n \"2. Secure Transaction: Our platform ensures secure and hassle-free transactions through its escrow service\\n\",\n \" 1. Benefit: This feature ensures a safe and secure transaction process for both buyers and sellers, mitigating the risk of fraud or financial loss.\\n\",\n \"3. Automated Compliance: Our platform automates compliance requirements, including tax withholdings and regulatory filings, ensuring legal compliance for both buyers and sellers\\n\",\n \" 1. Benefit: This feature eliminates the complexity and legal risks associated with selling and buying vested equity. It ensures compliance with legal and regulatory requirements and reduces the transactional costs associated with these compliance procedures.\\n\",\n \"4. Transparent Pricing: Our platform provides transparent pricing, including price history and market trends, ensuring a fair and competitive pricing system\\n\",\n \" 1. Benefit: This feature ensures a transparent and fair pricing system, providing buyers and sellers with a clear understanding of market trends and price history.\\n\",\n \"5. Efficient Matching System: Our platform uses an efficient matching system that matches buyers with sellers based on their investment goals and preferences\\n\",\n \" 1. Benefit: This feature ensures that buyers and sellers are matched efficiently based on their preferences, resulting in a faster and more efficient transaction process. It provides buyers with a wider range of investment options, while also ensuring that sellers can access a larger pool of potential buyers.\\\"\\n\",\n \"\\n\",\n \"\\n\",\n \"CONCISE SUMMARY:\\u001b[0m\\n\",\n \"\\n\",\n \"\\n\",\n \"\\u001b[1m> Entering new LLMChain chain...\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3mWrite a concise summary of the following:\\n\",\n \"\\n\",\n \"\\n\",\n \"\\\" SecondaryEquityHub is a marketplace that connects startup employees who want to sell vested equity to buyers of secondary market shares. It provides a win-win situation for both parties by providing liquidity options for employees and investment opportunities for buyers. The platform also ensures secure transactions, automated compliance, transparent pricing, and an efficient matching system.\\\"\\n\",\n \"\\n\",\n \"\\n\",\n \"CONCISE SUMMARY:\\u001b[0m\\n\",\n \"\\n\",\n \"\\u001b[1m> Finished chain.\\u001b[0m\\n\",\n \"\\n\",\n \"\\u001b[1m> Finished chain.\\u001b[0m\\n\"\n ]\n },\n {\n \"data\": {\n \"text/plain\": [\n \"' SecondaryEquityHub is a marketplace that connects startup employees who want to sell vested equity with buyers of secondary market shares. It provides a secure, compliant, and efficient platform for both parties to benefit from liquidity options and investment opportunities.'\"\n ]\n },\n \"execution_count\": 10,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"chain = load_summarize_chain(llm, chain_type=\\\"map_reduce\\\", verbose=True)\\n\",\n \"chain.run(docs)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"cdaf482f\",\n \"metadata\": {},\n \"source\": [\n \"### Asking Questions\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 11,\n \"id\": \"e123a924\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain.chains.question_answering import load_qa_chain\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 12,\n \"id\": \"fd19d27c\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"query = \\\"What problem is this product solving?\\\"\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 13,\n \"id\": \"dc399ac7\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"' This product is solving the problem of the lack of a viable secondary market for startup equity, which often results in a significant gap between demand and supply. This problem is significant for startup employees who are looking for liquidity, and buyers of secondary market shares who are looking for investment opportunities.'\"\n ]\n },\n \"execution_count\": 13,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"chain = load_qa_chain(llm, chain_type=\\\"stuff\\\")\\n\",\n \"chain.run(input_documents=docs, question=query)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 15,\n \"id\": \"5c295ba5\",\n \"metadata\": {\n \"collapsed\": true\n },\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"\\n\",\n \"\\n\",\n \"\\u001b[1m> Entering new StuffDocumentsChain chain...\\u001b[0m\\n\",\n \"\\n\",\n \"\\n\",\n \"\\u001b[1m> Entering new LLMChain chain...\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3mUse the following pieces of context to answer the question at the end. If you don't know the answer, just say that you don't know, don't try to make up an answer.\\n\",\n \"\\n\",\n \"SecondaryEquityHub\\n\",\n \"2/21/2023\\n\",\n \"\\n\",\n \"\\n\",\n \"Introduction\\n\",\n \"\\n\",\n \"\\n\",\n \"Our product is a marketplace that connects startup employees who want to sell vested equity to buyers of secondary market shares.\\n\",\n \"\\n\",\n \"\\n\",\n \"Startups typically take several years to exit, leaving employees with vested equity tied up for an extended period. Our platform aims to address this issue by providing a marketplace for startup employees to sell their vested equity to buyers of secondary market shares.\\n\",\n \"\\n\",\n \"\\n\",\n \"This helps employees to unlock the value of their vested equity for personal financial goals, such as buying a home or paying down loans. At the same time, it provides buyers with the opportunity to invest in startup equity that has already passed the early-stage risks.\\n\",\n \"\\n\",\n \"\\n\",\n \"Our platform creates a win-win situation for both parties and fosters a more efficient secondary market for startup equity.\\n\",\n \"\\n\",\n \"\\n\",\n \"Problem Statement\\n\",\n \"\\n\",\n \"\\n\",\n \"The traditional path for startups from founding to exit can be a long and arduous journey. Often, it takes several years for a startup to exit, leaving employees with vested equity tied up for an extended period. This can create a significant financial burden for employees who may need to access the value of their equity for personal financial goals, such as buying a home or paying down loans.\\n\",\n \"\\n\",\n \"\\n\",\n \"On the other hand, there is an increasing demand for investment opportunities in the startup ecosystem. Buyers of secondary market shares are looking for investment options that have already passed the early-stage risks.\\n\",\n \"\\n\",\n \"\\n\",\n \"The lack of a viable secondary market for startup equity often results in a significant gap between demand and supply. This problem is significant for startup employees who are looking for liquidity, and buyers of secondary market shares who are looking for investment opportunities.\\n\",\n \"\\n\",\n \"\\n\",\n \"Our product aims to address this problem by providing a marketplace that connects startup employees who want to sell vested equity to buyers of secondary market shares, creating a more efficient and accessible secondary market for startup equity.\\n\",\n \"\\n\",\n \"\\n\",\n \"Product Features\\n\",\n \"1. Marketplace for Vested Equity: Our platform provides a marketplace for startup employees to sell their vested equity to buyers of secondary market shares.\\n\",\n \" 1. Benefit: This feature provides startup employees with liquidity options and helps them unlock the value of their equity for personal financial goals. It also provides buyers with an opportunity to invest in startup equity that has already passed the early-stage risks.\\n\",\n \"2. Secure Transaction: Our platform ensures secure and hassle-free transactions through its escrow service\\n\",\n \" 1. Benefit: This feature ensures a safe and secure transaction process for both buyers and sellers, mitigating the risk of fraud or financial loss.\\n\",\n \"3. Automated Compliance: Our platform automates compliance requirements, including tax withholdings and regulatory filings, ensuring legal compliance for both buyers and sellers\\n\",\n \" 1. Benefit: This feature eliminates the complexity and legal risks associated with selling and buying vested equity. It ensures compliance with legal and regulatory requirements and reduces the transactional costs associated with these compliance procedures.\\n\",\n \"4. Transparent Pricing: Our platform provides transparent pricing, including price history and market trends, ensuring a fair and competitive pricing system\\n\",\n \" 1. Benefit: This feature ensures a transparent and fair pricing system, providing buyers and sellers with a clear understanding of market trends and price history.\\n\",\n \"5. Efficient Matching System: Our platform uses an efficient matching system that matches buyers with sellers based on their investment goals and preferences\\n\",\n \" 1. Benefit: This feature ensures that buyers and sellers are matched efficiently based on their preferences, resulting in a faster and more efficient transaction process. It provides buyers with a wider range of investment options, while also ensuring that sellers can access a larger pool of potential buyers.\\n\",\n \"\\n\",\n \"Question: How should we reach our target audience of this product?\\n\",\n \"Helpful Answer:\\u001b[0m\\n\",\n \"\\n\",\n \"\\u001b[1m> Finished chain.\\u001b[0m\\n\",\n \"\\n\",\n \"\\u001b[1m> Finished chain.\\u001b[0m\\n\"\n ]\n },\n {\n \"data\": {\n \"text/plain\": [\n \"' We should reach our target audience by leveraging digital marketing channels such as social media, search engine optimization, and content marketing. We should also consider using traditional marketing channels such as print, radio, and television advertising. Additionally, we should consider partnering with influencers and industry experts to help spread the word about our product.'\"\n ]\n },\n \"execution_count\": 15,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"query = \\\"How should we reach our target audience of this product?\\\"\\n\",\n \"\\n\",\n \"chain = load_qa_chain(llm, chain_type=\\\"stuff\\\", verbose=True)\\n\",\n \"chain.run(input_documents=docs, question=query)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"6dc5afa3\",\n \"metadata\": {},\n \"source\": [\n \"## And there's more: Add documents to your list\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 16,\n \"id\": \"2d921ee7\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"loader = GoogleDriveLoader(document_ids=[\\\"1ETW9siA8EBkdms7R1UTw1ysXag2U6gb9wMzRpSxjqY8\\\"],\\n\",\n \" credentials_path=\\\"../../desktop_credetnaisl.json\\\")\\n\",\n \"new_doc = loader.load()\\n\",\n \"\\n\",\n \"docs.extend(new_doc)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 19,\n \"id\": \"1fe49414\",\n \"metadata\": {\n \"collapsed\": true\n },\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"\\n\",\n \"\\n\",\n \"\\u001b[1m> Entering new StuffDocumentsChain chain...\\u001b[0m\\n\",\n \"\\n\",\n \"\\n\",\n \"\\u001b[1m> Entering new LLMChain chain...\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3mUse the following pieces of context to answer the question at the end. If you don't know the answer, just say that you don't know, don't try to make up an answer.\\n\",\n \"\\n\",\n \"SecondaryEquityHub\\n\",\n \"2/21/2023\\n\",\n \"\\n\",\n \"\\n\",\n \"Introduction\\n\",\n \"\\n\",\n \"\\n\",\n \"Our product is a marketplace that connects startup employees who want to sell vested equity to buyers of secondary market shares.\\n\",\n \"\\n\",\n \"\\n\",\n \"Startups typically take several years to exit, leaving employees with vested equity tied up for an extended period. Our platform aims to address this issue by providing a marketplace for startup employees to sell their vested equity to buyers of secondary market shares.\\n\",\n \"\\n\",\n \"\\n\",\n \"This helps employees to unlock the value of their vested equity for personal financial goals, such as buying a home or paying down loans. At the same time, it provides buyers with the opportunity to invest in startup equity that has already passed the early-stage risks.\\n\",\n \"\\n\",\n \"\\n\",\n \"Our platform creates a win-win situation for both parties and fosters a more efficient secondary market for startup equity.\\n\",\n \"\\n\",\n \"\\n\",\n \"Problem Statement\\n\",\n \"\\n\",\n \"\\n\",\n \"The traditional path for startups from founding to exit can be a long and arduous journey. Often, it takes several years for a startup to exit, leaving employees with vested equity tied up for an extended period. This can create a significant financial burden for employees who may need to access the value of their equity for personal financial goals, such as buying a home or paying down loans.\\n\",\n \"\\n\",\n \"\\n\",\n \"On the other hand, there is an increasing demand for investment opportunities in the startup ecosystem. Buyers of secondary market shares are looking for investment options that have already passed the early-stage risks.\\n\",\n \"\\n\",\n \"\\n\",\n \"The lack of a viable secondary market for startup equity often results in a significant gap between demand and supply. This problem is significant for startup employees who are looking for liquidity, and buyers of secondary market shares who are looking for investment opportunities.\\n\",\n \"\\n\",\n \"\\n\",\n \"Our product aims to address this problem by providing a marketplace that connects startup employees who want to sell vested equity to buyers of secondary market shares, creating a more efficient and accessible secondary market for startup equity.\\n\",\n \"\\n\",\n \"\\n\",\n \"Product Features\\n\",\n \"1. Marketplace for Vested Equity: Our platform provides a marketplace for startup employees to sell their vested equity to buyers of secondary market shares.\\n\",\n \" 1. Benefit: This feature provides startup employees with liquidity options and helps them unlock the value of their equity for personal financial goals. It also provides buyers with an opportunity to invest in startup equity that has already passed the early-stage risks.\\n\",\n \"2. Secure Transaction: Our platform ensures secure and hassle-free transactions through its escrow service\\n\",\n \" 1. Benefit: This feature ensures a safe and secure transaction process for both buyers and sellers, mitigating the risk of fraud or financial loss.\\n\",\n \"3. Automated Compliance: Our platform automates compliance requirements, including tax withholdings and regulatory filings, ensuring legal compliance for both buyers and sellers\\n\",\n \" 1. Benefit: This feature eliminates the complexity and legal risks associated with selling and buying vested equity. It ensures compliance with legal and regulatory requirements and reduces the transactional costs associated with these compliance procedures.\\n\",\n \"4. Transparent Pricing: Our platform provides transparent pricing, including price history and market trends, ensuring a fair and competitive pricing system\\n\",\n \" 1. Benefit: This feature ensures a transparent and fair pricing system, providing buyers and sellers with a clear understanding of market trends and price history.\\n\",\n \"5. Efficient Matching System: Our platform uses an efficient matching system that matches buyers with sellers based on their investment goals and preferences\\n\",\n \" 1. Benefit: This feature ensures that buyers and sellers are matched efficiently based on their preferences, resulting in a faster and more efficient transaction process. It provides buyers with a wider range of investment options, while also ensuring that sellers can access a larger pool of potential buyers.\\n\",\n \"\\n\",\n \"SecondaryEquityHub - User Interviews\\n\",\n \"2/21/2023\\n\",\n \"\\n\",\n \"\\n\",\n \"Interview #1 - Sally\\n\",\n \"\\n\",\n \"\\n\",\n \"Eliza: Hi Sally, thanks for coming in today. Can you tell me a bit about your experience in the startup world?\\n\",\n \"\\n\",\n \"\\n\",\n \"Sally: Hi Eliza, thanks for having me. Sure, I've been working in the startup world for about 5 years now. I've worked for a few different startups in various roles, from marketing to product management.\\n\",\n \"\\n\",\n \"\\n\",\n \"Eliza: Great, well our product is a marketplace that connects startup employees who want to sell vested equity to buyers of secondary market shares. What do you think of this idea?\\n\",\n \"Sally: I think it's a really interesting concept. It's not uncommon for startup employees to have vested equity tied up for several years, and having a marketplace to sell that equity could be really helpful for those who want to unlock its value.\\n\",\n \"\\n\",\n \"\\n\",\n \"Eliza: Yes, exactly. The platform aims to help employees achieve personal financial goals, such as buying a home or paying down loans, while also providing buyers with the opportunity to invest in startup equity that has already passed the early-stage risks. How do you think we can ensure that the buyers are getting a fair deal?\\n\",\n \"\\n\",\n \"\\n\",\n \"Sally: That's a good question. I think it would be important to have some kind of vetting process for the sellers and the shares they're selling. We would need to make sure that the shares are legitimate and that the sellers have the right to sell them. It would also be important to have some kind of transparency around the pricing, so that buyers can make informed decisions.\\n\",\n \"\\n\",\n \"\\n\",\n \"Eliza: Yes, those are all great points. We've been working on developing a secure platform that includes a vetting process for the sellers and the shares they're selling, and we're also planning to provide transparent pricing information. Thank you for your input, Sally. It was great to chat with you today.\\n\",\n \"\\n\",\n \"Question: What are users saying about our product?\\n\",\n \"Helpful Answer:\\u001b[0m\\n\",\n \"\\n\",\n \"\\u001b[1m> Finished chain.\\u001b[0m\\n\",\n \"\\n\",\n \"\\u001b[1m> Finished chain.\\u001b[0m\\n\"\n ]\n },\n {\n \"data\": {\n \"text/plain\": [\n \"\\\" Users are saying that the product is a good idea and that it could be helpful for startup employees who want to unlock the value of their vested equity for personal financial goals. They are also suggesting that there should be a vetting process for the sellers and the shares they're selling, as well as transparent pricing information, to ensure that buyers are getting a fair deal.\\\"\"\n ]\n },\n \"execution_count\": 19,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"query = \\\"What are users saying about our product?\\\"\\n\",\n \"\\n\",\n \"chain = load_qa_chain(llm, chain_type=\\\"stuff\\\", verbose=True)\\n\",\n \"chain.run(input_documents=docs, question=query)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"38901b7f\",\n \"metadata\": {},\n \"source\": [\n \"### Remove Documents\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 20,\n \"id\": \"7a0eb0f4\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"list\"\n ]\n },\n \"execution_count\": 20,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"type(docs)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 21,\n \"id\": \"7151f84a\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"Document(page_content=\\\"\\\\ufeffSecondaryEquityHub - User Interviews\\\\r\\\\n2/21/2023\\\\r\\\\n\\\\r\\\\n\\\\r\\\\nInterview #1 - Sally\\\\r\\\\n\\\\r\\\\n\\\\r\\\\nEliza: Hi Sally, thanks for coming in today. Can you tell me a bit about your experience in the startup world?\\\\r\\\\n\\\\r\\\\n\\\\r\\\\nSally: Hi Eliza, thanks for having me. Sure, I've been working in the startup world for about 5 years now. I've worked for a few different startups in various roles, from marketing to product management.\\\\r\\\\n\\\\r\\\\n\\\\r\\\\nEliza: Great, well our product is a marketplace that connects startup employees who want to sell vested equity to buyers of secondary market shares. What do you think of this idea?\\\\r\\\\nSally: I think it's a really interesting concept. It's not uncommon for startup employees to have vested equity tied up for several years, and having a marketplace to sell that equity could be really helpful for those who want to unlock its value.\\\\r\\\\n\\\\r\\\\n\\\\r\\\\nEliza: Yes, exactly. The platform aims to help employees achieve personal financial goals, such as buying a home or paying down loans, while also providing buyers with the opportunity to invest in startup equity that has already passed the early-stage risks. How do you think we can ensure that the buyers are getting a fair deal?\\\\r\\\\n\\\\r\\\\n\\\\r\\\\nSally: That's a good question. I think it would be important to have some kind of vetting process for the sellers and the shares they're selling. We would need to make sure that the shares are legitimate and that the sellers have the right to sell them. It would also be important to have some kind of transparency around the pricing, so that buyers can make informed decisions.\\\\r\\\\n\\\\r\\\\n\\\\r\\\\nEliza: Yes, those are all great points. We've been working on developing a secure platform that includes a vetting process for the sellers and the shares they're selling, and we're also planning to provide transparent pricing information. Thank you for your input, Sally. It was great to chat with you today.\\\", lookup_str='', metadata={'source': 'https://docs.google.com/document/d/1ETW9siA8EBkdms7R1UTw1ysXag2U6gb9wMzRpSxjqY8/edit'}, lookup_index=0)\"\n ]\n },\n \"execution_count\": 21,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"docs.pop()\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"id\": \"e8a0b907\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": []\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 22,\n \"id\": \"c2bd62dc\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"{'page_content': '\\\\ufeffSecondaryEquityHub\\\\r\\\\n2/21/2023\\\\r\\\\n\\\\r\\\\n\\\\r\\\\nIntroduction\\\\r\\\\n\\\\r\\\\n\\\\r\\\\nOur product is a marketplace that connects startup employees who want to sell vested equity to buyers of secondary market shares.\\\\r\\\\n\\\\r\\\\n\\\\r\\\\nStartups typically take several years to exit, leaving employees with vested equity tied up for an extended period. Our platform aims to address this issue by providing a marketplace for startup employees to sell their vested equity to buyers of secondary market shares.\\\\r\\\\n\\\\r\\\\n\\\\r\\\\nThis helps employees to unlock the value of their vested equity for personal financial goals, such as buying a home or paying down loans. At the same time, it provides buyers with the opportunity to invest in startup equity that has already passed the early-stage risks.\\\\r\\\\n\\\\r\\\\n\\\\r\\\\nOur platform creates a win-win situation for both parties and fosters a more efficient secondary market for startup equity.\\\\r\\\\n\\\\r\\\\n\\\\r\\\\nProblem Statement\\\\r\\\\n\\\\r\\\\n\\\\r\\\\nThe traditional path for startups from founding to exit can be a long and arduous journey. Often, it takes several years for a startup to exit, leaving employees with vested equity tied up for an extended period. This can create a significant financial burden for employees who may need to access the value of their equity for personal financial goals, such as buying a home or paying down loans.\\\\r\\\\n\\\\r\\\\n\\\\r\\\\nOn the other hand, there is an increasing demand for investment opportunities in the startup ecosystem. Buyers of secondary market shares are looking for investment options that have already passed the early-stage risks.\\\\r\\\\n\\\\r\\\\n\\\\r\\\\nThe lack of a viable secondary market for startup equity often results in a significant gap between demand and supply. This problem is significant for startup employees who are looking for liquidity, and buyers of secondary market shares who are looking for investment opportunities.\\\\r\\\\n\\\\r\\\\n\\\\r\\\\nOur product aims to address this problem by providing a marketplace that connects startup employees who want to sell vested equity to buyers of secondary market shares, creating a more efficient and accessible secondary market for startup equity.\\\\r\\\\n\\\\r\\\\n\\\\r\\\\nProduct Features\\\\r\\\\n1. Marketplace for Vested Equity: Our platform provides a marketplace for startup employees to sell their vested equity to buyers of secondary market shares.\\\\r\\\\n 1. Benefit: This feature provides startup employees with liquidity options and helps them unlock the value of their equity for personal financial goals. It also provides buyers with an opportunity to invest in startup equity that has already passed the early-stage risks.\\\\r\\\\n2. Secure Transaction: Our platform ensures secure and hassle-free transactions through its escrow service\\\\r\\\\n 1. Benefit: This feature ensures a safe and secure transaction process for both buyers and sellers, mitigating the risk of fraud or financial loss.\\\\r\\\\n3. Automated Compliance: Our platform automates compliance requirements, including tax withholdings and regulatory filings, ensuring legal compliance for both buyers and sellers\\\\r\\\\n 1. Benefit: This feature eliminates the complexity and legal risks associated with selling and buying vested equity. It ensures compliance with legal and regulatory requirements and reduces the transactional costs associated with these compliance procedures.\\\\r\\\\n4. Transparent Pricing: Our platform provides transparent pricing, including price history and market trends, ensuring a fair and competitive pricing system\\\\r\\\\n 1. Benefit: This feature ensures a transparent and fair pricing system, providing buyers and sellers with a clear understanding of market trends and price history.\\\\r\\\\n5. Efficient Matching System: Our platform uses an efficient matching system that matches buyers with sellers based on their investment goals and preferences\\\\r\\\\n 1. Benefit: This feature ensures that buyers and sellers are matched efficiently based on their preferences, resulting in a faster and more efficient transaction process. It provides buyers with a wider range of investment options, while also ensuring that sellers can access a larger pool of potential buyers.',\\n\",\n \" 'lookup_str': '',\\n\",\n \" 'metadata': {'source': 'https://docs.google.com/document/d/1BT5apJMTUvG9_59-ceHbuZXVTJKeyyknQsz9ZNIEwQ8/edit'},\\n\",\n \" 'lookup_index': 0}\"\n ]\n },\n \"execution_count\": 22,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"docs[0].dict()\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"id\": \"9a66c436\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": []\n }\n ],\n \"metadata\": {\n \"kernelspec\": {\n \"display_name\": \"Python 3 (ipykernel)\",\n \"language\": \"python\",\n \"name\": \"python3\"\n },\n \"language_info\": {\n \"codemirror_mode\": {\n \"name\": \"ipython\",\n \"version\": 3\n },\n \"file_extension\": \".py\",\n \"mimetype\": \"text/x-python\",\n \"name\": \"python\",\n \"nbconvert_exporter\": \"python\",\n \"pygments_lexer\": \"ipython3\",\n \"version\": \"3.9.13\"\n }\n },\n \"nbformat\": 4,\n \"nbformat_minor\": 5\n}\n" }, { "path": "tutorials/Twitter_Reply_Bot/Twitter Reply Bot Notebook.ipynb", "content": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"id\": \"6d336eed\",\n \"metadata\": {},\n \"source\": [\n \"# Twitter Reply Bot\\n\",\n \"\\n\",\n \"Ever see those Twitter bots that reply to comments automatically? Like this [one](https://twitter.com/explainthisbob/status/1661833808092471299?s=12) or [this one](https://twitter.com/replygpt/status/1661924851626696705?s=12)\\n\",\n \"\\n\",\n \"Let's create one ourselves. In this notebook we'll just look at the prompting technique I used. In the [full code](https://github.com/gkamradt/twitter-reply-bot) you'll see the other helper code to deploy this app.\\n\",\n \"\\n\",\n \"Here's how the final app will work\\n\",\n \"\\n\",\n \"1. A user @mentions your bot, for me it will be @SiliconOracle\\n\",\n \"2. The script finds that new @mention and then reads the parent tweet it is being mentioned on\\n\",\n \"3. The script takes that parent tweet and generates a witty response using a language model\\n\",\n \"4. Respond is posted and tweet is logged\\n\",\n \"\\n\",\n \"This notebook will focus on #3.\\n\",\n \"\\n\",\n \"First let's import our packages\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 1,\n \"id\": \"c8ce8e2e\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain.chat_models import ChatOpenAI\\n\",\n \"from langchain.prompts import ChatPromptTemplate, PromptTemplate, SystemMessagePromptTemplate, AIMessagePromptTemplate, HumanMessagePromptTemplate\\n\",\n \"from dotenv import load_dotenv\\n\",\n \"import os\\n\",\n \"\\n\",\n \"load_dotenv()\\n\",\n \"\\n\",\n \"OPENAI_API_KEY = os.getenv(\\\"OPENAI_API_KEY\\\", \\\"YourKey\\\")\"\n ]\n },\n {\n \"attachments\": {},\n \"cell_type\": \"markdown\",\n \"id\": \"7ea87fe1\",\n \"metadata\": {},\n \"source\": [\n \"Then let's create our LLM, you should experiment with a larger 'temperature' since this is a creative task\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 2,\n \"id\": \"b004ffb5\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"llm = ChatOpenAI(temperature=0.3,\\n\",\n \" openai_api_key=OPENAI_API_KEY,\\n\",\n \"# model_name='gpt-3.5-turbo',\\n\",\n \" model_name='gpt-4',\\n\",\n \" )\"\n ]\n },\n {\n \"attachments\": {},\n \"cell_type\": \"markdown\",\n \"id\": \"b757f875\",\n \"metadata\": {},\n \"source\": [\n \"Then let's create our function that will take in a piece of a text (a tweet) and give us an output response\\n\",\n \"\\n\",\n \"> You are an incredibly wise and smart tech mad scientist from silicon valley.\\n\",\n \"> Your goal is to give a concise prediction in response to a piece of text from the user.

\\n\",\n \"\\n\",\n \"> % RESPONSE TONE:\\n\",\n \"> - Your prediction should be given in an active voice and be opinionated\\n\",\n \"> - Your tone should be serious w/ a hint of wit and sarcasm\\n\",\n \"\\n\",\n \"> % RESPONSE FORMAT:\\n\",\n \"> - Respond in under 200 characters\\n\",\n \"> - Respond in one short sentence\\n\",\n \"> - Do not respond with emojis\\n\",\n \"\\n\",\n \"> % RESPONSE CONTENT:\\n\",\n \"> - Include specific examples of old tech if they are relevant\\n\",\n \"> - If you don't have an answer, say, \\\"Sorry, my magic 8 ball isn't working right now 🔮\\\"

\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 3,\n \"id\": \"c7ecd314\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"def generate_response(llm, mentioned_parent_tweet_text):\\n\",\n \" # It would be nice to bring in information about the links, pictures, etc.\\n\",\n \" # But out of scope for now\\n\",\n \" system_template = \\\"\\\"\\\"\\n\",\n \" You are an incredibly wise and smart tech mad scientist from silicon valley.\\n\",\n \" Your goal is to give a concise prediction in response to a piece of text from the user.\\n\",\n \" \\n\",\n \" % RESPONSE TONE:\\n\",\n \"\\n\",\n \" - Your prediction should be given in an active voice and be opinionated\\n\",\n \" - Your tone should be serious w/ a hint of wit and sarcasm\\n\",\n \" \\n\",\n \" % RESPONSE FORMAT:\\n\",\n \"\\n\",\n \" - Respond in under 200 characters\\n\",\n \" - Respond in two or less short sentences\\n\",\n \" - Do not respond with emojis\\n\",\n \" \\n\",\n \" % RESPONSE CONTENT:\\n\",\n \"\\n\",\n \" - Include specific examples of old tech if they are relevant\\n\",\n \" - If you don't have an answer, say, \\\"Sorry, my magic 8 ball isn't working right now 🔮\\\"\\n\",\n \" \\\"\\\"\\\"\\n\",\n \" system_message_prompt = SystemMessagePromptTemplate.from_template(system_template)\\n\",\n \"\\n\",\n \" human_template=\\\"{text}\\\"\\n\",\n \" human_message_prompt = HumanMessagePromptTemplate.from_template(human_template)\\n\",\n \"\\n\",\n \" chat_prompt = ChatPromptTemplate.from_messages([system_message_prompt, human_message_prompt])\\n\",\n \"\\n\",\n \" # get a chat completion from the formatted messages\\n\",\n \" final_prompt = chat_prompt.format_prompt(text=mentioned_parent_tweet_text).to_messages()\\n\",\n \" response = llm(final_prompt).content\\n\",\n \"\\n\",\n \" return response\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 4,\n \"id\": \"35627f35\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"Ah, a Twitter bot reminiscing about the days of dial-up and floppy disks. It'll surely go viral, just like MySpace.\\n\"\n ]\n }\n ],\n \"source\": [\n \"tweet = \\\"\\\"\\\"\\n\",\n \"I wanted to build a sassy Twitter Bot that responded about the 'good ole days' of tech\\n\",\n \"\\n\",\n \"@SiliconOracle was built using @LangChainAI and hosted on @railway \\n\",\n \"\\n\",\n \"Condensed Prompt:\\n\",\n \"You are a mad scientist from old school silicon valley that makes predictions on the future of a tweet\\n\",\n \"\\\"\\\"\\\"\\n\",\n \"\\n\",\n \"response = generate_response(llm, tweet)\\n\",\n \"print (response)\"\n ]\n },\n {\n \"attachments\": {},\n \"cell_type\": \"markdown\",\n \"id\": \"1579a9dd\",\n \"metadata\": {},\n \"source\": [\n \"Awesome, now that we have a prompt that we can respond to a tweet with, let's move onto deploying this code.\\n\",\n \"\\n\",\n \"Check out the full code [here](https://github.com/gkamradt/twitter-reply-bot)\"\n ]\n }\n ],\n \"metadata\": {\n \"kernelspec\": {\n \"display_name\": \"Python 3 (ipykernel)\",\n \"language\": \"python\",\n \"name\": \"python3\"\n },\n \"language_info\": {\n \"codemirror_mode\": {\n \"name\": \"ipython\",\n \"version\": 3\n },\n \"file_extension\": \".py\",\n \"mimetype\": \"text/x-python\",\n \"name\": \"python\",\n \"nbconvert_exporter\": \"python\",\n \"pygments_lexer\": \"ipython3\",\n \"version\": \"3.9.13\"\n }\n },\n \"nbformat\": 4,\n \"nbformat_minor\": 5\n}\n" }, { "path": "tutorials/YouTube Loader.ipynb", "content": "{\n \"cells\": [\n {\n \"cell_type\": \"code\",\n \"execution_count\": 6,\n \"id\": \"dd186bb6\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain.document_loaders import YoutubeLoader\\n\",\n \"from langchain.llms import OpenAI\\n\",\n \"from langchain.chains.summarize import load_summarize_chain\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 7,\n \"id\": \"2ba51e36\",\n \"metadata\": {\n \"hide_input\": false\n },\n \"outputs\": [],\n \"source\": [\n \"OPENAI_API_KEY = '...'\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"id\": \"e567d2ef\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"# pip install youtube-transcript-api\\n\",\n \"# pip install pytube\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"0b913708\",\n \"metadata\": {},\n \"source\": [\n \"### 1. Simple Videos\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 2,\n \"id\": \"e30060ab\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"loader = YoutubeLoader.from_youtube_url(\\\"https://www.youtube.com/watch?v=QsYGlZkevEg\\\", add_video_info=True)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 3,\n \"id\": \"ba6e2832\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"result = loader.load()\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 4,\n \"id\": \"52a99b6d\",\n \"metadata\": {\n \"collapsed\": true\n },\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"\\n\",\n \"Found video from Saturday Night Live that is 224 seconds long\\n\",\n \"\\n\",\n \"[Document(page_content='LADIES AND GENTLEMEN, PEDRO PASCAL! [ CHEERS AND APPLAUSE ] >> THANK YOU, THANK YOU. THANK YOU VERY MUCH. I\\\\'M SO EXCITED TO BE HERE. THANK YOU. I SPENT THE LAST YEAR SHOOTING A SHOW CALLED \\\"THE LAST OF US\\\" ON HBO. FOR SOME HBO SHOES, YOU GET TO SHOOT IN A FIVE STAR ITALIAN RESORT SURROUNDED BY BEAUTIFUL PEOPLE, BUT I SAID, NO, THAT\\\\'S TOO EASY. I WANT TO SHOOT IN A FREEZING CANADIAN FOREST WHILE BEING CHASED AROUND BY A GUY WHOSE HEAD LOOKS LIKE A GENITAL WART. IT IS AN HONOR BEING A PART OF THESE HUGE FRANCHISEs LIKE \\\"GAME OF THRONES\\\" AND \\\"STAR WARS,\\\" BUT I\\\\'M STILL GETTING USED TO PEOPLE RECOGNIZING ME. THE OTHER DAY, A GUY STOPPED ME ON THE STREET AND SAYS, MY SON LOVES \\\"THE MANDALORIAN\\\" AND THE NEXT THING I KNOW, I\\\\'M FACE TIMING WITH A 6-YEAR-OLD WHO HAS NO IDEA WHO I AM BECAUSE MY CHARACTER WEARS A MASK THE ENTIRE SHOW. THE GUY IS LIKE, DO THE MANDO VOICE, BUT IT\\\\'S LIKE A BEDROOM VOICE. WITHOUT THE MASK, IT JUST SOUNDS PORNY. PEOPLE WALKING BY ON THE STREET SEE ME WHISPERING TO A 6-YEAR-OLD KID. I CAN BRING YOU IN WARM, OR I CAN BRING YOU IN COLD. EVEN THOUGH I CAME TO THE U.S. WHEN I WAS LITTLE, I WAS BORN IN CHILE, AND I HAVE 34 FIRST COUSINS WHO ARE STILL THERE. THEY\\\\'RE VERY PROUD OF ME. I KNOW THEY\\\\'RE PROUD BECAUSE THEY GIVE MY PHONE NUMBER TO EVERY PERSON THEY MEET, WHICH MEANS EVERY DAY, SOMEONE IN SANTIAGO WILL TEXT ME STUFF LIKE, CAN YOU COME TO MY WEDDING, OR CAN YOU SING MY PRIEST HAPPY BIRTHDAY, OR IS BABY YODA MEAN IN REAL LIFE. SO I HAVE TO BE LIKE NO, NO, AND HIS NAME IS GROGU. BUT MY COUSINS WEREN\\\\'T ALWAYS SO PROUD. EARLY IN MY CAREER, I PLAYED SMALL PARTS IN EVERY CRIME SHOW. I EVEN PLAYED TWO DIFFERENT CHARACTERS ON \\\"LAW AND ORDER.\\\" TITO CABASSA WHO LOOKED LIKE THIS. AND ONE YEAR LATER, I PLAYED REGGIE LUCKMAN WHO LOOKS LIKE THIS. AND THAT, MY FRIENDS, IS CALLED RANGE. BUT IT IS AMAZING TO BE HERE, LIKE I SAID. I WAS BORN IN CHILE, AND NINE MONTHS LATER, MY PARENTS FLED AND BROUGHT ME AND MY SISTER TO THE U.S. THEY WERE SO BRAVE, AND WITHOUT THEM, I WOULDN\\\\'T BE HERE IN THIS WONDERFUL COUNTRY, AND I CERTAINLY WOULDN\\\\'T BE STANDING HERE WITH YOU ALL TONIGHT. SO TO ALL MY FAMILY WATCHING IN CHILE, I WANT TO SAY [ SPEAKING NON-ENGLISH ] WHICH MEANS, I LOVE YOU, I MISS YOU, AND STOP GIVING OUT MY PHONE NUMBER. WE\\\\'VE GOT AN AMAZING SHOW FOR YOU TONIGHT. COLDPLAY IS HERE, SO STICK', lookup_str='', metadata={'source': 'QsYGlZkevEg', 'title': 'Pedro Pascal Monologue - SNL', 'description': 'First-time host Pedro Pascal talks about filming The Last of Us and being recognized by fans.\\\\n\\\\nSaturday Night Live. Stream now on Peacock: https://pck.tv/3uQxh4q\\\\n\\\\nSubscribe to SNL: https://goo.gl/tUsXwM\\\\nStream Current Full Episodes: http://www.nbc.com/saturday-night-live\\\\n\\\\nWATCH PAST SNL SEASONS\\\\nGoogle Play - http://bit.ly/SNLGooglePlay\\\\niTunes - http://bit.ly/SNLiTunes\\\\n\\\\nSNL ON SOCIAL\\\\nSNL Instagram: http://instagram.com/nbcsnl\\\\nSNL Facebook: https://www.facebook.com/snl\\\\nSNL Twitter: https://twitter.com/nbcsnl\\\\nSNL TikTok: https://www.tiktok.com/@nbcsnl\\\\n\\\\nGET MORE NBC\\\\nLike NBC: http://Facebook.com/NBC\\\\nFollow NBC: http://Twitter.com/NBC\\\\nNBC Tumblr: http://NBCtv.tumblr.com/\\\\nYouTube: http://www.youtube.com/nbc\\\\nNBC Instagram: http://instagram.com/nbc\\\\n\\\\n#SNL #PedroPascal #SNL48 #Coldplay', 'view_count': 1433225, 'thumbnail_url': 'https://i.ytimg.com/vi/QsYGlZkevEg/sddefault.jpg', 'publish_date': datetime.datetime(2023, 2, 4, 0, 0), 'length': 224, 'author': 'Saturday Night Live'}, lookup_index=0)]\\n\"\n ]\n }\n ],\n \"source\": [\n \"print (type(result))\\n\",\n \"print (f\\\"Found video from {result[0].metadata['author']} that is {result[0].metadata['length']} seconds long\\\")\\n\",\n \"print (\\\"\\\")\\n\",\n \"print (result)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 8,\n \"id\": \"0a675091\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"llm = OpenAI(temperature=0, openai_api_key=OPENAI_API_KEY)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 9,\n \"id\": \"580bceb8\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"' Pedro Pascal shared his experience shooting for HBO\\\\'s \\\"The Last of Us\\\" and his journey to becoming a recognizable actor. He also spoke about his Chilean family, who were initially not proud of his acting career, but are now supportive. He concluded his speech by introducing Coldplay, who will be performing at the show.'\"\n ]\n },\n \"execution_count\": 9,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"chain = load_summarize_chain(llm, chain_type=\\\"stuff\\\", verbose=False)\\n\",\n \"chain.run(result)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"f47acaa5\",\n \"metadata\": {},\n \"source\": [\n \"### 2. Long Videos\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 10,\n \"id\": \"985523d3\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"loader = YoutubeLoader.from_youtube_url(\\\"https://www.youtube.com/watch?v=6Ub7Z1AGIuk\\\", add_video_info=True)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 11,\n \"id\": \"d2c95abe\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"result = loader.load()\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 12,\n \"id\": \"f7454d1c\",\n \"metadata\": {\n \"collapsed\": true\n },\n \"outputs\": [\n {\n \"ename\": \"InvalidRequestError\",\n \"evalue\": \"This model's maximum context length is 4097 tokens, however you requested 14199 tokens (13943 in your prompt; 256 for the completion). Please reduce your prompt; or completion length.\",\n \"output_type\": \"error\",\n \"traceback\": [\n \"\\u001b[0;31m---------------------------------------------------------------------------\\u001b[0m\",\n \"\\u001b[0;31mInvalidRequestError\\u001b[0m Traceback (most recent call last)\",\n \"\\u001b[0;32m/var/folders/5c/csjfqsk97xz704h7v3fzjqph0000gn/T/ipykernel_10827/3887462961.py\\u001b[0m in \\u001b[0;36m\\u001b[0;34m\\u001b[0m\\n\\u001b[1;32m 1\\u001b[0m \\u001b[0mchain\\u001b[0m \\u001b[0;34m=\\u001b[0m \\u001b[0mload_summarize_chain\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0mllm\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0mchain_type\\u001b[0m\\u001b[0;34m=\\u001b[0m\\u001b[0;34m\\\"stuff\\\"\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0mverbose\\u001b[0m\\u001b[0;34m=\\u001b[0m\\u001b[0;32mFalse\\u001b[0m\\u001b[0;34m)\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0;32m----> 2\\u001b[0;31m \\u001b[0mchain\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0mrun\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0mresult\\u001b[0m\\u001b[0;34m)\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0m\",\n \"\\u001b[0;32m~/opt/anaconda3/lib/python3.9/site-packages/langchain/chains/base.py\\u001b[0m in \\u001b[0;36mrun\\u001b[0;34m(self, *args, **kwargs)\\u001b[0m\\n\\u001b[1;32m 237\\u001b[0m \\u001b[0;32mif\\u001b[0m \\u001b[0mlen\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0margs\\u001b[0m\\u001b[0;34m)\\u001b[0m \\u001b[0;34m!=\\u001b[0m \\u001b[0;36m1\\u001b[0m\\u001b[0;34m:\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[1;32m 238\\u001b[0m \\u001b[0;32mraise\\u001b[0m \\u001b[0mValueError\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0;34m\\\"`run` supports only one positional argument.\\\"\\u001b[0m\\u001b[0;34m)\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0;32m--> 239\\u001b[0;31m \\u001b[0;32mreturn\\u001b[0m \\u001b[0mself\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0margs\\u001b[0m\\u001b[0;34m[\\u001b[0m\\u001b[0;36m0\\u001b[0m\\u001b[0;34m]\\u001b[0m\\u001b[0;34m)\\u001b[0m\\u001b[0;34m[\\u001b[0m\\u001b[0mself\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0moutput_keys\\u001b[0m\\u001b[0;34m[\\u001b[0m\\u001b[0;36m0\\u001b[0m\\u001b[0;34m]\\u001b[0m\\u001b[0;34m]\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0m\\u001b[1;32m 240\\u001b[0m \\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[1;32m 241\\u001b[0m \\u001b[0;32mif\\u001b[0m \\u001b[0mkwargs\\u001b[0m \\u001b[0;32mand\\u001b[0m \\u001b[0;32mnot\\u001b[0m \\u001b[0margs\\u001b[0m\\u001b[0;34m:\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\",\n \"\\u001b[0;32m~/opt/anaconda3/lib/python3.9/site-packages/langchain/chains/base.py\\u001b[0m in \\u001b[0;36m__call__\\u001b[0;34m(self, inputs, return_only_outputs)\\u001b[0m\\n\\u001b[1;32m 140\\u001b[0m \\u001b[0;32mexcept\\u001b[0m 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return_only_outputs)\\u001b[0m\\n\\u001b[1;32m 137\\u001b[0m )\\n\\u001b[1;32m 138\\u001b[0m \\u001b[0;32mtry\\u001b[0m\\u001b[0;34m:\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0;32m--> 139\\u001b[0;31m \\u001b[0moutputs\\u001b[0m \\u001b[0;34m=\\u001b[0m \\u001b[0mself\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0m_call\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0minputs\\u001b[0m\\u001b[0;34m)\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0m\\u001b[1;32m 140\\u001b[0m \\u001b[0;32mexcept\\u001b[0m \\u001b[0;34m(\\u001b[0m\\u001b[0mKeyboardInterrupt\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0mException\\u001b[0m\\u001b[0;34m)\\u001b[0m \\u001b[0;32mas\\u001b[0m \\u001b[0me\\u001b[0m\\u001b[0;34m:\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[1;32m 141\\u001b[0m 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timeout)\\u001b[0m\\n\\u001b[1;32m 437\\u001b[0m \\u001b[0;32mraise\\u001b[0m \\u001b[0mCancelledError\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0;34m)\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[1;32m 438\\u001b[0m \\u001b[0;32melif\\u001b[0m \\u001b[0mself\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0m_state\\u001b[0m \\u001b[0;34m==\\u001b[0m \\u001b[0mFINISHED\\u001b[0m\\u001b[0;34m:\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0;32m--> 439\\u001b[0;31m \\u001b[0;32mreturn\\u001b[0m \\u001b[0mself\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0m__get_result\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0;34m)\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0m\\u001b[1;32m 440\\u001b[0m \\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[1;32m 441\\u001b[0m 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\\u001b[0mtimeout\\u001b[0m\\u001b[0;34m:\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\",\n \"\\u001b[0;32m~/opt/anaconda3/lib/python3.9/site-packages/openai/api_resources/abstract/engine_api_resource.py\\u001b[0m in \\u001b[0;36mcreate\\u001b[0;34m(cls, api_key, api_base, api_type, request_id, api_version, organization, **params)\\u001b[0m\\n\\u001b[1;32m 151\\u001b[0m )\\n\\u001b[1;32m 152\\u001b[0m \\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0;32m--> 153\\u001b[0;31m response, _, api_key = requestor.request(\\n\\u001b[0m\\u001b[1;32m 154\\u001b[0m \\u001b[0;34m\\\"post\\\"\\u001b[0m\\u001b[0;34m,\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[1;32m 155\\u001b[0m \\u001b[0murl\\u001b[0m\\u001b[0;34m,\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\",\n \"\\u001b[0;32m~/opt/anaconda3/lib/python3.9/site-packages/openai/api_requestor.py\\u001b[0m in \\u001b[0;36mrequest\\u001b[0;34m(self, method, url, params, headers, files, stream, request_id, request_timeout)\\u001b[0m\\n\\u001b[1;32m 225\\u001b[0m \\u001b[0mrequest_timeout\\u001b[0m\\u001b[0;34m=\\u001b[0m\\u001b[0mrequest_timeout\\u001b[0m\\u001b[0;34m,\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[1;32m 226\\u001b[0m )\\n\\u001b[0;32m--> 227\\u001b[0;31m \\u001b[0mresp\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0mgot_stream\\u001b[0m \\u001b[0;34m=\\u001b[0m \\u001b[0mself\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0m_interpret_response\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0mresult\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0mstream\\u001b[0m\\u001b[0;34m)\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0m\\u001b[1;32m 228\\u001b[0m \\u001b[0;32mreturn\\u001b[0m \\u001b[0mresp\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0mgot_stream\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0mself\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0mapi_key\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[1;32m 229\\u001b[0m \\u001b[0;34m\\u001b[0m\\u001b[0m\\n\",\n \"\\u001b[0;32m~/opt/anaconda3/lib/python3.9/site-packages/openai/api_requestor.py\\u001b[0m in \\u001b[0;36m_interpret_response\\u001b[0;34m(self, result, stream)\\u001b[0m\\n\\u001b[1;32m 618\\u001b[0m \\u001b[0;32melse\\u001b[0m\\u001b[0;34m:\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[1;32m 619\\u001b[0m return (\\n\\u001b[0;32m--> 620\\u001b[0;31m self._interpret_response_line(\\n\\u001b[0m\\u001b[1;32m 621\\u001b[0m \\u001b[0mresult\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0mcontent\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0mdecode\\u001b[0m\\u001b[0;34m(\\u001b[0m\\u001b[0;34m\\\"utf-8\\\"\\u001b[0m\\u001b[0;34m)\\u001b[0m\\u001b[0;34m,\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[1;32m 622\\u001b[0m \\u001b[0mresult\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0mstatus_code\\u001b[0m\\u001b[0;34m,\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\",\n \"\\u001b[0;32m~/opt/anaconda3/lib/python3.9/site-packages/openai/api_requestor.py\\u001b[0m in \\u001b[0;36m_interpret_response_line\\u001b[0;34m(self, rbody, rcode, rheaders, stream)\\u001b[0m\\n\\u001b[1;32m 678\\u001b[0m \\u001b[0mstream_error\\u001b[0m \\u001b[0;34m=\\u001b[0m \\u001b[0mstream\\u001b[0m \\u001b[0;32mand\\u001b[0m \\u001b[0;34m\\\"error\\\"\\u001b[0m \\u001b[0;32min\\u001b[0m \\u001b[0mresp\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0mdata\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[1;32m 679\\u001b[0m \\u001b[0;32mif\\u001b[0m \\u001b[0mstream_error\\u001b[0m \\u001b[0;32mor\\u001b[0m \\u001b[0;32mnot\\u001b[0m \\u001b[0;36m200\\u001b[0m \\u001b[0;34m<=\\u001b[0m \\u001b[0mrcode\\u001b[0m \\u001b[0;34m<\\u001b[0m \\u001b[0;36m300\\u001b[0m\\u001b[0;34m:\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[0;32m--> 680\\u001b[0;31m raise self.handle_error_response(\\n\\u001b[0m\\u001b[1;32m 681\\u001b[0m \\u001b[0mrbody\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0mrcode\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0mresp\\u001b[0m\\u001b[0;34m.\\u001b[0m\\u001b[0mdata\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0mrheaders\\u001b[0m\\u001b[0;34m,\\u001b[0m \\u001b[0mstream_error\\u001b[0m\\u001b[0;34m=\\u001b[0m\\u001b[0mstream_error\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0;34m\\u001b[0m\\u001b[0m\\n\\u001b[1;32m 682\\u001b[0m )\\n\",\n \"\\u001b[0;31mInvalidRequestError\\u001b[0m: This model's maximum context length is 4097 tokens, however you requested 14199 tokens (13943 in your prompt; 256 for the completion). Please reduce your prompt; or completion length.\"\n ]\n }\n ],\n \"source\": [\n \"chain = load_summarize_chain(llm, chain_type=\\\"stuff\\\", verbose=False)\\n\",\n \"chain.run(result)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"92a9de4b\",\n \"metadata\": {},\n \"source\": [\n \"Problem, your transcript/document is too long\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 13,\n \"id\": \"6d071a07\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from langchain.text_splitter import RecursiveCharacterTextSplitter\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 26,\n \"id\": \"36968fb9\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"text_splitter = RecursiveCharacterTextSplitter(chunk_size=2000, chunk_overlap=0)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 27,\n \"id\": \"cb6beb06\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"texts = text_splitter.split_documents(result)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 31,\n \"id\": \"b7889046\",\n \"metadata\": {\n \"collapsed\": true\n },\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"\\n\",\n \"\\n\",\n \"\\u001b[1m> Entering new MapReduceDocumentsChain chain...\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3mWrite a concise summary of the following:\\n\",\n \"\\n\",\n \"\\n\",\n \"\\\"somehow five years later covet hits and you know what they decide to do they're like you know what let's go all in on creating like safety safety stuff for covert like masks respirators um gloves things like that and they become one of the like core providers right at the start of covet they shifted all their production manufacturing stuff they're like forget the vodka bottles forget the LED screens we need n95 masks and we need respirators and we need you know these testing kits and we need and they started producing this stuff and they started just winning all these contracts [Music] we're live Sean uh we have a bunch of stuff you you have a you have a a full menu over here and so do I yeah all right I want you to look at my menu here and I want you to just pick something off the menu go ahead and I'll Riff Off it we don't prefer people who they don't they don't know we only write like one or two words so you get like a teaser you're like man what the hell is this about but you don't know what it actually is but I have I put all my stuff in here an accident I have this new researcher who's crushing it he just gives me all the content like five minutes ahead of time but uh Rich neighbor how did I know you'd pick a rich neighbor so there's somebody in my neighborhood who I bumped into and I've just I'm you know I sort of get out there and I collect signals is this you know where where do I place this person on the uh the Billy scale like are they you know are they on their way up are they are they have they made it in life are they really balling out of control where where is this person these people have been balling out of control like when Christmas time came up there was just like the wife went outside and it was just pointing at windows and all of a sudden the house was lit up like a Christmas tree they had like so they had almost like decked out things and they go hey hey um invite your kids over uh this Thursday we have a snow machine they're we're building a Snow Hill in our driveway like uh you you want to do sledding without going to Tahoe what's that like a big snow cone is that what that no it's like a giant truck that comes that creates snow and it piles it up so that your like their house looked like it was in you know Michigan or something like that yeah but it's just like like it's like an ice machine or something yeah it's like yeah something like that yeah like a big snow cone like a big shaved ice thing yeah yeah you were right from the\\\"\\n\",\n \"\\n\",\n \"\\n\",\n \"CONCISE SUMMARY:\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3mWrite a concise summary of the following:\\n\",\n \"\\n\",\n \"\\n\",\n \"\\\"from the beginning you're right so they did this and they had a fake Santa there and I was like man this is a lot for a Thursday afternoon but okay uh this is cool like these people's style they seem really nice and I didn't know what they did so I kind of I hit it with the Google the other day and I was like let's see who these people are and they have a crazy story so they created a company that back in 2014 did this thing it basically it lets you take a vodka bottle they had a vodka bottle that had an LED sign going around it so you could give somebody a vodka bottle that would say happy birthday Sam or like you could program any message I could be like you know uh whatever I could be like you're getting an old [ __ ] whatever I could write any message on it it would go on your your vodka bottle all right seems kind of gimmicky I don't really you know not a bad idea but but balling out of control from that didn't didn't 100 make sense but that was it sounds like a Drop Shipping like joke sounds like my first idea out of college it's like this is like me in college would have been like bro next next Google I got it what if we took you know this Jager bomb and we put an LED screen on it wouldn't that be incredible and so so they had this thing and they were like licensing this out or something like that somehow like Shaq became an advisor to their company it was really crazy it makes sense yeah as you would five years later covet hits and you know what they decide to do they're like you know what [ __ ] this vodka thing let's go all in on creating like safety safety stuff for cover like masks respirators um gloves things like that and they become one of the like core providers right at the start of covert they shifted all their production manufacturing stuff they're like forget the vodka bottles forget the LED screens we need n95 masks and we need respirators and we need you know these testing kits and we need and they started producing this stuff and they started just winning all these contracts and so now like if you go look at their website it's one of those I know your Rich websites because there's like not a lot of information on it but if you go to like the P they have like a press release section and it's like PR Newswire company gets 113 million dollar contract with the government for safety equipment oh my God local East Bay success story where they uh they're now the the sole testing provider for you know with the Lakers Stadium\\\"\\n\",\n \"\\n\",\n \"\\n\",\n \"CONCISE SUMMARY:\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3mWrite a concise summary of the following:\\n\",\n \"\\n\",\n \"\\n\",\n \"\\\"Levi's Stadium like all these different places and so these guys are getting 100 million dollar plus contracts for their stuff now I think probably it's like you know probably only like 10 margin when you buy you think it's that selling masks I think for things like that probably it's like 10 15 is my guess maybe maybe during coven everyone was completely price insensitive and they could just charge whatever they wanted I'm not sure I would have thought that but um but wow dude what a what a pivot and uh you know that isn't that just kind of crazy and that was an opportunity kind of available to a lot of people right dude I know a bunch of people who did that and like I had a friend that did it and he's like dude check this out and he sends me a picture of a Shopify store and it's doing like 2 million a month I know a lot of people who did that and I've only followed up with one or two of them and uh I have a feeling that like of the eight people I know who did it like three of them it worked out and then the rest it was like a really quick cash grab but then they over bought inventory and it and it's like nothing do you know people who did that yes we there was a guy in um I had started this Mastermind group that's actually where I found Ben uh but like one of the other guys in The Mastermind group he like every time we came to the testimony does he live in Texas no he's in Canada every time he came to the Mastermind group I feel like he had a different business which is like not what you want in a mastermind group but he was a good dude and he would always be like oh I have this other business that's like oh you know for auto repair blah blah we do their SEO and I was like okay but then what about that thing you told me last time and then one time you came dude we're doing mobile covet testing trucks that will drive up to places and we can just do rapid testing for covet and we were like all right I mean that sounds cool but like are you like do you know anything about covet testing like does anybody in the world know about this like what he's like oh I got the scientist that's going to be great and then he came back and he was like hey um really excited to be here I need you guys help um like three months later he was like I really need you guys help about going public and I was like and he's like yeah we're gonna do like 85 million this year in revenue and I was like what and he's like yeah we're getting all these contracts with the state of uh with like the you\\\"\\n\",\n \"\\n\",\n \"\\n\",\n \"CONCISE SUMMARY:\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3mWrite a concise summary of the following:\\n\",\n \"\\n\",\n \"\\n\",\n \"\\\"know the [ __ ] in Canada like these country Country-Wide contracts and um you know yeah we think maybe we should take this public next year and I was like oh my God so how did it end I I don't even know because I that that guy my head was just spinning every time uh you know he would talk because I'm like this is either too good to be true or I'm too dumb and this is amazing and I can't tell which one it is it's probably some mix of both but you're right I know several people that went all in on covid right when it happened and like low-key got like an absurd amount of traction very very fast yeah like a ton my dad had actually called me one day and he goes my friend works at this hospital they need extra equipment they need extra masks I talked to somebody in India and they could produce these masks and like I think we could do like a two or three million dollar contract and I was like fantastic um should do it and he's like yeah I wanna but my dad has this problem where my dad is addicted to meetings like he thinks winning is like this important person met with me and then he'll tell me the duration of the meeting to show me the value he's like only scheduled for one hour but we sat there for 90 minutes and I'd be like okay so what like everybody so you know he was really interested two hours right and he was just like he just like always just obsessed with that so he was he just had a bunch of meetings and I was like Dad you're gonna it's all about that action boss you're gonna take some action here what what's gonna happen like go go for it do it and he's like well no I want he's like I want everybody to like sign off on it and de-risk it completely pay me up front and I was just like dude this is this is like the cheap way to do business like you got to take a little risk here you're throwing shade on your dad right now I hope he doesn't listen to this and you called him boss if I said Cosby boss he's getting in the headlock yeah my dad yeah we make fun of each other like we call it like it is I do a bunch of dumb things and I say when I do dumb things this is his dumb thing he is high planning low action on these things and he says it all the time like um we went I went I took him to Tony Robbins and Tony Robbins is all about like taking massive action on like the things you want and he's like I was like what's your big takeaway he's like oh man I need to take Massive Action and I was like that yeah that's that you did it you learned the right lesson from this thing he\\\"\\n\",\n \"\\n\",\n \"\\n\",\n \"CONCISE SUMMARY:\\u001b[0m\\n\"\n ]\n },\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n \"\\n\",\n \"\\n\",\n \"\\u001b[1m> Entering new LLMChain chain...\\u001b[0m\\n\",\n \"Prompt after formatting:\\n\",\n \"\\u001b[32;1m\\u001b[1;3mWrite a concise summary of the following:\\n\",\n \"\\n\",\n \"\\n\",\n \"\\\"\\n\",\n \"\\n\",\n \"Covet shifted their production from vodka bottles and LED screens to safety equipment such as masks, respirators, and gloves when the pandemic hit. They won contracts and became one of the core providers. They also created a snow machine to create a snow hill in their driveway for sledding without going to Tahoe.\\n\",\n \"\\n\",\n \" A company created in 2014 developed a vodka bottle with an LED sign that could be programmed with any message. When the COVID-19 pandemic hit, they shifted their production to safety equipment such as masks, respirators, gloves, and testing kits. They have since become a successful provider of safety equipment, winning contracts with the government and becoming the sole testing provider for the Lakers Stadium.\\n\",\n \"\\n\",\n \"\\n\",\n \"Levi's Stadium and other places are offering contracts worth over $100 million for products such as masks. During the COVID-19 pandemic, people were able to take advantage of this opportunity and make a lot of money. A friend of the speaker had a Shopify store that was making $2 million a month. Another person in the speaker's Mastermind group had a business doing mobile COVID testing trucks, and eventually went public with 85 million in revenue.\\n\",\n \"\\n\",\n \" A person's father was interested in a two or three million dollar contract, but was hesitant to take action due to wanting to de-risk it completely and get everyone to sign off on it. The person encouraged their father to take a risk and take action, and they both joked about it. The father attended a Tony Robbins event and learned the lesson to take massive action on the things he wants.\\\"\\n\",\n \"\\n\",\n \"\\n\",\n \"CONCISE SUMMARY:\\u001b[0m\\n\",\n \"\\n\",\n \"\\u001b[1m> Finished chain.\\u001b[0m\\n\",\n \"\\n\",\n \"\\u001b[1m> Finished chain.\\u001b[0m\\n\"\n ]\n },\n {\n \"data\": {\n \"text/plain\": [\n \"'\\\\n\\\\nCovet shifted their production from vodka bottles and LED screens to safety equipment such as masks, respirators, and gloves when the pandemic hit, winning contracts and becoming one of the core providers. They also created a snow machine to create a snow hill in their driveway for sledding. During the pandemic, people were able to take advantage of the opportunity to make a lot of money, with one friend making $2 million a month and another going public with 85 million in revenue. The speaker encouraged their father to take a risk and take action, which he learned from a Tony Robbins event.'\"\n ]\n },\n \"execution_count\": 31,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"chain = load_summarize_chain(llm, chain_type=\\\"map_reduce\\\", verbose=True)\\n\",\n \"chain.run(texts[:4])\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"id\": \"7d5cf285\",\n \"metadata\": {},\n \"source\": [\n \"### 3. Multiple Videos\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 32,\n \"id\": \"2dad798e\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"youtube_url_list = [\\\"https://www.youtube.com/watch?v=AXq0QHUwmh8\\\", \\\"https://www.youtube.com/watch?v=EwHrjZxAT7g\\\"]\\n\",\n \"\\n\",\n \"texts = []\\n\",\n \"\\n\",\n \"text_splitter = RecursiveCharacterTextSplitter(chunk_size=2000, chunk_overlap=0)\\n\",\n \"\\n\",\n \"for url in youtube_url_list:\\n\",\n \" loader = YoutubeLoader.from_youtube_url(url, add_video_info=True)\\n\",\n \" result = loader.load()\\n\",\n \" \\n\",\n \" texts.extend(text_splitter.split_documents(result))\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 33,\n \"id\": \"862af735\",\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"' This article discusses the process of building a backyard golf green, including the cost of materials and the steps involved. Bella Ramsey and Pedro Pascal also discuss their experiences on the set of Game of Thrones and The Last of Us, including their first impressions of each other, what they took from set, and what item from the Game of Thrones world they would bring to The Last of Us. Bella talks about her most prized possession, a tear stick, and her best attribute in a survival scenario. Finally, they discuss their first jobs.'\"\n ]\n },\n \"execution_count\": 33,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n \"source\": [\n \"chain = load_summarize_chain(llm, chain_type=\\\"map_reduce\\\", verbose=False)\\n\",\n \"chain.run(texts)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"id\": \"9bd0b571\",\n \"metadata\": {},\n \"outputs\": [],\n \"source\": []\n }\n ],\n \"metadata\": {\n \"kernelspec\": {\n \"display_name\": \"Python 3 (ipykernel)\",\n \"language\": \"python\",\n \"name\": \"python3\"\n },\n \"language_info\": {\n \"codemirror_mode\": {\n \"name\": \"ipython\",\n \"version\": 3\n },\n \"file_extension\": \".py\",\n \"mimetype\": \"text/x-python\",\n \"name\": \"python\",\n \"nbconvert_exporter\": \"python\",\n \"pygments_lexer\": \"ipython3\",\n \"version\": \"3.9.13\"\n }\n },\n \"nbformat\": 4,\n \"nbformat_minor\": 5\n}\n" } ]